鲁棒性模型自适应方法

针对工业过程控制普遍存在扰动特别是大扰动问题,通常采用模型自适应方法来加以消除·提出了采用基函数修正模型自适应增益系数的方法,利用高斯基函数的特点把过程扰动的影响作为基函数的输入,从而减小过程扰动的影响,特别是减小大扰动的影响·对线性过程模型改进了加法自适应算法,对非线性过程模型改进了乘法自适应算法·仿真试验结果表明所提方法对加法自适应和乘法自适应都是有效的,对大扰动具有明显的抑制作用,对过程扰动具有良好的鲁棒性·

Robust Model Parameter Adaptive Method

In order to solve the disturbance effect on industrial process,a model adaptive method based on Gaussian radial base function gain was proposed. Taking the derivation of the disturbance in a sample period as the input of the Gaussian radial base function, the effect of the disturbance, especially of big disturbance case,is reduced using this method, both additive adaptive and multiplicative adaptive algorithm were improved. The proposed method is able to restrain the disturbance effect and possesses good robust properties to process disturbance, especially to big disturbance.