基于混沌精英黏菌算法的无刷直流电机转速控制

针对传统比例-积分-微分(proportional integral differential, PID)在无刷直流电机转速控制中存在响应速度慢、稳定性差等缺点,提出了一种基于混沌精英黏菌算法的自适应控制方法。首先,分析并建立了无刷直流电机数学模型。其次,为进一步提高标准黏菌算法的收敛速度和求解精度,采用Tent混沌映射丰富种群多样性,同时引入精英反向学习策略扩大搜索范围。最后,将上述改进算法应用于无刷直流电机的速度环PID参数自整定。通过在不同运行条件下进行MATLAB仿真以及实验,结果表明:对比传统PID以及模糊PID,所提方法能够使得控制精度得到显著提高,并且具有响应速度快,抗干扰能力强等优势。

Research on Speed Control of Brushless DC Motor Based on Chaotic Elite Slime Mould Algorithm

In order to address the shortcomings of traditional PID in the speed control of brushless DC motor, such as slow response and poor stability, an adaptive control method based on chaotic elite slime mould algorithm was proposed. First, the mathematical model of brushless DC motor was analyzed and established. In addition, to further boost the convergence speed and solution precision of the standard slime mould algorithm, Tent chaotic mapping was introduced to enrich the population diversity, while the elite opposition-based learning strategy was developed to expand the search range. Final, the modified algorithm was applied to self-tune the speed loop PID parameters of brushless DC motor. The results of simulations and experiments under different operating conditions demonstrate that the control accuracy can be significantly improved by the proposed method compared with traditional PID and fuzzy PID, which also has the advantages of fast response as well as strong anti-interference ability.