Zero-sum Neuro-optimal Control of Modular and Reconfigurable Robots with External Collisions via Critic Only Policy Iteration
| Autor: | Zhenguo Zhang, Jingchen Chen, An Tianjiao, Bo Dong, Yuexi Wang |
|---|---|
| Rok vydání: | 2020 |
| Předmět: |
Lyapunov function
Artificial neural network business.industry Computer science 010401 analytical chemistry 02 engineering and technology Fuzzy control system Modular design 021001 nanoscience & nanotechnology Optimal control 01 natural sciences 0104 chemical sciences Dynamic programming symbols.namesake Position (vector) Control theory Adaptive system symbols Robot 0210 nano-technology business |
| Zdroj: | 2020 Chinese Automation Congress (CAC). |
| Popis: | In the cause of deal with this problem of optimal position and velocity tracking regarding modular reconfigurable robots (MRRs) with external collisions, a zero-sum neural-optimal control method ground on critical only policy iteration (COPI) scheme is proposed by adaptive dynamic programming (ADP). The MRR dynamics model uncertainty is compensated by adaptive fuzzy control method. Unique the critic neural network (NN) ground on policy iteration (PI) and ADP method is used as work out hamilton-Jacobi-Issacs (HJI) equation, then the approximated optimal control is obtained. Then Lyapunov's theory proved that the MRR system was stable. At length, simulation results make clear the virtue of the proposed method. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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