 Adaptive dynamic programming-based fault tolerant control for nonlinear time-delay systemsFarshad Rahimi Chaos, Solitons & Fractals, 2024, vol. 188, issue C Abstract: This study introduces a fault compensation control approach for a class of affine nonlinear time-delay systems using adaptive dynamic programming (ADP). By establishing an observer, the ADP-derived approach facilitates the estimation of potential actuator faults within the system. A novel value function is devised to incorporate the estimated fault and state delay. Subsequently, the control laws are derived from this innovative value function. The Hamilton–Jacobi–Bellman equation associated with this innovative value function is effectively solved using a critic neural network. Then, it is demonstrated through Lyapunov theory that the closed-loop systems achieve uniform ultimate boundedness. The efficacy of the current fault compensation strategy is validated through simulation instances. A notable contribution of the proposed method is its extension of the ADP technique to address the challenge of fault compensation in nonlinear time-delay systems. Keywords: Neural network; Fault compensation; Adaptive dynamic programming; Time-delay systems (search for similar items in EconPapers) Downloads: (external link) Related works: Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text Persistent link: https://EconPapers.repec.org/RePEc:eee:chsofr:v:188:y:2024:i:c:s0960077924010968 DOI: 10.1016/j.chaos.2024.115544 Access Statistics for this article Chaos, Solitons & Fractals is currently edited by Stefano Boccaletti and Stelios Bekiros More articles in Chaos, Solitons & Fractals from Elsevier |
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