Automatic intelligent initialization for a modified generalized minimum variance controller

When a self-tuning regulator (STR) is applied, is essential an adequate initialization. The initialization procedure must to fix the initial parameters, to select a model structure and to propose the desired control criterion. If the goal is to have adaptive control when the knowledge about the process is scarce or even do not exist, is essential to develop a tool that can initialize to the adaptive controller in autonomous way. This paper describes an initialization approach which is based in heuristic rules and intelligent procedures. Also is developed a modification to the generalized minimum variance controller with pole assignment approach to reduce the number of parameters that must be initialized and simplify the implementation for practical cases. Test results are included in the document with the aim to highlight the characteristics of the proposed initialization procedure.