一类不确定离散切换模糊时滞系统的鲁棒非脆弱控制

针对一类不确定离散切换模糊时滞系统,研究了在控制器增益存在摄动情况下的稳定性问题.利用切换技术和多Lyapunov函数方法,并以矩阵不等式形式给出了非脆弱状态反馈控制器存在的充分条件和切换律设计.最后通过数值仿真算例验证了设计方法的有效性和可行性.     

Robust control for a class of uncertain switched fuzzy systems

A model of uncertain switched fuzzy systems whose subsystems are uncertain fuzzy systems is presented. Robust controllers for a class of switched fuzzy systems are designed by using the Lyapunov function method. Stability conditions for global asymptotic stability are developed and a switching strategy is proposed. An example shows the effectiveness of the method.     

Robust H infinity static output feedback control of fuzzy systems: an ILMI approach.

This paper examines the problem of robust H infinity static output feedback control of a Takagi-Sugeno fuzzy system. The proposed robust H infinity static output feedback controller guarantees the pounds 2 gain of the mapping from the exogenous disturbances to the regulated output to be less than or equal to a prescribed level. The existence of a robust H infinity static output feedback control is given in terms of the solvability of bilinear matrix inequalities. An iterative algorithm based on the linear matrix inequality is developed to compute robust H infinity static output feedback gains. To reduce the conservatism of the design, the structural information of membership function characteristics is incorporated. A numerical example is used to illustrate the validity of the design methodologies.     

Robust receding horizon control of uncertain fuzzy systems

The optimal control of uncertain fuzzy systems with constraints is still an open problem. One candidate to deal with this problem is robust receding horizon control (RRHC) schemes, which can be formulated as a differential game. Our focus concerns numerically solving Hamilton–Jacobi–Issac (HJI) equations derived from RRHC schemes for uncertain fuzzy systems. The developed finite difference approximation scheme with sigmoidal transformation is a stable and convergent algorithm for HJI equations. Accelerated procedures with boundary value iteration are developed to increase the calculation accuracy with less time consumption. Then, the state-feedback RRHC controller is designed for some class of uncertain fuzzy systems with constraints. The value function calculated by numerical methods acts as the design parameter. The closed-loop system is proven to be asymptotically stable. An engineering implementation of the controller is discussed.     

Robust control of a class of uncertain nonlinear systems

This paper considers the robust control of a class of nonlinear systems with real time-varying parameter uncertainty. Interest is focused on the design of linear dynamic output feedback control and two problems are addressed. The first one is the robust stabilization and the other is the problem of robust performance in an H_∞ sense. A technique is proposed for designing stabilizing controllers for both problems by converting them into ‘scaled’ H_∞ control problems which do not involve parameter uncertainty.     

Robust control of a class of nonlinear uncertain systems

Robust control of a general class of uncertain nonlinear systems is investigated. The class of nonlinear systems includes many physical systems as special cases and has an important feature that the uncertainties in the system do not satisfy the matching conditions. Several robust control laws are proposed to make the system stable in the sense of either asymptotic stability or uniformly ultimately bounded stability. The results require no knowledge about the structure of the uncertainties. Although the uncertainties are assumed to be bounded in the Euclidean norm by a polynomial-type bounding function, there is no size restriction imposed on the bounding functions of the uncertainties. The extension to the trajectory tracking problem is also discussed     

Piecewise H infinity: controller design of discrete time fuzzy systems.

This paper presents a new H infinity controller design method for the discrete time fuzzy systems based on the piecewise Lyapunov functions. The basic idea of the proposed approach is to construct the controller for the fuzzy systems in such a way that a discrete time piecewise Lyapunov function can be used to establish the global stability with H infinity-disturbance attenuation performance of the resulting close loop fuzzy control systems. It is shown that the control laws can be obtained by solving a set of linear matrix inequalities (LMIs) that is numerically tractable with commercially available software. Numerical example is given to demonstrate the advantage of the proposed method.     

Output feedback fault-tolerant control for a class of discrete-time fuzzy bilinear systems

This paper studies the fault-tolerant control problem for a class of discrete-time fuzzy bilinear systems with unmeasurable states. A fuzzy detective observer is designed to detect the faults. Based on the fuzzy detective observer, a fuzzy controller is designed by solving a set of linear matrix inequalities (LMIs) to ensure that the closed-loop system without faults is asymptotically stable. For the discrete-time fuzzy bilinear system with faults, a fuzzy adaptive diagnostic observer is designed to estimate the faults by solving a set of LMIs. Then, a fuzzy faulttolerant controller is designed based on the fuzzy diagnostic observer to ensure that the closed-loop system with faults is asymptotically stable. At last, simulation results are presented to verify the effectiveness of the proposed output feedback fault-tolerant control method.     

一类不确定非线性切换系统的鲁棒容错控制

研究一类不确定非线性切换系统的鲁棒容错控制问题,当执行器失效或部分失效时,利用Lyapunov函数法建立切换闭环系统混杂状态反馈容错控制器存在的充分条件;然后运用线性矩阵不等式将鲁棒容错控制器设计问题转化为一组线性矩阵不等式的可行解问题,从而借助Matlab中线性矩阵不等式工具箱求解;最后通过数值算倒验证了所提出设计方法的有效性.     

Adaptive fuzzy control for a class of uncertain nonaffine nonlinear systems

An adaptive fuzzy control approach is proposed for a class of multiple-input-multiple-output (MIMO) nonlinear systems with completely unknown nonaffine functions. The MIMO systems are composed of n subsystems and each of subsystems is in the nested lower triangular form. It is difficult and complicated to control this class of systems due to the existence of unknown nonaffine functions and the couplings among the nested subsystems. This difficulty is overcome by introducing some special type Lyapunov functions and taking advantage of the mean-value theorem, the backstepping design method and the approximation property of the fuzzy systems. The proposed control approach can guarantee that all the signals in the closed-loop system are bounded. A simulation experiment is utilized to verify the feasibility of the proposed approach.     

Robust H infinity control for networked systems with random packet losses.

In this paper, the robust H infinity control problem is considered for a class of networked systems with random communication packet losses. Because of the limited bandwidth of the channels, such random packet losses could occur, simultaneously, in the communication channels from the sensor to the controller and from the controller to the actuator. The random packet loss is assumed to obey the Bernoulli random binary distribution, and the parameter uncertainties are norm-bounded and enter into both the system and output matrices. In the presence of random packet losses, an observer-based feedback controller is designed to robustly exponentially stabilize the networked system in the sense of mean square and also achieve the prescribed H infinity disturbance-rejection-attenuation level. Both the stability-analysis and controller-synthesis problems are thoroughly investigated. It is shown that the controller-design problem under consideration is solvable if certain linear matrix inequalities (LMIs) are feasible. A simulation example is exploited to demonstrate the effectiveness of the proposed LMI approach.     

Robust adaptive control of a class of nonlinear uncertain systems

A smooth robust dynamic feedback controller is constructed, and the problem of robust H∞ almost disturbance attenuation with internal stability is solved for high-order nonlinear systems with parameter uncertainties. Finally, illustrative example and simulation results demonstrate the effectiveness of the proposed method.     

Robust control through piecewise Lyapunov functions for discrete time-varying uncertain systems

This paper is concerned with the robust stabilization by state feedback of a linear discrete-time system with time-varying uncertain parameters. An optimization problem involving a set of linear matrix inequalities and scaling parameters provides both the robust feedback gain and the piecewise Lyapunov function used to ensure the closed-loop stability. In the case of linear time-varying systems involving the convex combination of two matrices, only two scaling parameters constrained into the interval [0,?1] are needed, allowing a simple numerical solution as illustrated by means of examples.     

基于自适应神经网络的一类不确定非线性系统的鲁棒H∞控制

针对一类不确定非线性多输入时变系统，提出了一种新的鲁棒H∞控制方案．通过引入2个自适应神经网络逼近器，提出了一个简化的Hamilton—Jaeobi—like不等式，并据此设计了非线性H∞控制器和匹配不确定项补偿控制器，消除了输入摄动项和估计器最优逼近误差的有界性假设．机器人系统的鲁棒跟踪控制仿真算例证实了所提出控制方案的有效性．     

Robust analysis and control for a class of uncertain nonlinear discrete-time systems

This paper deals with the problem of robust analysis and control of a class of nonlinear discrete-time systems with (constant) uncertain parameters. For the analysis problem we use a polynomial Lyapunov function and we generalize, for nonlinear systems, the “extended stability” notion proposed by Oliveira et al. (1999) in the context of linear discrete-time uncertain systems. As a result, we propose an LMI optimization problem to maximize an estimate of the domain of attraction, and also extend this approach to the synthesis problem by considering parameter-dependent Lyapunov functions and nonlinear multipliers. Numerical examples illustrate the approach and show its potential for solving analysis and control problems of nonlinear discrete-time systems.     

Robust tracking for a class of uncertain linear systems

Tracking of a specified nominal output within an arbitrary error bound in the presence of uncertainties is formulated in terms of topological neighbourhoods in the function space Lκ∞ [0, ∞). It is shown that an observer-based state-feedback controller can be constructed to effect the desired robust tracking for a class of multi-input-multi-output linear systems containing uncertain parameters. The controller and the observer gains for this structure are chosen on the basis of a quantitative pole placement. This pole placement is based on an inequality arrived at by separating the uncertain effects of the true system from a nominal set of equations containing no uncertainties. The applicability of the proposed scheme is illustrated by synthesizing a controller for a second-order system.     

Robust adaptive NN control for a class of uncertain discrete-time nonlinear MIMO systems

A robust adaptive NN output feedback control is proposed to control a class of uncertain discrete-time nonlinear multi-input–multi-output (MIMO) systems. The high-order neural networks are utilized to approximate the unknown nonlinear functions in the systems. Compared with the previous research for discrete-time MIMO systems, robustness of the proposed adaptive algorithm is obvious improved. Using Lyapunov stability theorem, the results show all the signals in the closed-loop system are semi-globally uniformly ultimately bounded, and the tracking errors converge to a small neighborhood of zero by choosing the design parameters appropriately.     

Robust H-infinity reliable control for a class of nonlinear uncertain neutral delay systems

This paper focuses on the robust H-infinity reliable control for a class of nonlinear neutral delay systems with uncertainties and actuator failures. We design a state feedback controller in terms of linear matrix inequality(LMI) such that the plant satisfies robust H-infinity performance for all adnfissible uncertainties, and actuator failures among a prespecified subset of actuators. An example is also given to illustrate the effectiveness of the proposed approach.     

State observer-based adaptive fuzzy output-feedback control for a class of uncertain nonlinear systems

This paper aims to develop state observer-based adaptive fuzzy control techniques for controlling a class of uncertain nonlinear systems with bounded external disturbances. An adaptive fuzzy observer is proposed to estimate the system state variables. It is shown that the observation errors obtained from the observer are uniformly ultimately bounded. Applying the estimated system state for design of an output-feedback controller, the uniformly ultimate boundedness of the tracking errors for the resulting closed-loop system can be guaranteed. A typical robot arm system is employed in our simulation studies, and the results demonstrate the usefulness and effectiveness of the proposed techniques for controlling nonlinear systems with bounded external disturbances.