Mobile Robot ADRC With an Automatic Parameter Tuning Mechanism via Modified Pigeon-Inspired Optimization
Xingshuo Hai, Zili Wang, Qiang Feng, Yi Ren, Binghui Xu, Jingjing Cui, Haibin Duan
- 发表年份
- 2019
- 引用次数
- 71
摘要
This article proposes an enhanced active disturbance rejection control (ADRC) method for the attitude deformation system of a self-developed mobile robot in conjunction with evolutionary game theory-based pigeon-inspired optimization (EGPIO). To achieve precise control of the object, EGPIO is employed as an automatic tuning mechanism for ADRC, and simultaneously improves the rapidity and robustness of the controller. In this novel algorithm, individuals in pigeon-inspired optimization (PIO) adjust their strategies dynamically as the evolutionary game proceeds so as to promote the adaptability of the original PIO. Thus, the optimal solutions calculated by EGPIO will be adopted as the main parameters of ADRC to control the mobile robot. The effectiveness of the novel controller is validated by a series of simulations, including cases with normal conditions and situations with disturbances. Experimental results indicate that the scheme we designed possesses better control performances and shows attractive advantages for efficiency and fault tolerance compared with conventional ADRC.
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