Adaptive Fault Estimation Observer Research Articles

Observer‐based fault tolerant control for a class of nonlinear multi‐agent systems with sensor faults

AbstractThis article focuses on the robust fault tolerant control (FTC) problem for a class of Lipschitz nonlinear multi‐agent systems(MASs) subject to sensor faults. Firstly, sensor faults are transformed into actuator faults via introducing a new intermediate auxiliary state variable, and a distributed adaptive fault estimation observer is designed to estimate the state information and the concerned faults by using the relative output estimation error. Then, the sufficient existence conditions for the observer to satisfy the robust performance index are given. Thirdly, based on the results of observer design, a new design method of dynamic output feedback controller is proposed to implement consensus of MASs and ensure the desired disturbance rejection performance. Finally, the simulation results are presented to illustrate the effectiveness of the proposed method.

Fault estimation for persistent dwell time switched systems with actuator and sensor faults

This paper investigates the fault estimation (FE) problem for a class of switched systems with external disturbances, actuator faults and sensor faults. A new adaptive FE observer is proposed to estimate the sensor and actuator faults simultaneously. Meanwhile, a more general and flexible persistent dwell time (PDT) switching signal is utilized to depict slow switching and fast switching phenomenon of switched systems. Then, sufficient conditions can be achieved to guarantee the stability of the estimation error dynamics. Finally, a simulation example of the circuit system is presented to show the effectiveness of the proposed FE scheme.

Event-triggered consensus control and fault estimation for time-delayed multi-agent systems with Markov switching topologies

This paper focuses on the consensus control and fault estimation problems for a class of time-delayed multi-agent systems with Markov switching topologies. Two different event-triggered mechanisms are adopted with hope to reduce burden of shared network and improve energy efficiency. Under Markov process, by establishing the consensus control protocol and designing a novel adaptive fault estimation observer, the consensus control and fault estimation problems are transformed into two stochastic stability problems in different forms. Then, according to the switching Lyapunov function method and free-weighting matrix technique, two delay-dependent stability criteria on the consensus control and fault estimation are derived, respectively. However, the two criteria containing nonlinear coupling terms are not standard linear matrix inequalities (LMIs) and cannot be solved directly with the LMI toolbox. In order to eliminate the coupling terms, two improved path-following algorithms are presented. These algorithms depend on the initial conditions, so it is very crucial to choose the appropriate preset parameters. The computational complexity is increasing with the number of iterations, system size and matrix dimension, which is a fully new challenge for the study of consensus control and fault estimation of multi-agent systems. Based on the algorithms, the switching consensus controller gains and model gain matrices of fault estimation can be efficiently solved out. Finally, a simulation example of tailless fighter airplanes is given to illustrate the practicality and validity of the theoretical results.

Fault estimation observer design for a class of nonlinear multiagent systems in finite‐frequency domain

SummaryThis paper focuses on the fault estimation observer design problem in the finite‐frequency domain for a class of Lipschitz nonlinear multiagent systems subject to system components or actuator fault. First, the relative output estimation error is defined based on the directed communication topology of multiagent systems, and an observer error system is obtained by connecting adaptive fault estimation observer and the state equation of the original system. Then, sufficient conditions for the existence of the fault estimation observer are obtained by using a generalized Kalman‐Yakubovich‐Popov lemma and properties of the matrix trace, which guarantee that the observer error system satisfies robustness performance in the finite‐frequency domain. Meanwhile, the pole assignment method is used to configure the poles of the observer error system in a certain area. Finally, the simulation results are presented to illustrate the effectiveness of the proposed method.

Adaptive Fault Estimation and Fault-Tolerant Control for Nonlinear System With Unknown Nonlinear Dynamic

This paper investigates the problems of fault estimation and fault-tolerant control for nonlinear system. The nonlinear part of the system is assumed to be unknown. Based on the adaptive approximation technique, which can be performed by fuzzy logic systems or neural networks, an adaptive fault estimation observer is designed, and the fault and the system state can be estimated simultaneously. Based on the estimation information, the observer-based fault-tolerant controller is designed. In this paper, the parameter matrices of the adaptive law and the observer and the controller can be calculated by slowing LMIs. To verify the proposed scheme, a simulation example is provided at the end of this paper.

Robust adaptive fault estimation and fault tolerant control for quadrotor attitude systems

ABSTRACTThis paper addresses the problem of fault estimation and fault tolerant control for quadrotor unmanned aerial vehicle. Firstly, a robust adaptive fault estimation observer (AFEO) is proposed to achieve fault estimation of quadrotor with actuator fault in the presence of external disturbances and parameter uncertainties. Furthermore, based on the estimation of fault, a dynamic output feedback fault tolerant controller (DOFFTC) is designed to stabilise the closed-loop system with faults and uncertainties. Sufficient conditions for the existence of both AFEO and DOFFTC are given in terms of linear matrix inequalities. Finally, simulation results are presented to illustrate the effectiveness of the proposed strategy.

Fault Diagnosis for Linear Discrete Systems Based on an Adaptive Observer

This paper presents a fault diagnosis algorithm to estimate the fault for a class of linear discrete systems based on an adaptive fault estimation observer. And observer gain matrix and adaptive adjusting rule of the fault estimator are designed. Furthermore, the adaptive regulating algorithm can guarantee the first-order difference of a Lyapunov discrete function to be negative, so that the observer is ensured to be stable and fault estimation errors are convergent. Finally, simulation results of an aircraft F-16 illustrate the advantages of the theoretic results that are obtained in this paper.

Actuator fault estimation for a class of nonlinear descriptor systems

This article proposes an actuator fault estimation approach for a class of nonlinear descriptor systems. The radial basis function (RBF) neural networks are utilised to model the actuator faults. The adaptive fault estimation observer is designed by exploiting the on-line learning ability of RBF neural networks to approximate the actuator fault. The adaptive algorithm of the RBF networks is established by the Lyapunov theory, and the design of the proposed observer is reformulated as a set of linear matrix inequalities (LMIs), which can be conveniently solved by standard LMI tools. Finally, two simulation examples are used to demonstrate the effectiveness of the proposed fault diagnosis method.