Research on robust fault-tolerant control of the controllable suspension based on knowledge-data fusion driven
Honglin Zhu,
Weiping Ding,
Mingliang Yang
et al.
Abstract:For the robust fault-tolerant control of the controllable suspension system, a control strategy driven by knowledge-data fusion is proposed. Firstly, the boundary fuzziness between perturbation type uncertainty and gain type fault is analyzed, and then a data-driven method is introduced to avoid the state estimation of system uncertainty and fault. The proximal policy optimization algorithm in reinforcement learning is selected to construct a “data control law”, to deal with uncertainty and fault. On the other… Show more
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