Adaptive fuzzy sliding mode algorithm-based decentralised control for a permanent magnet spherical actuator

ABSTRACT

The dynamic model of multi-degree-of-freedom permanent magnet (PM) spherical actuators is multivariate and nonlinear due to strong inter-axis couplings, which affects the trajectory tracking performance of the system. In this paper, a decentralised control strategy based on adaptive fuzzy sliding mode (AFSM) algorithm is developed for a PM spherical actuator to enhance its trajectory tracking performance. In this algorithm, the coupling terms are separated as subsystems from the entire system. The AFSM algorithm is applied in such a way that the fuzzy logic systems are used to approximate the subsystem with uncertainties. A sliding mode term is introduced to compensate for the effect of coupling terms and fuzzy approximation error. The stability of the proposed method is guaranteed by choosing the appropriate Lyapunov function. Both simulation and experimental results show that the proposed control algorithm can effectively handle various uncertainties and inter-axis couplings, and improve the trajectory tracking precision of the spherical actuator.

KEYWORDS:

• Permanent magnet spherical actuator
• decentralised control
• adaptive fuzzy sliding mode
• trajectory tracking

Acknowledgements

The authors would like to thank the editor and anonymous reviewers for their constructive comments and suggestions to improve the quality of this paper.

Disclosure statement

No potential conflict of interest was reported by the authors.

Additional information

Funding

This work was supported by the National Natural Science Foundation of China [grant numbers 51475033, 51475017].

Notes on contributors

Jingmeng Liu

Jingmeng Liu received the B.S. degree from Anhui Polytechnic University, Wuhu, China, in 1991 and the M.S. and Ph.D. degrees from Beihang University, Beijing, China, in 2000 and 2004, respectively. He is currently an Associate Professor with the School of Automation Science and Electrical Engineering, Beihang University. His current research interests include actuators, precision control, and mechatronics.

Xuerong Li

Xuerong Li received the B.S. degree from China Agricultural University, China, in 2012. She is currently working towards the Ph.D. degree in School of Automation Science and Electrical Engineering, Beihang University, China. Her current research interests include parallel robots, actuators and control systems.

Shaoxiong Cai

Shaoxiong Cai received the B.S. degree from Beijing Jiaotong University, Beijing, China, in 2009. He is currently working toward the M.S. degree in the School of Automation Science and Electrical Engineering, Beihang University, Beijing, China. His current research interests include robots, control, and navigation systems.

Weihai Chen

Weihai Chen received the B.S. degree from Zhejiang University, Hangzhou, China, in 1982 and the M.S. and Ph.D. degrees from Beihang University, Beijing, China, in 1988 and 1996, respectively. He is currently a Professor with the School of Automation Science and Electrical Engineering, Beihang University. His current research interests include modular robots, actuators, automation, and control.

Shaoping Bai

Shaoping Bai received the Ph.D. Degree in Mechanical and Production Engineering from the Nanyang Technological University, Singapore in 2001, the M.Eng. Degree from Tsinghua University and B.S. Degree from Harbin Institute of Technology in 1993 and 1988, respectively. He is currently an Associate Professor at the Department of Materials and Production, Aalborg University (AAU), Denmark. His research interests include dynamics and design, medical and assistive robots, parallel manipulators, and walking robots. He is a member of ASME and IEEE Robotics and Automation.