基于多目标粒子群算法的过热汽温自抗扰控制

doi:10.11930/j.issn.1004-9649.201908096

中国电力 ›› 2020, Vol. 53 ›› Issue (3): 126-133.DOI: 10.11930/j.issn.1004-9649.201908096

基于多目标粒子群算法的过热汽温自抗扰控制

牛海明¹, 于佼², 丁常富², 汪朝晖³, 田彬¹

1. 北京国电智深控制技术有限公司北京市电站自动化工程技术研究中心, 北京 102200;
2. 华北电力大学能源动力与机械工程学院, 河北保定 071003;
3. 北京化工大学自动化系, 北京 100029

收稿日期:2019-08-15 修回日期:2019-10-31 发布日期:2020-03-10
作者简介:牛海明(1980-)男,硕士,高级工程师,从事控制理论和控制技术研究,E-mail:12072301@chnenergy.com.cn;于佼(1994-)男,硕士研究生,从事火电机组自抗扰控制技术应用研究,E-mail:a1374332643@163.com
基金资助:
国家重点研发计划资助项目（2018YFB1500801）

Active Disturbance Rejection Control over Superheated Steam Temperature Based on Multi-objective Particle Swarm Optimization

NIU Haiming¹, YU Jiao², DING Changfu², WANG Zhaohui³, TIAN Bin¹

1. Beijing Engineering Research Center of Power Station Automation, Beijing GuoDian ZhiShen Co., Ltd., Beijing 102200, China;
2. School of Energy Power and Mechanical Engineering, North China Electric Power University, Baoding 071003, China;
3. Department of Automation, Beijing University of Chemical Technology, Beijing 100029, China

Received:2019-08-15 Revised:2019-10-31 Published:2020-03-10
Supported by:
This work is supported by the National Key R&D Program of China (No.2018YFB1500801)

摘要/Abstract

摘要： 针对火电机组过热汽温存在大惯性、大时滞和非线性的动态特性，以及扰动因素作用下参数不易整定的问题，提出自抗扰控制-线性自抗扰控制（ADRC-LADRC）串级控制策略，即外回路应用非线性自抗扰减小超调量，内回路应用线性自抗扰对扰动快速响应并加以抑制，同时采用多目标粒子群算法对自抗扰串级回路中的参数进行整定。测试与工程应用表明：基于多目标粒子群算法整定参数的ADRC-LADRC控制策略具有较好的控制性能和抗干扰能力，能够快速响应扰动并跟踪设定值，维持过热汽温的稳定。

关键词: 自抗扰控制, 过热汽温, 多目标粒子群算法, 串级控制系统

Abstract: Regarding the existing issues in the control of superheated steam temperature, which are related to the control system dynamic characteristics, such as large inertia, long duration of time lag and strong nonlinearities, as well as the difficulties to set the parameters of the controller under certain disturbances, this paper presents the cascade active disturbance rejection control-linear active disturbance rejection control (ADRC-LADRC) strategy. Specifically, in the outer loop the proposed method uses nonlinear active disturbance rejection control to reduce the overshoot, while in the inner loop it uses linear active disturbance rejection control to quickly respond to and then suppress the disturbance. At the same time, the multi-objective particle swarm optimization algorithm is used to optimize the parameters in the control loop. The test and engineering applications show that the ADRC-LADRC control strategy based on multi-objective particle swarm optimization algorithm has better control performance and strong anti-interference capability. Also it can quickly respond to disturbances and track the set values to keep the superheated steam temperature stable.

Key words: active disturbance rejection control (ADRC), superheated steam temperature, multi-objective particle swarm optimization algorithm (MOPSO), cascade control system

牛海明, 于佼, 丁常富, 汪朝晖, 田彬. 基于多目标粒子群算法的过热汽温自抗扰控制[J]. 中国电力, 2020, 53(3): 126-133.

NIU Haiming, YU Jiao, DING Changfu, WANG Zhaohui, TIAN Bin. Active Disturbance Rejection Control over Superheated Steam Temperature Based on Multi-objective Particle Swarm Optimization[J]. Electric Power, 2020, 53(3): 126-133.

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https://www.electricpower.com.cn/CN/Y2020/V53/I3/126

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基于多目标粒子群算法的过热汽温自抗扰控制

Active Disturbance Rejection Control over Superheated Steam Temperature Based on Multi-objective Particle Swarm Optimization

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Active Disturbance Rejection Control over Superheated Steam Temperature Based on Multi-objective Particle Swarm Optimization

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