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Article Dans Une Revue Engineering Applications of Artificial Intelligence Année : 2023

Fault-tolerant control based on adaptive dynamic programming for reentry vehicles subjected to state-dependent actuator fault

Guanjie Hu
Jianguo Guo
Yixin Ding
Zongyi Guo

Résumé

The paper addresses the problem of fault tolerant control (FTC) for reentry vehicles (RV) subject to actuator fault and perturbation. In contrast to the majority of papers assuming bounded and exogenous actuator fault effect, the adaptive dynamic programming (ADP) control algorithm has been considered here to tackle with the dependence of closed-loop states induced by the setup of an active FTC strategy. By this way, the FTC problem formulation takes theoretically into account the fact that an actuator fault can destabilize a closed-loop. First, the FTC problem in attitude tracking is transformed into an error-optimal control problem. Next, a cost function based on zero-sum game theory is considered to achieve tracking under the joint influence of state-dependent actuator faults and perturbations. Lyapunov theory has been next used to prove the stability of FTC architecture and the network weight convergence. Benefits of proposed ADP-FTC algorithm is finally highlighted on a numerical benchmark of RV.
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Dates et versions

hal-04104200 , version 1 (23-05-2023)

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Citer

Guanjie Hu, Jianguo Guo, Jérôme Cieslak, Yixin Ding, Zongyi Guo, et al.. Fault-tolerant control based on adaptive dynamic programming for reentry vehicles subjected to state-dependent actuator fault. Engineering Applications of Artificial Intelligence, 2023, 123, pp.106450. ⟨10.1016/j.engappai.2023.106450⟩. ⟨hal-04104200⟩
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