含控制时滞系统的实时故障诊断和最优容错控制

研究含有控制时滞的线性系统的故障诊断方法和最优容错控制问题.给出了最优容错控制律的存在唯一性条件,提出了最优容错控制律的设计算法.通过构造增广的降维状态观测器,设计了在线诊断故障的故障诊断器并同时实现了系统状态的观测,解决了最优容错控制的物理不可实现问题.利用观测器的输出得到物理可实现的动态最优容错控制律.仿真实例验证了故障诊断方法和动态最优容错控制律的有效性.     

时滞系统在高速网络下的最优扰动抑制

研究在含有控制时滞与测量时滞的系统在高速通讯网络下最优扰动抑制问题. 首先建立在高速通讯网络下含有控制时滞与测量时滞系统的离散化数学模型, 利用模型转换将时滞系统转化为形式上的无时滞系统. 然后通过求解离散Riccati方程和Stein方程设计含有状态反馈、扰动前馈和控制记忆项的最优控制律, 前馈项和控制记忆项分别补偿了扰动和控制时滞对系统性能的影响. 通过构造降维扰动状态观测器, 设计了含扰动前馈、输出反馈及 控制记忆项的动态控制律, 解决了前馈补偿器的物理不可实现问题. 仿真实例验证了所设计的最优控制律的有效性.     

控制时滞系统基于观测器的最优扰动抑制

研究在持续外界扰动作用下含有控制时滞线性系统的最优扰动抑制问题. 首先利用模型转换将控制时滞系统转化为无时滞系统. 然后证明最优控制律的存在唯一性, 并通过求解Riccati方程和Sylvester方程设计含前馈补偿器和控制记忆项的最优控制律, 其中的前馈控制项和控制记忆项分别补偿了扰动和控制时滞对系统的影响. 通过构造扰动状态观测器, 解决了前馈补偿器的物理不可实现问题. 仿真实例验证了所设计的最优控制律的有效性.     

含两类时滞的线性系统的故障诊断及故障可诊断性*

研究同时含有状态时滞和测量时滞的时滞系统的故障诊断方法及故障的可诊断性问题,提出一种同时对状态时滞和测量时滞进行变换的无时滞变换方法,并提出一种新的故障诊断器的构造方法,同时给出时滞系统的故障可诊断性的判据。首先通过提出一种同时对状态时滞和测量时滞进行转换的无时滞转换方法,将时滞系统转换成无时滞的系统;然后将故障诊断问题转换为状态观测问题,给出并证明了故障可诊断性的判据;最后通过构造一种不利用残差体现故障的新的故障诊断器,实现了故障的实时诊断并解决了故障诊断器的物理不可实现问题。仿真实例验证了该方法的可行     

含大时滞和噪声的网络化控制系统的最优故障诊断

研究含大测量时滞和噪声的网络控制系统(Networked control systems, NCS)的故障诊断问题, 提出一种新的基于无时滞转换方法的最优故障诊断器的设计方法. 该方法首先构造一个隐含故障状态的增广系统, 并利用无时滞转换方法将含有测量时滞的网络控制系统转换为无时滞系统. 然后给出了故障的可诊断性判据, 并利用对偶原理将最优故障诊断器的设计问题转换为状态反馈控制器设计问题. 最后, 通过构造一种满足二次型性能指标的最优故障诊断器, 实现了故障的实时诊断. 仿真示例验证了该方法的可行性和有效性.     

多时滞线性连续系统的最优H∞容错控制

针对状态具有多个时滞的线性连续系统,基于Lyapunov稳定性理论和线性矩阵不等式方法(LMI),采用无时滞记忆的状态反馈控制律,研究了在执行器发生故障的情况下,连续多时滞系统的最优H∞容错控制问题.首先,给出了系统没有干扰输入时存在无记忆状态反馈容错控制器的一个充分条件;进一步,给出了在H∞扰动衰减指标约束下,系统存在无记忆状态反馈H∞容错控制器的一个充分条件;最后,给出了最优无时滞记忆状态反馈H∞容错控制器的设计方法.仿真实例证明了所得最优H∞容错控制嚣设计方法的正确性和有效性.     

含状态和输入时滞的离散时间系统的近似最优跟踪控制

针对状 态和控制输入均含有时滞的离散时间系统, 提出最优跟踪控制的设计方法. 通 过引入一种新的状态向量, 将含有状态和控制输入时滞的离散时间系统转化为 含有虚拟扰动项的无时滞离散时间系统. 根据最优控制理论, 构造离散Riccati矩阵方 程和离散Stein矩阵方程的序列, 并证明该解序列一致收敛于变换后的离散时间系统的最优跟 踪控制策略. 利用最优控制的逐次逼近设计方法, 得到最优跟踪控制的近似 解, 并给出求解最优跟踪控制律的算法. 仿真算例表明了所提出最优跟踪控制 方法的有效性.     

基于观测器的离散时滞系统的故障诊断

研究含有测量时滞的线性离散系统的故障诊断问题,提出一种测量时滞的无时滞转换方法和基于降维状态观测器而不利用残差体现故障的故障诊断方法.首先通过构造一个含有故障状态的增广系统和进行测量时滞的无时滞转换,将时滞系统的故障诊断问题转化为无时滞增广系统的状态观测问题;然后给出了其诊断误差能按预先指定的指数速率趋于零的故障诊断器的设计方法.仿真算例验证了该方法的可行性和有效性.     

基于混沌优化的多模型容错控制方法

为了提高主动容错控制中故障诊断和容错控制律重组重构的快速性和可靠性,在建立了非线性受控对象正常或故障状态的神经网络模型的基础上,采用带有混沌动态量的自适应BP改进算法整定出系统各种运行模式下的控制律,由此建立了模型库;进而以一种隐形的故障诊断机制,通过对系统性能容忍度和模型失配度的在线计算判断系统的工作状态,并从动态模型库中调用与之匹配的控制律,从而达到容错效果.仿真结果表明,混沌机制的引入为提高系统发生故障时在线进行控制律重组重构的实时性和可靠性提供了一条有效途径.     

状态和控制含多时滞的离散系统H∞容错控制

针对状态和控制输入同时具有多个时滞的线性离散时间系统,基于Lyapunov稳定性理论和线性矩阵不等式方法(LMI),采用无时滞记忆的状态反馈控制律,研究了执行器故障情况下,离散多时滞系统的H∞容错控制问题.在采用连续执行器故障模型条件下,给出了系统没有干扰输入时存在无时滞记忆的状态反馈容错控制器的充分条件;进一步,给出了在H∞扰动衰减指标约束下,系统存在无时滞记忆的状态反馈H∞容错控制器的充分条件,并将结论推广到离散故障模型的情况.仿真结果证明了所提H∞容错控制器设计方法的正确性和有效性.     

Fault-tolerant cooperative output regulation for multi-vehicle systems with sensor faults

This paper presents a unified framework of fault diagnosis and fault-tolerant cooperative output regulation (FTCOR) for a linear discrete-time multi-vehicle system with sensor faults. The FTCOR control law is designed through three steps. A cooperative output regulation (COR) controller is designed based on the internal mode principle when there are no sensor faults. A sufficient condition on the existence of the COR controller is given based on the discrete-time algebraic Riccati equation (DARE). Then, a decentralised fault diagnosis scheme is designed to cope with sensor faults occurring in followers. A residual generator is developed to detect sensor faults of each follower, and a bank of fault-matching estimators are proposed to isolate and estimate sensor faults of each follower. Unlike the current distributed fault diagnosis for multi-vehicle systems, the presented decentralised fault diagnosis scheme in each vehicle reduces the communication and computation load by only using the information of the vehicle. By combing the sensor fault estimation and the COR control law, an FTCOR controller is proposed. Finally, the simulation results demonstrate the effectiveness of the FTCOR controller.     

Fault diagnosis and optimal fault-tolerant control for systems with delayed measurements and states

This note deals with the problems of fault diagnosis and fault-tolerant control for systems with delayed measurements and states. The main contribution consists in two aspects. First, by solving the Riccati equation and Sylvester equation, an optimal fault-tolerant control law is designed for systems with delayed measurements and states. The existence and uniqueness of the optimal fault-tolerant control law are proved. Second, the physically unrealizable problem of the optimal fault-tolerant control law is solved by proposing a novel fault diagnoser for systems with delayed measurements and states. Finally, a numerical example is given to demonstrate the feasibility and validity of the proposed schemes.     

Fault estimation and active fault-tolerant control for a class of nonlinear systems with actuator and sensor faults based on unknown input iterative learning

In this paper, fault estimation and active fault-tolerant control are studied for a class of nonlinear systems with simultaneous actuator and sensor faults, as well as unknown external disturbances. Firstly, the state equation of a class of nonlinear systems is transformed into an augmented system state equation by extending the sensor fault as an auxiliary state. Then, a novel fault estimation observer based on iterative learning with unknown inputs is designed to estimate the system state, as well as actuator and sensor faults. Subsequently, by using the fault estimation information, a dynamic output feedback active fault-tolerant control scheme is proposed to compensate for the influence of faults on the system. Lyapunov stability theory is used to prove the stability of the closed-loop system and the convergence of the fault estimation observer. The gain matrices of the fault estimation observer and fault-tolerant controller are obtained by solving linear matrix inequalities. Furthermore, the paper avoids the use of the $$ norm in the convergence proof of the conventional iterative learning algorithm, which reduces the amount of calculation in the derivation process. Finally, the effectiveness and accuracy of the proposed method are verified through simulation of the DC motor angular velocity system.     

Data-driven output-feedback fault-tolerant control for unknown dynamic systems with faults changing system dynamics

This paper studies the data-driven output-feedback fault-tolerant control (FTC) problem for unknown dynamic systems with faults changing system dynamics. In a framework of active FTC, two basic issues are addressed: the fault detection employing only the measured input–output information; the controller reconfiguration to achieve optimal output-feedback control in the presence of multiple faults. To detect faults and write the system state via the input–output data, an approach to data-driven design of a residual generator with a full-rank transformation matrix is presented. An output-feedback approximate dynamic programming method is developed to solve the optimal control problem under the condition that the unknown linear time-invariant discrete-time plant has multiple outputs. According to the above results and the proposed input–output data-based value function approximation structure of time-varying plants, a model-free output-feedback FTC scheme considering optimal performance is given. Finally, two numerical examples and a practical example of a DC motor control system are used to demonstrate the effectiveness of the proposed methods.     

Robust parameter-dependent fault-tolerant control for actuator and sensor faults

In this article, we study a robust fault-tolerant control (FTC) problem for linear systems subject to time-varying actuator and sensor faults. The faults under consideration are loss of effectiveness in actuators and sensors. Based on the estimated faults from a fault detection and isolation scheme, robust parameter-dependent FTC will be designed to stabilise the faulty system under all possible fault scenarios. The synthesis condition of such an FTC control law will be formulated in terms of linear matrix inequalities (LMIs) and can be solved efficiently by semi-definite programming. The proposed FTC approach will be demonstrated on a simple faulty system with different fault levels and fault estimation error bounds.     

无人机非确定性等价自适应容错飞行控制

针对存在执行器复合故障的固定翼无人机跟踪控制问题,本文提出一种基于非确定性等价原理的自适应容错飞行控制策略.该策略能够有效地估计无人机纵向动态中执行器的失效及漂移故障,保证故障发生后闭环系统的最优性能指标.在自适应容错飞行控制设计中,通过引入辅助系统并动态调节因子,构造非确定性等价原理中偏微分方程的近似解,以简化自适应律设计复杂度.此外,借助Lyapunov稳定性分析方法,证明了在所设计的自适应容错控制器作用下闭环系统的稳定性.最后,仿真验证表明所设计的控制方法能够保证故障无人机的闭环系统性能.     

Fault tolerant sliding mode control for T-S fuzzy stochastic time-delay system via a novel sliding mode observer approach

In this paper, a fault estimation and fault-tolerant control problem for a class of T-S fuzzy stochastic time-delay systems with actuator and sensor faults is investigated. A novel sliding mode observer is proposed, which can simultaneously estimate the system states, actuator and sensor faults with good accuracy. Based on the state and actuator fault estimation, a new sliding mode control scheme is developed, which can effectively eliminate the influence of actuator fault. Sufficient conditions for the existence of the proposed observer and fault-tolerant sliding mode controller are provided in terms of linear matrix inequality, and moreover, the reachability of the sliding mode surface can be guaranteed under the proposed control scheme. The propose sliding mode observer and fault-tolerant sliding mode controller can overcome the restrictive assumption that the input matrix of all local modes is the same. Finally, a numerical example is provided to verify the effectiveness of the proposed sliding mode observer and fault-tolerant sliding mode control technique.     

非线性系统有限时间自适应动态面容错控制

针对具有传感器故障的一类严格反馈非线性系统, 提出一种有限时间自适应动态面容错控制策略. 考虑的 传感器故障包括: 固定偏差故障、漂移故障、精度下降及失效故障. 以反步法为主要设计依据, 利用模糊逻辑系统处 理模型中的未知函数. 该控制策略的显著优势在于结合有限时间理论、容错控制、模糊逻辑控制及动态面控制, 使 得系统无论发生故障与否, 均使得系统在原点处是半全局实际有限时间稳定, 同时保证系统的实际输出信号在有限 时间内跟踪期望信号, 且跟踪误差收敛于坐标原点的小邻域内. 另外, 通过采用动态面控制技术克服了传统反步法 中的计算复杂问题. 最后, 仿真算例证明了该设计方案的有效性.