External disturbances or inaccurate mathematical model built will inevitably impose a disadvantageous effect on the robot system,which generates positioning errors,vibrations,as well as weakening control performances ...External disturbances or inaccurate mathematical model built will inevitably impose a disadvantageous effect on the robot system,which generates positioning errors,vibrations,as well as weakening control performances of the system. The strategy of combining adaptive radial basis function( RBF) neural network control and composite nonlinear feedback( CNF) control is studied,and a robot CNF controller based on RBF neural network compensation is proposed. The core is to use RBF neural network control to approach the uncertainty of the system online,as the compensation term of the CNF controller,and make full use of the advantages of the two control methods to reduce the influence of uncertain factors on the performance of the system. The convergence of closed-loop system is proved. Simulation results demonstrate the effectiveness of this strategy.展开更多
Transient performance for output regulation problems of linear discrete-time systems with input saturation is addressed by using the composite nonlinear feedback（CNF） control technique. The regulator is designed to ...Transient performance for output regulation problems of linear discrete-time systems with input saturation is addressed by using the composite nonlinear feedback（CNF） control technique. The regulator is designed to be an additive combination of a linear regulator part and a nonlinear feedback part. The linear regulator part solves the regulation problem independently which produces a quick output response but large oscillations. The nonlinear feedback part with well-tuned parameters is introduced to improve the transient performance by smoothing the oscillatory convergence. It is shown that the introduction of the nonlinear feedback part does not change the solvability conditions of the linear discrete-time output regulation problem. The effectiveness of transient improvement is illustrated by a numeric example.展开更多
In order to suppress the influence of uncertain factors on robot system and enable an uncertain robot system to track the reference input accurately,a strategy of combining composite nonlinear feedback(CNF)control and...In order to suppress the influence of uncertain factors on robot system and enable an uncertain robot system to track the reference input accurately,a strategy of combining composite nonlinear feedback(CNF)control and adaptive fuzzy control is studied,and a robot CNF controller based on adaptive fuzzy compensation is proposed.The key of this strategy is to use adaptive fuzzy control to approach the uncertainty of the system online,as the compensation term of the CNF controller,and make full use of the advantages of the two control methods to reduce the influence of uncertain factors on the performance of the system.The convergence of the closed-loop system is proved by feedback linearization and Lyapunov theory.The final simulation results confirm the effectiveness of this plan.展开更多
Composite nonlinear feedback （CNF） control techniquefor tracking control problems is extended to the output regulationproblem of singular linear systems with input saturation. A statefeedback CNF control law and an ...Composite nonlinear feedback （CNF） control techniquefor tracking control problems is extended to the output regulationproblem of singular linear systems with input saturation. A statefeedback CNF control law and an output feedback CNF controllaw are constructed respectively for the output regulation problemof singular linear systems with input saturation. It is shown thatthe output regulation problem by CNF control is solvable underthe same solvability conditions of the output regulation problemby linear control. However, with the virtue of the CNF control, thetransient performance of the closed-loop system can be improvedby carefully designing the linear part and the nonlinear part of theCNF control law. The design procedure and the improvement ofthe transient performance of the closed-loop system are illustratedwith a numerical simulation.展开更多
A composite nonlinear feedback tracking controller for motion control of robot manipulators is described. The structure of the controller is composed of a composite nonlinear feedback law plus full robot nonlinear dyn...A composite nonlinear feedback tracking controller for motion control of robot manipulators is described. The structure of the controller is composed of a composite nonlinear feedback law plus full robot nonlinear dynamics compensation. The stability is carried out in the presence of friction. The controller takes advantage of varying damping ratios induced by the composite nonlinear feedback control, so the transient performance of the closed-loop is remarkably improved. Simulation results demonstrate the feasibility of the proposed method.展开更多
This paper investigates the cooperative output regulation problem of linear multi-agent systems with a linear exogenous system(exo-system).The network topology is described by a directed graph which contains a directe...This paper investigates the cooperative output regulation problem of linear multi-agent systems with a linear exogenous system(exo-system).The network topology is described by a directed graph which contains a directed spanning tree with the exo-system as the root.Aiming at improving the transient performance of the multi-agent systems,a dynamic control law is developed by the composite nonlinear feedback(CNF)control technique.In particular,a distributed dynamic compensator independent of the interaction on the compensator states of agents among the network,is adopted.The solvability condition for the cooperative output regulation problem is obtained using the small-gain theory,which will not be destroyed by adding the nonlinear feedback part of the CNF control law.It is also shown that in the case with the exo-system not diverging exponentially,the small-gain condition can be guaranteed using the low-gain design.Finally,simulation results illustrate that the proposed CNF control law improves the transient performance for the cooperative output regulation of linear multi-agent systems.展开更多
This paper presents an optimization method of designing the integral sliding mode （ISM） based composite nonlinear feedback （CNF） controller for a class of low order linear systems with input saturation. The optima...This paper presents an optimization method of designing the integral sliding mode （ISM） based composite nonlinear feedback （CNF） controller for a class of low order linear systems with input saturation. The optimal CNF control is first designed as a nominal control to yield high tracking speed and low overshoot. The selection of all the tuning parameters for the CNF control law is turned into a minimization problem and solved automatically by particle swarm optimization （PSO） algorithm. Subsequently, the discontinuous control law is introduced to reject matched disturbances. Then, the optimal ISM-CNF control law is achieved as the sum of the optimal CNF control law and the discontinuous control law. The effectiveness of the optimal ISM-CNF controller is verified by comparing with a step by step designed one. High tracking performance is achieved by applying the optimal ISM-CNF controller to the tracking control of the micromirror.展开更多
This article is devoted to the problem of composite control design for continuous nonlinear singularly perturbed(SP)system using approximate feedback linearization(AFL)method.The essence of AFL method lies in the feed...This article is devoted to the problem of composite control design for continuous nonlinear singularly perturbed(SP)system using approximate feedback linearization(AFL)method.The essence of AFL method lies in the feedback linearization only of a certain part of the original nonlinear system.According to AFL approach,we suggest to solve feedback linearization problems for continuous nonlinear SP system by reducing it to two feedback linearization problems for slow and fast subsystems separately.The resulting AFL control is constructed in the form of asymptotic composition(composite control).Standard procedure for the composite control design consists of the following steps:1)system decomposition,2)solution of control problem for fast subsystem,3)solution of control problem for slow subsystem,4)construction of the resulting control in the form of the composition of slow and fast controls.The main difficulty during system decomposition is associated with dynamics separation condition for nonlinear SP system.To overcome this,we propose to change the sequence of the design procedure:1)solving the control problem for fast state variables part,2)system decomposition,3)solving the control problem for slow state variables part,4)construction of the resulting composite control.By this way,fast feedback linearizing control is chosen so that the dynamics separation condition would be met and the fast subsystem would be stabilizable.The application of the proposed approach is illustrated through several examples.展开更多
基金National Natural Science Foundation of China(Nos.61663030,61663032)Natural Science Foundation of Jiangxi Province,China(No.20142BAB207021)+3 种基金the Foundation of Jiangxi Educational Committee,China(No.GJJ150753)the Innovation Fund Designated for Graduate Students of Nanchang Hangkong University,China(Nos.YC2017027,2018YBXG014)the Open Fund of Key Laboratory of Image Processing and Pattern Recognition of Jiangxi Province(Nanchang Hangkong University),China(No.TX201404003)Key Laboratory of Nondestructive Testing(Nanchang Hangkong University),Ministry of Education,China(No.ZD29529005)
文摘External disturbances or inaccurate mathematical model built will inevitably impose a disadvantageous effect on the robot system,which generates positioning errors,vibrations,as well as weakening control performances of the system. The strategy of combining adaptive radial basis function( RBF) neural network control and composite nonlinear feedback( CNF) control is studied,and a robot CNF controller based on RBF neural network compensation is proposed. The core is to use RBF neural network control to approach the uncertainty of the system online,as the compensation term of the CNF controller,and make full use of the advantages of the two control methods to reduce the influence of uncertain factors on the performance of the system. The convergence of closed-loop system is proved. Simulation results demonstrate the effectiveness of this strategy.
基金supported by the National Natural Science Foundation of China(61074004)the Research Fund for the Doctoral Program of Higher Education(20110121110017)
文摘Transient performance for output regulation problems of linear discrete-time systems with input saturation is addressed by using the composite nonlinear feedback（CNF） control technique. The regulator is designed to be an additive combination of a linear regulator part and a nonlinear feedback part. The linear regulator part solves the regulation problem independently which produces a quick output response but large oscillations. The nonlinear feedback part with well-tuned parameters is introduced to improve the transient performance by smoothing the oscillatory convergence. It is shown that the introduction of the nonlinear feedback part does not change the solvability conditions of the linear discrete-time output regulation problem. The effectiveness of transient improvement is illustrated by a numeric example.
基金Supported by the National Natural Science Foundation of China(No.61663030,61663032)Natural Science Foundation of Jiangxi Province(No.20142BAB207021)+4 种基金the Foundation of Jiangxi Educational Committee(No.GJJ150753)the Innovation Fund Designated for Graduate Students of Nanchang Hangkong University(No.YC2017027)the Open Fund of Key Laboratory of Image Processing and Pattern Recognition of Jiangxi Province(Nanchang Hangkong University)(No.TX201404003)Key Laboratory of Nondestructive Testing(Nanchang Hangkong University),Ministry of Education(No.ZD29529005)the Reform Project of Degree and Postgraduate Education in Jiangxi(No.JXYJG-2017-131)
文摘In order to suppress the influence of uncertain factors on robot system and enable an uncertain robot system to track the reference input accurately,a strategy of combining composite nonlinear feedback(CNF)control and adaptive fuzzy control is studied,and a robot CNF controller based on adaptive fuzzy compensation is proposed.The key of this strategy is to use adaptive fuzzy control to approach the uncertainty of the system online,as the compensation term of the CNF controller,and make full use of the advantages of the two control methods to reduce the influence of uncertain factors on the performance of the system.The convergence of the closed-loop system is proved by feedback linearization and Lyapunov theory.The final simulation results confirm the effectiveness of this plan.
基金supported by the National Natural Science Foundation of China(61374035)
文摘Composite nonlinear feedback （CNF） control techniquefor tracking control problems is extended to the output regulationproblem of singular linear systems with input saturation. A statefeedback CNF control law and an output feedback CNF controllaw are constructed respectively for the output regulation problemof singular linear systems with input saturation. It is shown thatthe output regulation problem by CNF control is solvable underthe same solvability conditions of the output regulation problemby linear control. However, with the virtue of the CNF control, thetransient performance of the closed-loop system can be improvedby carefully designing the linear part and the nonlinear part of theCNF control law. The design procedure and the improvement ofthe transient performance of the closed-loop system are illustratedwith a numerical simulation.
基金supported by the National Natural Science Foundation of China (60428303)
文摘A composite nonlinear feedback tracking controller for motion control of robot manipulators is described. The structure of the controller is composed of a composite nonlinear feedback law plus full robot nonlinear dynamics compensation. The stability is carried out in the presence of friction. The controller takes advantage of varying damping ratios induced by the composite nonlinear feedback control, so the transient performance of the closed-loop is remarkably improved. Simulation results demonstrate the feasibility of the proposed method.
基金This work was supported in part by the National Natural Science Foundation of China under Grants 62273285 and 62173283in part by the Natural Science Foundation of Fujian Province of China under Grants 2021J01051.
文摘This paper investigates the cooperative output regulation problem of linear multi-agent systems with a linear exogenous system(exo-system).The network topology is described by a directed graph which contains a directed spanning tree with the exo-system as the root.Aiming at improving the transient performance of the multi-agent systems,a dynamic control law is developed by the composite nonlinear feedback(CNF)control technique.In particular,a distributed dynamic compensator independent of the interaction on the compensator states of agents among the network,is adopted.The solvability condition for the cooperative output regulation problem is obtained using the small-gain theory,which will not be destroyed by adding the nonlinear feedback part of the CNF control law.It is also shown that in the case with the exo-system not diverging exponentially,the small-gain condition can be guaranteed using the low-gain design.Finally,simulation results illustrate that the proposed CNF control law improves the transient performance for the cooperative output regulation of linear multi-agent systems.
基金This work was supported by National Natural Science Foundation of China （No. 61374036） and the Fundamental Research Funds for the Central Universities （No. SCUT 2014ZM0035）.
文摘This paper presents an optimization method of designing the integral sliding mode （ISM） based composite nonlinear feedback （CNF） controller for a class of low order linear systems with input saturation. The optimal CNF control is first designed as a nominal control to yield high tracking speed and low overshoot. The selection of all the tuning parameters for the CNF control law is turned into a minimization problem and solved automatically by particle swarm optimization （PSO） algorithm. Subsequently, the discontinuous control law is introduced to reject matched disturbances. Then, the optimal ISM-CNF control law is achieved as the sum of the optimal CNF control law and the discontinuous control law. The effectiveness of the optimal ISM-CNF controller is verified by comparing with a step by step designed one. High tracking performance is achieved by applying the optimal ISM-CNF controller to the tracking control of the micromirror.
基金supported by Russian Foundation for Basic Research(No.15-08-06859a)and by the Ministry of Education and Science of the Russian Federation in the framework of the basic part of the state order(No.2.8629.2017).
文摘This article is devoted to the problem of composite control design for continuous nonlinear singularly perturbed(SP)system using approximate feedback linearization(AFL)method.The essence of AFL method lies in the feedback linearization only of a certain part of the original nonlinear system.According to AFL approach,we suggest to solve feedback linearization problems for continuous nonlinear SP system by reducing it to two feedback linearization problems for slow and fast subsystems separately.The resulting AFL control is constructed in the form of asymptotic composition(composite control).Standard procedure for the composite control design consists of the following steps:1)system decomposition,2)solution of control problem for fast subsystem,3)solution of control problem for slow subsystem,4)construction of the resulting control in the form of the composition of slow and fast controls.The main difficulty during system decomposition is associated with dynamics separation condition for nonlinear SP system.To overcome this,we propose to change the sequence of the design procedure:1)solving the control problem for fast state variables part,2)system decomposition,3)solving the control problem for slow state variables part,4)construction of the resulting composite control.By this way,fast feedback linearizing control is chosen so that the dynamics separation condition would be met and the fast subsystem would be stabilizable.The application of the proposed approach is illustrated through several examples.
