Zhenhua Wang

Sensor Fault Estimation Filter Design for Discrete-time Linear Time-varying Systems

Abstract This paper proposes a sensor fault diagnosis method for a class of discrete-time linear time-varying (LTV) systems. In this paper, the considered system is firstly formulated as a descriptor system representation by considering the sensor faults as auxiliary state variables. Based on the descriptor system model, a fault estimation filter which can simultaneously estimate the state and the sensor fault magnitudes is designed via a minimum-variance principle. Then, a fault diagnosis scheme is presented by using a bank of the proposed fault estimation filters. The novelty of this paper lies in developing a sensor fault diagnosis method for discrete LTV systems without any assumption on the dynamic of fault. Another advantage of the proposed method is its ability to detect, isolate and estimate sensor faults in the presence of process noise and measurement noise. Simulation results are given to illustrate the effectiveness of the proposed method.

Fault Estimation for A Class of Discrete-Time Nonlinear Systems

This paper deals with actuator fault estimation for a class of discrete-time nonlinear systems whose linear part is described by a Linear Parameter-Varying (LPV) form and nonlinear term is Lipschitz. In this paper, an augmented system is constructed by considering the fault as an auxiliary state vector. Then, a robust fault estimation observer is designed based on the augmented system. The proposed fault estimation observer is able to attenuate the effect of the fault variation and measurement noise and the observer design is formulated as a Linear Matrix Inequality (LMI) feasibility problem, which can be easily solved. Finally, a missile model is used to demonstrate the effectiveness of the proposed method.

Simultaneous fault estimation and fault-tolerant tracking control for uncertain nonlinear discrete-time systems

ABSTRACT This paper deals with simultaneous fault estimation and control for a class of nonlinear systems with parameter uncertainty, which is described by Takagi–Sugeno (T–S) fuzzy model with parameter uncertainties and unknown disturbance. In this paper, a fuzzy reference model is used to generate error dynamic for tracking control. By considering actuator fault as an auxiliary state vector, we construct an augmented error system and propose a fault estimator/controller to achieve simultaneous fault estimation and fault-tolerant tracking control. H∞ approach is used in the design of estimator/controller to attenuate the effect of the unknown disturbance and parameter uncertainties. The design conditions are formulated into a set of linear matrix inequalities (LMIs), which can be efficiently solved. Finally, a pitch-axis nonlinear missile model is used to illustrate the effectiveness of the proposed method.

Fault diagnosis and robust fault-tolerant control for linear over-actuated systems

This paper proposes a novel fault diagnosis and robust fault-tolerant control strategy for over-actuated systems which subject to actuator faults. Firstly, the considered fault is formulated into an additive term (which is referred to as virtual fault). Then an augmented state observer is used to estimate this virtual additive fault. To achieve fault isolation and estimation for the over-actuated system, which is more difficult than that of an ordinary system, this paper considers the actuator fault as a sparse signal and proposes a constrained sparse optimization approach to recover the actual multiplicative fault in the over-actuated system. Based on the fault diagnosis result, a robust fault-tolerant controller is designed by the virtual actuator approach, which aims to construct a reconfiguration block to force the output of the reconfigured faulty plant approximated the behavior of a nominal system. Finally, the proposed fault diagnosis and fault-tolerant scheme is applied to an ADMIRE model. Simulation results demonstrate the effectiveness of the proposed method.

Zonotopic fault detection observer design for Takagi–Sugeno fuzzy systems

ABSTRACT This paper considers zonotopic fault detection observer design in the finite-frequency domain for discrete-time Takagi–Sugeno fuzzy systems with unknown but bounded disturbances and measurement noise. We present a novel fault detection observer structure, which is more general than the commonly used Luenberger form. To make the generated residual sensitive to faults and robust against disturbances, we develop a finite-frequency fault detection observer based on generalised Kalman–Yakubovich–Popov lemma and P-radius criterion. The design conditions are expressed in terms of linear matrix inequalities. The major merit of the proposed method is that residual evaluation can be easily implemented via zonotopic approach. Numerical examples are conducted to demonstrate the proposed method.

A self-healing control method for satellite attitude tracking based on simultaneous fault estimation and control design

This paper proposes a novel self-healing control method for satellite attitude tracking based on simultaneous fault estimation and control design. The proposed method integrates the fault estimation and fault-tolerant control units in a dynamic system, which is less complex and more reliable than the separately designed self-healing architectures. In this paper, the model reference approach is used to obtain a tracking error dynamic equation. Following this, an augmented error system is constructed by taking the fault as an auxiliary vector. Based on the augmented error system, a fault estimator/controller is designed to achieve robust fault-tolerant control and robust fault estimation simultaneously. The design conditions for the proposed fault estimator/controller are transformed as a set of linear matrix inequalities, which can be easily solved. Finally, numerical simulation results are given to demonstrate the effectiveness of proposed method.