双容液位系统的不确定时滞的鲁棒容错控制

针对双容液位控制系统的执行器失效等故障,通过线性化建模,研究了鲁棒自适应容错控制问题。首先在系统无故障正常工作时,考虑建模误差、输入信号的稳定性、系统参数等不确定性因素,利用不确定性上界自适应估计,设计了不确定时滞鲁棒控制器。同时,对系统进行故障检测,研究了一种修正控制律的自适应鲁棒容错控制器设计方法,该控制器通过修补执行器故障所带来的影响使该系统最终有界稳定。最后,通过仿真试验,验证了提出的方法的有效性。     

双容液位系统鲁棒自适应容错控制

针对双容液位控制系统的泄漏等故障,通过线性化建模,研究了鲁棒自适应主动容错控制问题.首先在系统无故障正常运行情形,考虑建模误差和外界干扰等不确定性,利用不确定性上界自适应估计,设计了鲁棒自适应控制器.与此同时,对系统进行故障监控,设计了故障诊断滤波器,并利用对不确定性上界的估计终值提出了一种新的故障检测算法,进一步基于神经网络故障逼近,研究了一种修正控制律的自适应鲁棒容错控制器设计方法,该控制器通过补偿故障所带来的影响使闭环系统最终一致有界稳定.最后,通过仿真试验,验证了提出的方法的有效性.     

基于LMI的一体化鲁棒主动容错控制器设计

针对一类发生执行器故障的非线性系统,提出基于线性矩阵不等式(LMI)的一体化鲁棒主动容错控制器设计方法.首先,设计含自适应律的鲁棒滑模观测器,并将观测器设计方法转化为LMI约束下的凸优化问题,进而实现执行器故障的鲁棒重构;然后,提出基于状态及故障估计的一体化主动容错控制器,同时通过LMI给出控制器增益解算方法;最后,通过数值算例验证容错控制器设计方法的有效性.     

未知时变惯量航天器自适应姿态跟踪容错控制

针对存在未知时变惯量不确定性、执行机构衰退故障和外部干扰力矩的非刚体航天器系统,研究了航天器自适应姿态跟踪容错控制问题,结合非线性鲁棒控制方法、自适应方法、容错控制理论和参数估计方法,提出了一种鲁棒自适应姿态跟踪容错控制器。所设计的控制器克服了执行器故障、惯量不确定性以及外界干扰对系统稳定性的影响,保证了航天器姿态及角速度能够跟踪上时变的期望状态,实现了跟踪误差系统最终一致有界稳定。最后通过数字仿真验证了所提方法的有效性,并且与已有方法进行了对比,说明了所提方法的优越性。     

多故障并发非线性系统一体化跟踪主动容错控制器设计

针对一类执行器及传感器同时发生故障的非线性系统,综合鲁棒滑模重构观测器及自适应滑模容错控制器设计技术,提出一体化跟踪主动容错控制方案.首先,将系统增维变换为广义系统,运用广义约束逆引入辅助矩阵,采用线性矩阵不等式设计观测器系数矩阵,综合自适应律给出广义鲁棒滑模观测器设计程式;在此基础之上,通过设计鲁棒滑模微分器估计输出向量微分,结合广义鲁棒滑模观测器状态估计结论,实现执行器及传感器故障同时重构.其次,基于故障重构及状态估计结论,提出自适应滑模的跟踪主动容错控制律设计程式.最后,通过开展飞行模拟转台伺服系统数值仿真,检验一体化跟踪主动容错控制器设计方法的有效性.     

不确定离散时滞系统的鲁棒容错控制器设计

研究了具有参数不确定性的离散时滞系统的鲁棒容错控制问题,针对执行器故障和传感器故障分别给出了使闭环系统仍能保证渐近稳定的充分条件,控制器的设计可以通过求解线性矩阵不等式(LMI)方法得到。设计实例及仿真结果验证了该方法的有效性。     

不确定离散时滞系统的鲁棒容错控制器设计

研究了具有参数不确定性的离散时滞系统的鲁棒容错控制问题,针对执行器故障和传感器故障分别给出了使闭环系统仍能保证渐近稳定的充分条件,控制器的设计可以通过求解线性矩阵不等式(LMI)方法得到.设计实例及仿真结果验证了该方法的有效性.     

基于输出反馈的鲁棒容错D-稳定性分析

研究线性不确定系统基于输出反馈的鲁棒容错控制问题.基于连续型执行器故障模式,利用线性矩阵不等式LMI,给出了系统基于输出反馈的鲁棒容错D-稳定的充分条件,并把控制器的设计方法归结为求解一族线性矩阵不等式组.与常规的方法相比,给出的控制器不仅保证闭环系统对执行器故障具有完整性,并且使闭环系统的极点配置在指定区域D中.通过仿真示例表明,无论执行器发生故障与否,得到的基于输出反馈的鲁棒容错控制器均保证闭环系统是D-稳定的,从而验证了所提出设计方法的有效性.     

模型不确定多智能体系统的鲁棒H∞容错一致性控制

针对具有模型不确定性的多智能体系统,考虑到任意智能体可能发生的执行器故障以及受到外界能量有限干扰,研究了鲁棒H_∞容错一致性控制的设计问题。首先,引入鲁棒二次稳定法处理多智能体系统建模中存在的模型不确定性;其次,利用LMI技术及Lyapunov稳定性理论等,对于任意智能体可能发生的执行器故障,设计了鲁棒H_∞被动容错控制器,使得模型不确定多智能体系统存在外界能量有限干扰时,在所设计的分布式控制协议下位置与速度状态趋于一致,且具有一定的扰动抑制性能。最后,通过MATLAB仿真验证了所提方法的有效性和可行性。     

鲁棒容错H_∞控制系统设计

研究了不确定线性系统的鲁棒容错H∞ 控制问题 ,针对传感器失效故障 ,提出一种对传感器失效具有完整性、对参数不确定性具有鲁棒性且满足给定干扰衰减指标的鲁棒容错控制器设计方法 ,并讨论了执行器失效的情况     

Robust adaptive actuator failure compensation for a class of uncertain nonlinear systems

This paper presents a robust adaptive state feedback control scheme for a class of parametric-strict-feedback nonlinear systems in the presence of time varying actuator failures. The designed adaptive controller compensates a general class of actuator failures without any need for explicit fault detection. The parameters, times, and patterns of the considered failures are completely unknown. The proposed controller is constructed based on a backstepping design method. The global boundedness of all the closed-loop signals is guaranteed and the tracking error is proved to converge to a small neighborhood of the origin. The proposed approach is employed for a two-axis positioning stage system as well as an aircraft wing system. The simulation results show the correctness and effectiveness of the proposed robust adaptive actuator failure compensation approach.     

Characteristic Model-based Adaptive Fault Tolerant Control for Four-motor Synchronization Systems Considering Actuator Failure

This article proposes a characteristic model-based adaptive fault tolerant control scheme to deal with actuator failure in four-motor synchronization systems, which usually causes sudden inertia ratio change and backlash increase. Firstly, the characteristic modeling method is applied into servo system to obtain a simplified system model without losing high-order features. Also, this model could reflect real-time system status through three characteristic parameters. Secondly, a particle swarm optimization algorithm-based estimator is designed to identify characteristic parameters online. By this way, the characteristic model could react to inertia ratio changes quickly and eliminate its negative effect in signal tracking. Thirdly, an improved adaptive electric anti-backlash method is used to restrain backlash. Compared to regular anti-backlash technique, this adaptive one uses a neural network-based fault detector to monitor motors and adjust bias current according to different actuator status, even when one motor breaks down. With these three steps combined, a fast terminal sliding mode controller is finally designed as fault tolerant controller and the stability of this closed-loop system is guaranteed by Lyapunov stability theorem. At last, the simulation and experiment results prove the effectiveness of the proposed control scheme in system control and fault tolerance.

     

执行机构部分失效的挠性航天器多界依赖容错控制

针对挠性航天器在轨运行时受到的外部干扰,输入时滞以及执行机构部分失效问题,本文提出了一种基于不确定参数的鲁棒H_∞容错控制方法.首先,将执行机构部分失效容错控制问题转化为不确定参数的鲁棒控制问题.然后,设计了一个新型的多界依赖状态反馈鲁棒H_∞控制算法.此算法不仅依赖时滞积分不等式分割参数和时滞界信息,还依赖部分失效因子.因此,本文设计的控制器能同时实现对输入时滞的敏感,对部分失效故障的容错及对外部干扰的抑制.最后,通过一系列的仿真验证本文方法的有效性.     

Adaptive actuator fault compensation for linear systems with matching and unmatching uncertainties

The problem of process systems subject to actuator faults (partial loss of actuator effectiveness) is considered. An active fault compensation control law is designed that utilizes compensation in a way that accounts for matching and unmatching uncertainties and the occurrence of actuator faults. The main idea is designing the robust compensation controller to guarantee closed-loop stability in the presence of faults, based on a neural network representation of the fault dynamics. Changes in the system due to faults are modeled as unknown nonlinear functions. The updating control law is derived such that all the parameters of the closed-loop system are bounded. An output feedback controller is used to the “healthy” system and the adaptive feedback controller is used to compensate for the effect of the dynamics caused by the fault. The advantage of fault compensation is the dynamics caused by faults can be accommodated online. The proposed design method is illustrated on a three-tank system.     

Fault tolerant control for singular systems with actuator saturation and nonlinear perturbation

In this paper, the problem of robust fault tolerant control for a class of singular systems subject to both time-varying state-dependent nonlinear perturbation and actuator saturation is investigated. A sufficient condition for the existence of a fixed-gain controller is first proposed which guarantees the regularity, impulse-free and stability of the closed-loop system under all possible faults. An optimization problem with LMI constraints is formulated to determine the largest contractively invariant ellipsoid. An adaptive fault tolerant controller is then developed to compensate for the failure effects on the system by estimating the fault and updating the design parameter matrices online. Both of these two controllers are in the form of a saturation avoidance feedback with the advantage of relatively small actuator capacities compared with the high gain counterpart. An example is included to illustrate the proposed procedures and their effectiveness.     

Robust fault-tolerant control for a biped robot using a recurrent cerebellar model articulation controller.

A design technique of a recurrent cerebellar model articulation controller (RCMAC)-based fault-tolerant control (FTC) system is investigated to rectify the nonlinear faults of a biped robot. The proposed RCMAC-based FTC (RCFTC) scheme contains two components: 1) an online fault estimation module based on an RCMAC is used to provide approximation information for any nonnominal behavior due to the system failure and modeling error of the biped robot; and 2) a controller module consisting of a computed torque controller and a robust FTC is utilized to achieve FTC. In the controller module, the computed torque controller reveals a basic stabilizing controller to stabilize the system, and the robust FTC is utilized to compensate for the effects of the system failure so as to achieve fault accommodation. The adaptive laws of the RCFTC system are rigorously established based on the Lyapunov function, so that the stability of the system can be guaranteed. Finally, two simulation cases of a biped robot are presented to illustrate the effectiveness of the proposed design method. Simulation results show that the RCFTC system can effectively recover the control performance for the system in the presence of the nonlinear faults and modeling uncertainties.     

基于神经网络的鲁棒自适应逆飞行控制

提出基于在线神经网络的超机动飞行自适应动态逆鲁棒控制方法.超机动飞行的基本控制律采用非线性动态逆方法设计,对于建模误差或者控制面损伤等因素导致的不确定性逆误差采用神经网络进行自适应补偿.通过动态逆控制律简化计算和飞机控制面故障自适应修复的仿真表明,神经网络通过在线补偿逆误差,能够有效降低非线性动态逆对模型准确性的要求,增强控制系统的鲁棒性.     

Fault‐Tolerant Control for Flutter of Airfoil Subject to Input Saturation

In this paper, a fault tolerant control is studied for a two‐dimensional airfoil with input saturation and actuator fault. The dynamic equation of airfoil flutter is firstly established, in which the cubic hard spring nonlinearity of pitch stiffness is considered. Then, an adaptive sliding mode fault tolerant control is derived by using an on‐line updating law to estimate the bound of the actuator fault such that no information about the fault is needed. Furthermore, an auxiliary design system is introduced to resolve actuator saturation in control. Next, Lyapunov stability analysis is carried out to prove that the system is asymptotically stable. Finally, the effectiveness of the proposed controller is verified through numerical simulations. Simulation results indicate that the adaptive sliding mode fault tolerant controller is effective in suppressing airfoil flutter under partial loss of actuator effectiveness performance and input saturation.