LMI Optimization of Sensors System for Elastic Vehicle Control Design Based on the Quadratic Performance Index
The statement of problem of optimization of sensors system in the control system of the elastic aerospace vehicle under condition of the stochastic system control design on the base of quadratic performance index is considered. The desired control system is the linear-quadratic-Gaussian (LQG) regulator which consists from the steady-state Kalman estimator and the optimal state-feedback gain. The LQG regulator minimizes some quadratic cost function that trades off regulation performance and control effort. This regulator is dynamic and relies on noisy output measurements to generate the control. Magnitudes of time-average values of quadratic performance indexes and maximum feasible values of dispersion of estimation of state vector are considered as linear matrix-inequalities-restrictions in the sensor system optimization problem on the base of minimization of offered goal function related with the number, type and accuracy of sensors. The uniqueness of the solution and high performance of the suggested method are typical for the convex programming problems.