基于多模型混合的广义最小方差控制性能评估

针对实际工业过程中控制系统经常会受到时变扰动的影响，致使针对单一扰动模型设计的性能评估方法不再适用于时变扰动控制系统的问题，提出了基于多模型混合的广义最小方差控制性能评估方法．该方法综合考虑被控对象输出方差与控制器输出方差的两个指标，同时提出了一种“判断—加权”的控制器设计策略．首先，在任一时间段选取使广义输出方差最小的控制器，并判断其与上一时间段采用的控制器是否一致；然后，在此基础上采用多模型混合思想进行控制器设计，并将其作用下的广义输出方差作为性能评估的基准．通过乙烯裂解炉仿真，验证了本文所述方法在时变系统性能评估中的有效性．

Performance Assessment of Control Systems Based on a Multiple-model Mixing Method with Generalization Minimum Variance

Almost all control loops in industry are under the influence of time-variant disturbances. Performance assessment based on a single model of disturbance is not sufficient for such systems. To solve this, we propose performance assessment of control systems based on a multiple model mixing method with generalized minimum variance. A trade-off is made between the manipulated variable variance and the controller output variance, and the strategy of judgement-weighting is proposed. First, the controller with the minimum generalized variance is chosen and the judgment made as to whether it is different from the previous chosen controller in each period. Then, based on the chosen controllers, a benchmark controller is obtained with the multiple models mixing method. Finally, the generalized variance of the control system under the effect of the benchmark controller serves as the standardwith which to assess a system with time-variant disturbances. Simulation of an ethylene-cracking furnace demonstrates that the proposed method can be applied to control systems with time-variant disturbances.