Affiliations: [a] School of Electrical Engineering, Southwest Jiaotong University, Chengdu, Sichuan, China | [b] School of Automation, Chengdu University of Information Technology, Chengdu, Sichuan, China | [c] Nature Inspired Computing and Engineering Research Group, Department of Computer Science, University of Surrey, Guildford, Surrey, UK | [d] School of Electrical Engineering, Sichuan University, Chengdu, Sichuan, China
Correspondence:
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Corresponding authors: Gexiang Zhang, School of Automation, Chengdu University of Information Technology, Chengdu 610225, Sichuan, China. E-mail: [email protected]. Ferrante Neri, Nature Inspired Computing and Engineering Research Group, Department of Computer Science, University of Surrey, Guildford, Surrey GU2 7XH, UK. E-mail: [email protected].
Abstract: To guarantee their locomotion, biped robots need to walk stably. The latter is achieved by a high performance in joint control. This article addresses this issue by proposing a novel human-simulated fuzzy (HF) membrane control system of the joint angles. The proposed control system, human-simulated fuzzy membrane controller (HFMC), contains several key elements. The first is an HF algorithm based on human-simulated intelligent control (HSIC). This HF algorithm incorporates elements of both multi-mode proportional-derivative (PD) and fuzzy control, aiming at solving the chattering problem of multi-mode switching while improving control accuracy. The second is a membrane architecture that makes use of the natural parallelisation potential of membrane computing to improve the real-time performance of the controller. The proposed HFMC is utilised as the joint controller for a biped robot. Numerical tests in a simulation are carried out with the planar and slope walking of a five-link biped robot, and the effectiveness of the HFMC is verified by comparing and evaluating the results of the designed HFMC, HSIC and PD. Experimental results demonstrate that the proposed HFMC not only retains the advantages of traditional PD control but also improves control accuracy, real-time performance and stability.
