自适应广义一般模型控制

针对一般模型控制的缺点，提出了两种改进的自适应广义一般模型控制方法.它们把传统的一般模型控制推广到相对阶大于1 同时又具有时变参数的复杂非线性过程.第1种控制策略主要利用强跟踪滤波器直接在线估计时变参数，来修正过程模型；另一种方法是将所有干扰因素归结为输入等价干扰，通过估计它来实现对过程的前馈控制.仿真实验结果验证了所提出方法的有效性.

ADAPTIVE GENERALIZED GENERIC MODEL CONTROL

This paper presents two improved adaptive control approaches,which extend conventional Generic Model Control(GMC) to complex nonlinear time-varying processes with relative order larger than 1.The first one can automatically modify the process model through estimating the time-varying parameters by Strong Tracking Filter(STF);the other one introduces a concept of Input Equivalent Disturbance(IED),which includes all the disturbance factors.The IED can be adaptively estimated by STF,and can be used in feedforward compensation of disturbances.Simulation results validate the effectiveness of these two approaches.