Feedback adaptive rate parameters optimization of full-order state observer
-
摘要: 针对现有全阶状态观测器的反馈自适应率PI参数的设计中存在寻找最优解困难的问题,提出了一种基于改进粒子群算法的反馈自适应率PI参数优化算法。首先根据频域方法给出反馈自适应参数的设计准则及影响其参数设计的主要因素;然后将利用设计准则设计好的几组参数值编码后混入随机初始种群,增加初始种群中优良品质个体的数量,提高收敛速度和搜索效率;最后通过编码、初始化种群及参数设置、适应度评价、更新粒子速度和位置得到PI参数最优值。实验结果表明,在斜坡给定0.2,0.6 pu转速时,无论空载启动还是负载运行,采用优化算法得到的PI参数进行速度估算时精度明显高于传统试凑法,能够满足矿井提升机的技术指标要求。Abstract: It is difficult to find the optimal solution in existing design of feedback adaptive rate PI parameters of full-order state observer, a feedback adaptive rate PI parameter optimization algorithm of full-order state observer based on improved particle swarm optimization algorithm was proposed. Firstly, according to frequency domain design method, design criterion of the feedback adaptive rate parameters and the main factors affecting parameter design were given. Then several sets of parameter values designed and encoded by the design criterion were mixed into the random initial population to increase the number of fine individuals in the initial population, so as to improve convergence speed and search efficiency. Finally, the optimal value of PI parameters was obtained by coding, initializing population and parameter setting, fitness evaluating and updating particle velocity and location. The experimental results show that the speed estimation accuracy of PI parameters obtained by the optimization algorithm is obviously better than that of the traditional trial method when the slope is given 0.2 pu and 0.6 pu rotational speed, regardless of no-load startup or load operation,and the accuracy can meet requirements of technical indexes of mine-used hoist.
点击查看大图
计量
- 文章访问数: 65
- HTML全文浏览量: 14
- PDF下载量: 5
- 被引次数: 0