考虑输入饱和的近空间飞行器姿态容错控制

针对近空间飞行器姿态控制中出现的执行器故障,输入饱和与外部干扰等问题,设计了一种基于二阶滑模干扰观测器和辅助系统的鲁棒容错跟踪控制方法.首先,将系统不确定,外部扰动和执行器故障作为复合干扰,设计super-twisting二阶滑模干扰观测器对其进行估计.然后为解决输入饱和问题构造了辅助分析系统,并借助backstepping方法,设计姿态容错跟踪控制器.利用Lyapunov方法,严格证明了所有闭环系统信号的收敛性.最后将所设计的控制方法应用于近空间飞行器姿态控制中,仿真结果验证了该控制方法的有效性.     

Iterative learning fault-tolerant control for injection molding processes against actuator faults

The injection molding process is a typical multi-phase batch process. As the filling and packing-holding phases share the same actuator, faults occurring in the actuators may cause serious impact on the performance and running time. Because these two phases are of crucial importance in relation to the final quality of the product, to solve this problem is essentially meaningful. This paper proposes iterative learning fault-tolerant control (ILTFC) in terms of common multi-phase batch processes and then applies it to the injection molding processes. To develop the ILFTC design, the multi-phase batch process is treated as a switched system composed of different dimensional subsystems and then converted to an equivalent two-dimensional (2D) switched fault-tolerant Rosser model. A hybrid fault-tolerant law is then designed based on an average dwell time method. Sufficient conditions and minimum running time guaranteeing the exponential stability under both normal and fault conditions are obtained. Under the proposed control law, the control performance and running time will restore to the previous level before actuator faults occur. The efficiency and merits of the proposed scheme is illustrated by an injection molding process, and results show that it can guarantee the stability and minimum running time whether the process is in normal operation or in case of actuator faults.     

基于事件触发机制的NNCS混合非脆弱容错控制

针对具有执行器故障和外界有限能量扰动的非线性网络化控制系统（NNCS），研究了离散事件触发通讯机制（DETCS）下的主—被动混合非脆弱容错控制器的设计问题。首先考虑了故障集，基于李亚普诺夫方法和状态反馈控制策略设计了被动非脆弱容错控制器，使得系统在发生已知故障类型时能够维持自身稳定，在发生未知故障初期减缓系统性能下降的速度。其次，基于H_∞理论设计的故障估计器在线实时检测系统故障，一旦获得未知故障信息，立即重构控制器进行补偿，确保系统渐近稳定并满足性能指标。最后，仿真算例验证了所提方法的正确性和有效性。     

四旋翼无人机不匹配扰动抗干扰控制

针对四旋翼无人机存在的不匹配干扰和执行器故障等现象,提出了一种基于有限时间观测器的飞行控制方案。从无人机的运动学模型出发,构建了受执行器故障和不匹配干扰影响的控制模型。将干扰观测器与非奇异终端滑模控制 (NTSMC) 方法相结合,以实现复合抗干扰和容错控制器设计。首先,设计了两个非线性有限时间扰动观测器来估计不匹配扰动和执行器故障,有限时间观测器使得估计误差在有限时间内收敛到零。其次,将观测器与NTSMC控制方法结合,以在有限的时间内实现跟踪,并有效地减少抖振。最后,从理论和仿真验证了控制方法的有效性和所期望的控制性能。     

临近空间飞行器的模型参考滑模容错控制

针对临近空间飞行器中未知的执行器控制效益损失和漂移故障,提出了一种模型参考滑模容错控制方法,保证故障系统对参考模型的稳定跟踪性能。利用跟踪误差系统设计容错控制器,首先构造积分滑模面,以增强系统鲁棒性并消除稳态误差;随后,在无需故障诊断单元的条件下设计模型参考滑模控制律,使其增益能实现自适应调节以处理未知故障影响,其中自适应律基于李雅普诺夫稳定性理论设计,保证闭环系统稳定。在临近空间飞行器纵向动力学模型上的仿真验证表明,该方法能处理执行器中发动机节流阀调节通道和升降舵偏转量通道的不同故障,保证系统获得满意的鲁棒容错跟踪性能。     

Detection,isolation and handling of actuator faults in distributed model predictive control systems

In this work, we focus on monitoring and reconfiguration of distributed model predictive control systems applied to general nonlinear processes in the presence of control actuator faults. Specifically, we consider nonlinear process systems controlled with a distributed control scheme in which two Lyapunov-based model predictive controllers manipulate two different sets of control inputs and coordinate their actions to achieve the desired closed-loop stability and performance specifications. To deal with control actuator faults which may reduce the ability of the distributed control system to stabilize the process, a model-based fault detection and isolation and fault-tolerant control system which detects and isolates actuator faults and determines how to reconfigure the distributed control system to handle the actuator faults while maintaining closed-loop stability is designed. A detailed mathematical analysis is carried out to determine precise conditions for the stabilizability of the fault detection and isolation and fault-tolerant control system. A chemical process example, consisting of two continuous stirred tank reactors and a flash tank separator with a recycle stream and involving stabilization of an unstable steady-state, is used to demonstrate the approach.     

基于迭代学习观测器的航天器姿态主动容错控制

针对含有外部扰动和执行器故障的一类航天器姿态控制系统,本文提出基于迭代学习观测器的主动容错控制方案.首先,建立了含有外部扰动和执行器故障的航天器姿态控制系统的运动学和动力学模型.其次,为了提高观测器的故障估计精度,在传统迭代学习观测器设计基础上引入上一时刻状态估计误差信息,文章提出一种改进型学习估计算法.进一步,基于滑模控制和指定时间稳定理论,利用学习观测器的故障估计信息设计指定时间主动容错控制器.与现有的航天器主动容错控制方案相比,本文所提出的算法的优势在于可以使故障系统的姿态能在指定时间跟踪上指令信号.基于Lyapunov方法,本文从理论上证明了改进型学习观测器和姿态容错控制系统的稳定性.最后,通过数值仿真,说明了所提容错控制方案的有效性和可行性.     

执行器故障多率采样间歇过程的鲁棒 耗散迭代学习容错控制

针对一类具有干扰和执行器故障的多率采样间歇过程,提出一种具有鲁棒耗散性能的迭代学习容错控制算法.通过提升技术将多采样率过程用慢速率采样的状态空间模型来描述,并基于二维系统理论,把迭代学习控制过程转化为等价2D Roesser故障系统,再沿时间和迭代方向设计具有耗散性能的反馈容错控制器,并以线性矩阵不等式形式给出容错控制器存在的充分条件,同时确保多率采样间歇过程在正常和故障条件下的耗散性能.注塑过程的注射速度控制仿真验证了方法的有效性和可行性.     

Unknown input modeling and robust fault diagnosis using black box observers

A key issue that needs to be addressed while performing fault diagnosis using black box models is that of robustness against abrupt changes in unknown inputs. A fundamental difficulty with the robust FDI design approaches available in the literature is that they require some a priori knowledge of the model for unmeasured disturbances or modeling uncertainty. In this work, we propose a novel approach for modeling abrupt changes in unmeasured disturbances when innovation form of state space model (i.e. black box observer) is used for fault diagnosis. A disturbance coupling matrix is developed using singular value decomposition of the extended observability matrix and further used to formulate a robust fault diagnosis scheme based on generalized likelihood ratio test. The proposed modeling approach does not require any a priori knowledge of how these faults affect the system dynamics. To isolate sensor and actuator biases from step jumps in unmeasured disturbances, a statistically rigorous method is developed for distinguishing between faults modeled using different number of parameters. Simulation studies on a heavy oil fractionator example show that the proposed FDI methodology based on identified models can be used to effectively distinguish between sensor biases, actuator biases and other soft faults caused by changes in unmeasured disturbance variables. The fault tolerant control scheme, which makes use of the proposed robust FDI methodology, gives significantly better control performance than conventional controllers when soft faults occur. The experimental evaluation of the proposed FDI methodology on a laboratory scale stirred tank temperature control set-up corroborates these conclusions.     

Fault-tolerant control of linear systems using adaptive virtual actuator

In this paper, design and development of fault-tolerant control (FTC) is investigated for linear systems subject to loss of effectiveness and time-varying additive actuator faults as well as an external disturbance using the fault-hiding approach. The main aim of this approach is to keep the nominal controller and to design a virtual actuator that is inserted between the faulty plant and the nominal controller in order to hide actuator faults and disturbances from the nominal controller, and consequently the performance of the system before and after the occurrence of actuator faults is kept to be the same. The proposed adaptive virtual actuator does not require a separated fault detection, isolation and identification (FDII) unit and both state and output feedback cases are considered. An illustrative example is given to demonstrate the effectiveness of the proposed adaptive virtual actuator in both cases.     

Fault-tolerant control strategy for multicylinder hydraulic press machine based on dynamic control allocation and adjustable multiobjective optimization

A hierarchical controller is proposed for achieving high-accuracy control and the dynamic balance with the presence of multiple faults of actuator, the external disturbance, and the model uncertainties in multicylinder hydraulic press machine (MCHPM). The method divides the controller design into three steps: Virtual fault-tolerant control law, control allocation algorithm, and actuator control law, which are progressive. First, to precisely compensate the lumped disturbances including the multiple faults of actuator, the external disturbance, and the model uncertainties, a disturbance observer (DO) is developed. By combining the observer with the sliding mode control (SMC), a virtual fault-tolerant control law is designed. Second, a highly integrated control allocation algorithm for the virtual fault-tolerant control law is proposed to get the desired driving force, taking into account dynamic control allocation (DCA), multiobjective optimization (MOO) and Analytic Hierarchy Process (AHP) simultaneously. Third, taking the driving force obtained from above control allocation algorithm as the desired target, the control law of each cylinder is calculated. The global stability for the whole system is proved by the Lyapunov theory. Lastly, results of simulation and experiment show that the proposed controller can effectively handle different faults and have more superior control performance.     

Fuzzy Iterative Learning Control-based Design of Fault Tolerant Guaranteed Cost Controller for Nonlinear Batch Processes

International Journal of Control, Automation and Systems - For nonlinear batch processes with actuator faults and external disturbances, a fault-tolerant guaranteed cost controller is proposed...     

考虑有执行器故障和有界扰动的鲁棒自适应容错补偿控制

考虑在执行器故障和外界干扰下, 用直接自适应状态反馈控制策略解决线性时不变连续时间系统的鲁棒容错补偿控制问题. 提出更一般且更实际的执行器故障模型. 在执行器故障和扰动的上界都未知下, 提出自适应律在线估计未知控制器参数. 然后基于自适应策略的信息, 构造一类鲁棒自适应状态反馈控制器自动补偿故障和扰动的影响. 基于李亚普诺夫定理, 在执行器故障和干扰下, 所得的自适应闭环系统可以被保证渐进稳定. 最后给出一个火箭整流罩模型的例子和它的仿真结果.     

执行器故障重复过程的鲁棒迭代学习容错控制方法及应用

针对具有执行器故障和外界扰动的线性重复过程,给出一种鲁棒迭代学习容错控制策略.首先,基于二维(2D)系统理论,设计鲁棒迭代学习容错控制器,将迭代学习控制系统等效转化为2D模型;然后,利用线性矩阵不等式(LMI)技术,分析和优化控制系统在时间和迭代方向上的容错性能以及对干扰的抑制性能,同时给出系统满足这些性能的充分条件,并进一步通过求解LMI凸优化问题获得控制器参数;最后,通过对旋转控制系统的仿真结果验证了所提出算法的有效性.     

From data to diagnosis and control using generalized orthonormal basis filters. Part II: Model predictive and fault tolerant control

Given a state space model together with the state noise and measurement noise characteristics, there are well established procedures to design a Kalman filter based model predictive control (MPC) and fault diagnosis scheme. In practice, however, such disturbance models relating the true root cause of the unmeasured disturbances with the states/outputs are difficult to develop. To alleviate this difficulty, we reformulate the MPC scheme proposed by K.R. Muske and J.B. Rawlings [Model predictive control with linear models, AIChE J. 39 (1993) 262–287] and the fault tolerant control scheme (FTCS) proposed by J. Prakash, S.C. Patwardhan, and S. Narasimhan [A supervisory approach to fault tolerant control of linear multivariable systems, Ind. Eng. Chem. Res. 41 (2002) 2270–2281] starting from the innovations form of state space model identified using generalized orthonormal basis function (GOBF) parameterization. The efficacy of the proposed MPC scheme and the on-line FTCS is demonstrated by conducting simulation studies on the benchmark shell control problem (SCP) and experimental studies on a laboratory scale continuous stirred tank heater (CSTH) system. The analysis of the simulation and experimental results reveals that the MPC scheme formulated using the identified observers produces superior regulatory performance when compared to the regulatory performance of conventional MPC controller even in the presence of significant plant model mismatch. The FTCS reformulated using the innovations form of state space model is able to isolate sensor as well as actuator faults occurring sequentially in time. In particular, the proposed FTCS is able to eliminate offset between the true value of the measured variable and the setpoint in the presence of sensor biases. Thus, the simulation and experimental study clearly demonstrate the advantages of formulating MPC and generalized likelihood ratio (GLR) based fault diagnosis schemes using the innovations form of state space model identified from input output data.     

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.     

Intelligent state estimation for fault tolerant nonlinear predictive control

There is growing realization that on-line model maintenance is the key to realizing long term benefits of a predictive control scheme. In this work, a novel intelligent nonlinear state estimation strategy is proposed, which keeps diagnosing the root cause(s) of the plant model mismatch by isolating the subset of active faults (abrupt changes in parameters/disturbances, biases in sensors/actuators, actuator/sensor failures) and auto-corrects the model on-line so as to accommodate the isolated faults/failures. To carry out the task of fault diagnosis in multivariate nonlinear time varying systems, we propose a nonlinear version of the generalized likelihood ratio (GLR) based fault diagnosis and identification (FDI) scheme (NL-GLR). An active fault tolerant NMPC (FTNMPC) scheme is developed that makes use of the fault/failure location and magnitude estimates generated by NL-GLR to correct the state estimator and prediction model used in NMPC formulation. This facilitates application of the fault tolerant scheme to nonlinear and time varying processes including batch and semi-batch processes. The advantages of the proposed intelligent state estimation and FTNMPC schemes are demonstrated by conducting simulation studies on a benchmark CSTR system, which exhibits input multiplicity and change in the sign of steady state gain, and a fed batch bioreactor, which exhibits strongly nonlinear dynamics. By simulating a regulatory control problem associated with an unstable nonlinear system given by Chen and Allgower [H. Chen, F. Allgower, A quasi infinite horizon nonlinear model predictive control scheme with guaranteed stability, Automatica 34(10) (1998) 1205–1217], we also demonstrate that the proposed intelligent state estimation strategy can be used to maintain asymptotic closed loop stability in the face of abrupt changes in model parameters. Analysis of the simulation results reveals that the proposed approach provides a comprehensive method for treating both faults (biases/drifts in sensors/actuators/model parameters) and failures (sensor/ actuator failures) under the unified framework of fault tolerant nonlinear predictive control.     

Robust Fault‐Tolerant Control of Launch Vehicle Via GPI Observer and Integral Sliding Mode Control

A robust fault‐tolerant attitude control scheme is proposed for a launch vehicle (LV) in the presence of unknown external disturbances, mismodeling dynamics, actuator faults, and actuator's constraints. The input‐output representation is employed to describe the rotational dynamics of LV rendering three independently decoupled second order single‐input‐single‐output (SISO) systems. In the differential algebraic framework, general proportional integral (GPI) observers are used for the estimations of the states and of the generalized disturbances, which include internal perturbations, external disturbances, and unknown actuator failures. In order to avoid the defects of the conventional sliding surface, a new nonlinear integral sliding manifold is introduced for the robust fault‐tolerant sliding mode controller design. The stability of the GPI observer and that of the closed‐loop system are guaranteed by Lyapunov's indirect and direct methods, respectively. The convincing numerical simulation results demonstrate the proposed control scheme is with high attitude tracking performance in the presence of various disturbances, actuator faults, and actuator constraints.