Evolution of Controllers Under a Generalized Structure Encoding/Decoding Scheme with Application to Magnetic Levitation System (Wenchao Xue)

Evolutionary search has been widely implemented for the adjustment of controllers’ parameters. Nevertheless, the structure of controllers, which has a more important role in control systems, has been seldom studied. To this end, an evolutionary design method of controllers is proposed to optimize both structures and parameters simultaneously in this article. A controller is made up of a combination of some basic controller components and relevant parameters. The design of controllers can be transformed into an optimization problem involving the structure (represented by discrete vectors) and parameters (represented by real numbers). A generalized structure encoding/decoding scheme is developed. Guided by the performance indicators, intelligent algorithms for both combinatorial and numerical optimization are employed to iteratively and cooperatively evolve the controller structure and parameters, respectively. In order to effectively reduce some redundant or infeasible solutions, a set of generation rules for the controller structure are put forward, which also ensures the feasibility of the structure. Furthermore, this method is applied to a magnetic levitation ball system with nonlinear dynamics and external disturbance. Both simulation and experiment results demonstrate the effectiveness and practicability of the proposed method.

Publication:

IEEE Transactions on Industrial Electronics (Volume: 69, Issue: 9, Sept. 2022)

Author:

Bin Xin

School of Automation, Beijing Institute of Technology, Beijing, China

Beijing Advanced Innovation Center for Intelligent Robots and Systems, Beijing Institute of Technology, Beijing, China

Yipeng Wang

School of Automation, Beijing Institute of Technology, Beijing, China

Peng Cheng Laboratory, Shenzhen, China

Wenchao Xue

Key Laboratory of Systems and Control, Academy of Mathematics and Systems Science, Chinese Academy of Sciences, Beijing, China

School of Mathematical Sciences, University of Chinese Academy of Sciences, Beijing, China

E-mail: wenchaoxue@amss.ac.cn

Tao Cai

School of Automation, Beijing Institute of Technology, Beijing, China

Zhun Fan

Guangdong Provincial Key Laboratory of Digital Signal and Image Processing and the Key Laboratory of Intelligent Manufacturing Technology, Ministry of Education, Shantou University, Shantou, China

Jiaoyang Zhan

School of Automation, Beijing Institute of Technology, Beijing, China

Jie Chen

School of Automation, Beijing Institute of Technology, Beijing, China

Beijing Advanced Innovation Center for Intelligent Robots and Systems, Beijing Institute of Technology, Beijing, China