JOURNAL ARTICLE

Event-Triggered Robust Adaptive Sliding Mode Fault-Tolerant Control For Nonlinear Systems

Bin GuoYong Chen

Year: 2019 Journal:   IEEE Transactions on Industrial Informatics Vol: 16 (11)Pages: 6982-6992   Publisher: Institute of Electrical and Electronics Engineers

Abstract

In this article, a novel two-channel event-triggered adaptive fault-tolerant control approach is designed to handle the degree freedom nonlinear system with disturbances. The main purpose of this article is to maintain the output tracking ability while reducing the transmission burden. The objective is realized by designing a novel adaptive sliding mode controller integrated with the event trigger mechanism. Concretely, the state, actuator fault, and lumped disturbance information are obtained by designing a composite observer, in which the disturbance upper bound is not needed. Then, the obtained information is utilized to design the controller. In the proposed method, the lumped disturbance and nonlinear estimated values are contained in the sliding mode manifold to enhance the robustness. Additionally, an adaptive parameter is also integrated into the controller to compensate for the disturbance. Furthermore, a specific event-triggered controller is proposed to keep the tracking ability and to reduce the transmission load of the fault system. The no Zeno phenomenon performance is analyzed and, finally, the applications to a suspension system and a two-tank system are given to show the fault tolerance ability of the proposed method.

Keywords:
Control theory (sociology) Robustness (evolution) Nonlinear system Fault tolerance Actuator Sliding mode control Control engineering Computer science Controller (irrigation) Robust control Engineering Adaptive control Control system Control (management) Artificial intelligence

Metrics

54
Cited By
3.80
FWCI (Field Weighted Citation Impact)
30
Refs
0.94
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Citation History

Topics

Adaptive Control of Nonlinear Systems
Physical Sciences →  Engineering →  Control and Systems Engineering
Stability and Control of Uncertain Systems
Physical Sciences →  Engineering →  Control and Systems Engineering
Adaptive Dynamic Programming Control
Physical Sciences →  Computer Science →  Computational Theory and Mathematics

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