摘要
研究核电站蒸发器水位控制优化问题,由于蒸汽发生器是核电站中最重要设备之一,水位控制对核电站的安全运行起着决定性的作用,并要求系统稳定运行,快速响应。针对蒸汽发生器是一个高度复杂、非线性、时变的系统,传统的串级PID控制等控制方法难以取得满意的控制效果,把自抗扰控制方法引入蒸汽发生器水位的串级控制系统中,解决传统PID快速性和超调的矛盾,且能够动态补偿对象模型的内扰和外扰。另外,自抗扰控制器的参数较多且参数难以整定,采用混沌搜索的粒子群混合优化算法来对优化选择参数进行仿真。仿真结果表明,改进方法的鲁棒性和控制品质优于传统的串级PID控制方法,方法的可行性和有效性。
The steam generator is one of the most important equipments at nuclear power plant, and its water level control of steam generator is very important to the safety and the economic operation of nuclear power plant. As the steam generator is a highly complex, nonlinear, time -varying system, the traditional cascade PID control and other control methods are difficult to obtain satisfactory control effects. The disturbance rejection control method, as a new nonlinear PID control method, was introduced to the water level control of steam generator in this paper, which can solve the contradiction between speed and overshoot in the conventional PID control system and compensate the internal and external disturbances of the object model dynamically. In addition, the parameters of ADRC are numerous and they are difficult to be tuned. Therefore, they were optimized by the hybrid algorithms of chaotic search and particle swarm optimization in this paper. The simulation results show that its robustness and its control quality are better than the traditional cascade PID control, therefore, this method is feasible and effective.
出处
《计算机仿真》
CSCD
北大核心
2012年第2期188-193,共6页
Computer Simulation
基金
国家自然科学基金项目(61040013)
上海市教委重点学科建设项目(J51301)
关键词
蒸汽发生器
水位控制
自抗扰控制
粒子群算法
混沌
串级控制
Steam generator
Water level control
Active disturbances rejection control
Particle swarm optimization （PSO）
Chaos
Cascade control
