Abstract
Most adaptive controllers do not assume any a priori knowledge about the process to be controlled. In most situations there is, however, some knowledge about the process. This knowledge should be used to improve the performance compared to the “black box” approach of earlier adaptive controllers. The a priori knowledge is in this paper used in the estimation of the process and also in the design of the controller. The use in the design is new compared to earlier approaches. The a priori knowledge is used here to design a nominal controller. The unmodelled part of the process is estimated and an adaptive stability augmentation signal is added to the nominal controller. Different types of a priori knowledge and design methods are discussed and the performances are investigated through analysis and simulation.
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