摘要
提出一种基于混合粒子群算法和细菌觅食算法的温度控制器,重点研究了菌群优化粒子群(BFO-PSO)算法的性能,包括突变、交叉、步长变化、趋化步骤和细菌的生命周期等。利用MATLAB仿真平台将其与传统比例积分微分算法(PID)及粒子群算法(PSO)进行控制效果对比,发现该方法效率高。与传统PID和PSO调节的PID相比,细菌觅食优化算法的智能PID在系统响应速度和系统稳定性能上都有很大的提高。
A temperature controller based on hybrid particle swarm optimization(PSO)and bacterial foraging algorithm is proposed.The performance of PSO is studied,including mutation,crossover,step size change,chemotactic step and bacterial life cycle.The MATLAB simulation platform is used to compare the control effect with the traditional PID controller and the particle swarm optimization(PSO),and it is found that the method has higher efficiency.Compared with traditional PID and PSO,the intelligent PID of bacteria foraging optimization algorithm has a great improvement in the system response speed and system stability performance.
作者
鲍克勤
阮绵虎
汤豪
BAO Keqin;RUAN Mianhu;TANG Hao(School of Automation Engineering,Shanghai University of Electric Power,Shanghai 200090,China)
出处
《上海电力大学学报》
CAS
2023年第2期189-194,共6页
Journal of Shanghai University of Electric Power
基金
国家自然科学基金(61905139)。