Design of fault tolerant control scheme for a class of non-linear collaborative systems

Author(s):  
Lina Yao ◽  
Yueying Chen ◽  
Li Shi
Entropy ◽  
2018 ◽  
Vol 20 (11) ◽  
pp. 820 ◽  
Author(s):  
Lina Yao ◽  
Wei Wu ◽  
Yunfeng Kang ◽  
Lifan Li

In this paper, a fault-tolerant control scheme is presented for a class of stochastic distribution collaborative control systems, which are composed of three subsystems connected in series to complete the control target. The radial basis function neural network is used to approximate the output probability density function of the third subsystem, which is also the output of the entire system. When fault occurs in the first subsystem, an adaptive diagnostic observer is designed to estimate the value of fault. However, the first subsystem does not have the ability of self-recovery, minimum rational entropy controllers are designed in the latter subsystems to compensate the influence of the fault and minimize the entropy of the system output. A numerical simulation is given to verify the effectiveness of the proposed scheme.


Author(s):  
Jun Zhou ◽  
Jing Chang ◽  
Zongyi Guo

The paper describes the design of a fault-tolerant control scheme for an uncertain model of a hypersonic reentry vehicle subject to actuator faults. In order to improve superior transient performances for state tracking, the proposed method relies on a back-stepping sliding mode controller combined with an adaptive disturbance observer and a reference vector generator. This structure allows for a faster response and reduces the overshoots compared to linear conventional disturbance observers based sliding mode controller. Robust stability and performance guarantees of the overall closed-loop system are obtained using Lyapunov theory. Finally, numerical simulations results illustrate the effectiveness of the proposed technique.


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