Abstract :
We present the parameter robust risk-sensitive control theory to deal with the parameter uncertainties of a system. In this synthesis, the parameter uncertainties are decomposed into three parts, and are reflected in the cost function and the noise models. This new method improves the tolerance of a controller to parameter uncertainties in a system. We apply the newly developed method to satellite structure attitude control application. The linearized version of the satellite structure attitude model is derived for the attitude hold mode. To determine the performance of the parameter robust risk-sensitive control method, the steady-state mean square histories of the state and input variables are calculated by finding the covariance matrices. Moreover, the performance robustness of parameter robust risk-sensitive control is compared with the classical linear quadratic Gaussian control. Finally, as an application of this parameter robust risk-sensitive control, we consider commercially operating remote sensing satellite. The numerical simulations show that the parameter robust risk-sensitive control method has better performance and stability characteristics than the classical linear quadratic Gaussian control method, especially when the parameter uncertainties are large.
Keywords :
artificial satellites; attitude control; control system synthesis; covariance matrices; remote sensing; robust control; uncertain systems; covariance matrices; numerical simulation; parameter robust risk sensitive control synthesis; remote sensing satellite; satellite structure attitude control; steady state mean square method; system parameter uncertainties;