Distributed Fault Estimation Observer Design With Adjustable Parameters for a Class of Nonlinear Interconnected Systems.

In this study, a new distributed fault estimation observer (DFEO) design method is proposed based on unknown input observer (UIO) for interconnected systems with external disturbances. The coupling terms among interconnected subsystems are utilised to construct DFEO. At the same time, according to the characteristics of UIO, external interference is completely decoupled to improve the robustness of fault estimation. Furthermore, the authors propose a multi‐constraint design with robust and regional pole configurations to analyse and design gain matrices of DFEO, which can be calculated using linear matrix inequalities. Furthermore, asymptotic estimation of sensor faults is discussed with the help of DFEO. Finally, a simulation of the interconnected system is provided to illustrate the effectiveness of the proposed technique.

This paper is concerned with the adaptive decentralized fault-tolerant tracking control problem for a class of uncertain interconnected nonlinear systems with unknown strong interconnections. An algebraic graph theory result is introduced to address the considered interconnections. In addition, to achieve the desirable tracking performance, a neural-network-based robust adaptive decentralized fault-tolerant control (FTC) scheme is given to compensate the actuator faults and system uncertainties. Furthermore, via the Lyapunov analysis method, it is proven that all the signals of the resulting closed-loop system are semiglobally bounded, and the tracking errors of each subsystem exponentially converge to a compact set, whose radius is adjustable by choosing different controller design parameters. Finally, the effectiveness and advantages of the proposed FTC approach are illustrated with two simulated examples.

This paper focuses the development of an adaptive observer-based distributed fault estimation observer (DFEO) for multi-agent nonlinear time-delay systems under a directed communication topology. The process involves constructing a fault estimation observer for each agent based on their relative output estimation errors. An adaptive DFEO design is proposed for multi-agent systems with a directed communication topology. Furthermore, investigating the effect of faulty agents on the criteria of fault detection on healthy agents. The proposed design is represented with Linear Matrix Inequalities (LMIs) to establish a systematic design procedure. The study also includes simulation results to demonstrate the effectiveness of the proposed design techniques.

Distributed finite-time fault estimation and fault-tolerant control for cyber-physical systems with matched uncertainties

Global H ∞ control for a class of interconnected nonlinear systems

In this paper, a distributed fault estimation observer based on intermediate estimator method is studied, which eliminates the constraints of observer matching conditions on fault estimation. First, the relative output estimation errors of MASs and intermediate estimator system are established based on communication topology. Second, we constructed a new Lyapunov function containing both original system state and intermediate estimation variables, the sufficient conditions for the stability of the global dynamic error system are obtained, and the gain matrix of the distributed fault estimation observer is calculated. At the end of this paper, the effectiveness and feasibility of the developed method are illustrated in two cases: the system satisfies and not satisfy the observer matching condition.

In this study, under the directed communication topology, an adaptive observer‐based distributed fault estimation observer (DFEO) is studied with the use of a linear matrix inequality (LMI) for multi‐agent systems. Firstly, for each agent, a corresponding fault estimation observer is constructed based on their relative output estimation errors. To consider DFEO design from an overall perspective, the whole error dynamics is obtained by defining global error vectors. Then an adaptive technique‐based DFEO design is proposed for multi‐agent systems with directed communication topology. Moreover, the proposed design can be represented with LMIs to establish a systematic design procedure. Finally, simulation results are presented to illustrate the effectiveness of the proposed design techniques.

International audience

In this paper, an observer‐based event‐triggered distributed model predictive control method is proposed for a class of nonlinear interconnected systems with bounded disturbances, considering unmeasurable states. First of all, the state observer is constructed. It is proved that the observation error is bounded. Second, distributed model predictive controller is designed by using observed value. Meanwhile, the event‐triggered mechanism is set by using the error between the actual output and the predicted output. The setting of event‐triggered mechanism not only ensures the error between the actual output and the predicted output within a certain range, but also reduces the calculation amounts of solving the optimization problem. The states of each subsystem enter the terminal invariant set by distributed model predictive control, and then are stabilized in the invariant set under the action of output feedback control law. In addition, sufficient conditions are given to ensure the feasibility of the algorithm and the stability of the closed‐loop system. Finally, the numerical example is given, and the simulation results verify the effectiveness of the proposed algorithm.

In this work, the problem of fault and state estimation is studied for Takagi–Sugeno fuzzy systems with time-varying delay and external disturbance over a finite horizon. A fuzzy rule-based fault estimator with two tuning parameters, including the current system output information, is designed. Based on which, the Luenberger state observer is then considered to estimate the immeasurable states of the system addressed. The aim of taking into account the tuning parameters in the estimator design is to improve the accuracy of the fault estimation. More precisely, by defining error variables in accordance with actual and estimated system states and faults, an augmented system is formulated to achieve the desired results. By using the existing stability theory and integral inequality, a delay-dependent criterion for ensuring that the states of the augmented system are bounded over a finite horizon is derived. Subsequently, conditions for determining the observer gain matrices are presented. Two simulation examples, including an application example of the truck-trailer model, are provided to demonstrate the advantages of the theoretical results that have been established. In particular, the importance of the use of tuning parameters is discussed.

SummaryThis paper proposes a framework of fault estimation observer design in finite‐frequency domain for discrete‐time systems. First, under the multiconstrained idea, a full‐order fault estimation observer in finite‐frequency domain is designed to achieve fault estimation by using the generalized Kalman–Yakubovich–Popov lemma to reduce conservatism generated by the entire frequency domain. Then, a reduced‐order fault estimation observer is constructed, which results in a new fault estimator to realize fault estimation using current output information. Furthermore, by introducing slack variables, improved results on full‐order fault estimation observer and reduced‐order fault estimation observer design with finite‐frequency specifications are obtained such that different Lyapunov matrices can be separately designed for each constraint. Simulation results are presented to illustrate the advantages of the theoretic results obtained. Copyright © 2014 John Wiley & Sons, Ltd.

In this paper, a class of nonlinear interconnected systems with uncertain time varying parameters (TVPs) is considered. Both the interconnections and the isolated subsystems are nonlinear. Sliding mode control method and adaptive techniques are employed together to design an observer to estimate the state variables of the systems in presence of unknown TVPs. The Lyapunov direct method is used to analysis the stability of the sliding motion and it is not required to solve the so‐called constrained Lyapunov problem (CLP). A set of conditions is developed under which the augmented systems formed by the error dynamical systems and the designed adaptive laws, are globally uniformly ultimately bounded. A simulation example is presented and the results show that the method proposed in this paper is effective.

This article investigates the finite-time fault-estimation problem for a class of Lipschitz nonlinear systems with actuator faults and unknown input disturbances. Specifically, the original system is preliminarily decoupled into two reduced-order subsystems using a linear nonsingular transformation. A novel finite-time observer is proposed to estimate actuator faults in finite time. Subsequently, the proposed finite-time observer is extended to nonlinear systems with unknown input disturbances to investigate the robust fault-estimation problem. The actuator fault and unknown input disturbance are estimated simultaneously using two finite-time observations. Furthermore, a fault-estimation scheme is designed based on finite-time observers. The finite-time stability of the observers is then analysed using the Moreno–Lyapunov function method. The analytical proofs presented herein demonstrate that estimation errors can converge to a region of zero in finite time. Finally, the effectiveness of the developed finite-time observers and fault-estimation scheme was validated through simulations of a sample single-link flexible-joint robot.

Neural network learning algorithm for a class of interconnected nonlinear systems

Finite-horizon [formula omitted] fault estimation for linear discrete time-varying systems with delayed measurements