A distributed control system is designed for plasma spraying equipment and the configurations of system software and hardware is discussed. Through founding an expert database, the spraying process parameters are work...A distributed control system is designed for plasma spraying equipment and the configurations of system software and hardware is discussed. Through founding an expert database, the spraying process parameters are worked out and the initialization and control of spraying process are realized. The plasma spraying system with this control configuration can simplify the spraying operation, improve automation level of spray process, and approach the experience criterion as soon as possible.展开更多
In this paper, platoons of autonomous vehicles operating in urban road networks are considered. From a methodological point of view, the problem of interest consists of formally characterizing vehicle state trajectory...In this paper, platoons of autonomous vehicles operating in urban road networks are considered. From a methodological point of view, the problem of interest consists of formally characterizing vehicle state trajectory tubes by means of routing decisions complying with traffic congestion criteria. To this end, a novel distributed control architecture is conceived by taking advantage of two methodologies: deep reinforcement learning and model predictive control. On one hand, the routing decisions are obtained by using a distributed reinforcement learning algorithm that exploits available traffic data at each road junction. On the other hand, a bank of model predictive controllers is in charge of computing the more adequate control action for each involved vehicle. Such tasks are here combined into a single framework:the deep reinforcement learning output(action) is translated into a set-point to be tracked by the model predictive controller;conversely, the current vehicle position, resulting from the application of the control move, is exploited by the deep reinforcement learning unit for improving its reliability. The main novelty of the proposed solution lies in its hybrid nature: on one hand it fully exploits deep reinforcement learning capabilities for decisionmaking purposes;on the other hand, time-varying hard constraints are always satisfied during the dynamical platoon evolution imposed by the computed routing decisions. To efficiently evaluate the performance of the proposed control architecture, a co-design procedure, involving the SUMO and MATLAB platforms, is implemented so that complex operating environments can be used, and the information coming from road maps(links,junctions, obstacles, semaphores, etc.) and vehicle state trajectories can be shared and exchanged. Finally by considering as operating scenario a real entire city block and a platoon of eleven vehicles described by double-integrator models, several simulations have been performed with the aim to put in light the main f eatures of the proposed approach. Moreover, it is important to underline that in different operating scenarios the proposed reinforcement learning scheme is capable of significantly reducing traffic congestion phenomena when compared with well-reputed competitors.展开更多
In this paper,distributed model predictive control(DMPC) for island DC micro-grids(MG) with wind/photovoltaic(PV)/battery power is proposed,which coordinates all distributed generations(DG) to stabilize the bus voltag...In this paper,distributed model predictive control(DMPC) for island DC micro-grids(MG) with wind/photovoltaic(PV)/battery power is proposed,which coordinates all distributed generations(DG) to stabilize the bus voltage together with the insurance of having computational efficiency under a real-time requirement.Based on the feedback of the bus voltage,the deviation of the current is dispatched to each DG according to cost over the prediction horizon.Moreover,to avoid the excessive fluctuation of the battery power,both the discharge-charge switching times and costs are considered in the model predictive control(MPC) optimization problems.A Lyapunov constraint with a time-varying steady-state is designed in each local MPC to guarantee the stabilization of the entire system.The voltage stabilization of the MG is achieved by this strategy with the cooperation of DGs.The numeric results of applying the proposed method to a MG of the Shanghai Power Supply Company shows the effectiveness of the distributed economic MPC.展开更多
This paper proposes a distributed control method based on the differential flatness(DF) property of robot swarms. The swarm DF mapping is established for underactuated differentially flat dynamics, according to the co...This paper proposes a distributed control method based on the differential flatness(DF) property of robot swarms. The swarm DF mapping is established for underactuated differentially flat dynamics, according to the control objective. The DF mapping refers to the fact that the system state and input of each robot can be derived algebraically from the flat outputs of the leaders and the cooperative errors and their finite order derivatives. Based on the proposed swarm DF mapping, a distributed controller is designed. The distributed implementation of swarm DF mapping is achieved through observer design. The effectiveness of the proposed method is validated through a numerical simulation of quadrotor swarm synchronization.展开更多
DC-DC converter-based multi-bus DC microgrids(MGs) in series have received much attention, where the conflict between voltage recovery and current balancing has been a hot topic. The lack of models that accurately por...DC-DC converter-based multi-bus DC microgrids(MGs) in series have received much attention, where the conflict between voltage recovery and current balancing has been a hot topic. The lack of models that accurately portray the electrical characteristics of actual MGs while is controller design-friendly has kept the issue active. To this end, this paper establishes a large-signal model containing the comprehensive dynamical behavior of the DC MGs based on the theory of high-order fully actuated systems, and proposes distributed optimal control based on this. The proposed secondary control method can achieve the two goals of voltage recovery and current sharing for multi-bus DC MGs. Additionally, the simple structure of the proposed approach is similar to one based on droop control, which allows this control technique to be easily implemented in a variety of modern microgrids with different configurations. In contrast to existing studies, the process of controller design in this paper is closely tied to the actual dynamics of the MGs. It is a prominent feature that enables engineers to customize the performance metrics of the system. In addition, the analysis of the stability of the closed-loop DC microgrid system, as well as the optimality and consensus of current sharing are given. Finally, a scaled-down solar and battery-based microgrid prototype with maximum power point tracking controller is developed in the laboratory to experimentally test the efficacy of the proposed control method.展开更多
We address the control problem of microgrids and present a fully distributed control system which consists of primary controller,secondary controller,and optimal active power sharing controller.Different from the exis...We address the control problem of microgrids and present a fully distributed control system which consists of primary controller,secondary controller,and optimal active power sharing controller.Different from the existing control structure in microgrids,all these controllers are implemented as local controllers at each distributed generator.Thus,the requirement for a central controller is obviated.The performance analysis of the proposed control systems is provided,and the finite-time convergence properties for distributed secondary frequency and voltage controllers are achieved.Moreover,the distributed control system possesses the optimal active power sharing property.In the end,a microgrid test system is investigated to validate the effectiveness of the proposed control strategies.展开更多
In this paper, the leader-following tracking problem of fractional-order multi-agent systems is addressed. The dynamics of each agent may be heterogeneous and has unknown nonlinearities. By assumptions that the intera...In this paper, the leader-following tracking problem of fractional-order multi-agent systems is addressed. The dynamics of each agent may be heterogeneous and has unknown nonlinearities. By assumptions that the interaction topology is undirected and connected and the unknown nonlinear uncertain dynamics can be parameterized by a neural network, an adaptive learning law is proposed to deal with unknown nonlinear dynamics, based on which a kind of cooperative tracking protocols are constructed. The feedback gain matrix is obtained to solve an algebraic Riccati equation. To construct the fully distributed cooperative tracking protocols, the adaptive law is also adopted to adjust the coupling weight. With the developed control laws,we can prove that all signals in the closed-loop systems are guaranteed to be uniformly ultimately bounded. Finally, a simple simulation example is provided to illustrate the established result.展开更多
Based on the idea of backstepping design, distributedcoordinated tracking problems under directed topology are discussedfor multiple Euler-Lagrange (EL) systems. The dynamicleader case is considered. First, with the...Based on the idea of backstepping design, distributedcoordinated tracking problems under directed topology are discussedfor multiple Euler-Lagrange (EL) systems. The dynamicleader case is considered. First, with the parameter-linearity property,a distributed coordinated adaptive control scheme is proposedfor EL systems in the presence of parametric uncertainties.Then, subject to nonlinear uncertainties and external disturbances,an improved adaptive control algorithm is developed by usingneural-network (NN) approximation of nonlinear functions. Bothproposed algorithms can make tracking errors for each followerultimately bounded. The closed-loop systems are investigated byusing the combination of graph theory, Lyapunov theory, and BarbalatLemma. Numerical examples and comparisons with othermethods are provided to show the effectiveness of the proposedcontrol strategies.展开更多
This paper addresses the problem of distributed secondary control for islanded AC microgrids with external disturbances.By using a full-order sliding-mode(FOSM)approach,voltage regulation and frequency restoration are...This paper addresses the problem of distributed secondary control for islanded AC microgrids with external disturbances.By using a full-order sliding-mode(FOSM)approach,voltage regulation and frequency restoration are achieved in finite time.For voltage regulation,a distributed observer is proposed for each distributed generator(DG)to estimate a reference voltage level.Different from some conventional observers,the reference voltage level in this paper is accurately estimated under directed communication topologies.Based on the observer,a new nonlinear controller is designed in a backstepping manner such that an FOSM surface is reached in finite time.On the surface,the voltages of DGs are regulated to the reference level in finite time.For frequency restoration,a distributed controller is further proposed such that a constructed FOSM surface is reached in finite time,on which the frequencies of DGs are restored to a reference level in finite time under directed communication topologies.Finally,case studies on a modified IEEE 37-bus test system are conducted to demonstrate the effectiveness,the robustness against load changes,and the plug-and-play capability of the proposed controllers.展开更多
Reliable load frequency control(LFC) is crucial to the operation and design of modern electric power systems. Considering the LFC problem of a four-area interconnected power system with wind turbines, this paper prese...Reliable load frequency control(LFC) is crucial to the operation and design of modern electric power systems. Considering the LFC problem of a four-area interconnected power system with wind turbines, this paper presents a distributed model predictive control(DMPC) based on coordination scheme.The proposed algorithm solves a series of local optimization problems to minimize a performance objective for each control area. The generation rate constraints(GRCs), load disturbance changes, and the wind speed constraints are considered. Furthermore, the DMPC algorithm may reduce the impact of the randomness and intermittence of wind turbine effectively. A performance comparison between the proposed controller with and without the participation of the wind turbines is carried out. Analysis and simulation results show possible improvements on closed–loop performance, and computational burden with the physical constraints.展开更多
This article presents a distributed periodic eventtriggered(PET)optimal control scheme to achieve generation cost minimization and average bus voltage regulation in DC microgrids.In order to accommodate the generation...This article presents a distributed periodic eventtriggered(PET)optimal control scheme to achieve generation cost minimization and average bus voltage regulation in DC microgrids.In order to accommodate the generation constraints of the distributed generators(DGs),a virtual incremental cost is firstly designed,based on which an optimality condition is derived to facilitate the control design.To meet the discrete-time(DT)nature of modern control systems,the optimal controller is directly developed in the DT domain.Afterward,to reduce the communication requirement among the controllers,a distributed event-triggered mechanism is introduced for the DT optimal controller.The event-triggered condition is detected periodically and therefore naturally avoids the Zeno phenomenon.The closed-loop system stability is proved by the Lyapunov synthesis for switched systems.The generation cost minimization and average bus voltage regulation are obtained at the equilibrium point.Finally,switch-level microgrid simulations validate the performance of the proposed optimal controller.展开更多
Because of an unexpected signal noise within the network or an unpredictedfault with personal computers (PCs), many problems emerge in the implementation of distributednumerical control (DNC) with PCs-based network. T...Because of an unexpected signal noise within the network or an unpredictedfault with personal computers (PCs), many problems emerge in the implementation of distributednumerical control (DNC) with PCs-based network. To solve the problems, an industrial solution ofinvolving the field-bus technology in DNC communicating area is provided. A kind of advancedField-bus, named controller area network (CAN), is originally developed to support cheap and rathersimple automotive applications. However, because of its good performance and low cost, it is alsobeing considered in automated-manufacturing and process control environments to interconnectintelligent devices, such as modem sensors and actuators. Recently it creates a new role for CANBusin DNC that brings new thinking to DNC. CAN is used as the network platform for connecting machinetools to share information with each other reliably. Additionally, thanks to also applying of'plug-in' technology and a special interface of hardware, this solution exhibits some highcompatibility with different pedigree numerical control (NC) systems, such as Fanuc, Siemens,Cincinnati and so on. In order to improve CANBus for DNC application, a communicating competitionmodel of the basic CAN protocol, called CC model, is then highlighted. This model is able to satisfythe requirements that different machine tools share the communicating bandwidth fairly when theyrun concurrently. Finally the novel view of the latest advancement in CANBus-based DNC incombination with the manufacturing paradigm is also presented.展开更多
In this paper, an online optimal distributed learning algorithm is proposed to solve leader-synchronization problem of nonlinear multi-agent differential graphical games. Each player approximates its optimal control p...In this paper, an online optimal distributed learning algorithm is proposed to solve leader-synchronization problem of nonlinear multi-agent differential graphical games. Each player approximates its optimal control policy using a single-network approximate dynamic programming(ADP) where only one critic neural network(NN) is employed instead of typical actorcritic structure composed of two NNs. The proposed distributed weight tuning laws for critic NNs guarantee stability in the sense of uniform ultimate boundedness(UUB) and convergence of control policies to the Nash equilibrium. In this paper, by introducing novel distributed local operators in weight tuning laws, there is no more requirement for initial stabilizing control policies. Furthermore, the overall closed-loop system stability is guaranteed by Lyapunov stability analysis. Finally, Simulation results show the effectiveness of the proposed algorithm.展开更多
Time-delay phenomena extensively exist in practical systems,e.g.,multi-agent systems,bringing negative impacts on their stabilities.This work analyzes a collaborative control problem of redundant manipulators with tim...Time-delay phenomena extensively exist in practical systems,e.g.,multi-agent systems,bringing negative impacts on their stabilities.This work analyzes a collaborative control problem of redundant manipulators with time delays and proposes a time-delayed and distributed neural dynamics scheme.Under assumptions that the network topology is fixed and connected and the existing maximal time delay is no more than a threshold value,it is proved that all manipulators in the distributed network are able to reach a desired motion.The proposed distributed scheme with time delays considered is converted into a time-variant optimization problem,and a neural dynamics solver is designed to solve it online.Then,the proposed neural dynamics solver is proved to be stable,convergent and robust.Additionally,the allowable threshold value of time delay that ensures the proposed scheme’s stability is calculated.Illustrative examples and comparisons are provided to intuitively prove the validity of the proposed neural dynamics scheme and solver.展开更多
In this paper,a resilient distributed control scheme against replay attacks for multi-agent networked systems subject to input and state constraints is proposed.The methodological starting point relies on a smart use ...In this paper,a resilient distributed control scheme against replay attacks for multi-agent networked systems subject to input and state constraints is proposed.The methodological starting point relies on a smart use of predictive arguments with a twofold aim:1)Promptly detect malicious agent behaviors affecting normal system operations;2)Apply specific control actions,based on predictive ideas,for mitigating as much as possible undesirable domino effects resulting from adversary operations.Specifically,the multi-agent system is topologically described by a leader-follower digraph characterized by a unique leader and set-theoretic receding horizon control ideas are exploited to develop a distributed algorithm capable to instantaneously recognize the attacked agent.Finally,numerical simulations are carried out to show benefits and effectiveness of the proposed approach.展开更多
The chattering characteristic of sliding mode control isanalyzed when it is applied in distributed control systems (DCSs).For a DCS with random time delay and packet dropout, a discreteswitching system model with ti...The chattering characteristic of sliding mode control isanalyzed when it is applied in distributed control systems (DCSs).For a DCS with random time delay and packet dropout, a discreteswitching system model with time varying sampling period isconstructed based on the time delay system method. The reachinglaw based sliding mode controller is applied in the proposedsystem. The exponential stability condition in the form of linearmatrix inequality is figured out based on the multi-Lyaponov functionmethod. Then, the chattering characteristic is analyzed for theswitching system, and a chattering region related with time varyingsampling period and external disturbance is proposed. Finally, numericalexamples are given to illustrate the validity of the analysisresult.展开更多
This paper studies the fully distributed formation control problem of multi-robot systems without global position measurements subject to unknown longitudinal slippage constraints.It is difficult for robots to obtain ...This paper studies the fully distributed formation control problem of multi-robot systems without global position measurements subject to unknown longitudinal slippage constraints.It is difficult for robots to obtain accurate and stable global position information in many cases,such as when indoors,tunnels and any other environments where GPS(global positioning system)is denied,thus it is meaningful to overcome the dependence on global position information.Additionally,unknown slippage,which is hard to avoid for wheeled robots due to the existence of ice,sand,or muddy roads,can not only affect the control performance of wheeled robot,but also limits the application scene of wheeled mobile robots.To solve both problems,a fully distributed finite time state observer which does not require any global position information is proposed,such that each follower robot can estimate the leader’s states within finite time.The distributed adaptive controllers are further designed for each follower robot such that the desired formation can be achieved while overcoming the effect of unknown slippage.Finally,the effectiveness of the proposed observer and control laws are verified by simulation results.展开更多
For a distributed drive electric vehicle(DDEV) driven by four in-wheel motors, advanced vehicle dynamic control methods can be realized easily because motors can be controlled independently, quickly and precisely. A...For a distributed drive electric vehicle(DDEV) driven by four in-wheel motors, advanced vehicle dynamic control methods can be realized easily because motors can be controlled independently, quickly and precisely. And direct yaw-moment control(DYC) has been widely studied and applied to vehicle stability control. Good vehicle handling performance: quick yaw rate transient response, small overshoot, high steady yaw rate gain, etc, is required by drivers under normal conditions, which is less concerned, however. Based on the hierarchical control methodology, a novel control system using direct yaw moment control for improving handling performance of a distributed drive electric vehicle especially under normal driving conditions has been proposed. The upper-loop control system consists of two parts: a state feedback controller, which aims to realize the ideal transient response of yaw rate, with a vehicle sideslip angle observer; and a steering wheel angle feedforward controller designed to achieve a desired yaw rate steady gain. Under the restriction of the effect of poles and zeros in the closed-loop transfer function on the system response and the capacity of in-wheel motors, the integrated time and absolute error(ITAE) function is utilized as the cost function in the optimal control to calculate the ideal eigen frequency and damper coefficient of the system and obtain optimal feedback matrix and feedforward matrix. Simulations and experiments with a DDEV under multiple maneuvers are carried out and show the effectiveness of the proposed method: yaw rate rising time is reduced, steady yaw rate gain is increased, vehicle steering characteristic is close to neutral steer and drivers burdens are also reduced. The control system improves vehicle handling performance under normal conditions in both transient and steady response. State feedback control instead of model following control is introduced in the control system so that the sense of control intervention to drivers is relieved.展开更多
In this paper,the distributed fuzzy fault-tolerant tracking consensus problem of leader-follower multi-agent systems(MASs)is studied.The objective system includes actuator faults,mismatched parameter uncertainties,non...In this paper,the distributed fuzzy fault-tolerant tracking consensus problem of leader-follower multi-agent systems(MASs)is studied.The objective system includes actuator faults,mismatched parameter uncertainties,nonlinear functions,and exogenous disturbances under switching communication topologies.To solve this problem,a distributed fuzzy fault-tolerant controller is proposed for each follower by adaptive mechanisms to track the state of the leader.Furthermore,the fuzzy logic system is utilized to approximate the unknown nonlinear dynamics.An error estimator is introduced between the mismatched parameter matrix and the input matrix.Then,a selective adaptive law with relative state information is adopted and applied.When calculating the Lyapunov function’s derivative,the coupling terms related to consensus error and mismatched parameter uncertainties can be eliminated.Finally,a numerical simulation is given to validate the effectiveness of the proposed protocol.展开更多
This paper investigates the distributed fault-tolerant containment control(FTCC)problem of nonlinear multi-agent systems(MASs)under a directed network topology.The proposed control framework which is independent on th...This paper investigates the distributed fault-tolerant containment control(FTCC)problem of nonlinear multi-agent systems(MASs)under a directed network topology.The proposed control framework which is independent on the global information about the communication topology consists of two layers.Different from most existing distributed fault-tolerant control(FTC)protocols where the fault in one agent may propagate over network,the developed control method can eliminate the phenomenon of fault propagation.Based on the hierarchical control strategy,the FTCC problem with a directed graph can be simplified to the distributed containment control of the upper layer and the fault-tolerant tracking control of the lower layer.Finally,simulation results are given to demonstrate the effectiveness of the proposed control protocol.展开更多
文摘A distributed control system is designed for plasma spraying equipment and the configurations of system software and hardware is discussed. Through founding an expert database, the spraying process parameters are worked out and the initialization and control of spraying process are realized. The plasma spraying system with this control configuration can simplify the spraying operation, improve automation level of spray process, and approach the experience criterion as soon as possible.
文摘In this paper, platoons of autonomous vehicles operating in urban road networks are considered. From a methodological point of view, the problem of interest consists of formally characterizing vehicle state trajectory tubes by means of routing decisions complying with traffic congestion criteria. To this end, a novel distributed control architecture is conceived by taking advantage of two methodologies: deep reinforcement learning and model predictive control. On one hand, the routing decisions are obtained by using a distributed reinforcement learning algorithm that exploits available traffic data at each road junction. On the other hand, a bank of model predictive controllers is in charge of computing the more adequate control action for each involved vehicle. Such tasks are here combined into a single framework:the deep reinforcement learning output(action) is translated into a set-point to be tracked by the model predictive controller;conversely, the current vehicle position, resulting from the application of the control move, is exploited by the deep reinforcement learning unit for improving its reliability. The main novelty of the proposed solution lies in its hybrid nature: on one hand it fully exploits deep reinforcement learning capabilities for decisionmaking purposes;on the other hand, time-varying hard constraints are always satisfied during the dynamical platoon evolution imposed by the computed routing decisions. To efficiently evaluate the performance of the proposed control architecture, a co-design procedure, involving the SUMO and MATLAB platforms, is implemented so that complex operating environments can be used, and the information coming from road maps(links,junctions, obstacles, semaphores, etc.) and vehicle state trajectories can be shared and exchanged. Finally by considering as operating scenario a real entire city block and a platoon of eleven vehicles described by double-integrator models, several simulations have been performed with the aim to put in light the main f eatures of the proposed approach. Moreover, it is important to underline that in different operating scenarios the proposed reinforcement learning scheme is capable of significantly reducing traffic congestion phenomena when compared with well-reputed competitors.
基金supported by the National Key R&D Program of China (2018AAA0101701)the National Natural Science Foundation of China (62073220,61833012)。
文摘In this paper,distributed model predictive control(DMPC) for island DC micro-grids(MG) with wind/photovoltaic(PV)/battery power is proposed,which coordinates all distributed generations(DG) to stabilize the bus voltage together with the insurance of having computational efficiency under a real-time requirement.Based on the feedback of the bus voltage,the deviation of the current is dispatched to each DG according to cost over the prediction horizon.Moreover,to avoid the excessive fluctuation of the battery power,both the discharge-charge switching times and costs are considered in the model predictive control(MPC) optimization problems.A Lyapunov constraint with a time-varying steady-state is designed in each local MPC to guarantee the stabilization of the entire system.The voltage stabilization of the MG is achieved by this strategy with the cooperation of DGs.The numeric results of applying the proposed method to a MG of the Shanghai Power Supply Company shows the effectiveness of the distributed economic MPC.
基金Project supported by the National Natural Science Foundation of China (Nos. 62373025, 12332004,62003013, and 11932003)。
文摘This paper proposes a distributed control method based on the differential flatness(DF) property of robot swarms. The swarm DF mapping is established for underactuated differentially flat dynamics, according to the control objective. The DF mapping refers to the fact that the system state and input of each robot can be derived algebraically from the flat outputs of the leaders and the cooperative errors and their finite order derivatives. Based on the proposed swarm DF mapping, a distributed controller is designed. The distributed implementation of swarm DF mapping is achieved through observer design. The effectiveness of the proposed method is validated through a numerical simulation of quadrotor swarm synchronization.
基金supported in part by the National Natural Science Foundation of China(62173255, 62188101)Shenzhen Key Laboratory of Control Theory and Intelligent Systems,(ZDSYS20220330161800001)。
文摘DC-DC converter-based multi-bus DC microgrids(MGs) in series have received much attention, where the conflict between voltage recovery and current balancing has been a hot topic. The lack of models that accurately portray the electrical characteristics of actual MGs while is controller design-friendly has kept the issue active. To this end, this paper establishes a large-signal model containing the comprehensive dynamical behavior of the DC MGs based on the theory of high-order fully actuated systems, and proposes distributed optimal control based on this. The proposed secondary control method can achieve the two goals of voltage recovery and current sharing for multi-bus DC MGs. Additionally, the simple structure of the proposed approach is similar to one based on droop control, which allows this control technique to be easily implemented in a variety of modern microgrids with different configurations. In contrast to existing studies, the process of controller design in this paper is closely tied to the actual dynamics of the MGs. It is a prominent feature that enables engineers to customize the performance metrics of the system. In addition, the analysis of the stability of the closed-loop DC microgrid system, as well as the optimality and consensus of current sharing are given. Finally, a scaled-down solar and battery-based microgrid prototype with maximum power point tracking controller is developed in the laboratory to experimentally test the efficacy of the proposed control method.
基金supported by National Natural Science Foundation of China(61273108)the Fundamental Research Funds for the Central Universities(106112013CDJZR175501)the Scientific Research Foundation for the Returned Overseas Chinese Scholars,State Education Ministry
文摘We address the control problem of microgrids and present a fully distributed control system which consists of primary controller,secondary controller,and optimal active power sharing controller.Different from the existing control structure in microgrids,all these controllers are implemented as local controllers at each distributed generator.Thus,the requirement for a central controller is obviated.The performance analysis of the proposed control systems is provided,and the finite-time convergence properties for distributed secondary frequency and voltage controllers are achieved.Moreover,the distributed control system possesses the optimal active power sharing property.In the end,a microgrid test system is investigated to validate the effectiveness of the proposed control strategies.
基金supported by the National Natural Science Foundation of China(61303211)Zhejiang Provincial Natural Science Foundation of China(LY17F030003,LY15F030009)
文摘In this paper, the leader-following tracking problem of fractional-order multi-agent systems is addressed. The dynamics of each agent may be heterogeneous and has unknown nonlinearities. By assumptions that the interaction topology is undirected and connected and the unknown nonlinear uncertain dynamics can be parameterized by a neural network, an adaptive learning law is proposed to deal with unknown nonlinear dynamics, based on which a kind of cooperative tracking protocols are constructed. The feedback gain matrix is obtained to solve an algebraic Riccati equation. To construct the fully distributed cooperative tracking protocols, the adaptive law is also adopted to adjust the coupling weight. With the developed control laws,we can prove that all signals in the closed-loop systems are guaranteed to be uniformly ultimately bounded. Finally, a simple simulation example is provided to illustrate the established result.
基金supported by the National Natural Science Foundation of China(6130400561174200)the Research Fund for the Doctoral Program of Higher Education of China(20102302110031)
文摘Based on the idea of backstepping design, distributedcoordinated tracking problems under directed topology are discussedfor multiple Euler-Lagrange (EL) systems. The dynamicleader case is considered. First, with the parameter-linearity property,a distributed coordinated adaptive control scheme is proposedfor EL systems in the presence of parametric uncertainties.Then, subject to nonlinear uncertainties and external disturbances,an improved adaptive control algorithm is developed by usingneural-network (NN) approximation of nonlinear functions. Bothproposed algorithms can make tracking errors for each followerultimately bounded. The closed-loop systems are investigated byusing the combination of graph theory, Lyapunov theory, and BarbalatLemma. Numerical examples and comparisons with othermethods are provided to show the effectiveness of the proposedcontrol strategies.
基金supported in part by the Australian Research Council Discovery Project(DP160103567)the program of Jiangsu Specially-Appointed Professor(RK043STP19001)+1 种基金the fund of high-level talents at NJUPT(XK0430919039)the fund of scientific and technological innovation projects for overseas students in Nanjing(RK043NLX19004)。
文摘This paper addresses the problem of distributed secondary control for islanded AC microgrids with external disturbances.By using a full-order sliding-mode(FOSM)approach,voltage regulation and frequency restoration are achieved in finite time.For voltage regulation,a distributed observer is proposed for each distributed generator(DG)to estimate a reference voltage level.Different from some conventional observers,the reference voltage level in this paper is accurately estimated under directed communication topologies.Based on the observer,a new nonlinear controller is designed in a backstepping manner such that an FOSM surface is reached in finite time.On the surface,the voltages of DGs are regulated to the reference level in finite time.For frequency restoration,a distributed controller is further proposed such that a constructed FOSM surface is reached in finite time,on which the frequencies of DGs are restored to a reference level in finite time under directed communication topologies.Finally,case studies on a modified IEEE 37-bus test system are conducted to demonstrate the effectiveness,the robustness against load changes,and the plug-and-play capability of the proposed controllers.
基金supported by National Natural Science Foundation of China(61533013,61273144)Scientific Technology Research and Development Plan Project of Tangshan(13130298B)Scientific Technology Research and Development Plan Project of Hebei(z2014070)
文摘Reliable load frequency control(LFC) is crucial to the operation and design of modern electric power systems. Considering the LFC problem of a four-area interconnected power system with wind turbines, this paper presents a distributed model predictive control(DMPC) based on coordination scheme.The proposed algorithm solves a series of local optimization problems to minimize a performance objective for each control area. The generation rate constraints(GRCs), load disturbance changes, and the wind speed constraints are considered. Furthermore, the DMPC algorithm may reduce the impact of the randomness and intermittence of wind turbine effectively. A performance comparison between the proposed controller with and without the participation of the wind turbines is carried out. Analysis and simulation results show possible improvements on closed–loop performance, and computational burden with the physical constraints.
基金supported by the U.S.Office of Naval Research(N00014-21-1-2175)。
文摘This article presents a distributed periodic eventtriggered(PET)optimal control scheme to achieve generation cost minimization and average bus voltage regulation in DC microgrids.In order to accommodate the generation constraints of the distributed generators(DGs),a virtual incremental cost is firstly designed,based on which an optimality condition is derived to facilitate the control design.To meet the discrete-time(DT)nature of modern control systems,the optimal controller is directly developed in the DT domain.Afterward,to reduce the communication requirement among the controllers,a distributed event-triggered mechanism is introduced for the DT optimal controller.The event-triggered condition is detected periodically and therefore naturally avoids the Zeno phenomenon.The closed-loop system stability is proved by the Lyapunov synthesis for switched systems.The generation cost minimization and average bus voltage regulation are obtained at the equilibrium point.Finally,switch-level microgrid simulations validate the performance of the proposed optimal controller.
基金Science and Technology Program Foundation of Chongqing(No.7210)
文摘Because of an unexpected signal noise within the network or an unpredictedfault with personal computers (PCs), many problems emerge in the implementation of distributednumerical control (DNC) with PCs-based network. To solve the problems, an industrial solution ofinvolving the field-bus technology in DNC communicating area is provided. A kind of advancedField-bus, named controller area network (CAN), is originally developed to support cheap and rathersimple automotive applications. However, because of its good performance and low cost, it is alsobeing considered in automated-manufacturing and process control environments to interconnectintelligent devices, such as modem sensors and actuators. Recently it creates a new role for CANBusin DNC that brings new thinking to DNC. CAN is used as the network platform for connecting machinetools to share information with each other reliably. Additionally, thanks to also applying of'plug-in' technology and a special interface of hardware, this solution exhibits some highcompatibility with different pedigree numerical control (NC) systems, such as Fanuc, Siemens,Cincinnati and so on. In order to improve CANBus for DNC application, a communicating competitionmodel of the basic CAN protocol, called CC model, is then highlighted. This model is able to satisfythe requirements that different machine tools share the communicating bandwidth fairly when theyrun concurrently. Finally the novel view of the latest advancement in CANBus-based DNC incombination with the manufacturing paradigm is also presented.
文摘In this paper, an online optimal distributed learning algorithm is proposed to solve leader-synchronization problem of nonlinear multi-agent differential graphical games. Each player approximates its optimal control policy using a single-network approximate dynamic programming(ADP) where only one critic neural network(NN) is employed instead of typical actorcritic structure composed of two NNs. The proposed distributed weight tuning laws for critic NNs guarantee stability in the sense of uniform ultimate boundedness(UUB) and convergence of control policies to the Nash equilibrium. In this paper, by introducing novel distributed local operators in weight tuning laws, there is no more requirement for initial stabilizing control policies. Furthermore, the overall closed-loop system stability is guaranteed by Lyapunov stability analysis. Finally, Simulation results show the effectiveness of the proposed algorithm.
基金supported in part by the National Natural Science Foundation of China (62176109)the Natural Science Foundation of Gansu Province(21JR7RA531)+7 种基金the Team Project of Natural Science Foundation of Qinghai Province China (2020-ZJ-903)the State Key Laboratory of Integrated Services Networks (ISN23-10)the Gansu Provincial Youth Doctoral Fund of Colleges and Universities (2021QB-003)the Fundamental Research Funds for the Central Universities (lzujbky-2021-65)the Supercomputing Center of Lanzhou Universitythe Natural Science Foundation of Chongqing(cstc2019jcyjjq X0013)the CAAIHuawei Mind Spore Open Fund (CAAIXS JLJJ-2021-035A)the Pioneer Hundred Talents Program of Chinese Academy of Sciences
文摘Time-delay phenomena extensively exist in practical systems,e.g.,multi-agent systems,bringing negative impacts on their stabilities.This work analyzes a collaborative control problem of redundant manipulators with time delays and proposes a time-delayed and distributed neural dynamics scheme.Under assumptions that the network topology is fixed and connected and the existing maximal time delay is no more than a threshold value,it is proved that all manipulators in the distributed network are able to reach a desired motion.The proposed distributed scheme with time delays considered is converted into a time-variant optimization problem,and a neural dynamics solver is designed to solve it online.Then,the proposed neural dynamics solver is proved to be stable,convergent and robust.Additionally,the allowable threshold value of time delay that ensures the proposed scheme’s stability is calculated.Illustrative examples and comparisons are provided to intuitively prove the validity of the proposed neural dynamics scheme and solver.
文摘In this paper,a resilient distributed control scheme against replay attacks for multi-agent networked systems subject to input and state constraints is proposed.The methodological starting point relies on a smart use of predictive arguments with a twofold aim:1)Promptly detect malicious agent behaviors affecting normal system operations;2)Apply specific control actions,based on predictive ideas,for mitigating as much as possible undesirable domino effects resulting from adversary operations.Specifically,the multi-agent system is topologically described by a leader-follower digraph characterized by a unique leader and set-theoretic receding horizon control ideas are exploited to develop a distributed algorithm capable to instantaneously recognize the attacked agent.Finally,numerical simulations are carried out to show benefits and effectiveness of the proposed approach.
基金supported by the National Natural Science Fundation of China(5147618751506221)+1 种基金the Natural Science Basic Research Plan in Shaanxi Province of China(2015JQ51792015JM5207)
文摘The chattering characteristic of sliding mode control isanalyzed when it is applied in distributed control systems (DCSs).For a DCS with random time delay and packet dropout, a discreteswitching system model with time varying sampling period isconstructed based on the time delay system method. The reachinglaw based sliding mode controller is applied in the proposedsystem. The exponential stability condition in the form of linearmatrix inequality is figured out based on the multi-Lyaponov functionmethod. Then, the chattering characteristic is analyzed for theswitching system, and a chattering region related with time varyingsampling period and external disturbance is proposed. Finally, numericalexamples are given to illustrate the validity of the analysisresult.
基金supported by the National Natural Science Foundation of China(61922063,61773289)Shanghai Shuguang Project(18SG18)+2 种基金Shanghai Natural Science Foundation(19ZR1461400)Shanghai Sailing Program(20YF1452900)Fundamental Research Funds for the Central Universities。
文摘This paper studies the fully distributed formation control problem of multi-robot systems without global position measurements subject to unknown longitudinal slippage constraints.It is difficult for robots to obtain accurate and stable global position information in many cases,such as when indoors,tunnels and any other environments where GPS(global positioning system)is denied,thus it is meaningful to overcome the dependence on global position information.Additionally,unknown slippage,which is hard to avoid for wheeled robots due to the existence of ice,sand,or muddy roads,can not only affect the control performance of wheeled robot,but also limits the application scene of wheeled mobile robots.To solve both problems,a fully distributed finite time state observer which does not require any global position information is proposed,such that each follower robot can estimate the leader’s states within finite time.The distributed adaptive controllers are further designed for each follower robot such that the desired formation can be achieved while overcoming the effect of unknown slippage.Finally,the effectiveness of the proposed observer and control laws are verified by simulation results.
基金Supported by National Basic Research Program of China(973 Program,Grant No.2011CB711200)National Science and Technology Support Program of China(Grant No.2015BAG17B00)National Natural Science Foundation of China(Grant No.51475333)
文摘For a distributed drive electric vehicle(DDEV) driven by four in-wheel motors, advanced vehicle dynamic control methods can be realized easily because motors can be controlled independently, quickly and precisely. And direct yaw-moment control(DYC) has been widely studied and applied to vehicle stability control. Good vehicle handling performance: quick yaw rate transient response, small overshoot, high steady yaw rate gain, etc, is required by drivers under normal conditions, which is less concerned, however. Based on the hierarchical control methodology, a novel control system using direct yaw moment control for improving handling performance of a distributed drive electric vehicle especially under normal driving conditions has been proposed. The upper-loop control system consists of two parts: a state feedback controller, which aims to realize the ideal transient response of yaw rate, with a vehicle sideslip angle observer; and a steering wheel angle feedforward controller designed to achieve a desired yaw rate steady gain. Under the restriction of the effect of poles and zeros in the closed-loop transfer function on the system response and the capacity of in-wheel motors, the integrated time and absolute error(ITAE) function is utilized as the cost function in the optimal control to calculate the ideal eigen frequency and damper coefficient of the system and obtain optimal feedback matrix and feedforward matrix. Simulations and experiments with a DDEV under multiple maneuvers are carried out and show the effectiveness of the proposed method: yaw rate rising time is reduced, steady yaw rate gain is increased, vehicle steering characteristic is close to neutral steer and drivers burdens are also reduced. The control system improves vehicle handling performance under normal conditions in both transient and steady response. State feedback control instead of model following control is introduced in the control system so that the sense of control intervention to drivers is relieved.
基金This work was supported by Tianjin Natural Science Foundation of China(20JCYBJC01060,20JCQNJC01450)the National Natural Science Foundation of China(61973175)Tianjin Postgraduate Scientific Research and Innovation Project(2020YJSZXB03,2020YJSZXB12).
文摘In this paper,the distributed fuzzy fault-tolerant tracking consensus problem of leader-follower multi-agent systems(MASs)is studied.The objective system includes actuator faults,mismatched parameter uncertainties,nonlinear functions,and exogenous disturbances under switching communication topologies.To solve this problem,a distributed fuzzy fault-tolerant controller is proposed for each follower by adaptive mechanisms to track the state of the leader.Furthermore,the fuzzy logic system is utilized to approximate the unknown nonlinear dynamics.An error estimator is introduced between the mismatched parameter matrix and the input matrix.Then,a selective adaptive law with relative state information is adopted and applied.When calculating the Lyapunov function’s derivative,the coupling terms related to consensus error and mismatched parameter uncertainties can be eliminated.Finally,a numerical simulation is given to validate the effectiveness of the proposed protocol.
基金supported in part by the National Natural Science Foundation of China(61873056,61621004,61420106016)the Fundamental Research Funds for the Central Universities in China(N2004001,N2004002,N182608004)the Research Fund of State Key Laboratory of Synthetical Automation for Process Industries in China(2013ZCX01)。
文摘This paper investigates the distributed fault-tolerant containment control(FTCC)problem of nonlinear multi-agent systems(MASs)under a directed network topology.The proposed control framework which is independent on the global information about the communication topology consists of two layers.Different from most existing distributed fault-tolerant control(FTC)protocols where the fault in one agent may propagate over network,the developed control method can eliminate the phenomenon of fault propagation.Based on the hierarchical control strategy,the FTCC problem with a directed graph can be simplified to the distributed containment control of the upper layer and the fault-tolerant tracking control of the lower layer.Finally,simulation results are given to demonstrate the effectiveness of the proposed control protocol.