汤伟,胡祥满,孙小乐.基于模拟退火粒子群混合算法的纸浆浓度控制系统[J].包装工程,2017,38(7):15-20.
TANG Wei,HU Xiang-man,SUN Xiao-le.The Control System of Pulp Concentration Based on the Hybrid Algorithm of Simulated Annealed Particle Swarm Optimization[J].Packaging Engineering,2017,38(7):15-20. |
| 基于模拟退火粒子群混合算法的纸浆浓度控制系统 |
| The Control System of Pulp Concentration Based on the Hybrid Algorithm of Simulated Annealed Particle Swarm Optimization |
| 投稿时间：2017-01-08 修订日期：2017-04-10 |
| DOI： |
| 中文关键词: 纸浆浓度 控制系统 模拟退火 粒子群优化 |
| 英文关键词: pulp concentration control system simulated annealed particle swarm optimization |
| 基金项目:陕西省重点科技创新团队计划 (2014KCT-15)；陕西省科技统筹创新工程计划 (战略性新兴产业重大产品(群)) (2016KTCQ01-35) |
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| 中文摘要: |
| 目的 为了得到最优的控制器参数，以满足纸浆浓度实际控制要求，更好地克服控制难点。方法 提出一种模拟退火粒子群混合算法，并应用于纸浆浓度控制系统，对其PID控制器参数进行整定优化，基于MATLAB的.m程序和Simulink进行仿真，并与其他整定方法进行比较。结果 该优化方法能够得到较为理想的控制效果，系统过度平稳、响应快、超调小、调整时间短、鲁棒性好，其输出响应曲线上升时间为9 s，超调量为3.07%，调整时间为22.8 s。结论 基于此混合算法的优化控制，不仅兼顾2种算法各自的优点，且相对于二者各自的优化控制及传统整定方法具有显著优越性，可以更好地满足现场控制要求。 |
| 英文摘要: |
| The work aims to obtain the optimal controller parameters to meet the actual requirements and overcome the difficulties in the control process of pulp concentration. A hybrid algorithm of simulated annealed particle swarm optimization was proposed and applied to the pulp concentration control system for tuning and optimizing the PID controller parameters. Simulations were done based on .m program and Simulink in MATLAB and comparison to other tuning methods was made. This optimization method could get relatively ideal control effect and the system was featured by stable transition, fast response, low overshoot, short adjusting time and good robustness. The rise time of the output response curve was 9 s, the overshoot was 3.07%, and the adjusting time was 22.8 s. It was concluded that the optimal control based on this hybrid algorithm has not only the advantages of both algorithms and is significantly superior to them with respect to their respective optimal control and traditional tuning methods, which can better meet the requirements of field control. |
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