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Fixed-Time Control for a Flexible Smart Structure With Actuator Failure: A Broad Learning System Approach
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DOI：10.1109/TCYB.2023.3271314.png)
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Abstract
En 中文
This article proposes an adaptive fault-tolerant control (AFTC) approach based on a fixed-time sliding mode for suppressing vibrations of an uncertain, stand-alone tall building-like structure (STABLS). The method incorporates adaptive improved radial basis function neural networks (RBFNNs) within the broad learning system (BLS) to estimate model uncertainty and uses an adaptive fixed-time sliding mode approach to mitigate the impact of actuator effectiveness failures. The key contribution of this article is its demonstration of theoretically and practically guaranteed fixed-time performance of the flexible structure against uncertainty and actuator effectiveness failures. Additionally, the method estimates the lower bound of actuator health when it is unknown. Simulation and experimental results confirm the efficacy of the proposed vibration suppression method.
Keywords:
Broad learning system (BLS)
fault-tolerant control
fixed-time performance
neural network
vibration suppression control
Journal
IF:
10.5
Papers:
1.1W
Citations:
5.0W
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