Optimal Cost Control and Monitoring of a System of Uncertainty

Abstract

In this paper, we designed a controller for an interval system and fixed cost function. The closed-loop system stability and cost function is guaranteed to be no more than a certain upper bound with all admissible uncertainties as well as a controller gain perturbation uncertainty with a sufficient pre-condition. We found that a modified interval system described by matrix factorization will lead to less conservative conclusions. Then we used linear matrix inequality to solve the problem, which converts the orginal issue into a convex optimization problem and minimizes the upper bound of the closed-loop system cost. The effectiveness of this approach has been verified with data simulation on Matlab and field experiment. The result of experiment is also compared with the benchmarks.