| 基于改进粒子群算法的PID参数优化方法研究 |
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| 引用本文： | 熊伟丽,徐保国,周其明. 基于改进粒子群算法的PID参数优化方法研究[J]. 计算机工程, 2005, 31(24): 41-43 |
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| 作者姓名： | 熊伟丽 徐保国 周其明 |
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| 作者单位： | 1. 江南大学控制科学与工程研究中心,无锡,214122
2. 92823部队三中队,三亚,572021 |
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| 基金项目： | 国家自然科学基金资助项目（60474030） |
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| 摘 要： | 针对标准粒子群算法的一些缺点进行了改进，提出了MWPSO优化算法，即Multi-Weight PSO。将MWPSO优化算法用几个标准测试函数进行测试，结果表明该算法优化结果的指标参数比标准PSO算法有所提高。在此基础上，用MWPSO优化算法对PID控制中的参数进行优化并将结果与遗传算法的结果进行比较，优化结果在保证PID控制稳定性基础上提高了PID控制的精度，且编码简单、易于实现。具有较好的应用前景。
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| 关 键 词： | 粒子群优化算法 MWPSO优化算法 遗传算法 PD参数优化 |
| 文章编号： | 1000-3428（2005）24-0041-03 |
| 收稿时间： | 2005-08-04 |
| 修稿时间： | 2005-08-04 |
Study on Optimization of PID Parameter Based on Improved PSO |
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| XIONG Weili,XU Baoguo,ZHOU Qiming. Study on Optimization of PID Parameter Based on Improved PSO[J]. Computer Engineering, 2005, 31(24): 41-43 |
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| Authors: | XIONG Weili XU Baoguo ZHOU Qiming |
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| Affiliation: | 1.Control Science and Engineering Research Center, Southern Yangtze University, Wuxi 214122;2.3^th Lochus of No.92823 Army, Sanya 572021 |
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| Abstract: | Aiming at the disadvantage of classical PSO algorithm, this paper improves PSO algorithm and puts forward a new algorithm named Multi-Weight PSO. It uses the MWPSO to optimize the standard test functions and analyzes the test results, and finds the test results are better than before. Basing on these test results, it uses the MWPSO to optimize the PID parameters and finds the result of MWPSO is better than GA. This method makes it possible to improve the precision of PID control without influencing its stability. Also this method makes codes simpler and easier to realize, which means a better prospective. |
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| Keywords: | Particle swarm optimization(PSO) MWPSO GA Optimized PID parameter |
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