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针对锅炉过热汽温对象具有大惯性、大迟延、时变性等特点,提出一种基于最小均方算法的自适应模型算法控制-比例串级预测控制系统.通过最小均方自适应滤波器在线实时辨识被控对象的预测模型参数,再结合改进的自适应模型算法控制在线修正控制器参数.仿真结果表明:该控制策略实施简单、超调小,控制效果明显优于PID-P串级控制;且在降负荷实验中能有效适应对象参数时变,保证调节性能较好.
Aiming at the characteristics of boiler superheated steam temperature, such as large inertia, large delay and time-varying, an adaptive model algorithm control-proportional cascade predictive control system based on least mean square algorithm is proposed. By means of the least mean square adaptive filter The parameters of the predictive model are identified and the parameters of the controller are modified with the improved adaptive model algorithm. The simulation results show that the control strategy is simple, overshoot and the control effect is better than PID-P cascade control. And in the load-lowering experiment can effectively adapt to the time-varying parameters of the object, to ensure good regulation performance.