Differential flatness-based distributed control of underactuated robot swarms

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.

Chattering analysis for discrete sliding mode control ofdistributed control systems

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.

Development of Distributed Control System for Neutral Beam Injector on EAST

A distributed control system of Neutral Beam Injector （NBI） on the Experimental Advanced Superconducting Tokamak （EAST-NBI） is briefly presented in this paper. The control system is developed in accordance with the experimental operational characteristics of the EAST- NBI. The NBI control system （NBICS）, which is based on the computer network technologies and classified according to the control levels, consists of three levels： a remote monitoring layer, a server control layer, and a field control layer. The 3-layer architecture is capable of extending the system functions and upgrading devices. The timing system provides the reference clock of the synchronization and interlock for the EAST-NBI system. An interlock system ensures the safety of the experiment operators and field devices. Both of the ion sources of the beamline are designed to operate independently. This lays an important foundation for developing a control system for the second beamline on EAST. Experimental results demonstrate that the NBICS meets functional requirements of the EAST-NBI control, and makes experimental operations visual and automatic.

Cooperative Sensing and Distributed Control of a Diffusion Process Using Centroidal Voronoi Tessellations

This paper considers how to use a group of robots to sense and control a diffusion process.The diffusion process is modeled by a partial differential equation (PDE),which is a both spatially and temporally variant system.The robots can serve as mobile sensors,actuators,or both.Centroidal Voronoi Tessellations based coverage control algorithm is proposed for the cooperative sensing task.For the diffusion control problem,this paper considers spraying control via a group of networked mobile robots equipped with chemical neutralizers,known as smart mobile sprayers or actuators,in a domain of interest having static mesh sensor network for concentration sensing.This paper also introduces the information sharing and consensus strategy when using centroidal Voronoi tessellations algorithm to control a diffusion process.The information is shared not only on where to spray but also on how much to spray among the mobile actuators.Benefits from using CVT and information consensus seeking for sensing and control of a diffusion process are demonstrated in simulation results.

Robust distributed controller design of rotational single-link smart materials beam

A dynamic modelling and controller design were presented for a single-link smart materials beam, a flexible beam bonded with piezoelectric actuators and sensors for better control performance. Taking into account bounded disturbances, a robust distributed controller was constructed based on the system model, which was described by a set of partial differential equations (PDEs) and boundary conditions (BCs) . Subsequently, a finite dimensional controller was further developed, and it was proven that this controller can stabilize the finite dimensional model with arbitrary number of flexible modes. Keywords Dynamic modelling - Robust distributed controller - Flexible beam - Smart material

Plasma spraying system with distributed controlling

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.

Study on optimal state estimation strategy with dual distributed controllers based on Kalman filtering

Considering dual distributed controllers, a design of optimal state estimation strategy is studied for the wireless sensor and actuator network(WSAN). In particular, the optimal linear quadratic(LQ) control strategy with estimated plant state is formulated as a non-cooperative game with network-induced delays. Then, using the Kalman filter approach, an optimal estimation of the plant state is obtained based on the information fusion of the distributed controllers. Finally, an optimal state estimation strategy is derived as a linear function of the current estimated plant state and the last control strategy of multiple controllers. The effectiveness of the proposed closed-loop control strategy is verified by the simulation experiments.

Distributed Control for <i>n</i>×<i>n</i>Cooperative Systems Governed by Hyperbolic Operator of Infinite Order

In this study, a distributed optimal control problem for n × n cooperative hyperbolic systems with infinite order operators and Dirichlet conditions are considered. The existence and uniqueness of the state of these systems are proved. The necessary and sufficient conditions for optimality of distributed control with constraints are found, and the set of equations and inequalities that defining the optimal control of these systems is also obtained. Finally, some examples for the control problem without constraints are given.

Implementation of Distributed Control System for Rice Mill Using C#

The paper presents the distributed control system for rice mill using C#language.The real-time manufacturing system can be implemented by utilizing the signal from the real time control units that is more operative than other old-fashioned control systems in the extent of modern industrial days.The software-based Distributed Control System(DCS)is novel fashionable than any other conventional control systems in the state-ofthe-art manufacturing developments.This research study emphasizes on the implementation of the DCS-based rice mill using visual C#.net.The Industrial Ethernet(IE)is realized between the top level controller for the operator and the controlled station for the remote devices.The model of client-server approach is more appropriate for the automation and manufacturing research purposes.In this study,the computer graphical simulation of the complete control development is depicted in real-time status quo by visual C#language under Visual Studio 2008 software.The parallel ports in the computers of remote terminal level and the master terminal level controllers have been interconnected with port interface coding by visual C#program.

Distributed Control of Nonholonomic Robots Without Global Position Measurements Subject to Unknown Slippage Constraints

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.

H∞ Robustness for Distributed Control in Autonomous Microgrids Considering Cyber Disturbances

The physical connections and logical relationships between microgrids and communication networks allow microgrids to develop into typical cyber-physical systems(CPSs).With the extensive use of open communication mechanisms,the impact of cyber disturbances in public communication networks cannot be diminshed.In this paper,a parameter optimal method for a distributed secondary controller based on the robust control theory and consensus algorithm is presented to enhance the robustness of a secondary control system under data disturbance,parameter perturbation,and time delay.First,a distributed secondary control strategy of microgrids is demonstrated that coordinates frequency and voltage restoration and power sharing.Then,considering the impact of cyber events on the secondary control,a distributed robust controller gain design method is proposed to satisfy the H∞ performance index.The solution of the distributed robust control is transformed into a linear matrix in equation problem and latency margin is simultaneously obtained.Finally,a test microgrid CPS is simulated with and without time delay to investigate the impact of cyber events on system operational states and the effectiveness and robustness of the proposed method.

Leader-follower Optimal Selection Method for Distributed Control System in Active Distribution Networks

Aiming at the shortcomings of a traditional centralized control in an active distribution network(AND),this paper proposes a leader-follower distributed group cooperative control strategy to realize multiple operation and control tasks for an ADN.The distributed information exchange protocols of the distributed generation(DG)group devoted to node voltage regulation or exchange power control are developed using a DG power utilization ratio as the consensus variable.On these bases,this study further investigates the leader optimal selection method for a DG group to improve the response speed of the distributed control system.Furthermore,a single or multiple leader selection model is established to minimize the constraints of the one-step convergence factor and the number of leaders to improve the response speed of the distributed control system.The simulation results of the IEEE 33 bus standard test system show the effectiveness of the proposed distributed control strategy.In addition,the response speed of a DG control group can be improved effectively when the single or multiple leaders are selected optimally.

Distributed Robust UAVs Formation Control Based on Semidefinite Programming

The formation control of unmanned aerial vehicle(UAV)swarms is of significant importance in various fields such as transportation,emergency management,and environmental monitoring.However,the complex dynamics,nonlinearity,uncertainty,and interaction among agents make it a challenging problem.In this paper,we propose a distributed robust control strategy that uses only local information of UAVs to improve the stability and robustness of the formation system in uncertain environments.We establish a nominal control strategy based on position relations and a semi-definite programming model to obtain control gains.Additionally,we propose a robust control strategy under the rotation setΩto address the noise and disturbance in the system,ensuring that even when the rotation angles of the UAVs change,they still form a stable formation.Finally,we extend the proposed strategy to a quadrotor UAV system with high-order kinematic models and conduct simulation experiments to validate its effectiveness in resisting uncertain disturbances and achieving formation control.

Autonomous Vehicle Platoons In Urban Road Networks:A Joint Distributed Reinforcement Learning and Model Predictive Control Approach

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.

Virtually coupled train set control subject to space-time separation:A distributed economic MPC approach with emergency braking configuration

The emerging virtual coupling technology aims to operate multiple train units in a Virtually Coupled Train Set(VCTS)at a minimal but safe distance.To guarantee collision avoidance,the safety distance should be calculated using the state-of-the-art space-time separation principle that separates the Emergency Braking(EB)trajectories of two successive units during the whole EB process.In this case,the minimal safety distance is usually numerically calculated without an analytic formulation.Thus,the constrained VCTS control problem is hard to address with space-time separation,which is still a gap in the existing literature.To solve this problem,we propose a Distributed Economic Model Predictive Control(DEMPC)approach with computation efficiency and theoretical guarantee.Specifically,to alleviate the computation burden,we transform implicit safety constraints into explicitly linear ones,such that the optimal control problem in DEMPC is a quadratic programming problem that can be solved efficiently.For theoretical analysis,sufficient conditions are derived to guarantee the recursive feasibility and stability of DEMPC,employing compatibility constraints,tube techniques and terminal ingredient tuning.Moreover,we extend our approach with globally optimal and distributed online EB configuration methods to shorten the minimal distance among VCTS.Finally,experimental results demonstrate the performance and advantages of the proposed approaches.

Optimal Cooperative Secondary Control for Islanded DC Microgrids via a Fully Actuated Approach

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.

A PI+R Control Scheme Based on Multi-Agent Systems for Economic Dispatch in Isolated BESSs

Battery energy storage systems(BESSs)are widely used in smart grids.However,power consumed by inner impedance and the capacity degradation of each battery unit become particularly severe,which has resulted in an increase in operating costs.The general economic dispatch(ED)algorithm based on marginal cost(MC)consensus is usually a proportional(P)controller,which encounters the defects of slow convergence speed and low control accuracy.In order to solve the distributed ED problem of the isolated BESS network with excellent dynamic and steady-state performance,we attempt to design a proportional integral(PI)controller with a reset mechanism(PI+R)to asymptotically promote MC consensus and total power mismatch towards 0 in this paper.To be frank,the integral term in the PI controller is reset to 0 at an appropriate time when the proportional term undergoes a zero crossing,which accelerates convergence,improves control accuracy,and avoids overshoot.The eigenvalues of the system under a PI+R controller is well analyzed,ensuring the regularity of the system and enabling the reset mechanism.To ensure supply and demand balance within the isolated BESSs,a centralized reset mechanism is introduced,so that the controller is distributed in a flow set and centralized in a jump set.To cope with Zeno behavior and input delay,a dwell time that the system resides in a flow set is given.Based on this,the system with input delays can be reduced to a time-delay free system.Considering the capacity limitation of the battery,a modified MC scheme with PI+R controller is designed.The correctness of the designed scheme is verified through relevant simulations.

STABILITY ANALYSIS AND COOPERATIVE CONTROL OF DISTRIBUTED MULTI-AGENT SYSTEM WITH SAMPLED COMMUNICATION

The cooperative control and stability analysis problems for the multi-agent system with sampled com- munication are investigated. Distributed state feedback controllers are adopted for the cooperation of networked agents. A theorem in the form of linear matrix inequalities（LMI） is derived to analyze the system stability. An- other theorem in the form of optimization problem subject to LMI constraints is proposed to design the controller, and then the algorithm is presented. The simulation results verify the validity and the effectiveness of the pro- posed approach.

Distributed Economic MPC for Synergetic Regulation of the Voltage of an Island DC Micro-Grid

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.

Distributed Control of Thermostatically Controlled Loads in Distribution Network with High Penetration of Solar PV

High penetration of solar energy can result in voltage rise in midday,while growth in residential air conditioning is the main contributor of overloading and voltage drop issues during peak demand time.This paper provides a hierarchical control scheme to coordinate multiple groups of aggregated thermostatically controlled loads to regulate network loading and voltage in a distribution network.Considering the limited number of messages that can be exchanged in a realistic communication environment,an event-triggered distributed control strategy is proposed in this paper.Through intermittent on and off toggling of air conditioners,the required active power adjustment is shared among participating aggregators to solve the issue.A case study is conducted and simulation results are presented to demonstrate the performance of the proposed control scheme.