Tracking Control Via Linear Quadratic Gaussian and Guaranteed Cost Output Feedback Control to a DC Motor Reaction Wheel
This paper observes the problem of tracking control using Linear Quadratic Gaussian (LQG) and guaranteed cost output feedback controls. The reason to investigate this problem is that the lack of performance and instability of dynamic systems often occur due to noises and uncertainties. LQG is used to design an optimal regulator considering the process and measurement noises. The guaranteed cost control is used to build the controller of uncertain systems whose result is not only to make systems stable but also to attain an admissible performance. As an example of uncertain system, a dc motor reaction wheel is investigated to show the comparison and effectiveness of two different controllers.
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