A general method of controller design is developed for the purpose offormation keeping and reconfiguration of nonlinear systems with multiple subsystems, such as theformation of multiple aircraft, ground vehicles, or ...A general method of controller design is developed for the purpose offormation keeping and reconfiguration of nonlinear systems with multiple subsystems, such as theformation of multiple aircraft, ground vehicles, or robot arms. The model consists of multiplenonlinear systems. Controllers are designed to keep the subsystems in a required formation and tocoordinate the subsystems in the presence of environmental changes. A step-by-step algorithm ofcontroller design is developed. Sufficient conditions for the stability of formation tracking areproved. Simulations and experiments are conducted to demonstrate some useful coordination strategiessuch as movement with a leader, simultaneous movement, series connection of formations, andhuman-machine interaction.展开更多
This paper proposes a switching multi-objective model predictive control(MOMPC) algorithm for constrained nonlinear continuous-time process systems.Different cost functions to be minimized in MPC are switched to satis...This paper proposes a switching multi-objective model predictive control(MOMPC) algorithm for constrained nonlinear continuous-time process systems.Different cost functions to be minimized in MPC are switched to satisfy different performance criteria imposed at different sampling times.In order to ensure recursive feasibility of the switching MOMPC and stability of the resulted closed-loop system,the dual-mode control method is used to design the switching MOMPC controller.In this method,a local control law with some free-parameters is constructed using the control Lyapunov function technique to enlarge the terminal state set of MOMPC.The correction term is computed if the states are out of the terminal set and the free-parameters of the local control law are computed if the states are in the terminal set.The recursive feasibility of the MOMPC and stability of the resulted closed-loop system are established in the presence of constraints and arbitrary switches between cost functions.Finally,implementation of the switching MOMPC controller is demonstrated with a chemical process example for the continuous stirred tank reactor.展开更多
An advanced nonlinear robust control scheme is proposed for multi-machine power systems equipped with thyristor-controlled series compensation (TCSC). First, a decentralized nonlinear robust control approach based on ...An advanced nonlinear robust control scheme is proposed for multi-machine power systems equipped with thyristor-controlled series compensation (TCSC). First, a decentralized nonlinear robust control approach based on the feedback linearization and H∞ theory is introduced to eliminate the nonlinearities and interconnections of the studied system, and to attenuate the exogenous disturbances that enter die system. Then, a system model is built up, which has considered all the generators’ and TCSC’s dynamics, and the effects of uncertainties such as disturbances. Next, a decentralized nonlinear robust coordinated control law is developed based on this model. Simulation results on a six-machine power system show that the transient stability of the power system is obviously improved and die power transfer capacity of long distance transmission lines is enhanced regardless of fault locations and system operation points. In addition, the control law has engineering practicality since all the variables in the expression of he control strategy can be measured locally.展开更多
This paper proposes a new type of nonlinear controllers and a large phase angle allowance design method based on the multi-objective optimal control system. With the proposed method, the performance of the system beco...This paper proposes a new type of nonlinear controllers and a large phase angle allowance design method based on the multi-objective optimal control system. With the proposed method, the performance of the system becomes better than that of the original system. Then, an example of the radar servo system is designed with a large phase angle allowance multi-objective optimal design method. Finally, the performance based on computer simulation demonstrates that the multi-objective optimal system is superior to linear optimal systems.展开更多
Nonlinear model predictive control(NMPC)scheme is an effective method of multi-objective optimization control in complex industrial systems.In this paper,a NMPC scheme for the wet limestone flue gas desulphurization(W...Nonlinear model predictive control(NMPC)scheme is an effective method of multi-objective optimization control in complex industrial systems.In this paper,a NMPC scheme for the wet limestone flue gas desulphurization(WFGD)system is proposed which provides a more flexible framework of optimal control and decision-making compared with PID scheme.At first,a mathematical model of the FGD process is deduced which is suitable for NMPC structure.To equipoise the model’s accuracy and conciseness,the wet limestone FGD system is separated into several modules.Based on the conservation laws,a model with reasonable simplification is developed to describe dynamics of different modules for the purpose of controller design.Then,by addressing economic objectives directly into the NMPC scheme,the NMPC controller can minimize economic cost and track the set-point simultaneously.The accuracy of model is validated by the field data of a 1000 MW thermal power plant in Henan Province,China.The simulation results show that the NMPC strategy improves the economic performance and ensures the emission requirement at the same time.In the meantime,the control scheme satisfies the multiobjective control requirements under complex operation conditions(e.g.,boiler load fluctuation and set point variation).The mathematical model and NMPC structure provides the basic work for the future development of advanced optimized control algorithms in the wet limestone FGD systems.展开更多
This paper presents a Nonlinear Model Predictive Controller(NMPC)for the path following of autonomous vehicles and an algorithm to adaptively adjust the preview distance.The prediction model includes vehicle dynamics,...This paper presents a Nonlinear Model Predictive Controller(NMPC)for the path following of autonomous vehicles and an algorithm to adaptively adjust the preview distance.The prediction model includes vehicle dynamics,path following dynamics,and system input dynamics.The single-track vehicle model considers the vehicle’s coupled lateral and longitudinal dynamics,as well as nonlinear tire forces.The tracking error dynamics are derived based on the curvilinear coordinates.The cost function is designed to minimize path tracking errors and control effort while considering constraints such as actuator bounds and tire grip limits.An algorithm that utilizes the optimal preview distance vector to query the corresponding reference curvature and reference speed.The length of the preview path is adaptively adjusted based on the vehicle speed,heading error,and path curvature.We validate the controller performance in a simulation environment with the autonomous racing scenario.The simulation results show that the vehicle accurately follows the highly dynamic path with small tracking errors.The maximum preview distance can be prior estimated and guidance the selection of the prediction horizon for NMPC.展开更多
In allusion to the characteristics of the open complex giant system, an open multilevel hierarchic intelligent control system is established for the eco-industrial system. With the idea of the open engineering system,...In allusion to the characteristics of the open complex giant system, an open multilevel hierarchic intelligent control system is established for the eco-industrial system. With the idea of the open engineering system, using the hall for workshop of metasynthetic engineering （HWME）, intelligent control techniques, the expert system and the design of experiments are integrated within the framework of the nonlinear multiobjective decision support system to develop a robust, top-level design specification so as to make the system have the quality of adaptive control, self-organizing, self-learning and robustness. Finally, an illustrative example is given to clarify the effectiveness of the method.展开更多
In this paper,distributed power flow controller(DPFC)constraints are analyzed.The energy balance relationship between fundamental wave and third harmonic in series and shunt-side converter is deduced.A proportional in...In this paper,distributed power flow controller(DPFC)constraints are analyzed.The energy balance relationship between fundamental wave and third harmonic in series and shunt-side converter is deduced.A proportional integral(PI)controller of the DPFC is constructed.The PI controller uses the voltage amplitude and phase angle injected into the system in the series side,along with the modulation ratio of the three-phase converter on the shunt side as the control variables.A multiobjective coordinated control equation is proposed,which factors the constraints of the energy balance between series and shunt side,device capacity limit,safe operation limit,fundamental component,as well as third harmonic component of the injection voltage at the series side.The equation minimizes the variance between the actual value of the control target and its given value to ensure that the DC capacitor voltage,both in the series and shunt side,is stable at target value.Simulations are conducted to verify correctness and effectiveness of the proposed control method.展开更多
In this paper,the problems of robust consensus tracking control for the second-order multi-agent system with uncertain model parameters and nonlinear disturbances are considered.An adaptive control strategy is propose...In this paper,the problems of robust consensus tracking control for the second-order multi-agent system with uncertain model parameters and nonlinear disturbances are considered.An adaptive control strategy is proposed to smooth the agent’s trajectory,and the neural network is constructed to estimate the system’s unknown components.The consensus conditions are demonstrated for tracking a leader with nonlinear dynamics under an adaptive control algorithm in the absence of model uncertainties.Then,the results are extended to the system with unknown time-varying disturbances by applying the neural network estimation to compensating for the uncertain parts of the agents’models.Update laws are designed based on the Lyapunov function terms to ensure the effectiveness of robust control.Finally,the theoretical results are verified by numerical simulations,and a comparative experiment is conducted,showing that the trajectories generated by the proposed method exhibit less oscillation and converge faster.展开更多
Dear Editor,This letter addresses the challenge of achieving robust global coordination in multi-agent systems(MASs)subject to heterogeneous actuator saturation and additive input disturbances.We develop a novel distr...Dear Editor,This letter addresses the challenge of achieving robust global coordination in multi-agent systems(MASs)subject to heterogeneous actuator saturation and additive input disturbances.We develop a novel distributed control framework that strategically integrates a redesigned saturation function to handle the nonlinear actuator constraint and a high-gain feedback mechanism for effective disturbance rejection.展开更多
In this paper, the platoon control problem of autonomous vehicles in highway is studied. Since the autonomous vehicles have the characteristics of nonlinearities, external disturbances and strong coupling, a novel ada...In this paper, the platoon control problem of autonomous vehicles in highway is studied. Since the autonomous vehicles have the characteristics of nonlinearities, external disturbances and strong coupling, a novel adaptive fuzzy sliding coordinated control system is constructed to supervise the longitudinal and lateral motions of autonomous vehicles, in which the fuzzy system is employed to approximate the unknown nonlinear functions. Due to the low sensitivity to disturbances and plant parameter variations, the proposed control approach is an efficient way to handle with the complex dynamic plants operating under un-certainty conditions. The asymptotic stability of adaptive coordinated platoon close-loop control system is verified based on the Lyapunov stability theory. The results indicate that the presented adaptive coordinated platoon control approach can accurately achieve the tracking performance and ensures the stability and riding comfort of autonomous vehicles in a platoon. Finally,simulation test is exploited to demonstrate the effectiveness of the proposed control approach.展开更多
针对含不确定因素的多输入多输出非线性微分代数系统,提出一种目标全息反馈鲁棒自适应控制方法(robust adaptive control with objective holographic feedbacks,RACOHF).该方法考虑到了系统模型参数的不确定性和外部扰动,同时将外部输...针对含不确定因素的多输入多输出非线性微分代数系统,提出一种目标全息反馈鲁棒自适应控制方法(robust adaptive control with objective holographic feedbacks,RACOHF).该方法考虑到了系统模型参数的不确定性和外部扰动,同时将外部输入扰动视为模型不确定性参数的变化,在目标全息反馈控制方法的基础上,通过设计模型不确定性部分的自适应调节律,实现多目标的自适应跟踪控制.将该方法应用于中间再热式汽轮发电机组蒸汽调节阀和励磁的协调控制,结果表明,在系统部分参数不确定和存在外部扰动的情况下,所提出方法能确保发电机机端电压和有功功率等目标量在期望的工作点上运行而不发生静态偏移.与目标全息反馈非线性控制(nonlinear control with objective holographic feedbacks,NCOHF)相比,所提出的方法(RACOHF)能更好地协调系统的动、静态性能.展开更多
文摘A general method of controller design is developed for the purpose offormation keeping and reconfiguration of nonlinear systems with multiple subsystems, such as theformation of multiple aircraft, ground vehicles, or robot arms. The model consists of multiplenonlinear systems. Controllers are designed to keep the subsystems in a required formation and tocoordinate the subsystems in the presence of environmental changes. A step-by-step algorithm ofcontroller design is developed. Sufficient conditions for the stability of formation tracking areproved. Simulations and experiments are conducted to demonstrate some useful coordination strategiessuch as movement with a leader, simultaneous movement, series connection of formations, andhuman-machine interaction.
基金Supported by the National Natural Science Foundation of China(61374111)the Natural Science Foundation of Zhejiang Province(LY13F030006)Agricultural Key Program of Ningbo City(2014C10068)
文摘This paper proposes a switching multi-objective model predictive control(MOMPC) algorithm for constrained nonlinear continuous-time process systems.Different cost functions to be minimized in MPC are switched to satisfy different performance criteria imposed at different sampling times.In order to ensure recursive feasibility of the switching MOMPC and stability of the resulted closed-loop system,the dual-mode control method is used to design the switching MOMPC controller.In this method,a local control law with some free-parameters is constructed using the control Lyapunov function technique to enlarge the terminal state set of MOMPC.The correction term is computed if the states are out of the terminal set and the free-parameters of the local control law are computed if the states are in the terminal set.The recursive feasibility of the MOMPC and stability of the resulted closed-loop system are established in the presence of constraints and arbitrary switches between cost functions.Finally,implementation of the switching MOMPC controller is demonstrated with a chemical process example for the continuous stirred tank reactor.
基金This work was supported by Chinese National Natural Science Foundation(No.50377018)Chinese National Key Basic Research Fund(No.G1998020309)by New Energy and Industrial Technology Development Organization of Japan.
文摘An advanced nonlinear robust control scheme is proposed for multi-machine power systems equipped with thyristor-controlled series compensation (TCSC). First, a decentralized nonlinear robust control approach based on the feedback linearization and H∞ theory is introduced to eliminate the nonlinearities and interconnections of the studied system, and to attenuate the exogenous disturbances that enter die system. Then, a system model is built up, which has considered all the generators’ and TCSC’s dynamics, and the effects of uncertainties such as disturbances. Next, a decentralized nonlinear robust coordinated control law is developed based on this model. Simulation results on a six-machine power system show that the transient stability of the power system is obviously improved and die power transfer capacity of long distance transmission lines is enhanced regardless of fault locations and system operation points. In addition, the control law has engineering practicality since all the variables in the expression of he control strategy can be measured locally.
基金partly supported by the Natural Science Foundation of Guangdong (No.06023131)
文摘This paper proposes a new type of nonlinear controllers and a large phase angle allowance design method based on the multi-objective optimal control system. With the proposed method, the performance of the system becomes better than that of the original system. Then, an example of the radar servo system is designed with a large phase angle allowance multi-objective optimal design method. Finally, the performance based on computer simulation demonstrates that the multi-objective optimal system is superior to linear optimal systems.
基金Financial support from the National Key R&D Program of China(No.2017YFB0601805)。
文摘Nonlinear model predictive control(NMPC)scheme is an effective method of multi-objective optimization control in complex industrial systems.In this paper,a NMPC scheme for the wet limestone flue gas desulphurization(WFGD)system is proposed which provides a more flexible framework of optimal control and decision-making compared with PID scheme.At first,a mathematical model of the FGD process is deduced which is suitable for NMPC structure.To equipoise the model’s accuracy and conciseness,the wet limestone FGD system is separated into several modules.Based on the conservation laws,a model with reasonable simplification is developed to describe dynamics of different modules for the purpose of controller design.Then,by addressing economic objectives directly into the NMPC scheme,the NMPC controller can minimize economic cost and track the set-point simultaneously.The accuracy of model is validated by the field data of a 1000 MW thermal power plant in Henan Province,China.The simulation results show that the NMPC strategy improves the economic performance and ensures the emission requirement at the same time.In the meantime,the control scheme satisfies the multiobjective control requirements under complex operation conditions(e.g.,boiler load fluctuation and set point variation).The mathematical model and NMPC structure provides the basic work for the future development of advanced optimized control algorithms in the wet limestone FGD systems.
基金“National Science and Technology Council”(NSTC 111-2221-E-027-088)。
文摘This paper presents a Nonlinear Model Predictive Controller(NMPC)for the path following of autonomous vehicles and an algorithm to adaptively adjust the preview distance.The prediction model includes vehicle dynamics,path following dynamics,and system input dynamics.The single-track vehicle model considers the vehicle’s coupled lateral and longitudinal dynamics,as well as nonlinear tire forces.The tracking error dynamics are derived based on the curvilinear coordinates.The cost function is designed to minimize path tracking errors and control effort while considering constraints such as actuator bounds and tire grip limits.An algorithm that utilizes the optimal preview distance vector to query the corresponding reference curvature and reference speed.The length of the preview path is adaptively adjusted based on the vehicle speed,heading error,and path curvature.We validate the controller performance in a simulation environment with the autonomous racing scenario.The simulation results show that the vehicle accurately follows the highly dynamic path with small tracking errors.The maximum preview distance can be prior estimated and guidance the selection of the prediction horizon for NMPC.
文摘In allusion to the characteristics of the open complex giant system, an open multilevel hierarchic intelligent control system is established for the eco-industrial system. With the idea of the open engineering system, using the hall for workshop of metasynthetic engineering （HWME）, intelligent control techniques, the expert system and the design of experiments are integrated within the framework of the nonlinear multiobjective decision support system to develop a robust, top-level design specification so as to make the system have the quality of adaptive control, self-organizing, self-learning and robustness. Finally, an illustrative example is given to clarify the effectiveness of the method.
基金This work was supported in part by the State Grid Corporation of China(Grant No.52150016000Y)in part by the State Key Laboratory of Power Grid Safety and Energy Conservation(China Electric Power Research Institute)Open Fund,the Major Projects of Technical Innovation in Hubei(Grant No.2018AAA050)the Major Projects of Technical Innovation in Hubei(Grant No.2019AAA016).
文摘In this paper,distributed power flow controller(DPFC)constraints are analyzed.The energy balance relationship between fundamental wave and third harmonic in series and shunt-side converter is deduced.A proportional integral(PI)controller of the DPFC is constructed.The PI controller uses the voltage amplitude and phase angle injected into the system in the series side,along with the modulation ratio of the three-phase converter on the shunt side as the control variables.A multiobjective coordinated control equation is proposed,which factors the constraints of the energy balance between series and shunt side,device capacity limit,safe operation limit,fundamental component,as well as third harmonic component of the injection voltage at the series side.The equation minimizes the variance between the actual value of the control target and its given value to ensure that the DC capacitor voltage,both in the series and shunt side,is stable at target value.Simulations are conducted to verify correctness and effectiveness of the proposed control method.
基金supported by the Science&Technology Department of Sichuan Province under Grant No.2020YJ0044。
文摘In this paper,the problems of robust consensus tracking control for the second-order multi-agent system with uncertain model parameters and nonlinear disturbances are considered.An adaptive control strategy is proposed to smooth the agent’s trajectory,and the neural network is constructed to estimate the system’s unknown components.The consensus conditions are demonstrated for tracking a leader with nonlinear dynamics under an adaptive control algorithm in the absence of model uncertainties.Then,the results are extended to the system with unknown time-varying disturbances by applying the neural network estimation to compensating for the uncertain parts of the agents’models.Update laws are designed based on the Lyapunov function terms to ensure the effectiveness of robust control.Finally,the theoretical results are verified by numerical simulations,and a comparative experiment is conducted,showing that the trajectories generated by the proposed method exhibit less oscillation and converge faster.
基金supported in part by the National Natural Science Foundation of China(62522313,62473207,U25A20301)the Fundamental Research Funds for the Central Universities(2024SMECP03)。
文摘Dear Editor,This letter addresses the challenge of achieving robust global coordination in multi-agent systems(MASs)subject to heterogeneous actuator saturation and additive input disturbances.We develop a novel distributed control framework that strategically integrates a redesigned saturation function to handle the nonlinear actuator constraint and a high-gain feedback mechanism for effective disturbance rejection.
基金supported by the National Natural Science Foundation of China(Grant Nos.61304193&U1564208)National Key R&D Program of China(Grant No.2016YFB0100900)
文摘In this paper, the platoon control problem of autonomous vehicles in highway is studied. Since the autonomous vehicles have the characteristics of nonlinearities, external disturbances and strong coupling, a novel adaptive fuzzy sliding coordinated control system is constructed to supervise the longitudinal and lateral motions of autonomous vehicles, in which the fuzzy system is employed to approximate the unknown nonlinear functions. Due to the low sensitivity to disturbances and plant parameter variations, the proposed control approach is an efficient way to handle with the complex dynamic plants operating under un-certainty conditions. The asymptotic stability of adaptive coordinated platoon close-loop control system is verified based on the Lyapunov stability theory. The results indicate that the presented adaptive coordinated platoon control approach can accurately achieve the tracking performance and ensures the stability and riding comfort of autonomous vehicles in a platoon. Finally,simulation test is exploited to demonstrate the effectiveness of the proposed control approach.
文摘针对含不确定因素的多输入多输出非线性微分代数系统,提出一种目标全息反馈鲁棒自适应控制方法(robust adaptive control with objective holographic feedbacks,RACOHF).该方法考虑到了系统模型参数的不确定性和外部扰动,同时将外部输入扰动视为模型不确定性参数的变化,在目标全息反馈控制方法的基础上,通过设计模型不确定性部分的自适应调节律,实现多目标的自适应跟踪控制.将该方法应用于中间再热式汽轮发电机组蒸汽调节阀和励磁的协调控制,结果表明,在系统部分参数不确定和存在外部扰动的情况下,所提出方法能确保发电机机端电压和有功功率等目标量在期望的工作点上运行而不发生静态偏移.与目标全息反馈非线性控制(nonlinear control with objective holographic feedbacks,NCOHF)相比,所提出的方法(RACOHF)能更好地协调系统的动、静态性能.
