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投稿时间:2022-09-27
投稿时间:2022-09-27
中文摘要: 针对火电厂燃料控制这一非线性、滞后性、强干扰的被控对象,设计基于改进灰狼优化算法的自抗扰控制器。对燃料控制系统不同工况进行了阶跃仿真实验、扰动测试、鲁棒性测试以及变工况实验。实验结果表明,相较于传统比例-积分(PI)控制器和专家经验整定的自抗扰控制器,改进灰狼优化算法的自抗扰控制器可以实现燃料量的快速、稳定调节,在抗扰动及变工况过程中有较好的控制效果,具有较强的鲁棒性。
Abstract:Aiming at the controlled object of thermal power plant fuel control,which is nonlinear,large lag and strong disturbance,an active disturbance rejection controller based on the improved grey wolf optimization algorithm is designed.Through the step simulation experiment,disturbance experiment,robustness experiment and variable working condition experiment of the fuel control system is conducted under different working conditions.The experimental results show that,compared with the traditional PI controller and the active disturbance rejection controller based on expert experience,the active disturbance rejection controller based on the improved grey wolf optimization algorithm can realize the fast and stable adjustment of the fuel.It has better control effect in the process of disturbance and variable working condition,and has strong robustness.
keywords: active disturbance rejection controller thermal power fuel controller system improved grey wolf optimization algorithm
文章编号:20230106 中图分类号:TM621 文献标志码:
基金项目:
作者 | 单位 | |
蔡志鹏 | 上海电力大学 自动化工程学院 | caizhipeng0407@163.com |
许建强 | 上海电力大学 自动化工程学院 | |
王旻洁 | 上海电力大学 自动化工程学院 | |
汤豪 | 上海电力大学 自动化工程学院 |
引用文本:
蔡志鹏,许建强,王旻洁,等.基于改进灰狼优化算法自抗扰控制器在火电燃料控制系统中的应用[J].上海电力大学学报,2023,39(1):33-39.
CAI Zhipeng,XU Jianqiang,WANG Minjie,et al.Application of Active Disturbance Rejection Controller Based on Improved Grey Wolf Optimization Algorithm in Thermal Power Fuel Control System[J].Journal of Shanghai University of Electric Power,2023,39(1):33-39.
蔡志鹏,许建强,王旻洁,等.基于改进灰狼优化算法自抗扰控制器在火电燃料控制系统中的应用[J].上海电力大学学报,2023,39(1):33-39.
CAI Zhipeng,XU Jianqiang,WANG Minjie,et al.Application of Active Disturbance Rejection Controller Based on Improved Grey Wolf Optimization Algorithm in Thermal Power Fuel Control System[J].Journal of Shanghai University of Electric Power,2023,39(1):33-39.