Actuator and sensor faults estimation for discrete-time descriptor linear parameter-varying systems in finite frequency domain

ABSTRACT

This paper investigates the problem of fault estimation for discrete-time descriptor linear parameter-varying systems with actuator faults, sensor faults and external disturbances. First, in order to estimate the actuator and sensor faults simultaneously, an augmented system is constructed, where the auxiliary state vector consists of the original state vector and the sensor fault vector. Then, considering the fact that many faults usually occur in finite frequency ranges, a novel fault estimation observer with finite frequency specifications is designed, where the conservatism can be reduced compared with the traditional fault estimation design methods in full frequency domain. By employing the generalised Kalman–Yakubovich–Popov lemma and two finite frequency H _∞ performance indices, the sufficient conditions of the proposed observer are given in terms of linear matrix inequalities. Furthermore, by using slack variables, improved results on the fault estimation observer design are obtained, which are convenient to calculate fault estimation observer parameters for different frequency ranges. An example is presented to illustrate the effectiveness of the proposed method.

KEYWORDS:

• Discrete-time systems
• Lyapunov methods
• state-space models
• state estimation
• fault diagnosis

Disclosure statement

No potential conflict of interest was reported by the authors.

Additional information

Funding

National Natural Science Foundation of China [grant number 61473068], [grant number 61273148], [grant number 61621004], [grant number 61420106016]; Fundamental Research Funds for the Central Universities [grant number N140402002], [grant number N170405004]; Research Fund of State Key Laboratory of Synthetical Automation for Process Industries [grant number 2013ZCX01].

Notes on contributors

Jin Wei

Jin Wei received the B.S. degree in automation from Dezhou University, Dezhou, China, in 2015, and the M.S. degree in control engineering from Northeastern University, Shenyang, China, in 2018, respectively. Her main research interests include fault diagnosis, fault estimation and iterative learning control.

Yue Wu

Yue Wu received the M.S. degree in control science and engineering from Dalian Maritime University, Dalian, China, in 2015, respectively. He is currently pursuing the Ph.D. degree in navigation guidance and control from Northeastern University, Shenyang, China. His current research interests include fault tolerant control, fault detection and isolation, adaptive control and cyber-physical system security.

Jiuxiang Dong

Jiuxiang Dong received the B.S. degree in mathematics and applied mathematics, the M.S. degree in applied mathematics from Liaoning Normal University, China, in 2001 and 2004, respectively. He received the Ph.D. degree in navigation guidance and control from Northeastern University, China in 2009. He is currently a Professor at the College of Information Science and Engineering, Northeastern University. His research interests include fuzzy control, robust control and reliable control. Dr. Dong is an Associate Editor for the International Journal of Control, Automation, and Systems (IJCAS).