In this paper, the robust adaptive fuzzy tracking control problem is discussed for a class of perturbed strict-feedback nonlinear systems. The fuzzy logic systems in Mamdani type are used to approximate unknown nonlin...In this paper, the robust adaptive fuzzy tracking control problem is discussed for a class of perturbed strict-feedback nonlinear systems. The fuzzy logic systems in Mamdani type are used to approximate unknown nonlinear functions. A design scheme of the robust adaptive fuzzy controller is proposed by use of the backstepping technique. The proposed controller guarantees semi-global uniform ultimate boundedness of all the signals in the derived closed-loop system and achieves the good tracking performance. The possible controller singularity problem which may occur in some existing adaptive control schemes with feedback linearization techniques can be avoided. In addition, the number of the on-line adaptive parameters is not more than the order of the designed system. Finally, two simulation examples are used to demonstrate the effectiveness of the proposed control scheme.展开更多
This paper investigates the problem of Spacecraft Formation-Containment Flying Control(SFCFC)when the desired translational velocity is time-varying.In SFCFC problem,there are multiple leader spacecraft and multiple f...This paper investigates the problem of Spacecraft Formation-Containment Flying Control(SFCFC)when the desired translational velocity is time-varying.In SFCFC problem,there are multiple leader spacecraft and multiple follower spacecraft and SFCFC can be divided into leader spacecraft’s formation control and follower spacecraft’s containment control.First,under the condition that only a part of leader spacecraft can have access to the desired time-varying translational velocity,a velocity estimator is designed for each leader spacecraft.Secondly,based on the estimated translational velocity,a distributed formation control algorithm is designed for leader spacecraft to achieve the desired formation and move with the desired translational velocity simultaneously.Then,to ensure all follower spacecraft converge to the convex hull formed by the leader spacecraft,a distributed containment control algorithm is designed for follower spacecraft.Moreover,to reduce the dependence of the designed control algorithms on the graph information and increase system robustness,the control gains are changing adaptively and the parametric uncertainties are handled,respectively.Finally,simulation results are provided to illustrate the effectiveness of the theoretical results.展开更多
This article mainly investigates the fuzzy optimization robust control issue for nonlinear networked systems characterized by the interval type-2(IT2)fuzzy technique under a differential evolution algorithm.To provide...This article mainly investigates the fuzzy optimization robust control issue for nonlinear networked systems characterized by the interval type-2(IT2)fuzzy technique under a differential evolution algorithm.To provide a more reasonable utilization of the constrained communication channel,a novel adaptive memory event-triggered(AMET)mechanism is developed,where two event-triggered thresholds can be dynamically adjusted in the light of the current system information and the transmitted historical data.Sufficient conditions with less conservative design of the fuzzy imperfect premise matching(IPM)controller are presented by introducing the Wirtinger-based integral inequality,the information of membership functions(MFs)and slack matrices.Subsequently,under the IPM policy,a new MFs intelligent optimization technique that takes advantage of the differential evolution algorithm is first provided for IT2 TakagiSugeno(T-S)fuzzy systems to update the fuzzy controller MFs in real-time and achieve a better system control effect.Finally,simulation results demonstrate that the proposed control scheme can obtain better system performance in the case of using fewer communication resources.展开更多
In this paper,a survey of adaptive fuzzy for uncertain nonlinear systems is presented.The first part introduces adaptive fuzzy control emergence and some typical control methods for uncertain nonlinear systems with ma...In this paper,a survey of adaptive fuzzy for uncertain nonlinear systems is presented.The first part introduces adaptive fuzzy control emergence and some typical control methods for uncertain nonlinear systems with matching conditions(single-input singleoutput systems,multi-input multi-output systems).The last part presents the adaptive fuzzy state feedback and output-feedback control methods for uncertain nonlinear systems with non-matching conditions based on the backstepping technique,including strictfeedback systems,pure-feedback systems and non-strict-feedback systems.展开更多
In this paper, adaptive neural control is proposed for a class of multi-input multi-output （MIMO） nonlinear unknown state time-varying delay systems in block-triangular control structure. Radial basis function （RBF...In this paper, adaptive neural control is proposed for a class of multi-input multi-output （MIMO） nonlinear unknown state time-varying delay systems in block-triangular control structure. Radial basis function （RBF） neural net- works （NNs） are utilized to estimate the unknown continuous functions. The unknown time-varying delays are compensated for using integral-type Lyapunov-Krasovskii functionals in the design. The main advantage of our result not only efficiently avoids the controller singularity, but also relaxes the restriction on unknown virtual control coefficients. Boundedness of all the signals in the closed-loop of MIMO nonlinear systems is achieved, while The outputs of the systems are proven to converge to a small neighborhood of the desired trajectories. The feasibility is investigated by two simulation examples.展开更多
This paper studied a continuous-time model of a production maintenance system in which a manufacturing firm produces a single product selling some and stocking the remaining. The problem of adaptive control of a produ...This paper studied a continuous-time model of a production maintenance system in which a manufacturing firm produces a single product selling some and stocking the remaining. The problem of adaptive control of a production-maintenance system with unknown deterioration has been presented. Using Liapunov technique, the production rate and updating rule of deterioration rate are derived as non-linear functions of inventory level perturbation. Numerical analysis for the system has been presented for a set of parameter values and demand rate.展开更多
An adaptive neural fuzzy (NF) controller is developed in this paper for active vibration suppression in flexible structures. A recurrent identification network (RIN) is developed to adaptively identify system dynamics...An adaptive neural fuzzy (NF) controller is developed in this paper for active vibration suppression in flexible structures. A recurrent identification network (RIN) is developed to adaptively identify system dynamics of the plant. A novel recurrent training (RT) technique is suggested to train the RIN so as to optimize nonlinear input-output mapping and to enhance convergence. The effectiveness of the developed controller and the related techniques has been verified experimentally corresponding to different control scenarios. Test results show that the proposed RIN can effectively recognize the time-varying dynamics of the plant. The RT-based hybrid training technique can improve the adaptive capability of the control system to accommodate different system conditions and enhance the training convergence. The developed NF controller is a robust and stable vibration suppression system, and it outperforms other related NF controllers.展开更多
We investigate the projective synchronization of different chaotic systems with nonlinearity inputs. Based on the adaptive technique, sliding mode control method and pole assignment technique, a novel adaptive project...We investigate the projective synchronization of different chaotic systems with nonlinearity inputs. Based on the adaptive technique, sliding mode control method and pole assignment technique, a novel adaptive projective synchro- nization scheme is proposed to ensure the drive system and the response system with nonlinearity inputs can be rapidly synchronized up to the given scaling factor.展开更多
基金This work was supported by the National Natural Science Foundation of China (No.60674055)the Taishan Scholar programme and the NaturalScience Foundation of Shandong Province (No.Y2006G04)
文摘In this paper, the robust adaptive fuzzy tracking control problem is discussed for a class of perturbed strict-feedback nonlinear systems. The fuzzy logic systems in Mamdani type are used to approximate unknown nonlinear functions. A design scheme of the robust adaptive fuzzy controller is proposed by use of the backstepping technique. The proposed controller guarantees semi-global uniform ultimate boundedness of all the signals in the derived closed-loop system and achieves the good tracking performance. The possible controller singularity problem which may occur in some existing adaptive control schemes with feedback linearization techniques can be avoided. In addition, the number of the on-line adaptive parameters is not more than the order of the designed system. Finally, two simulation examples are used to demonstrate the effectiveness of the proposed control scheme.
基金supported by the National Natural Science Foundation of China(Nos.61876050,61673135,61603114).
文摘This paper investigates the problem of Spacecraft Formation-Containment Flying Control(SFCFC)when the desired translational velocity is time-varying.In SFCFC problem,there are multiple leader spacecraft and multiple follower spacecraft and SFCFC can be divided into leader spacecraft’s formation control and follower spacecraft’s containment control.First,under the condition that only a part of leader spacecraft can have access to the desired time-varying translational velocity,a velocity estimator is designed for each leader spacecraft.Secondly,based on the estimated translational velocity,a distributed formation control algorithm is designed for leader spacecraft to achieve the desired formation and move with the desired translational velocity simultaneously.Then,to ensure all follower spacecraft converge to the convex hull formed by the leader spacecraft,a distributed containment control algorithm is designed for follower spacecraft.Moreover,to reduce the dependence of the designed control algorithms on the graph information and increase system robustness,the control gains are changing adaptively and the parametric uncertainties are handled,respectively.Finally,simulation results are provided to illustrate the effectiveness of the theoretical results.
基金supported by the National Natural Science Foundation of China(61973105,62373137)。
文摘This article mainly investigates the fuzzy optimization robust control issue for nonlinear networked systems characterized by the interval type-2(IT2)fuzzy technique under a differential evolution algorithm.To provide a more reasonable utilization of the constrained communication channel,a novel adaptive memory event-triggered(AMET)mechanism is developed,where two event-triggered thresholds can be dynamically adjusted in the light of the current system information and the transmitted historical data.Sufficient conditions with less conservative design of the fuzzy imperfect premise matching(IPM)controller are presented by introducing the Wirtinger-based integral inequality,the information of membership functions(MFs)and slack matrices.Subsequently,under the IPM policy,a new MFs intelligent optimization technique that takes advantage of the differential evolution algorithm is first provided for IT2 TakagiSugeno(T-S)fuzzy systems to update the fuzzy controller MFs in real-time and achieve a better system control effect.Finally,simulation results demonstrate that the proposed control scheme can obtain better system performance in the case of using fewer communication resources.
基金Thisworkwas supported in part by theNationalNatural Science Foundation ofChina[grant number 61773188].
文摘In this paper,a survey of adaptive fuzzy for uncertain nonlinear systems is presented.The first part introduces adaptive fuzzy control emergence and some typical control methods for uncertain nonlinear systems with matching conditions(single-input singleoutput systems,multi-input multi-output systems).The last part presents the adaptive fuzzy state feedback and output-feedback control methods for uncertain nonlinear systems with non-matching conditions based on the backstepping technique,including strictfeedback systems,pure-feedback systems and non-strict-feedback systems.
基金supported by the National Natural Science Foundation of China(Nos.60864001,61074124)
文摘In this paper, adaptive neural control is proposed for a class of multi-input multi-output （MIMO） nonlinear unknown state time-varying delay systems in block-triangular control structure. Radial basis function （RBF） neural net- works （NNs） are utilized to estimate the unknown continuous functions. The unknown time-varying delays are compensated for using integral-type Lyapunov-Krasovskii functionals in the design. The main advantage of our result not only efficiently avoids the controller singularity, but also relaxes the restriction on unknown virtual control coefficients. Boundedness of all the signals in the closed-loop of MIMO nonlinear systems is achieved, while The outputs of the systems are proven to converge to a small neighborhood of the desired trajectories. The feasibility is investigated by two simulation examples.
文摘This paper studied a continuous-time model of a production maintenance system in which a manufacturing firm produces a single product selling some and stocking the remaining. The problem of adaptive control of a production-maintenance system with unknown deterioration has been presented. Using Liapunov technique, the production rate and updating rule of deterioration rate are derived as non-linear functions of inventory level perturbation. Numerical analysis for the system has been presented for a set of parameter values and demand rate.
文摘An adaptive neural fuzzy (NF) controller is developed in this paper for active vibration suppression in flexible structures. A recurrent identification network (RIN) is developed to adaptively identify system dynamics of the plant. A novel recurrent training (RT) technique is suggested to train the RIN so as to optimize nonlinear input-output mapping and to enhance convergence. The effectiveness of the developed controller and the related techniques has been verified experimentally corresponding to different control scenarios. Test results show that the proposed RIN can effectively recognize the time-varying dynamics of the plant. The RT-based hybrid training technique can improve the adaptive capability of the control system to accommodate different system conditions and enhance the training convergence. The developed NF controller is a robust and stable vibration suppression system, and it outperforms other related NF controllers.
基金Project supported by the National Natural Science Foundation of China (Grant Nos. 60971107 and 60973152)the Natural Science Foundation of Liaoning Province, China (Grant No. 20082165)
文摘We investigate the projective synchronization of different chaotic systems with nonlinearity inputs. Based on the adaptive technique, sliding mode control method and pole assignment technique, a novel adaptive projective synchro- nization scheme is proposed to ensure the drive system and the response system with nonlinearity inputs can be rapidly synchronized up to the given scaling factor.
