Zheng Chu, Jingchang Chen, Qianglong Chen, Weijiang Yu, Tao He, Haotian Wang, Weihua Peng, Ming Liu, Bing Qin, Ting Liu. Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers). 2024.

This paper investigates the design problem of sliding mode observer (SMO) using quantized measurements for a class of Markovian jump systems against actuator faults. Such a problem arises in modern networked-based digital systems, where data have to be transmitted and exchanged over a digital communication channel. In this paper, a new descriptor SMO approach using quantized signals is presented, in which a discontinuous input is synthesized to reject actuator faults by an offline static compensation of quantization effects. It is revealed that the lower bound on the density of a logarithmic quantizer is 1/3, under which the quantization effects could be compensated completely by using the SMO approach. Based on the proposed observer method, the asymptotical estimations of state vector and quantization errors can be obtained simultaneously. Finally, an example of a linearized model of an F-404 aircraft engine system is included to show the effectiveness of the presented observer design method.

This paper investigates the problem of sensor fault estimation and fault-tolerant control for Markovian jump systems with time delay and Lipschitz nonlinearities. The issues involved here are: i) sensor faults; ii) model Lipchitz nonlinearities; iii) system structure changes governed by Markovian jumping parameters; and iv) time delay in system states. Such type of mathematical models can represent a large number of practical systems in the actual engineering. A new estimation technique (named proportional and derivative sliding mode observer) is developed to deal with this design problem. The proposed observer is mode-dependent type in which a derivative gain and a proportional gain are introduced to provide more design freedom, and a discontinuous input term is introduced to eliminate the effects of sensor faults. By employing the developed estimation technique, the asymptotic estimations of system states and sensor faults can be obtained simultaneously. Based on the estimation, an observer-based fault-tolerant control scheme is developed to stabilize the resulting closed-loop system. Finally, a numerical example is presented to illustrate the effectiveness and applicability of the proposed technique.

This paper addresses the problem of fault estimation and fault-tolerant control for a class of Takagi-Sugeno (T-S) fuzzy Itô stochastic systems subject to simultaneously sensor and actuator faults. The main difficulty in this study is that sensor faults, actuator faults, and stochastic noise that are governed by Brownian motion are taken into simultaneous consideration in a unified framework, and traditional fault-tolerant approaches are not effective to solve this research issue. A new descriptor fuzzy sliding-mode observer approach is presented in this paper to obtain the simultaneous estimates of system state, sensor fault, and actuator fault vectors. Based on the state estimates, an observer-based fault-tolerant control (FTC) scheme is developed to stabilize the resulting closed-loop system. Finally, a simulation example is provided to show the effectiveness of the proposed fault-tolerant approach.