Actuator Fault Reconstruction Research Articles

Sensor fault reconstruction for wind turbine benchmark model using a modified sliding mode observer

<p><span lang="EN-GB">This paper proposes a fault diagnosis scheme applied to a wind turbine system. The technique used is based on a modified sliding mode observer (SMO), which permits the reconstruction of actuator and sensor faults. A wind turbine benchmark with a real sequence of wind speed is exploited to validate the proposed fault detection and diagnosis scheme. Rotor speed, generator speed, blade pitch angle, and generator torque have different orders of magnitude. As a result, the dedicated sensors are susceptible to faults of quite varying magnitudes, and estimating simultaneous sensor faults with accuracy using a classical SMO is difficult. To address this issue, some modifications are made to the classic SMO. In order to test the efficiency of the modified SMO, several sensor fault scenarios have been simulated, first in the case of separate faults and then in the case of simultaneous faults. The simulation results show that the sensor faults are isolated, detected, and reconstructed accurately in the case of separate faults. In the case of simultaneous faults, with the proposed modification of SMO, the faults are precisely isolated, detected, and reconstructed, even though they have quite different amplitudes; thus, the relative gap does not exceed 0.08% for the generator speed sensor fault.</span></p>

Actuator fault reconstruction using FDI system based on sliding mode observers

Interplanetary space missions require spacecraft autonomy in order to fulfill the mission objective. The fault detection and isolation (FDI) system increases the level of autonomy and can ensure the safety of the spacecraft by detecting and isolating potential faults before they become critical. The proposed FDI system is based on an innovative bank of SMOs (sliding mode observers), designed for different fault scenarios cases. The FDI system design aims to detect and isolate actuators and measurement units’ faults used by the satellite control system and considers the nonlinear model of the satellite dynamics. This approach gives the possibility of fault reconstruction based on the information provided by an equivalent injection signal, allowing to reconstruct external perturbances and faults. The SMO chattering phenomenon is avoided by using the pseudo-sliding function, being a linear approximation of the signum function, which gives the possibility of using the equivalent injection signal for fault reconstruction purposes. The proposed fault reconstruction methodology is illustrated by a case study for a 6U Cubesat.

Research on fault-tolerant consensus of heterogeneous multi-agent systems based on adaptive robust sliding mode observer

Abstract The fault-tolerant consensus control for heterogeneous multi-agent systems with actuator faults and external disturbances is studied in this paper. Firstly, considering the unknown actuator fault information and the influence of external disturbance on the observer, a robust sliding mode observer with adaptive laws modification was proposed to realize the actuator fault reconstruction. Secondly, a fault-tolerant controller is designed based on the reconstructed values obtained from the adaptive robust sliding mode observer, and the original heterogeneous complex dynamic high-dimensional system is converted into two low-dimensional closed-loop error systems by decoupling method. Furthermore, Lyapunov and Ricatti theories are used to obtain the controller gain solution method. Finally, a simulation experiment of fault-tolerant consensus control for heterogeneous multi-agent systems is carried out with one leading agent and four following agents, and the effectiveness and feasibility of the proposed method are verified.

Robust actuator fault reconstruction for Takagi‐Sugeno fuzzy systems with unknown input via a synthesized learning and sliding‐mode observer

AbstractThe issue of robust actuator fault reconstruction for a class of Takagi‐Sugeno (T‐S) fuzzy systems with actuator fault and unknown input via a novel Synthesized Learning and Sliding‐Mode Observer (SLSMO) is investigated in this paper. Through a coordinate transformation technique, the considered T‐S fuzzy system is decomposed into two separate subsystems: Subsystem 1 affected only by actuator fault and Subsystem 2 affected by unknown input and actuator fault. In the SLSMO methodology, for Subsystem 1, a new reduced‐order Fuzzy Learning Observer (FLO) is explored to accurately reconstruct actuator fault, while a reduced‐order Fuzzy Sliding Mode Observer (FSMO) is employed for Subsystem 2 such that it has strong robustness against actuator fault and unknown input. Stability and convergence of the fuzzy SLSMO are explicitly proved using Lyapunov's indirect method. The design issue of the reduced‐order FLO and of the reduced‐order FSMO can be uniformly formulated in terms of some Linear Matrix Inequalities (LMIs) that can be directly solved using LMI optimization technique. In addition, a new full‐order FLO is suggested for actuator fault reconstruction in a class of T‐S fuzzy system without unknown input. At the end, a numerical example is applied to verify the effectiveness and superiority of the proposed approaches.

Simultaneous Sensor and Actuator Fault Reconstruction by Using a Sliding Mode Observer, Fuzzy Stability Analysis, and a Nonlinear Optimization Tool

This paper proposes a Takagi–Sugeno (TS) fuzzy sliding mode observer (SMO) for simultaneous actuator and sensor fault reconstruction in a class of nonlinear systems subjected to unknown disturbances. First, the nonlinear system is represented by a TS fuzzy model with immeasurable premise variables. By filtering the output of the TS fuzzy model, an augmented system whose actuator fault is a combination of the original actuator and sensor faults is constructed. An performance criteria is considered to minimize the effect of the disturbance on the state estimations. Then, by using two further transformation matrices, a non-quadratic Lyapunov function (NQLF), and fmincon in MATLAB as a nonlinear optimization tool, the gains of the SMO are designed through the stability analysis of the observer. The main advantages of the proposed approach in comparison to the existing methods are using nonlinear optimization tools instead of linear matrix inequalities (LMIs), utilizing NQLF instead of simple quadratic Lyapunov functions (QLF), choosing SMO as the observer, which is robust to the uncertainties, and assuming that the premise variables are immeasurable. Finally, a practical continuous stirred tank reactor (CSTR) is considered as a nonlinear dynamic, and the numerical simulation results illustrate the superiority of the proposed approach compared to the existing methods.

Fault reconstruction and fault tolerant control design for a network of dynamical systems

This paper investigates the problems of the fault reconstruction and fault compensation controller design for a network of dynamic systems in which subsystems are interconnected through each subsystem’s outputs. First, under some assumptions, we prove that the minimum phase system condition, the observer matching condition and the controllability can be kept for the overall system. Second, an augmented descriptor system is constructed and we further prove that the minimum phase system condition, the observer matching condition are kept, and then a reduced-order observer is designed for the augmented system to obtain the estimates of the overall system states and the sensor faults simultaneously. Third, an interval observer is designed for the measured output, and based on the interval observer, an asymptotical actuator fault reconstruction method is developed. Finally, an observer-based H infinite and fault compensation scheme is designed and the stability of the closed-loop system is analyzed. We point out that the closed-loop system satisfies the so-called separation property. In the end, a simulation example is given to demonstrate the effectiveness of the proposed methods.

A fault estimation and fault-tolerant control based sliding mode observer for LPV descriptor systems with time delay

This paper considers the problem of fault-tolerant control (FTC) and fault reconstruction of actuator faults for linear parameter varying (LPV) descriptor systems with time delay. A polytopic sliding mode observer (PSMO) is synthesized to achieve simultaneous reconstruction of LPV polytopic descriptor system states and actuator faults. Exploiting the reconstructed actuator faults and state estimates, a fault-tolerant controller is designed to compensate the impact of actuator faults on system performance by stabilizing the closed-loop LPV delayed descriptor system. Besides, the controller and PSMO gains are obtained throughout the resolution of linear matrix inequalities (LMIs) using convex optimization techniques. The developed PSMO could force the output estimation error to converge to zero in a finite time when the actuators faults are bounded through the reinjection of the output estimation error via a nonlinear switching term. Simulation results applied to a given numerical system are presented to highlight the superiority and effectiveness of the proposed approach.

Robust Actuator Fault Reconstruction for Takagi-Sugeno Fuzzy Systems with Time-varying Delays via a Synthesized Learning and Luenberger Observer

This paper addresses the problem of robust actuator fault reconstruction for Takagi-Sugeno (T-S) fuzzy systems subjects to actuator faults, unknown inputs and time-varying delays via a Fuzzy Synthesized Learning and Luenberger Observer (FSL2O). Through a coordinate transformation, the original T-S fuzzy system is decomposed into two subsystems: subsystem-1 effected by actuator faults and subsystem-2 effected by unknown inputs. In the presented FSL2O methodology, a Reduced-Order Fuzzy Learning Observer (ROFLO) is explored for the subsystem-1 to reconstruct actuator faults accurately while a Reduced-Order Fuzzy State (Luenberger) Observer (ROFSO) is designed for the subsystem-2 based on the H∞ control technique such that it has strong robustness against the unknown inputs. The synthesized design of the ROFLO and the ROFSO is formulated in a unified manner in terms of Linear Matrix Inequalities (LMIs) that can be conveniently solved using LMI optimization technique. In addition, as a comparison, a full-order FLO is suggested for robust actuator fault reconstruction. Finally, a numerical example and simulation are provided to demonstrate the effectiveness of the proposed approaches.

A Novel Adaptive Observer-Based Fault Reconstruction and State Estimation Method for Markovian Jump Systems

The issues of actuator fault reconstruction, sensor fault reconstruction, and state estimation are considered in this article for Markovian jump systems, using a novel adaptive observer approach. First, by utilizing coordinate transformation technology, the original plant is decoupled into two subplants. The actuator faults and sensor faults are separated in different subplants. Then, two novel observers are proposed, respectively. With the two proposed adaptive observers, state estimation, sensor faults, and actuator faults reconstruction can be achieved. Finally, a numerical example is employed to verify the effectiveness of the theoretical results and to make comparisons with some existing fault reconstruction schemes.

Adaptive SMO-Based Fault Estimation for Markov Jump Systems With Simultaneous Additive and Multiplicative Actuator Faults

This article studies the problem of fault reconstruction, disturbance estimation, and state estimation for Markovian jump systems (MJSs) with simultaneous additive and multiplicative actuator faults. First, we rewrite the original Markov jump linear systems into an extended form, where the extended vector is composed of an actuator fault vector, a disturbance vector, and a state vector. Then, by proposing a continuous adaptive sliding-mode observer for the extended-form MJSs, the state estimation, actuator fault reconstruction, and disturbance estimation can be achieved. Moreover, the stochastic stability of the overall error plant can be guaranteed. Finally, a simulation example is employed to illustrate the effectiveness of our theoretical results.

Robust sliding mode observer design for simultaneous fault reconstruction in perturbed Takagi-Sugeno fuzzy systems using non-quadratic stability analysis

Appearing faults in a practical system is dispensable, and if it is not compensated, it results in poor system performance or even dysfunction of the system. The fault detection has become a promising challenging issue to guarantee the safety and reliability of systems. In this paper, a novel fuzzy-based sliding mode observer for the simultaneous actuator and sensor fault reconstruction of nonlinear systems subjected to external disturbance is proposed. The proposed approach employs the Takagi-Sugeno fuzzy model, sliding mode observer and non-quadratic Lyapunov function. First, by filtering the system output, a fictitious system whose actuator faults are the original actuator and sensor faults is constructed. Then, by considering the performance criteria, the effect of disturbance on the state estimations is minimized. It is proved that the estimations asymptotically converge to their actual values for non-perturbed systems. In the process of designing the observer gains, some transformation matrices are obtained by solving linear matrix inequalities. The proposed approach has some superiority over the existing methods. First, considering the non-quadratic Lyapunov function leads to relaxed results and good estimation performance. Second, using the sliding mode observer makes the proposed approach insensitive to the uncertainties and unknown inputs and determines the shape and size of the fault. Third, assuming the premise variables are immeasurable makes the presented approach more applicable. In conclusion, two practical systems are considered and simulation results illustrate the merits of the proposed approach in comparison with the recent methods from the fast and precise fault detection performance viewpoints.

Hybrid sliding mode observer for uncertain linear switching system with actuator faults

This paper investigates the problem of designing a hybrid sliding mode observer for mode identification and actuator fault reconstruction, applicable for a class of linear switching systems. For each operating mode constituting the whole system, only one observer is doomed to accomplish the two aforementioned tasks in the presence of exogenous disturbances. The method uses [Formula: see text] concept in the design of the sliding motion so that the effect of uncertainties on the residuals generation for mode recognition and on the reconstruction of the actuator faults will be minimized. Simulation results highlight the efficiency and the effectiveness of the proposed method.

Sliding mode observer for fault reconstruction of time-delay and sampled-output systems – a Time Shift Approach

This paper presents a novel Time Shift Approach for actuator fault reconstruction of systems with output time-delay based on a sliding mode observer (SMO). Arbitrary output delay duration, possibly uncertain and time-varying, can be considered. Ideal sliding mode is made possible even in the presence of delay. This is particularly important since chattering problems can be circumvented so that the proposed approach is conveniently applicable to the case of sampled-output systems. In order to allow a smooth fault reconstruction using noncausal filters, an intentional output delay of one or more sampling periods is introduced. Numerical simulations illustrate the effectiveness of the proposed methodology.

An Actuator Fault Detection and Reconstruction Scheme for Hex-Rotor Unmanned Aerial Vehicle

The detection and the reconstruction of actuator faults in a flight control system are crucial to avoid negative impacts on the aircraft itself, as well as human and environmental systems. In this paper, an actuator fault detection and reconstruction scheme based on fault classification for the hex-rotor unmanned aerial vehicle are designed. First, the fault type of actuator is analyzed and classified, then an actuator fault model is established based on multiple fault classification. Second, a fault detection and reconstruction (FDR) scheme for the hex-rotor unmanned aerial vehicle is proposed. In the proposed scheme, a fault observer group based on an extended Kalman filter (EKF) is designed for fault detection and isolation, and the flight state feedback required by the fault observer group is provided by the multi-sensor navigation unit (MSNU). Then, a fault reconstruction algorithm of the actuator is proposed by using the output of the fault observer group. The designed FDR system is applied to hex-rotor unmanned aerial vehicle prototype for its evaluation. The simulation results show that the proposed design is capable of fault detection and the reconstruction of actuator faults, and the actual flight verifies the effectiveness of the proposed methods.

Fault diagnosis based on sliding mode observer for LPV descriptor systems

AbstractThis paper considers the problem of fault detection and reconstruction of actuator faults for linear parameter varying descriptor systems. A polytopic sliding mode observer (PSMO) is constructed to achieve simultaneous reconstruction of LPV polytopic descriptor system states and actuator faults. Sufficient conditions for the existence and design algorithm of the proposed polytopic sliding mode observer are provided. In addition, the design of the PSMO is formulated in terms of linear matrix inequalities that can be suitably solved using convex optimization techniques. This PSMO can force the output estimation error to converge to zero in a finite time when the actuators faults are bounded through the reinjection of the output estimation error via a nonlinear switching term. The effectiveness of the design technique is illustrated through a simulation of an anaerobic bioreactor.

Actuator fault reconstruction based on a robust adaptive observer

A fault reconstruction method based on a robust adaptive observer is proposed to handle the actuator additive faults that exist in a non-linear descriptor system that satisfies the Lipschitz conditions. First, a robust adaptive fault reconstruction observer is proposed. This method has the desired robust performance and can achieve accurate reconstructions of both abrupt and time-varying faults in the presence of an external unknown disturbance. Then, to improve the transition process of fault reconstruction, an improved robust adaptive fault reconstruction observer is proposed. The improved robust adaptive fault reconstruction algorithm, which uses different coefficients for the proportion output errors and the derivative output errors, can enhance the rapidity and accuracy of fault reconstruction. The robust adaptive and improved robust adaptive observers are based on the linear matrix inequality technique. According to the Lyapunov stability theory, the stability conditions of the methods are derived. Additionally, the influence of an external unknown disturbance on the actuator fault reconstruction is suppressed using a robust method. Finally, two different examples are used to demonstrate the effectiveness of the proposed fault reconstruction methods.

Robust Output Disturbance, Actuator and Sensor Faults Reconstruction Using H∞ Sliding Mode Descriptor Observer for Uncertain Nonlinear Boiler System

This paper deals with a robust sliding mode descriptor observer for estimation of states and reconstruction of actuator and sensor faults simultaneously in the presence of uncertainties, measurement noise and output disturbances. In the proposed method, the well-known H∞ concepts are used for minimizing the effects of the uncertainty in the estimation of the states and reconstruction of the faults by using the Linear Matrix Inequalities (LMIs). By considering the sensor fault and output disturbance as auxiliary state vectors, an augmented system is established. As a case study, an industrial boiler is considered and the proposed robust observer illustrates the robust performance on estimation of its states and reconstruction of its faults in the presence of uncertainties.

Actuator Fault Reconstruction based Adaptive Polytopic Observer for a Class of Continuous-Time LPV Systems

Actuator Fault Reconstruction based Adaptive Polytopic Observer for a Class of Continuous-Time LPV Systems

Faults reconstruction for output time-delay systems: sliding mode observer approach

This paper addresses actuator and sensor faults reconstruction based on a new sliding mode observer (SMO) for output time-delay systems. Therefore, using the Lyapunov-Krasovskii functional, the stability of the estimation error dynamics is guaranteed. Also, the linear matrix inequality (LMI) technique is applied to express the observer synthesis. After that, the proposed SMO is used to obtain actuator and sensor faults reconstruction. To show the validity and the applicability of the proposed approaches, a numerical example is provided.

Simultaneous actuator and sensor fault estimation for discrete‐time Lipschitz nonlinear systems in finite‐frequency domain

SummaryThis paper addresses the problem of actuator and sensor fault reconstruction simultaneously with finite‐frequency specifications for discrete‐time Lipschitz nonlinear systems. First, an augmented system description is given by extending the sensor fault as an auxiliary state vector. Then, a multiobjective unknown input proportional‐integral observer is designed, and the nonlinear error dynamics are transformed into a linear parameter‐varying system based on the use of a reformulated Lipschitz property. Sufficient conditions for the design of a fault estimator with 2 finite‐frequency performances are derived in terms of linear matrix inequalities where a slack variable is introduced to reduce the conservativeness of the design. The proposed method can provide less restrictive linear matrix inequality conditions and get a better fault estimation performance than the existing one in the full frequency domain. Simulation results are given to show the effectiveness of the proposed techniques.