Robust Sliding Mode Observer based Fault Estimation for Certain Class of Uncertain Nonlinear Systems

This paper proposes a new scheme for estimating the actuator and sensor fault for Lipschitz nonlinear systems with unstructured uncertainties using the sliding mode observer (SMO) technique. Initially, a coordinate transformation is introduced to transform the original state vector into two parts such that the actuator faults only appear in the dynamics of the second state vector. The concept of equivalent output error injection is then employed to estimate the actuator fault. The effects of system uncertainties on the estimation errors of states and faults are minimized by integrating an uncertainty attenuation level into the observer. The sufficient conditions for the state estimation error to be bounded and satisfy a prescribed performance are derived and expressed as a linear matrix inequality (LMI) optimization problem. Furthermore, the proposed actuator fault estimation method is extended to sensor fault estimation. Finally, the effectiveness of the proposed scheme in estimating actuator and sensor faults has been illustrated considering an example of a single‐link flexible joint robot system.     

Sensor Fault Diagnosis Based on a Sliding Mode and Unknown Input Observer for Takagi‐Sugeno Systems with Uncertain Premise Variables

This paper presents the design of a sliding mode and an unknown input observer for Takagi‐Sugeno (TS) systems. Contrary to the common approaches reported in the literature, which considers exact premise variables, this work deals with the problem of inexact measurements of the premise variables. The proposed method is based on a criteria to be robust to disturbances, sensor noise and uncertainty on the premise variables. The observer convergence and stability are established by considering a quadratic Lyapunov function, which relies on a set of Linear Matrix Inequalities. Then, a dedicated observer scheme is considered to detect and isolate sensor faults. Finally, the performance and applicability of the proposed approach are illustrated through numerical experiments on a nonlinear model that represents the lateral dynamics of an electric vehicle.     

Composite Disturbance‐Observer‐Based Control and Control for High Speed Trains with Actuator Faults

To guarantee the position and velocity tracking performance of high speed trains (HSTs) with actuator faults, a composite control algorithm consisting of the disturbance‐observer‐based control (DOBC) and control is proposed. Based on the multiple point‐mass model, the dynamics of HSTs is established by a cascade of carriages which are connected by flexible couplers, during the procedure of which, the running resistance, actuator faults and multiple disturbances are taken into account. The multiple disturbances are composed of two parts, one of which is the ramp resistance due to the track slope, the other is unknown gusts which can be modeled as a harmonic disturbance with time‐varying frequency. The unknown gusts is estimated and rejected via the DOBC methodology, meanwhile, the running resistance and the ramp resistance are attenuated by the control methodology. According to the Lyapunov stability analysis and LMI‐based algorithms, main results are derived such that the closed‐loop system is asymptotically stable and the desired performance can be guaranteed. Compared with the numeral simulation results with the single control method, it is demonstrated that the proposed control methodology is more effective and the system has a higher precision of position and velocity tracking.     

基于滑模观测器和广义观测器的故障估计方法

针对受未知干扰影响的一类非线性系统,提出一种基于滑模观测器和广义观测器的执行器故障和传感器故障估计方法.首先通过线性变换将原系统解耦为两个降阶的子系统,其中一个子系统受执行器故障和干扰的影响,另一个含有传感器故障和干扰,进一步将后一个子系统转化为广义系统.对两类子系统分别设计滑模观测器和广义观测器,给出估计误差一致最终有界的条件,得到系统状态和未知干扰的估计值.然后,利用等效输出控制原理重构执行器故障,引入干扰补偿保证重构算法的鲁棒性,再根据广义观测器的结果获得传感器故障的估计值.最后,通过计算机仿真验证了本文方法的有效性.     

Approximation Optimal Vibration for Networked Nonlinear Vehicle Active Suspension with Actuator Time Delay

This paper is concerned with the modelling and vibration control problem for networked nonlinear vehicle active suspension (NNVAS) with actuator time delay. Inserting in‐vehicle communication network to active suspension, a novel model for NNVAS is established based on the Takagi‐Sugeno fuzzy fusion technology first. By introducing a transformation vector, NNVAS with actuator time delay is reformed as a delay‐free nonlinear system. Then, an approximation optimal vibration controller (AOVC) is proposed by using an iterative algorithm, which consists of suspension state item, a road disturbance state item, and a compensated item for nonlinear response. Dependant on the control performance in each iteration, the computability of proposed AOVC is realized. A reduced‐order observer is designed to solve the physical unrealizable problem of road disturbances. Finally, compared with the open‐loop system and control scheme without network setting, the capability of improving control performance under AOVC is illustrated.     

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.     

Simultaneous Actuator and Sensor Faults Reconstruction Based on Robust Sliding Mode Observer for a Class of Nonlinear Systems

This paper proposes a new robust fault reconstruction and estimation design for a class of nonlinear system described by the Takagi‐Sugeno model with unmeasurable premise variables subject to faults affecting actuators, sensor faults, and unknown disturbances. The augmented Takagi‐Sugeno system is introduced with a new fault vector which has two origins: the first one represents actuator faults, the second one denotes faults affecting sensors. The main contribution is focused primarily to conceive a sliding mode observer with two discontinuous terms designed to compensate for fault behavior and disturbance variation from the system states estimation. In the formalism of linear matrix inequalities, we derive sufficient conditions to guarantee the state estimation error stability and to obtain the observer gains. Meanwhile, additional effort is made to achieve simultaneous faults and disturbance reconstruction. Simulation results are given to illustrate the proposed approach performances.     

Adaptive robust actuator fault compensation for linear systems using a novel fault estimation mechanism

This paper investigates the problem of adaptive fault‐tolerant control for a class of linear systems with time‐varying actuator faults. The outage and loss‐of‐effectiveness fault cases are covered. An active fault compensation control law was designed in two steps. Firstly, the time‐varying fault parameters were estimated based on a novel adaptive observer. Compared with the traditional adaptive observer, the actuator fault estimations are faster and the high‐frequency oscillations can be attenuated effectively. Such oscillations are usually caused by increasing the gains of adaptive laws to deal with abrupt changes in system dynamics. Then, based on online estimations of the fault parameters, an adaptive fault‐tolerant controller was constructed to compensate for the loss of actuator effectiveness and to eliminate the effect of fault estimation error. The asymptotic stability and an adaptive performance of a closed‐loop system can be guaranteed, even in the case of actuator faults and disturbances. Simulation results are given to verify the effectiveness and superiority of the proposed method. Copyright © 2015 John Wiley & Sons, Ltd.     

基于高增益鲁棒滑模观测器的故障检测和隔离

针对一类同时具有执行器和传感器故障的不确定线性系统,讨论了基于观测器的故障检测和隔离方法.首先,通过引入增维向量,使得在构造的增维系统中,故障向量包含了原系统的执行器故障和传感器故障.通过构造辅助输出使增维系统的观测器匹配条件得以满足,同时设计高增益滑模观测器对辅助输出进行估计.然后,对增维系统构造鲁棒滑模观测器并用作故障检测观测器,通过滑模控制项来抑制干扰,使观测器具有鲁棒性.在此基础上,结合多观测器故障隔离思想,提出了可以同时对执行器故障和传感器故障进行检测和隔离的方法. 最后,通过对一个五阶飞行器模型进行仿真,证明了所提方法的有效性.     

Robust fault diagnosis of disturbed linear systems via a sliding mode high order differentiator

A fault estimator for linear systems affected by disturbances is proposed. Faults appearing explicitly in the state equation and in the system output (actuator faults and sensor faults) are considered. With this design neither the estimation of the state vector nor the estimation of the disturbances is required, implying that the structural conditions are less restrictive than the ones required to design an unknown input observer. Furthermore, the number of unknown inputs (faults plus disturbances) may be greater than the number of outputs. The faults are written as an algebraic expression of a high-order derivative of a function depending on the output. Thus, the reconstruction of the fault signals is carried out by means of a sliding mode high-order differentiator, which requires the derivative of the faults to have a bounded norm.     

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.     

Non‐Fragile Observer‐Based Control for Uncertain Neutral‐Type Systems via Sliding Mode Technique

This paper is concerned with the problem of observer‐based control for a class of uncertain neutral‐type systems subjected to external disturbance by utilizing sliding mode technique. A novel sliding mode control (SMC) strategy is proposed based on the state estimate and the output. A new sufficient condition of robust asymptotic stability with disturbance attenuation level for the overall systems composed of the original system and error system in the sliding mode is derived in terms of a linear matrix inequality (LMI). Then, a new adaptive controller is designed to guarantee the reachability of the predefined sliding surface in finite‐time. Finally, numerical examples are provided to verify the effectiveness of the proposed method.