Aero‐Engine DCS Fault‐Tolerant Control with Markov Time Delay Based On Augmented Adaptive Sliding Mode Observer

2018 ◽  
Vol 22 (2) ◽  
pp. 788-802
Author(s):  
Ledi Zhang ◽  
Shousheng Xie ◽  
Yu Zhang ◽  
Litong Ren ◽  
Bin Zhou ◽  
...  
2020 ◽  
Vol 10 (4) ◽  
pp. 1278
Author(s):  
Zhilu Zhang ◽  
Benxian Xiao

For the problem of multiple sensor fault detection and reconstruction in the forklift fault-tolerant control system, a sliding mode observer (SMO) with adaptive regulation law is proposed. Based on the three-degree-of-freedom (3-DOF) model of forklift, a linear state equation with output disturbance is designed as its equivalent sensor fault model. The sensor fault is converted into an actuator fault by defining an auxiliary state variable as an output signal filter. Then the SMO-based method of sensor fault detection and reconstruction is given. Without knowing the upper bound of an unknown fault, an adaptive sliding mode observer (ASMO) can also be effective through the adaptive algorithm. Finally, experimental results further verify the effectiveness of the method, and provide a foundation for forklift fault-tolerant control.


Author(s):  
Bingqian Li ◽  
Wenhan Dong ◽  
Xiaoshan Ma

In this paper, a backstepping fault-tolerant control based on sliding-mode observer is proposed for the unmanned thrust-vectoring aircraft (UTVA) control. First, the UTVA model with the uncertainty, control surface damage and actuator faults is described, which is divided into fast loop and slow loop. Next, the cascade observers including a high-order SMO and the discontinuous projection adaptive law are proposed to estimate the states with compensating the uncertainty and control surface damage, and the sliding-mode observer is designed to identify actuator faults and estimate fault parameters. Then, the backstepping fault-tolerant control combining the estimation of states and fault parameters is proposed to achieve the global fault-tolerant control, which compensates the uncertainty, control surface damage and actuator faults. Finally, simulation results are given to demonstrate the effectiveness for UTVA.


2019 ◽  
Vol 2019 ◽  
pp. 1-13 ◽  
Author(s):  
Liang Zheng ◽  
Xuelian Dong ◽  
Qian Luo ◽  
Menglan Zeng ◽  
Xinping Yang ◽  
...  

In this paper, an adaptive sliding mode fault tolerant control (ASMFTC) approach is proposed for a class of nonlinear systems with actuator fault, uncertainty, and external disturbance. Specifically, first, a novel observer is proposed to estimate the state, actuator fault, and external disturbance. Then, by utilising the observed information, a novel output sliding mode observer is constructed. In the control method, an adaptive law and two compensators are designed to attenuate the unknown estimation errors, actuator fault, and disturbance. Furthermore, the reaching ability of the sliding motion is analysed and the H-infinite performance is introduced to ensure the robustness of the system. Finally, a flexible single joint manipulator system and a two-cart system are used to verify the effectiveness of the proposed method.


Author(s):  
Riadh Hmidi ◽  
Ali Ben Brahim ◽  
Slim Dhahri ◽  
Fayçal Ben Hmida ◽  
Anis Sellami

This paper proposes fault-tolerant control design for uncertain nonlinear systems described under Takagi-Sugeno fuzzy systems with local nonlinear models that satisfy the Lipschitz condition. First, by transforming sensor faults as ‘pseudo-actuator’ faults, an adaptive sliding mode observer is designed in order to simultaneously estimate system states, actuator and sensor faults despite the presence of norm-bounded uncertainties. Second, an adaptive sliding mode controller is suggested to provide a solution to stabilize the closed-loop system, even in the event of simultaneous occurrence of faults in actuators and sensors. Next, the main objective of the fault-tolerant control strategy is to compensate for the effects of fault based on the feedback information. Therefore, using the LMI optimization method, sufficient conditions are developed with [Formula: see text] to calculate the gains of the observer and the controller. Then, particular attention is paid to the simultaneous maximization, by convex multi-objective optimization, of the Lipschitz nonlinear constant in Takagi-Sugeno fuzzy modelling and uncertainties attenuation level. The results of the simulation illustrate the effectiveness of our fault-tolerant control approach using a nonlinear inverted pendulum with a cart system.


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