输出慢采样控制系统的多变量预测控制策略

Multi-variable Predictive Control Strategy for a Slow Sampling Output Control System

  • 摘要: 由于多速率系统慢采样输出通道的周期与基准周期不同步使得模型预测控制算法不适用.针对此类问题,提出一种适用于多速率系统的模型辨识及模型预测控制策略.首先,针对稳态时间内慢采样输出采样点个数的不同,提出2种建立单位阶跃响应模型的方法;其次,提出在每个基准周期用模型预测值对实际输出值进行预测,并利用该输出采样时刻得到的实际预测误差信息对输出预测值进行校正的控制策略,解决多速率系统慢采样输出通道周期与基准周期不同步的问题.最后,在典型重油分馏塔仿真系统上应用所提控制策略,通过对不同慢采样周期和模型失配程度的设置,验证该控制策略的有效性和适用范围.

     

    Abstract: Given that the periods of slow sampling output channels are not synchronous with the reference period, the model predictive control algorithm is inapplicable to the multi-rate system. To solve this problem, we propose a model identification and model predictive control strategy applied to the multi-rate system. First, in accordance with the different numbers of sampling points in the steady-state time, we propose two methods to establish the unit step response model. Second, we present a model predictive control strategy to solve the asynchronicity of the control periods of the slow sampling output channels with the reference period. A characteristic of the control strategy is that the actual output value is predicted by the model predictive value of each reference period and the actual forecast error is used to correct the output forecast value. Finally, the control strategy is applied to a typical heavy oil distillation column system. The validity and the application range of the control strategy are verified by setting various slow sampling periods and model mismatch degrees.

     

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