In this paper, an indirect adaptive fuzzy output feedback controller with supervisory mode for a class of unknown nonlinear systems is developed. The proposed approach does not need the availability of the state varia...In this paper, an indirect adaptive fuzzy output feedback controller with supervisory mode for a class of unknown nonlinear systems is developed. The proposed approach does not need the availability of the state variables, moreover, a supervisory controller is appended to the adaptive fuzzy controller to force the state to be within the constraint set. Therefore, if the adaptive fuzzy controller cannot maintain the stability, the supervisory controller starts to work to guarantee stability. On the other hand, if the adaptive fuzzy controller works well, the supervisory controller will be de-activated. The overall adaptive fuzzy control scheme guarantees the stability of the whole closed-loop systems. The simulation results confirm the effectiveness of the proposed method.展开更多
Up to present,the problem of the evaluation of fault diagnosability for nonlinear systems has been investigated by many researchers.However,no attempt has been done to evaluate the diagnosability of multiple faults oc...Up to present,the problem of the evaluation of fault diagnosability for nonlinear systems has been investigated by many researchers.However,no attempt has been done to evaluate the diagnosability of multiple faults occurring simultaneously for nonlinear systems.This paper proposes a method based on differential geometry theories to solve this problem.Then the evaluation of fault diagnosability for affine nonlinear systems with multiple faults occurring simultaneously is achieved.To deal with the effect of control laws on the evaluation results of fault diagnosability,a design scheme of the evaluation of fault diagnosability is proposed.Then the influence of uncertainties on the evaluation results of fault diagnosability for affine nonlinear systems with multiple faults occurring simultaneously is analyzed.The numerical simulation results are obtained to show the effectiveness of the proposed evaluation scheme of fault diagnosability.展开更多
The problem of adaptive stabilization of a class of multi-input nonlinear systems with unknown parameters both in the state vector-field and the input vector-field has been considered. By employing the control Lyapuno...The problem of adaptive stabilization of a class of multi-input nonlinear systems with unknown parameters both in the state vector-field and the input vector-field has been considered. By employing the control Lyapunov function method, a direct adaptive controller is designed to complete the global adaptive stability of the uncertain system. At the same time, the controller is also verified to possess the optimality. Example and simulations are provided to illustrate the effectiveness of the proposed method.展开更多
The problem of robustifying linear quadratic regulators （LQRs） for a class of uncertain affine nonlinear systems is considered. First, the exact linearization technique is used to transform an uncertain nonlinear sy...The problem of robustifying linear quadratic regulators （LQRs） for a class of uncertain affine nonlinear systems is considered. First, the exact linearization technique is used to transform an uncertain nonlinear system into a linear one and an optimal LQR is designed for the corresponding nominal system. Then, based on the integral sliding mode, a design approach to robustifying the optimal regulator is studied. As a result, the system exhibits global robustness to uncertainties and the ideal sliding mode dynamics is the same as that of the optimal LQR for the nominal system. A global robust optimal sliding mode control （GROSMC） is realized. Finally, a numerical simulation is demonstrated to show the effectiveness and superiority of the proposed algorithm compared with the conventional optimal LQR.展开更多
The global stabilization problem of nonlinear systems with uncertain structure is dealt with. Based on control Lyapunov function （CLF）, a sufficient and necessary condition for Lyapunov stabilization is given. From ...The global stabilization problem of nonlinear systems with uncertain structure is dealt with. Based on control Lyapunov function （CLF）, a sufficient and necessary condition for Lyapunov stabilization is given. From the condition, several simply sufficient conditions for the globally asymptotical stability are deduced. A state feedback control law is designed to globally asymptotically stabilize the equilibrium of the closed system. Last, a simulation shows the effectiveness of the method.展开更多
The static output feedback H∞ control is explored for a class of nonlinear singular system with norm-bounded uncertainty. On certain suppose, the zero solution asymptotically stability is analyzed by means of Lyapuno...The static output feedback H∞ control is explored for a class of nonlinear singular system with norm-bounded uncertainty. On certain suppose, the zero solution asymptotically stability is analyzed by means of Lyapunov function and Lyapunov stability theory. Based on which, a sufficient condition is presented such that the system is zero solution asymptotically stable and has H∞ norm constraint γ. Then, the static output feedback H∞ controller is designed to guarantee the resulting closed-loop system has the same performance. Finally, an example proves the effectiveness of the conclusion.展开更多
针对一类具有不确定系统函数和方向未知的不确定增益函数的非线性系统,提出了一种鲁棒自适应神经网络控制算法.本算法采用RBF神经网络(Radial based function neural network,RBFNN)逼近模型不确定性,外界干扰和建模误差采用非线性阻尼...针对一类具有不确定系统函数和方向未知的不确定增益函数的非线性系统,提出了一种鲁棒自适应神经网络控制算法.本算法采用RBF神经网络(Radial based function neural network,RBFNN)逼近模型不确定性,外界干扰和建模误差采用非线性阻尼项进行补偿,将动态面控制(Dynamic surface control,DSC)与后推方法结合,消除了反推法的计算膨胀问题,降低了控制器的复杂性;尤其是采用Nussbaum函数处理系统中方向未知的不确定虚拟控制增益函数,不仅可以避免可能存在的控制器奇异值问题,而且还能使得整个系统的在线学习参数显著减少,与DSC方法优点结合,使得控制算法的计算量大为减少,便于计算机实现.稳定性分析证明了所得闭环系统是半全局一致最终有界(Semi-global uniformly ultimately bounded,SGUUB)的,并且跟踪误差可以收敛到原点的一个较小邻域.最后,计算机仿真结果表明了本文所提出控制器的有效性.展开更多
基金Supported by National Natural Science Foundation of China （60674036）, the Science and Technical Development Plan of Shandong Province （2004GG4204014）, the Program for New Century Excellent Talents in University of China （NCET-07-0513）, the Key Science and Technique Foundation of Ministry of Education of China （108079）, and the Excellent Young and Middle-aged Scientist Award of Shandong Province of China （2007BS01010）
基金Supported by National Natural Science Foundation of P. R. China (60274019)National Key Basic Research and Development Program of P. R. China (2002CB312200)
文摘In this paper, an indirect adaptive fuzzy output feedback controller with supervisory mode for a class of unknown nonlinear systems is developed. The proposed approach does not need the availability of the state variables, moreover, a supervisory controller is appended to the adaptive fuzzy controller to force the state to be within the constraint set. Therefore, if the adaptive fuzzy controller cannot maintain the stability, the supervisory controller starts to work to guarantee stability. On the other hand, if the adaptive fuzzy controller works well, the supervisory controller will be de-activated. The overall adaptive fuzzy control scheme guarantees the stability of the whole closed-loop systems. The simulation results confirm the effectiveness of the proposed method.
基金National Natural Science Foundation of China （60674036, 60974003）, the Natural Science Foundation for Distinguished Young Scholar of Shandong Province of China （JQ200919）, the Program for New Century Excellent Talents in University of China （NCET-07-0513）, the Key Science and Technique Foundation of Ministry of Education of China （108079）, the Excellent Young and Middle-Aged Scientist Award Grant of Shandong Province of China （2007BS01010）
基金the Natural Science Foundation of Fujian Province,China(2019J05024)the Education Department Foundation of Fujian Province,China(JAT170091).
文摘Up to present,the problem of the evaluation of fault diagnosability for nonlinear systems has been investigated by many researchers.However,no attempt has been done to evaluate the diagnosability of multiple faults occurring simultaneously for nonlinear systems.This paper proposes a method based on differential geometry theories to solve this problem.Then the evaluation of fault diagnosability for affine nonlinear systems with multiple faults occurring simultaneously is achieved.To deal with the effect of control laws on the evaluation results of fault diagnosability,a design scheme of the evaluation of fault diagnosability is proposed.Then the influence of uncertainties on the evaluation results of fault diagnosability for affine nonlinear systems with multiple faults occurring simultaneously is analyzed.The numerical simulation results are obtained to show the effectiveness of the proposed evaluation scheme of fault diagnosability.
文摘The problem of adaptive stabilization of a class of multi-input nonlinear systems with unknown parameters both in the state vector-field and the input vector-field has been considered. By employing the control Lyapunov function method, a direct adaptive controller is designed to complete the global adaptive stability of the uncertain system. At the same time, the controller is also verified to possess the optimality. Example and simulations are provided to illustrate the effectiveness of the proposed method.
基金supported by the Doctoral Foundation of Qingdao University of Science and Technology(0022330).
文摘The problem of robustifying linear quadratic regulators （LQRs） for a class of uncertain affine nonlinear systems is considered. First, the exact linearization technique is used to transform an uncertain nonlinear system into a linear one and an optimal LQR is designed for the corresponding nominal system. Then, based on the integral sliding mode, a design approach to robustifying the optimal regulator is studied. As a result, the system exhibits global robustness to uncertainties and the ideal sliding mode dynamics is the same as that of the optimal LQR for the nominal system. A global robust optimal sliding mode control （GROSMC） is realized. Finally, a numerical simulation is demonstrated to show the effectiveness and superiority of the proposed algorithm compared with the conventional optimal LQR.
基金This project was supported by the National Natural Science Foundation of Fujian province (A0510025) .
文摘The global stabilization problem of nonlinear systems with uncertain structure is dealt with. Based on control Lyapunov function （CLF）, a sufficient and necessary condition for Lyapunov stabilization is given. From the condition, several simply sufficient conditions for the globally asymptotical stability are deduced. A state feedback control law is designed to globally asymptotically stabilize the equilibrium of the closed system. Last, a simulation shows the effectiveness of the method.
基金National Natural Science Foundation of P. R. China (60574027)Opening Project of National Laboratory of Indus-trial Control Technology of Zhejiang University (0708001)
基金supported by the National Natural Science Foundation of China (60574011)
文摘The static output feedback H∞ control is explored for a class of nonlinear singular system with norm-bounded uncertainty. On certain suppose, the zero solution asymptotically stability is analyzed by means of Lyapunov function and Lyapunov stability theory. Based on which, a sufficient condition is presented such that the system is zero solution asymptotically stable and has H∞ norm constraint γ. Then, the static output feedback H∞ controller is designed to guarantee the resulting closed-loop system has the same performance. Finally, an example proves the effectiveness of the conclusion.
文摘针对一类具有不确定系统函数和方向未知的不确定增益函数的非线性系统,提出了一种鲁棒自适应神经网络控制算法.本算法采用RBF神经网络(Radial based function neural network,RBFNN)逼近模型不确定性,外界干扰和建模误差采用非线性阻尼项进行补偿,将动态面控制(Dynamic surface control,DSC)与后推方法结合,消除了反推法的计算膨胀问题,降低了控制器的复杂性;尤其是采用Nussbaum函数处理系统中方向未知的不确定虚拟控制增益函数,不仅可以避免可能存在的控制器奇异值问题,而且还能使得整个系统的在线学习参数显著减少,与DSC方法优点结合,使得控制算法的计算量大为减少,便于计算机实现.稳定性分析证明了所得闭环系统是半全局一致最终有界(Semi-global uniformly ultimately bounded,SGUUB)的,并且跟踪误差可以收敛到原点的一个较小邻域.最后,计算机仿真结果表明了本文所提出控制器的有效性.
