Details

Autor(en) / Beteiligte

• Meng, Fancheng
• Yang, Shuo
• Li, Yafeng
• Wang, Jinlei

Titel

RFAC Based Task-Oriented Active Sharing Control for a Class of Robotic Rehabilitation Training Systems

Ist Teil von

• 2018 37th Chinese Control Conference (CCC), 2018, p.5471-5475

Ort / Verlag

Technical Committee on Control Theory, Chinese Association of Automation

Erscheinungsjahr

2018

Quelle

IEEE Electronic Library Online

Beschreibungen/Notizen

• This paper proposes a robust fuzzy adaptive critic controller (RFAC) for a class of robotic rehabilitation systems. Based on the RFAC control approach, the robotic rehabilitation system can utilize a robust fuzzy actor to generate an optimal task-oriented active sharing control behavior under the guidance of a fuzzy critic. Specifically, if the control behavior generated by the fuzzy actor is good for rehabilitation training, then the critic will give a reward, otherwise, the critic will punish the fuzzy actor to modify its control behavior. Finally, the RFAC can find the optimal control policy for the real robotic rehabilitation training through the reward-punishment mechanism. In addition, to attenuate the effects of the approximation error and various uncertainties in the system, a recently developed robust integral of the sign of the error feedback technique is also integrated into the developed RFAC agent. Lyapunov stability analysis shows the RFAC can yield a semi-global asymptotic result. Also, simulation experiments verify that the RFAC has good performance.