Hammersteinモデルを用いた非線形同定に基づく一般化予測制御系の構成法

抄録

Two types of new adaptive generalized predictive control (GPC) system design methods are proposed for a class of non-linear systems described by Hammerstein model. These methods consist of two parts, that is, non-linear system identification part and GPC design one. Since Hammerstein model is a serial connection of static non-linear block and dynamic linear one; firstly we identify each characteristics based on observed input-output data. Then, two types of GPC design methods are applied to the identified model. One method is based on decomposition of the system to non-linear part and linear one. The GPC is designed for the latter part and actual input is computed in consideration of the former part. The other method strictly designs the GPC for the whole non-linear system by using the optimization technique. Effectiveness of the methods is examined through numerical examples.