Abstract
In this paper, two-optimal robust fuzzy proportional-integralderivative (FPID) and linear-quadratic regulator (LQR) controllers have been implemented for attitude control of a geostationary satellite, utilising momentum wheels. In the designed FPID controller, two fuzzy inference engines have been used, from which the second engine, is accounted to control the satellite attitude in severe deviations and preventing the system from instability. The designed FPID controller is optimised using the multi-objective genetic algorithm (MOGA) based on desired objective functions, which are deviation error from equilibrium states and control efforts. The optimal FPID controller is designed in such a way that while making extremum the desired objective functions, it also provides an appropriate controlling performance. Throughout designing robust LQR controller, design matrices of R and Q are selected in such a way to form a balance between the made control efforts and the settling time of the system.
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