Adaptive Fault Diagnosis Observer Research Articles

Fault tolerant compensation strategy for stochastic distribution systems with communication constraints

A new type of fault tolerant compensation strategy on the basis of sliding mode predictive control is presented for stochastic distribution systems (SDSs) in case of time-delay and packet dropout. The random packet loss process from the sensor to the controller is described as the independent Bernoulli distribution and a packet loss compensation strategy is introduced to compensate for the impact of packet loss on the system. To obtain information about the unknown fault, the adaptive fault diagnosis (FD) observer is devised on the basis of residual information. A fault tolerant control (FTC) strategy that combines the sliding mode control (SMC) and model predictive control (MPC) is put forward to make SDSs with fault still have good tracking performance. The proposed algorithm is applied to the fiber length distribution control in the papermaking process, and the simulation results prove the efficiency of the scheme.

Robust adaptive fault detection and diagnosis observer design for a class of nonlinear systems with uncertainty and unknown time-varying internal delay

This paper introduces a novel robust adaptive fault detection and diagnosis (FDD) observer design approach for a class of nonlinear systems with parametric uncertainty, unknown system fault and time-varying internal delays. The conditions for the existence of the proposed FDD are obtained based on the well-known Linear Matrix Inequalities (LMI) technique. Using Lyapunov stability theory, the adaptation laws for updating the observer weights and unknown faults estimation are derived based on which the convergence of the state estimation error to zero and asymptotic stability of the error dynamics are proven. Toward this, a new structural algorithm for FDD observer design is also derived based on LMIs. The performance of the proposed method is also investigated while applying to some industrial systems. Simulation results illustrate superior performance of the proposed method for the systems subject to time-varying unknown delays on states, uncertainty in nonlinear system modeling and unknown system faults.

Fault diagnosis and fault‐tolerant control of uncertain network control systems

SummaryIn this article, the equivalent control strategy based on Laplace transform is proposed for the problem of stochastic delay in networked control systems. The original system is transformed into an equivalent control system without random delay block by Laplace transform. Then, a new augmented variable and equivalent control system is introduced to construct an augmented system. An adaptive fault diagnosis observer is designed based on the augmented system. The adaptive turning rate of the observer is obtained by solving the corresponding linear matrix inequality. Based on the information of online fault diagnosis and state estimation, a fault‐tolerant controller based on PI control strategy is designed to compensate the fault. Finally, a model of the switched reluctance motor system is considered to show the effectiveness of this method.

Model Predictive Fault-Tolerant Tracking Control for PDF Control Systems With Packet Losses

In this article, a fault-tolerant tracking control strategy is investigated for nonlinear probability density function (PDF) control systems with the actuator fault, uncertainties, unknown disturbance, and random packet losses. The control input signal dropout and measurement signal dropouts are described as the independent Bernoulli distribution. An adaptive fault diagnosis (FD) observer based on the Lyapunov function is given to simultaneously estimate the fault, disturbance, and state with packet losses. Different from the traditional robust fault-tolerant control (FTC), a new active fault-tolerant tracking controller is designed based on the model predictive control framework, which has better adaptive fault-tolerant performance. Finally, the validity of the proposed FTC method has been proved by a simulation study of a papermaking process.

Discrete-Time 2-Order Sliding Mode Fault-Tolerant Tracking Control for Non-Gaussian Nonlinear Stochastic Distribution Control Systems with Missing Measurements

In this paper, a method of fault diagnosis (FD) and fault-tolerant tracking control (FTTC) is investigated for non-Gaussian nonlinear stochastic distribution control (SDC) systems with missing measurements. The phenomenon of the randomly occurring missing measurements is described as a Bernoulli process. The missing measurements during transmission are compensated with the data successfully transmitted at the previous moment. The residual signal of the fault diagnosis observer is different from that of the general system. Using the integral of the error of the output probability density function (PDF) as the driving information, the system state and fault can be estimated by an adaptive fault diagnosis observer. Then, a novel fault-tolerant tracking controller is designed based on a discrete-time 2-order sliding mode to make the post-fault PDF still track the target. Two simulated examples are included to illustrate the effectiveness of the theoretical results.

Minimum rational entropy fault tolerant control for non-Gaussian singular stochastic distribution control systems using T-S fuzzy modelling

ABSTRACTIn this paper, a new fault diagnosis (FD) and fault tolerant control (FTC) algorithm for a non-Gaussian nonlinear singular stochastic distribution control (SDC) system is studied. The rational square-root fuzzy logic model is used to approximate the output probability density function of non-Gaussian processes and a Takagi-Sugeno (T-S) fuzzy model is employed to transform the non-Gaussian nonlinear SDC system into a fuzzy SDC system. An adaptive fuzzy fault diagnosis observer is constructed to achieve reconstruction of system state and fault. Based on the estimated fault information, the controller is reconfigured by minimising the performance index with regard to the rational entropy subjected to mean constraint. Minimum rational entropy fault tolerant control is introduced to make the output of the past-fault SDC system still have the minimum uncertainty. Simulation results are provided to demonstrate the validity of the FD and minimum rational entropy FTC algorithm.

Fault Diagnosis and Statistical Information Tracking Fault Tolerant Control for Non-Gaussian Non-linear Stochastic Systems

A novel fault diagnosis and fault tolerant control algorithm for non-Gaussian non-linear stochastic systems is presented in this paper. Different from conventional fault diagnosis algorithms, the statistical information function rather than the output value is used as the driven information to design the adaptive fault diagnosis observer. Finally, based on the fault diagnosis information, a new fault-tolerant controller based on sliding mode tracking control scheme is designed to make the post-fault statistical information function still track the target one. A simulated example is included to illustrate the effectiveness of the theoretical results.

Fault diagnosis and model predictive tolerant control for non-Gaussian stochastic distribution control systems based on T-S fuzzy model

A Takagi-Sugeno (T-S) fuzzy model is applied to approximate the nonlinear dynamics of stochastic distribution control (SDC) systems, in which linear radial basis function (RBF) neural network is adopted to approximate the output probability density function (PDF) of non-Gaussian SDC systems. Considering the situation that fault may occur, a fuzzy adaptive fault diagnosis observer is designed to estimate the fault value. Besides, the Lyapunov stability theory is used to analyse the stability of the observation error system. Based on the fault estimation information and model predictive control (MPC) algorithm, the active fault tolerant control strategy is given. Finally, a simulation example is given to verify the effectiveness of the proposed control algorithm.

离心式压缩机执行器故障诊断方法设计

针对一类满足利普希茨条件的离心式压缩机系统，提出了一种新型压缩机执行器故障诊断方法。设计自适应诊断观测器，实时动态采集压缩机执行器故障前后的信息，对压缩机执行器故障进行精确跟踪，达到故障诊断的目的。利用Lyapounov函数分析了设计系统的稳定性。仿真结果表明，自适应诊断观测器能够实时精准的跟踪离心式压缩机执行器故障，证明了该方法的有效性。 A novel compressor actuator fault diagnosis method is proposed for the centrifugal compressor system satisfying Lipschitz condition. By collecting the real-time status of the compressor actuator faulty and normal conditions, adaptive diagnostic observer is design, and then the compressor actuator fault is tracked accurately, which realizes the fault detection. The stability of design system is analyzed by using Lyapounov function. The results show that the adaptive fault diagnosis observer can accurately track the centrifugal compressor actuator fault, which proves the effectiveness of the proposed method.

An online fault tolerant actor-critic neuro-control for a class of nonlinear systems using neural network HJB approach

In this paper, we propose an actor-critic neuro-control for a class of continuous-time nonlinear systems under nonlinear abrupt faults, which is combined with an adaptive fault diagnosis observer (AFDO). Together with its estimation laws, an AFDO scheme, which estimates the faults in real time, is designed based on Lyapunov analysis. Then, based on the designed AFDO, a fault tolerant actor- critic control scheme is proposed where the critic neural network (NN) is used to approximate the value function and the actor NN updates the fault tolerant policy based on the approximated value function in the critic NN. The weight update laws for critic NN and actor NN are designed using the gradient descent method. By Lyapunov analysis, we prove the uniform ultimately boundedness (UUB) of all the states, their estimation errors, and NN weights of the fault tolerant system under the unpredictable faults. Finally, we verify the effectiveness of the proposed method through numerical simulations.

Fault Diagnosis and Initiative Tolerant Control for Wind Energy Conversion System

The fault mathematical model of the transmission of wind energy conversion system is established,and adaptive fault diagnosis observer is constructed in the presence of unknown disturbance,it can detect the faults of the system,and adaptive estimate this fault.Then,based on fault diagnosis observer,an initiative tolerant controller is designed to ensure the stability of the transmission of wind energy conversion system in case of the fault.The detail proof of stability for the system is given.The simulation results of different fault types of main transmission chain show the effectiveness and feasibility of adaptive fault diagnosis and initiative tolerant methods.

Fault estimation and accommodation for networked control systems with nonuniform sampling periods

SummaryThis paper deals with the problem of fault estimation and accommodation for a class of networked control systems with nonuniform uncertain sampling periods. Firstly, the reason why the adaptive fault diagnosis observer cannot be applied to networked control systems is analyzed. Based on this analysis, a novel robust fault estimation observer is constructed to estimate both continuous‐time fault and system states by using nonuniformly discrete‐time sampled outputs. Furthermore, using the obtained states and fault information, a nonuniformly sampled‐data fault tolerant control law is designed to preserve the stability of the closed‐loop system. The proposed scheme can not only guarantee the impact of continuous‐time uncertainties and discrete‐time sampled estimation errors on the faulty system to satisfy a H ∞ performance index but also repress the negative effect of the unknown intersample behavior of continuous‐time fault by use of an inequality technique. Finally, simulation results are included to demonstrate the feasibility of the proposed method. Copyright © 2014 John Wiley & Sons, Ltd.

Adaptive Nonlinear Actuator Fault Diagnosis for Uncertain Nonlinear Systems with Time‐Varying Delays

ABSTRACTAn actuator fault diagnosis method is presented in this paper for a class of time‐delayed nonlinear systems via the use of adaptive updating rules. The considered system is represented by a dynamic state space model where the time delays are embedded into the state vector. Model parameters are not perfectly known, which lead us to consider norm bounded uncertainties. An adaptive fault diagnosis observer is designed where the Lyapunov stability theory is used to obtain the required adaptive tuning rule for estimation of the nonlinear actuator fault. A simulated numerical example is included to demonstrate the effectiveness of the proposed approach.

비선형 연속 시간 시스템을 위한 적응 고장 진단 관측기 기반 슬라이딩 모드 제어기 설계

In this paper, we propose an AFDO (Adaptive Fault Diagnosis Observer) and a fault tolerant controller for a class of nonlinear continuous-time system under the nonlinear abrupt actuator faults. Together with its estimation laws, the AFDO which estimates that the actuator faults is designed by using the Lyapunov analysis. Then, based on the designed AFDO, an adaptive sliding mode controller is proposed as the fault tolerant controller. Using Lyapunov stability analysis, we also prove the uniform boundedness of the state, the output and the fault estimation errors, and the asymptotic stability of the tracking error under the nonlinear time-varying faults. Finally, we illustrate the effectiveness of the proposed diagnosis method and the control scheme thorough computer simulations.

基于输出时滞方法的采样数据系统故障估计

The problem of fault estimation for a class of non-uniformly sampled-data systems is investigated from the time delay point of view in this paper. Firstly, the output delay approach is employed to model the sampled-data system as a continuous-time one with time-varying delay output. Then, based on the analysis of the inapplicability of the adaptive fault diagnosis observer in such class of time-delay systems, a novel augmented fault estimation observer design method is proposed to guarantee the exponential convergence of the estimation errors. Furthermore, an extension to the case of time varying fault estimation for the noisy sampled-data systems is studied. Finally, simulation results of a flight control system are presented to demonstrate the effectiveness of the proposed method.

Analysis and design of robust estimation filter for a class of continuous-time nonlinear systems

This article addresses the design of a multiconstrained robust estimation filter (MREF) for a class of continuous-time nonlinear systems in the presence of input and output disturbances. By constructing an augmented system, the MREF achieves the estimation of both states and faults, under existence conditions that are less restrictive than those associated with existing adaptive fault diagnosis observer (AFDO) and sliding mode observer design. Moreover, a detailed discussion on and comparison with the AFDO design are given. Furthermore, by introducing slack variables, improved results on MREF design are obtained such that different Lyapunov functions can be separately designed for multiple constraints. Simulation results are presented to illustrate our contributions.

An output delay approach to fault estimation for sampled-data systems

The problem of fault estimation for a class of non-uniformly sampled-data systems is investigated from the time delay point of view in this paper. Firstly, the output delay approach is employed to model the sampled-data system as a continuous-time one with time-varying delay output. Then, based on the analysis of the inapplicability of the adaptive fault diagnosis observer in such class of time-delay systems, a novel augmented fault estimation observer design method is proposed to guarantee the exponential convergence of the estimation errors. Furthermore, an extension to the case of time varying fault estimation for the noisy sampled-data systems is studied. Finally, simulation results of a flight control system are presented to demonstrate the effectiveness of the proposed method.

Fault Estimation for Nonlinear Dynamic Systems

In this paper, the problems of fault detection and estimation for nonlinear dynamic systems are considered by using fault detection observer and adaptive fault diagnosis observer. Based on Lyapunov stability theory and linear matrix inequality (LMI) techniques, a new sufficient condition in terms of LMIs for the proposed problem is derived. At the same time, we get the adaptive fault estimation algorithm. The LMI condition can be easily solved by MATLAB LMI toolbox. Finally, a flexible joint robotic example is given to illustrate the efficiency of the proposed approach.

Fast adaptive fault estimation and accommodation for nonlinear time‐varying delay systems

AbstractThis paper studies the problem of fault estimation and accommodation for a class of nonlinear time‐varying delay systems using adaptive fault diagnosis observer (AFDO). A novel fast adaptive fault estimation algorithm that does not need the derivative of the output vector is proposed to enhance the performance of fault estimation. Meanwhile, a delay‐dependent criteria is obtained based on free weighting matrix method with the purpose of reducing the conservatism of the AFDO design. On the basis of fault estimation, an observer‐based fault‐tolerant controller is designed to guarantee the stability of the closed‐loop system. In terms of matrix inequality, we derive sufficient conditions for the existence of the adaptive observer and fault‐tolerant controller. Simulation results are presented to illustrate the efficiency of the proposed method. Copyright © 2009 John Wiley and Sons Asia Pte Ltd and Chinese Automatic Control Society

Less conservative criteria for fault accommodation of time‐varying delay systems using adaptive fault diagnosis observer

AbstractThis paper studies the problem of fault accommodation of time‐varying delay systems using adaptive fault diagnosis observer. Based on the proposed fast adaptive fault estimation (FAFE) algorithm using only a measured output, a delay‐dependent criteria is first established to reduce the conservatism of the design procedure, and the FAFE algorithm can enhance the performance of fault estimation. On the basis of fault estimation, the observer‐based fault‐tolerant tracking control is then designed to guarantee tracking performance of the closed‐loop systems. Furthermore, comprehensive analysis is presented to discuss the calculation steps using linear matrix inequality technique. Finally, simulation results of a stirred tank reactor model are presented to illustrate the efficiency of the proposed techniques. Copyright © 2009 John Wiley & Sons, Ltd.