H8 Model Predictive Control: theory and application
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Abstract"Future industrial systems will require control systems to be more reliable, autonomous, robust, and yet efficient. The emphasis of this thesis is to introduce a robust control algorithm definition that addresses the needs of future industrial environments. The proposed controller is based on an adaptive concept with a two-step approach. In step one, the system model is identified in a closed-loop by a robust technique. In step two, the obtained system model from step one is used to formulate a robust controller. The system identification is the central part of the controller design since the controller can only be as good as the model that is used to design it. In order to improve the performance and robustness of the system identification, this thesis proposes expert system supervised multiple system identifications. The role of the expert system is to periodically evaluate the estimated models and to propose-one for the controller design. The robust controller is formulated by the H00 (sub )optimal design procedure using the proposed system model. The idea behind this controller design technique is to combine an on-line identification algorithm with a control design method that yields a time-varying controller which follows the changing plant. The effectiveness of the proposed robust controller in an industrial environment is demonstrated by simulation and experimental tests. The proposed robust controller as a power system stabilizer has been tested by simulations on a power system model and in the experimental environment using the micro-synchronous generator at the University of Calgary. "
Bibliography: p. 270-293