基于概率鲁棒的改进自抗扰控制器设计

doi:10.3969/j.issn.2097-0706.2022.10.008

摘要/Abstract

摘要：

过热汽温是火电机组日常运行的重要参数，为适应其大惯性大滞后的特性，常采用串级控制策略进行控制，但控制结构较为复杂，控制器整定较为繁琐。一种改进的自抗扰控制器可简化传统过热汽温的控制结构并获得满意的控制效果，但由可再生能源系统接入引起的不确定性客观存在，改进的自抗扰控制仅是在标称工况下设计的，无法有效应对不确定性。采用不确定系统的随机分析方法——概率鲁棒设计改进自抗扰控制器，旨在保证机组工况发生变化时控制器仍可最大概率满足控制指标要求。仿真结果表明，基于概率鲁棒的改进自抗扰控制器能够获得良好的动态性能与强鲁棒性，展现了其未来应用于火电机组的前景。

关键词: 火电机组, 过热汽温, 概率鲁棒, 自抗扰控制, 不确定性, 随机分析, 可再生能源

Abstract:

Superheated steam temperature （SST） is a vital parameter for the daily operation of a coal-fired power unit because it is related to the efficiency and the safety of the unit. Due to SST's characteristics of large inertia and delay， cascade control strategies are usually applied to the control of the parameter. However， the structures of cascade control systems are complex， which brings challenges to the tuning of controllers. A hybrid active disturbance rejection controller （HADRC） can simplify the control structure of SST and perform satisfying control. Nevertheless， uncertainties caused by the access of renewable energy systems exist. The original HADRC designed based on the nominal system is unable to handle with uncertainties effectively. To meet the control requirements under variable working conditions with maximum probability，a HADRC is designed based on the stochastic analysis method—probabilistic robustness（PR）. Simulation results illustrate that the PR-based HADRC is of fast dynamic performance and strong robustness， which shows its promising prospect in future applications to coal-fired power units.

Key words: coal-fired power unit, superheated steam temperature, probabilistic robustness, active disturbance rejection control, uncertainty, stochastic analysis, renewable energy

中图分类号:

TM921.5：TK39

史耕金, 李东海, 丁艳军. 基于概率鲁棒的改进自抗扰控制器设计[J]. 综合智慧能源, 2022, 44(10): 57-64.

SHI Gengjin, LI Donghai, DING Yanjun. Design of a hybrid active disturbance rejection control based on probabilistic robustness[J]. Integrated Intelligent Energy, 2022, 44(10): 57-64.

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控制策略	σ/%	t_s/s	J_sp	J_ud1	J_ud2
OPI-PI	13.6	2 900	680.9	329.6	656.3
IPI-PI	0	1 122	336.5	92.4	350.0
ADRC-PI	1.3	700	344.2	92.2	292.9
MADRC-PI	1.0	578	260.6	82.8	238.8
HADRC	0.2	424	215.1	41.6	202.9
PR-HADRC	0.2	299	153.5	8.5	114.0

控制策略	概率估计值
OPI-PI	0.081 6
IPI-PI	0.231 6
ADRC-PI	0.180 0
MADRC-PI	0.249 6
HADRC	0.427 2
PR-HADRC	0.909 2