This algorithm can effectively overcome the model mismatch, unknown disturbance and parameter variation.
该算法能够有效地克服模型失配、扰动和系统参数变化等情况。
A solution as compensating the controlled quantity by fuzzy inference is put forward in this paper to the problem of model mismatch caused by the predictive function control.
针对预测函数控制中模型失配的影响，提出了用模糊推理对控制量进行补偿的新型预测函数控制。
Simulations show that the predictive PID controller remains excellent control performance under disturbance, noise and model mismatch, which is very suitable for large time delay process.
通过仿真表明：在干扰、噪音存在和模型失配的情况下，预测PID控制器具有良好的控制性能，特别适合大纯滞后系统的控制。
Model predictive control the accuracy of the model do not ask for much on the model mismatch, non-minimum phase systems, the impact of uncertain interference robustness, higher performance.
模型预测控制对模型精度要求不高，对模型失配、非最小相位系统、不确定干扰的影响具有较强的鲁棒性，具有较高的控制性能。
Model mismatch is a common problem in model predictive control, as well as one of the most important reasons of bad performance.
模型失配是预测控制中普遍存在的问题，是导致预测控制器性能下降的重要原因。
Model mismatch is a common problem in model predictive control, as well as one of the most important reasons of bad performance.
模型失配是预测控制中普遍存在的问题，是导致预测控制器性能下降的重要原因。
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