In order to achieve an automatic leveling function for work platforms of aerial vehicles with mixed-booms( MAV) in full elevating domain,an auto-leveling mechanism for the platform is proposed based on a control metho...In order to achieve an automatic leveling function for work platforms of aerial vehicles with mixed-booms( MAV) in full elevating domain,an auto-leveling mechanism for the platform is proposed based on a control method of booms-constraint,where mixed-boom structures and elevating characteristics are considered. Three models of constraint strategies include non-constraint model,elevating constraint model and lowering constraint model,which is designed to meet the leveling requirements in full working extent. Through the hydro-mechatronic unified modeling,a virtual prototype model is set up based on the auto-leveling mechanism,and leveling performances of the platform are studied during booms elevating to the maximum working height and extent. Simulation results show that the control method of booms-constraint can realize auto-leveling of the platform under two typical working conditions,meanwhile a leveling deviation appears at the constrained point,but the platform inclination is adjusted in the permissible range. The control method does not only restrict booms' freedom elevating to a certain extent,but also impacts the booms extending to the maximum working range. Experimental results verify that the auto-leveling mechanism based on booms-constraint control is valid and rational,which provides an effective technology approach for development of the platform leveling of MAV.展开更多
Based on bounded network-induced time-delay, the networked control system is modeled as a linear time-variant singular system. Using the Lyapunov theory and the linear matrix inequality approach, the criteria for dela...Based on bounded network-induced time-delay, the networked control system is modeled as a linear time-variant singular system. Using the Lyapunov theory and the linear matrix inequality approach, the criteria for delay-independent stability and delay-dependent stability of singular networked control systems are derived and transformed to a feasibility problem of linear matrix inequality formulation, which can be solved by the Matlab LMI toolbox, and the feasible solutions provide the maximum allowable delay bound that makes the system stable. A numerical example is provided, which shows that the analysis method is valid and the stability criteria are feasible.展开更多
This paper addresses the control design for automatic train operation of high-speed trains with protection constraints.A new resilient nonlinear gain-based feedback control approach is proposed,which is capable of gua...This paper addresses the control design for automatic train operation of high-speed trains with protection constraints.A new resilient nonlinear gain-based feedback control approach is proposed,which is capable of guaranteeing,under some proper non-restrictive initial conditions,the protection constraints control raised by the distance-to-go(moving authority)curve and automatic train protection in practice.A new hyperbolic tangent function-based model is presented to mimic the whole operation process of high-speed trains.The proposed feedback control methods are easily implementable and computationally inexpensive because the presence of only two feedback gains guarantee satisfactory tracking performance and closed-loop stability,no adaptations of unknown parameters,function approximation of unknown nonlinearities,and attenuation of external disturbances in the proposed control strategies.Finally,rigorous proofs and comparative simulation results are given to demonstrate the effectiveness of the proposed approaches.展开更多
A constrained decoupling (generalized predictive control) GPC algorithm is proposed for MIMO (malti-input multi-output) system. This algorithm takes account of all constraints of inputs and their increments. By solvin...A constrained decoupling (generalized predictive control) GPC algorithm is proposed for MIMO (malti-input multi-output) system. This algorithm takes account of all constraints of inputs and their increments. By solving matrix equations, the multi-step predictive decoupling controllers are realized. This algorithm need not solve Diophantine functions, and weakens the cross-coupling of the variables. At last the simulation results demon- strate the effectiveness of this proposed strategy.展开更多
The decision-making and optimization of two-echelon inventory coordination were analyzed with service level constraint and controllable lead time sensitive to order quantity.First,the basic model of this problem was e...The decision-making and optimization of two-echelon inventory coordination were analyzed with service level constraint and controllable lead time sensitive to order quantity.First,the basic model of this problem was established and based on relevant analysis,the original model could be transformed by minimax method.Then,the optimal order quantity and production quantity influenced by service level constraint were analyzed and the boundary of optimal order quantity and production quantity was given.According to this boundary,the effective method and tactics were put forward to solve the transformed model.In case analysis,the optimal expected total cost of two-echelon inventory can be obtained and it was analyzed how service level constraint and safety factor influence the optimal expected total cost of two-echelon inventory.The results show that the optimal expected total cost of two-echelon inventory is constrained by the higher constraint between service level constraint and safety factor.展开更多
Mixed-weight least-squares (MWLS) predictive control algorithm, compared with quadratic programming (QP) method, has the advantages of reducing the computer burden, quick calculation speed and dealing with the case in...Mixed-weight least-squares (MWLS) predictive control algorithm, compared with quadratic programming (QP) method, has the advantages of reducing the computer burden, quick calculation speed and dealing with the case in which the optimization is infeasible. But it can only deal with soft constraints. In order to deal with hard constraints and guarantee feasibility, an improved algorithm is proposed by recalculating the setpoint according to the hard constraints before calculating the manipulated variable and MWLS algorithm is used to satisfy the requirement of soft constraints for the system with the input constraints and output constraints. The algorithm can not only guarantee stability of the system and zero steady state error, but also satisfy the hard constraints of input and output variables. The simulation results show the improved algorithm is feasible and effective.展开更多
Because model switching system is a typical form of Takagi-Sugeno(T-S) model which is an universal approximator of continuous nonlinear systems, we describe the model switching system as mixed logical dynamical (ML...Because model switching system is a typical form of Takagi-Sugeno(T-S) model which is an universal approximator of continuous nonlinear systems, we describe the model switching system as mixed logical dynamical (MLD) system and use it in model predictive control (MPC) in this paper. Considering that each local model is only valid in each local region,we add local constraints to local models. The stability of proposed multi-model predictive control (MMPC) algorithm is analyzed, and the performance of MMPC is also demonstrated on an inulti-multi-output(MIMO) simulated pH neutralization process.展开更多
A dynamics-based adaptive control approach is proposed for a planar dual-arm space robot in the presence of closed-loop constraints and uncertain inertial parameters of the payload. The controller is capable of contro...A dynamics-based adaptive control approach is proposed for a planar dual-arm space robot in the presence of closed-loop constraints and uncertain inertial parameters of the payload. The controller is capable of controlling the po- sition and attitude of both the satellite base and the payload grasped by the manipulator end effectors. The equations of motion in reduced-order form for the constrained system are derived by incorporating the constraint equations in terms of accelerations into Kane's equations of the unconstrained system. Model analysis shows that the resulting equations perfectly meet the requirement of adaptive controller design. Consequently, by using an indirect approach, an adaptive control scheme is proposed to accomplish position/attitude trajectory tracking control with the uncertain parameters be- ing estimated on-line. The actuator redundancy due to the closed-loop constraints is utilized to minimize a weighted norm of the joint torques. Global asymptotic stability is proven by using Lyapunov's method, and simulation results are also presented to demonstrate the effectiveness of the proposed approach.展开更多
A parametric variational principle and the corresponding numerical algo- rithm are proposed to solve a linear-quadratic (LQ) optimal control problem with control inequality constraints. Based on the parametric varia...A parametric variational principle and the corresponding numerical algo- rithm are proposed to solve a linear-quadratic (LQ) optimal control problem with control inequality constraints. Based on the parametric variational principle, this control prob- lem is transformed into a set of Hamiltonian canonical equations coupled with the linear complementarity equations, which are solved by a linear complementarity solver in the discrete-time domain. The costate variable information is also evaluated by the proposed method. The parametric variational algorithm proposed in this paper is suitable for both time-invariant and time-varying systems. Two numerical examples are used to test the validity of the proposed method. The proposed algorithm is used to astrodynamics to solve a practical optimal control problem for rendezvousing spacecrafts with a finite low thrust. The numerical simulations show that the parametric variational algorithm is ef- fective for LQ optimal control problems with control inequality constraints.展开更多
A new scheme of adaptive control is proposed for a class of linear time-invariant( LTI) dynamical systems,especially in aerospace,with matched parametric uncertainties and input constraints. Based on a typical and c...A new scheme of adaptive control is proposed for a class of linear time-invariant( LTI) dynamical systems,especially in aerospace,with matched parametric uncertainties and input constraints. Based on a typical and conventional direct model reference adaptive control scheme,various modifications have been employed to achieve the goal. "C omposite model reference adaptive control"of higher performance is seam-lessly combined with "positive μ-mod",which consequently results in a smooth tracking trajectory despite of the input constraints. In addition,bounded-gain forgetting is utilized to facilitate faster convergence of parameter estimates. The stability of the closed-loop systemcan be guaranteed by using Lyapunov theory.The merits and effectiveness of the proposed method are illustrated by a numerical example of the longitudinal dynamical systems of a fixed-wing airplane.展开更多
Constraint is an important aspect of role-based access control and is sometimes argued to be the principal motivation for role-based access control (RBAC). But so far'few authors have discussed consistency mainten...Constraint is an important aspect of role-based access control and is sometimes argued to be the principal motivation for role-based access control (RBAC). But so far'few authors have discussed consistency maintenance for constraint in RBAC model. Based on researches of constraints among roles and types of inconsistency among constraints, this paper introduces correaponding formal rules, rulebased reasoning and corresponding methods to detect, avoid and resolve these inconsistencies. Finally,the paper introduces briefly the application of consistency maintenance in ZD-PDM, an enterprise-ori-ented product data management (PDM) system.展开更多
A kind of direct methods is presented for the solution of optimal control problems with state constraints. These methods are sequential quadratic programming methods. At every iteration a quadratic programming which i...A kind of direct methods is presented for the solution of optimal control problems with state constraints. These methods are sequential quadratic programming methods. At every iteration a quadratic programming which is obtained by quadratic approximation to Lagrangian function and linear approximations to constraints is solved to get a search direction for a merit function. The merit function is formulated by augmenting the Lagrangian function with a penalty term. A line search is carried out along the search direction to determine a step length such that the merit function is decreased. The methods presented in this paper include continuous sequential quadratic programming methods and discreate sequential quadratic programming methods.展开更多
The suboptimal reliable guaranteed cost control (RGCC) with multi-criterion constraints is investigated for a class of uncertain continuous-time systems with sensor faults. A fault model in sensors, which considers ou...The suboptimal reliable guaranteed cost control (RGCC) with multi-criterion constraints is investigated for a class of uncertain continuous-time systems with sensor faults. A fault model in sensors, which considers outage or partial degradation of sensors, is adopted. The influence of the disturbance on the quadratic stability of the closed-loop systems is analyzed. The reliable state-feedback controller is developed by a linear matrix inequalities (LMIs) approach, to minimize the upper bound of a quadratic cost function under the conditions that all the closed-loop poles be placed in a specified disk, and that the prescribed level of H∞ disturbance attenuation and the upper bound constraints of control inputs’ magnitudes be guaranteed. Thus, with the above multi-criterion constraints, the resulting closed-loop system can provide satisfactory stability, transient property, a disturbance rejection level and minimized quadratic cost performance despite possible sensor faults.展开更多
We present a nonlinear flow control scheme based on a buffer management model with physical constraints. It extends previous result of Pitsillides et al. in [6] by improving the queue length regulation for better serv...We present a nonlinear flow control scheme based on a buffer management model with physical constraints. It extends previous result of Pitsillides et al. in [6] by improving the queue length regulation for better service of network traffics. Besides a single node system, we also address the decentralized control of many cascaded nodes. The proposed discontinuous controller asymptotically regulates the buffer queue length at the output port of a router/switch to a constant reference value, under unknown time varying interfering traffics and saturation constraints on control input and states. Its continuous approximation achieves practical regulation with an ultimate bound on the regulation error tunable by a design parameter.展开更多
This paper deals with maximum principle for some optimal control problem governed by some elliptic variational inequalities. Some state constraints are discussed. The basic techniques used here are based on those in [...This paper deals with maximum principle for some optimal control problem governed by some elliptic variational inequalities. Some state constraints are discussed. The basic techniques used here are based on those in [1] and a new penalty functional defined in this paper.展开更多
Necessary conditions for optimality are proved for smooth infinite horizon optimal control problems with unilateral state constraints (pathwise constraints) and with terminal conditions on the states at the infinite h...Necessary conditions for optimality are proved for smooth infinite horizon optimal control problems with unilateral state constraints (pathwise constraints) and with terminal conditions on the states at the infinite horizon. The aim of the paper is to obtain strong necessary conditions including transversality conditions at infinity, which in many cases lead to a set of candidates for optimality containing only a few elements, similar to what is the case in finite horizon problems. However, strong growth conditions are needed for the results to hold.展开更多
Feasibility analysis of soft constraints for input and output variables is critical for model predictive control(MPC).When encountering the infeasible situation, some way should be found to adjust the constraints to g...Feasibility analysis of soft constraints for input and output variables is critical for model predictive control(MPC).When encountering the infeasible situation, some way should be found to adjust the constraints to guarantee that the optimal control law exists. For MPC integrated with soft sensor, considering the soft constraints for critical variables additionally makes it more complicated and difficult for feasibility analysis and constraint adjustment. Therefore, the main contributions are that a linear programming approach is proposed for feasibility analysis, and the corresponding constraint adjustment method and procedure are given as well. The feasibility analysis gives considerations to the manipulated, secondary and critical variables, and the increment of manipulated variables as well. The feasibility analysis and the constraint adjustment are conducted in the entire control process and guarantee the existence of optimal control. In final, a simulation case confirms the contributions in this paper.展开更多
This paper presents a two-stage robust model predictive control (RMPC) aigorithm named as IRMFC for uncertain linear integrating plants described by a state-space model with input constraints. The global convergence...This paper presents a two-stage robust model predictive control (RMPC) aigorithm named as IRMFC for uncertain linear integrating plants described by a state-space model with input constraints. The global convergence of the resulted closed loop system is guaranteed under mild assumption. The simulation example shows its validity and better performance than conventional Min-Max RMPC strategies.展开更多
The optimal control problems of hyperbolic H-hemivariational inequalities with the state constraints and nonnomotone multivalued mapping term are considered.The optimal solutions are obtained.In addition,their approxi...The optimal control problems of hyperbolic H-hemivariational inequalities with the state constraints and nonnomotone multivalued mapping term are considered.The optimal solutions are obtained.In addition,their approximating problems are also studied.展开更多
基金Supported by the National Natural Science Foundation of China(No.51509006)National Key Technology R&D Program(No.2015BAF07B08)Fundamental Research Funds for the Central Universities of Chang’an University(No.310825161008)
文摘In order to achieve an automatic leveling function for work platforms of aerial vehicles with mixed-booms( MAV) in full elevating domain,an auto-leveling mechanism for the platform is proposed based on a control method of booms-constraint,where mixed-boom structures and elevating characteristics are considered. Three models of constraint strategies include non-constraint model,elevating constraint model and lowering constraint model,which is designed to meet the leveling requirements in full working extent. Through the hydro-mechatronic unified modeling,a virtual prototype model is set up based on the auto-leveling mechanism,and leveling performances of the platform are studied during booms elevating to the maximum working height and extent. Simulation results show that the control method of booms-constraint can realize auto-leveling of the platform under two typical working conditions,meanwhile a leveling deviation appears at the constrained point,but the platform inclination is adjusted in the permissible range. The control method does not only restrict booms' freedom elevating to a certain extent,but also impacts the booms extending to the maximum working range. Experimental results verify that the auto-leveling mechanism based on booms-constraint control is valid and rational,which provides an effective technology approach for development of the platform leveling of MAV.
基金the National Natural Science Foundation of China (60574011)the National Natural Science Foundation of Liaoning Province (2050770).
文摘Based on bounded network-induced time-delay, the networked control system is modeled as a linear time-variant singular system. Using the Lyapunov theory and the linear matrix inequality approach, the criteria for delay-independent stability and delay-dependent stability of singular networked control systems are derived and transformed to a feasibility problem of linear matrix inequality formulation, which can be solved by the Matlab LMI toolbox, and the feasible solutions provide the maximum allowable delay bound that makes the system stable. A numerical example is provided, which shows that the analysis method is valid and the stability criteria are feasible.
基金supported jointly by the National Natural Science Foundation of China(61703033,61790573)Beijing Natural Science Foundation(4192046)+1 种基金Fundamental Research Funds for Central Universities(2018JBZ002)State Key Laboratory of Rail Traffic Control and Safety(RCS2018ZT013),Beijing Jiaotong University
文摘This paper addresses the control design for automatic train operation of high-speed trains with protection constraints.A new resilient nonlinear gain-based feedback control approach is proposed,which is capable of guaranteeing,under some proper non-restrictive initial conditions,the protection constraints control raised by the distance-to-go(moving authority)curve and automatic train protection in practice.A new hyperbolic tangent function-based model is presented to mimic the whole operation process of high-speed trains.The proposed feedback control methods are easily implementable and computationally inexpensive because the presence of only two feedback gains guarantee satisfactory tracking performance and closed-loop stability,no adaptations of unknown parameters,function approximation of unknown nonlinearities,and attenuation of external disturbances in the proposed control strategies.Finally,rigorous proofs and comparative simulation results are given to demonstrate the effectiveness of the proposed approaches.
基金Supported by the National Natural Science Foundation of China (No.60374037, No.60574036), the Program for New Century Excellent Talents in University of China (NCET), and the Specialized Research Fund for the Doctoral Program of Higher Edu-cation of China (No.20050055013).
文摘A constrained decoupling (generalized predictive control) GPC algorithm is proposed for MIMO (malti-input multi-output) system. This algorithm takes account of all constraints of inputs and their increments. By solving matrix equations, the multi-step predictive decoupling controllers are realized. This algorithm need not solve Diophantine functions, and weakens the cross-coupling of the variables. At last the simulation results demon- strate the effectiveness of this proposed strategy.
基金Project(71102174,71372019)supported by the National Natural Science Foundation of ChinaProject(9123028)supported by the Beijing Natural Science Foundation of China+3 种基金Project(20111101120019)supported by the Specialized Research Fund for Doctoral Program of Higher Education of ChinaProject(11JGC106)supported by the Beijing Philosophy&Social Science Foundation of ChinaProjects(NCET-10-0048,NCET-10-0043)supported by the Program for New Century Excellent Talents in University of ChinaProject(2010YC1307)supported by Excellent Young Teacher in Beijing Institute of Technology of China
文摘The decision-making and optimization of two-echelon inventory coordination were analyzed with service level constraint and controllable lead time sensitive to order quantity.First,the basic model of this problem was established and based on relevant analysis,the original model could be transformed by minimax method.Then,the optimal order quantity and production quantity influenced by service level constraint were analyzed and the boundary of optimal order quantity and production quantity was given.According to this boundary,the effective method and tactics were put forward to solve the transformed model.In case analysis,the optimal expected total cost of two-echelon inventory can be obtained and it was analyzed how service level constraint and safety factor influence the optimal expected total cost of two-echelon inventory.The results show that the optimal expected total cost of two-echelon inventory is constrained by the higher constraint between service level constraint and safety factor.
基金National Key Basic Research and Development(No.2002CB312200)
文摘Mixed-weight least-squares (MWLS) predictive control algorithm, compared with quadratic programming (QP) method, has the advantages of reducing the computer burden, quick calculation speed and dealing with the case in which the optimization is infeasible. But it can only deal with soft constraints. In order to deal with hard constraints and guarantee feasibility, an improved algorithm is proposed by recalculating the setpoint according to the hard constraints before calculating the manipulated variable and MWLS algorithm is used to satisfy the requirement of soft constraints for the system with the input constraints and output constraints. The algorithm can not only guarantee stability of the system and zero steady state error, but also satisfy the hard constraints of input and output variables. The simulation results show the improved algorithm is feasible and effective.
文摘Because model switching system is a typical form of Takagi-Sugeno(T-S) model which is an universal approximator of continuous nonlinear systems, we describe the model switching system as mixed logical dynamical (MLD) system and use it in model predictive control (MPC) in this paper. Considering that each local model is only valid in each local region,we add local constraints to local models. The stability of proposed multi-model predictive control (MMPC) algorithm is analyzed, and the performance of MMPC is also demonstrated on an inulti-multi-output(MIMO) simulated pH neutralization process.
基金supported by the National Natural Science Foundation of China(11272027)
文摘A dynamics-based adaptive control approach is proposed for a planar dual-arm space robot in the presence of closed-loop constraints and uncertain inertial parameters of the payload. The controller is capable of controlling the po- sition and attitude of both the satellite base and the payload grasped by the manipulator end effectors. The equations of motion in reduced-order form for the constrained system are derived by incorporating the constraint equations in terms of accelerations into Kane's equations of the unconstrained system. Model analysis shows that the resulting equations perfectly meet the requirement of adaptive controller design. Consequently, by using an indirect approach, an adaptive control scheme is proposed to accomplish position/attitude trajectory tracking control with the uncertain parameters be- ing estimated on-line. The actuator redundancy due to the closed-loop constraints is utilized to minimize a weighted norm of the joint torques. Global asymptotic stability is proven by using Lyapunov's method, and simulation results are also presented to demonstrate the effectiveness of the proposed approach.
基金supported by the National Natural Science Foundation of China(Nos.11102031 and 11272076)the Fundamental Research Funds for Central Universities(No.DUT13LK25)+2 种基金the Key Laboratory Fund of Liaoning Province(No.L2013015)the China Postdoctoral Science Foundation(No.2014M550155)the State Key Laboratory of Mechanics and Control of Mechanical Structures(Nanjing University of Aeronautics and Astronautics)(No.MCMS-0114G02)
文摘A parametric variational principle and the corresponding numerical algo- rithm are proposed to solve a linear-quadratic (LQ) optimal control problem with control inequality constraints. Based on the parametric variational principle, this control prob- lem is transformed into a set of Hamiltonian canonical equations coupled with the linear complementarity equations, which are solved by a linear complementarity solver in the discrete-time domain. The costate variable information is also evaluated by the proposed method. The parametric variational algorithm proposed in this paper is suitable for both time-invariant and time-varying systems. Two numerical examples are used to test the validity of the proposed method. The proposed algorithm is used to astrodynamics to solve a practical optimal control problem for rendezvousing spacecrafts with a finite low thrust. The numerical simulations show that the parametric variational algorithm is ef- fective for LQ optimal control problems with control inequality constraints.
基金Supported by Deep Exploration Technology and Experimentation Project(201311194-04)
文摘A new scheme of adaptive control is proposed for a class of linear time-invariant( LTI) dynamical systems,especially in aerospace,with matched parametric uncertainties and input constraints. Based on a typical and conventional direct model reference adaptive control scheme,various modifications have been employed to achieve the goal. "C omposite model reference adaptive control"of higher performance is seam-lessly combined with "positive μ-mod",which consequently results in a smooth tracking trajectory despite of the input constraints. In addition,bounded-gain forgetting is utilized to facilitate faster convergence of parameter estimates. The stability of the closed-loop systemcan be guaranteed by using Lyapunov theory.The merits and effectiveness of the proposed method are illustrated by a numerical example of the longitudinal dynamical systems of a fixed-wing airplane.
文摘Constraint is an important aspect of role-based access control and is sometimes argued to be the principal motivation for role-based access control (RBAC). But so far'few authors have discussed consistency maintenance for constraint in RBAC model. Based on researches of constraints among roles and types of inconsistency among constraints, this paper introduces correaponding formal rules, rulebased reasoning and corresponding methods to detect, avoid and resolve these inconsistencies. Finally,the paper introduces briefly the application of consistency maintenance in ZD-PDM, an enterprise-ori-ented product data management (PDM) system.
文摘A kind of direct methods is presented for the solution of optimal control problems with state constraints. These methods are sequential quadratic programming methods. At every iteration a quadratic programming which is obtained by quadratic approximation to Lagrangian function and linear approximations to constraints is solved to get a search direction for a merit function. The merit function is formulated by augmenting the Lagrangian function with a penalty term. A line search is carried out along the search direction to determine a step length such that the merit function is decreased. The methods presented in this paper include continuous sequential quadratic programming methods and discreate sequential quadratic programming methods.
基金the National Natural Science Foundation of China (No. 60574082)the National Creative Research Groups Sci-ence Foundation of China (No. 60721062)the China Postdoc-toral Science Foundation (No. 20070411178)
文摘The suboptimal reliable guaranteed cost control (RGCC) with multi-criterion constraints is investigated for a class of uncertain continuous-time systems with sensor faults. A fault model in sensors, which considers outage or partial degradation of sensors, is adopted. The influence of the disturbance on the quadratic stability of the closed-loop systems is analyzed. The reliable state-feedback controller is developed by a linear matrix inequalities (LMIs) approach, to minimize the upper bound of a quadratic cost function under the conditions that all the closed-loop poles be placed in a specified disk, and that the prescribed level of H∞ disturbance attenuation and the upper bound constraints of control inputs’ magnitudes be guaranteed. Thus, with the above multi-criterion constraints, the resulting closed-loop system can provide satisfactory stability, transient property, a disturbance rejection level and minimized quadratic cost performance despite possible sensor faults.
基金Supported in part by the National Science Foundation under grants ANI-0081527 and ECS-0093176
文摘We present a nonlinear flow control scheme based on a buffer management model with physical constraints. It extends previous result of Pitsillides et al. in [6] by improving the queue length regulation for better service of network traffics. Besides a single node system, we also address the decentralized control of many cascaded nodes. The proposed discontinuous controller asymptotically regulates the buffer queue length at the output port of a router/switch to a constant reference value, under unknown time varying interfering traffics and saturation constraints on control input and states. Its continuous approximation achieves practical regulation with an ultimate bound on the regulation error tunable by a design parameter.
文摘This paper deals with maximum principle for some optimal control problem governed by some elliptic variational inequalities. Some state constraints are discussed. The basic techniques used here are based on those in [1] and a new penalty functional defined in this paper.
文摘Necessary conditions for optimality are proved for smooth infinite horizon optimal control problems with unilateral state constraints (pathwise constraints) and with terminal conditions on the states at the infinite horizon. The aim of the paper is to obtain strong necessary conditions including transversality conditions at infinity, which in many cases lead to a set of candidates for optimality containing only a few elements, similar to what is the case in finite horizon problems. However, strong growth conditions are needed for the results to hold.
文摘Feasibility analysis of soft constraints for input and output variables is critical for model predictive control(MPC).When encountering the infeasible situation, some way should be found to adjust the constraints to guarantee that the optimal control law exists. For MPC integrated with soft sensor, considering the soft constraints for critical variables additionally makes it more complicated and difficult for feasibility analysis and constraint adjustment. Therefore, the main contributions are that a linear programming approach is proposed for feasibility analysis, and the corresponding constraint adjustment method and procedure are given as well. The feasibility analysis gives considerations to the manipulated, secondary and critical variables, and the increment of manipulated variables as well. The feasibility analysis and the constraint adjustment are conducted in the entire control process and guarantee the existence of optimal control. In final, a simulation case confirms the contributions in this paper.
文摘This paper presents a two-stage robust model predictive control (RMPC) aigorithm named as IRMFC for uncertain linear integrating plants described by a state-space model with input constraints. The global convergence of the resulted closed loop system is guaranteed under mild assumption. The simulation example shows its validity and better performance than conventional Min-Max RMPC strategies.
文摘The optimal control problems of hyperbolic H-hemivariational inequalities with the state constraints and nonnomotone multivalued mapping term are considered.The optimal solutions are obtained.In addition,their approximating problems are also studied.