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作 者:汪衍凯 刘忠晨 许彦杰 WANG Yan-kai;LIU Zhong-chen;XU Yan-jie(School of Information and Electrical Engineering,Shandong University of Construction,Jinan 250101,China)
机构地区:[1]山东建筑大学信息与电气工程学院,济南250101
出 处:《南通职业大学学报》2022年第4期80-84,共5页Journal of Nantong Vocational University
摘 要:日光具有时变性及易干扰性,为使日光得到充分合理的利用,实现智能照明系统更有效的控制,提出一种基于粒子群算法(PSO)优化的模糊自适应PID算法,通过PSO算法得到最优PID初始参数,并利用模糊规则对参数进行自适应修正。仿真结果表明,与普通PID算法相比,该算法在最优化初始参数的基础上,上升时间、超调量和稳态时间等指标均得到明显的改善,增强了系统的响应性、稳定性和鲁棒性,具有良好的应用前景。Sunlight varies with time and is vulnerable to interference. In order to make full and reasonable use of sunlight and achieve more effective control of intelligent lighting system, a fuzzy self-adaptive PID algorithm based on particle swarm optimization(PSO) is proposed. The optimal initial parameters of PID are obtained through PSO algorithm, and fuzzy rules are used to make adaptive corrections to the parameters. The results of simulation experiment show that with the ordinary PID algorithm, the parameters such as rise time,overshoot and steady-state time are significantly improved on the basis of the optimized initial parameters of the algorithm, which enhances the responsiveness, stability and robustness of the system. It has good application prospects.
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