IN PARTIAL FULFILMENT OF THE REQUIREMENTS FOR THE

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 algo-rithm 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 sys-tem 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 perfor-mance 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 H ∞ (sub)optimal design procedure using the proposed system model. The idea behind this controller design technique is to combine a