This paper extends the sequence model approximation (SMA) approach to hierachical control of large-scale steady state systems.
本文将序列模型逼近法推广到稳态大系统的递阶优化与控制中去。
Simulations demonstrate that SVM has good nonlinear approximation capability for inverse model, and the proposed control system has good dynamic and static performances as well as good robustness.
仿真研究表明，SVM具有优良的逆模型辨识能力，基于模糊控制补偿的支持向量机逆控制系统的动态性能好、跟踪精度高、鲁棒稳定性强。
PID gain predictive control based on two approximation model is proposed for the problems of the traditional PID control and predictive control.
提出一种基于二次逼近模型的PID增益预测控制，并阐述了该系统的结构、算法和应用特点。
If the two preconditions are difficult to satisfy, the model error caused by the linear approximation will become difficult to control.
如果这两个前提难以满足，由线性化近似模型带来的模型误差将变得难以控制。
A sliding model control term is used to compensate for the effects of approximation errors.
一个滑模控制项用于消除神经网络逼近误差的影响。
Then the Neural Network PID control is realised in the model. This method makes full use of nonlinear function approximation of the Neural Network.
这种方法充分利用了神经网络的非线性函数逼近能力，构造神经网络自整定PID控制器。
Then the Neural Network PID control is realised in the model. This method makes full use of nonlinear function approximation of the Neural Network.
这种方法充分利用了神经网络的非线性函数逼近能力，构造神经网络自整定PID控制器。
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