Details

Autor(en) / Beteiligte

• Jia, Yingmin
• Zhang, Weicun
• Fu, Yongling
• Zhao, Shoujun

Titel

Adaptive Optimal Tracking Control for Continuum Robots with Uncertain Dynamics

Ist Teil von

• Proceedings of 2022 Chinese Intelligent Systems Conference, 2022, Vol.951, p.697-711

Ort / Verlag

Singapore: Springer

Erscheinungsjahr

2022

Link zum Volltext

Quelle

Alma/SFX Local Collection

Beschreibungen/Notizen

• In this paper, we propose an online adaptive tracking control strategy for continuum robots by using integral reinforcement learning (IRL). Based on the assumption of piecewise constant curvature (PCC), a dynamic model formed of Euler-Lagrange equation is established and auxiliary tracking error function is defined. An actor/critic structure is introduced to learn the approximate solution to the HJB equation without requiring the explicit knowledge of the dynamic model. Lyapunov stability theory is used to show the asymptotic stability of the closed-loop system. A simulation result is given to demonstrate the effectiveness of the proposed control strategy.