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

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。

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.