Active Optimal Fault-Tolerant Control Method for Multi-fault Concurrent Modular Manipulator Based on Adaptive Dynamic Programming
| Autor: | Fan Zhou, Yucheng Liu, Bing Li, Bo Dong, Yuanchun Li, Fu Liu, Huiqiu Lu |
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| Rok vydání: | 2019 |
| Předmět: |
Lyapunov function
0209 industrial biotechnology Observer (quantum physics) Artificial neural network Computer science Concurrency Hamilton–Jacobi–Bellman equation Fault tolerance 02 engineering and technology Fault (power engineering) Dynamic programming Computer Science::Hardware Architecture symbols.namesake 020901 industrial engineering & automation Control theory 0202 electrical engineering electronic engineering information engineering symbols 020201 artificial intelligence & image processing Manipulator Actuator Computer Science::Operating Systems Computer Science::Distributed Parallel and Cluster Computing |
| Zdroj: | Advances in Neural Networks – ISNN 2019 ISBN: 9783030228071 ISNN (2) |
| DOI: | 10.1007/978-3-030-22808-8_15 |
| Popis: | In this paper, a novel active optimal fault-tolerant control (FTC) scheme is designed based on adaptive dynamic programming (ADP) for modular manipulator when sensor and actuator faults are concurrency. Firstly, the sensor fault is transformed into the pseudo-actuator fault by constructing a nonlinear transformation with diffeomorphism theory. Secondly, the faults estimated by the adaptive fault observer are applied to establish an improved performance index function. Next, the online policy iteration (PI) algorithm is used to solve the Hamilton-Jacobi-Bellman (HJB) equation via establishing a critic neural network. The optimal fault-tolerant controller is proved to be uniformly ultimately bounded (UUB) based on Lyapunov stable theory. Finally, the effectiveness of the proposed multi-fault-tolerant control algorithm is verified by simulation results. |
| Databáze: | OpenAIRE |
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