A mixed control method combining fuzzy model-based control and neural network control is presented for a class of uncertain nonlinear system with multiple time delays.

一类多时滞不确定非线性系统，基于模型的模糊控制和神经网络控制相结合的混合控制方法。

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Model predictive control (MPC), also known as receding horizon control (RHC), is a class of model-based control theories that use linear or nonlinear process models to forecast system behavior.

模型预测控制(MPC)，也称为滚动时域控制(RHC)，是一种基于模型的控制理论，采用线性或非线性模型预测系统的活动。

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As a model-based control algorithm, the performance of controller will be hard to be improved only by re-tuning the parameters of controller if there is serious mismatch between model and plant.

作为基于模型的优化控制算法，如果模型预测控制算法的预测模型与实际对象的失配程度很严重，则仅靠整定控制器参数将难以改善控制器性能。

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