基于一个学习逼近的非线性系统的故障调节

很多学者对故障诊断和容错控制问题给予很大关注.特别是对于安全系统,故障诊断固然重要,最快地调节故障系统也是很重要的.例如当今的高性能飞行器即使发生故障仍需保持基本的运行状态.对于非线性系统提出一种故障调节控制器的设计方法,通过修正控制律补偿故障所带来的影响.故障发生后使用的神经网络用于逼近故障函数并提供故障的修正行为.即主动容错.故障调节后闭环系统是稳定的.仿真算例证明了此方法的有效性.     

基于自适应观测器控制系统的快速故障调节

针对基于自适应观测器故障调节设计中的两个难点,即系统满足严格正实(SPR)条件与故障估计的准确性和快速性,首先引入适当的坐标变换,有效地放松了严格SPR条件,适用于一大类控制系统的故障诊断;其次,针对变换后的系统,提出一种快速故障估计的设计方法,明显改善了故障估计的性能;再次,基于故障估计值修正控制律以补偿故障所带来的影响,使故障调节后的系统稳定;最后通过仿真实验验证了该方法的有效性.     

基于神经网络观测器的一类非线性系统的故障调节

将一般形式的非线性模型线性化为输出反馈型．针对该类系统,首先利用神经网络的一致逼近任意非线性连续函数的性质,构造神经网络自适应观测器,以获取反映故障信息的残差;然后根据残差信息在线估计故障;最后通过修正控制律来补偿故障所带来的影响．并采用Lyapunov稳定性理论证明了系统的稳定性．仿真结果验证了该方法的有效性．     

基于自适应模糊状态观测器的非线性系统鲁棒故障检测

针对仿射非线性系统,采用自适应模糊系统进行非线性补偿,提出了一种基于自适应模糊状态观测器的鲁棒故障检测方法.为确保观测器对嗓声干扰和系统参数不确定误差的鲁棒性,给出了闭环系统在有界嗓声干扰和系统参数不确定误差下的稳定性定理,并进行了详尽的证明.仿真结果表明该方法的有效性及对嗓声干扰和系统参数不确定误差的鲁棒性.     

一类非线性系统的自适应模糊滑模控制

对一类具有不确定性的非线性系统,根据滑模控制原理并利用模糊系统的逼近能力,提出了一种自适应模糊滑模控制系统的设计方法.控制结构中采用模糊系统自适应朴偿过程的不确定性.利用李雅普诺夫理论,证明了控制算法是全局稳定的,跟踪误差可收敛到零的一个邻域内.     

一类非线性系统的模糊自适应滑模输出反馈控制

针对一类非线性系统，提出一种新的模糊自适应滑模输出反馈控制方法，该方法不需要非线性系统的状态可测的假设。基于李亚普诺夫函数方法，给出了模糊自适应输出反馈控制律以及在线调节的参数自适应律，证明了模物闭环系统的稳定性和跟踪误差的收敛性。     

基于调节函数的一类三角结构非线性系统的自适应滑模控制

针对一类三角结构的非线性系统,基于状态参考自适应控制算法和滑模控制技术,研究了其在非匹配未知参数和不确定性干扰下的跟踪控制问题,提出了自适应滑模控制策略,实现了不确定非线性系统的鲁棒输出跟踪.与一般自适应控制相比,允许系统存在非参数化的不确定性和未知扰动,增强了控制系统鲁棒性.仿真算例证明了理论研究成果的正确性和可行性.     

一类MIMO非线性系统的直接自适应模糊滑模控制

针对一类具有下三角形函数控制增益矩阵的非线性系统, 基于滑模控制原理, 并利用Ⅱ型模糊系统的逼近能力, 提出了一种直接自适应模糊滑模控制器设计的新方案. 通过引入积分型李雅普诺夫函数及逼近误差自适应补偿项, 证明了闭环系统是全局稳定的, 跟踪误差收敛到零. 仿真结果表明了该方法的有效性.     

基于自适应滑模观测器的不匹配非线性系统执行器故障重构

针对一类含有未知干扰的不匹配非线性Lipschitz系统,提出了基于自适应滑模观测器的执行器故障重构方法.首先引入辅助输出矩阵,使得辅助输出系统的观测器匹配条件得以满足,同时设计了高增益观测器实现对未知辅助输出的精确估计;然后针对辅助输出系统建立故障重构滑模观测器,设计了自适应律在线修正滑模控制器增益,考虑故障上界未知的前提下,提出了观测器状态估计误差稳定的存在定理,运用Schur补引理将观测器反馈增益矩阵设计方法转化为求解线性矩阵不等式约束优化问题,同时引入线性变换矩阵,在故障上界未知的前提下设计了滑模控制增益,使得输出估计误差收敛稳定,确保了滑模运动在有限时间内发生,在此基础上利用等效控制输出误差注入原理实现了执行器故障重构;最后通过仿真算例验证了本文方法的有效性.     

一类约束非线性系统的自适应模糊容错控制

针对一类输出受限的非线性系统,提出了一种自适应模糊容错控制方案。在考虑可能发生的执行器故障的情况下,采用非线性映射的方法处理系统受约束的输出变量,从而将约束量的初值选取区间扩大为整个约束空间;用有界的参考信号代换未知函数的自变量,再用模糊逼近器处理这些未知函数,并结合自适应技术处理代换误差和逼近误差,从而使得闭环系统为全局一致最终有界,系统输出可以有效跟踪参考信号。仿真结果进一步验证了本文方法的有效性。     

Fault accommodation for nonlinear systems using fuzzy adaptive sliding control

An active fault accommodation control law is developed for a class of nonlinear systems to guarantee the closed-loop stability in the presence of a fault, based on a fuzzy logic system representation of the dynamics due to faults. It uses fuzzy logic system to approximate the dynamic caused by the fault. Through the adaptive process of the parameters, the dynamics caused by the fault is counteracted. The fuzzy sliding mode control is introduced to attenuate the fuzzy approximation error. Simultaneity, the closed-loop system is stable in Lyapunov sense and the tracking error converges to a neighbourhood of zero. The example of the proposed design indicates that the fault accommodation control law is effective for a nonlinear system.     

Fault tolerant control using virtual actuator for continuous‐time Lipschitz nonlinear systems

In this brief, we extend the existing results on fault tolerant control via virtual actuator approach to a class of systems with Lipschitz nonlinearities to maintain the closed‐loop stability after actuator faults. This generalization is established by relying on the input‐to‐state stability properties of cascaded systems. The virtual actuator block, placed between faulty plant and nominal controller, generates useful input signals for faulty plant by using output signals of the nominal controller to guarantee the closed‐loop stability in the presence of actuator faults. This design problem is reduced to a matrix inequality that can be turned to an LMI by fixing a variable to a constant value and solving the resulting LMI feasibility problem. The proposed fault tolerant control method is successfully evaluated using a nonlinear system. Copyright © 2013 John Wiley & Sons, Ltd.     

非线性系统的直接自适应输出反馈监督模糊控制

针对一类单输入单输出非线性不确定系统，提出一种稳定的直接自适应模糊输出反馈监督控制算法，该算法不需要系统的状态完全可测的假设条件，监督控制不仅迫使系统的状态在指定的集合内，而且当模糊自适应控制处于良好的工作状态时，监督控制可以关闭，证明了整个模糊自适应输出反馈控制算法可以保证闭环系统稳定。     

Robust fast adaptive fault estimation and tolerant control for T-S fuzzy systems with interval time-varying delay

This paper studies the problem of fault estimation (FE) and the active fault tolerant control (FTC) for Takagi–Sugeno (T-S) fuzzy systems with interval time-varying delay and norm-bounded external disturbance. Based on the fast adaptive fault estimation (FAFE) algorithm, our attention focuses on designing an adaptive observer-based controller to guarantee the filtering error system to be asymptotically stable and satisfy theH_∞ performance index. By constructing a new Lyapunov–Krasovskii functional including the information of the lower and upper delay bounds, the sufficient delay-dependent conditions have been established to guarantee the existence of adaptive observer-based controller in terms of linear matrix inequalities (LMIs). Compared with the constant delay and time-varying delay, the interval time-varying delay is the less conservative form. Furthermore, we make full use of the information of the delay and no terms are ignored when the stability of the system is analysed. In addition, the results for the systems with time-varying structured uncertainties are established. The results of the active FTC are showed in terms of LMIs. Finally, two examples are given to verify the effectiveness of the proposed method.     

A fault accommodation control for nonlinear systems

Based on the use of neural networks for representation of the dynamics of faults, an active fault accommodation control law is proposed that guarantees the closed-loop stability for a class of nonlinear systems with faults. An example of using the control design proposed demonstrates the efficiency of this law for a typical nonlinear system. __________ Translated from Kibernetika i Sistemnyi Analiz, No. 1, pp. 10–18, January–February 2006.     

Stable adaptive fuzzy control of nonlinear systems using small-gain theorem and LMI approach

A new design scheme of stable adaptive fuzzy control for a class of nonlinear systems is proposed in this paper. The T-S fuzzy model is employed to represent the systems. First, the concept of the so-called parallel distributed compensation (PDC) and linear matrix inequality (LMI) approach are employed to design the state feedback controller without considering the error caused by fuzzy modeling. Sufficient conditions with respect to decay rate α are derived in the sense of Lyapunov asymptotic stability. Finally, the error caused by fuzzy modeling is considered and the input-tostate stable (ISS) method is used to design the adaptive compensation term to reduce the effect of the modeling error. By the small-gain theorem, the resulting closed-loop system is proved to be input-to-state stable. Theoretical analysis verifies that the state converges to zero and all signals of the closed-loop systems are bounded. The effectiveness of the proposed controller design methodology is demonstrated through numerical simulation on the chaotic Henon system.     

Fault recoverability analysis of switched nonlinear systems

The recoverability reflects the capability of the system to tolerate the worst faults over a prescribed set under admissible energy constraints. In this paper, we present the minimum amount of control energy required to drive the initial state of a nonlinear system to the origin under certain assumptions, and we also give the corresponding optimal control law. This result is then extended to switched nonlinear systems under given switching signals. On this basis, a novel fault recoverability evaluation scheme is proposed for switched nonlinear systems with respect to the given limit of energy cost. Simulation results verify the effectiveness of the proposed method.     

Adaptive type-2 fuzzy sliding mode controller for SISO nonlinear systems subject to actuator faults

In this paper, an adaptive type-2 fuzzy sliding mode control to tolerate actuator faults of unknown nonlinear systems with external disturbances is presented. Based on a redundant actuation structure, a novel type-2 adaptive fuzzy fault tolerant control scheme is proposed using sliding mode control. Two adaptive type-2 fuzzy logic systems are used to approximate the unknown functions, whose adaptation laws are deduced from the stability analysis. The proposed approach allows to ensure good tracking performance despite the presence of actuator failures and external disturbances, as illustrated through a simulation example.