An application of genetic algorithms with binary and real coding for approximate synthesis of suboptimal control in deterministic systems

We propose a solution for the suboptimal control synthesis problem in deterministic systems with genetic algorithms that look for a conditional global extremum with binary and real coding. We construct an algorithm for solving this problem; this algorithm has been implemented in software. We show examples of specific applications and perform a comparison of these results with other methods; the comparison proves the efficiency of our algorithms.