Optimal Control Using Evolutionary Algorithms
Resumen
Optimal Control Problems involve dynamic systems that are subject to
algebraic or differential constraints and whose evolution may be characterized by a
performance index. Such a problem can be solved by the well known Evolutionary
Algorithms. This paper proposes an evolutionary algorithm having usual characteristics
concerning the mutation and crossover operators. Generally speaking, the EA gave good
results and the convergence was acceptable. But for a specific problem instance, the
evolutionary algorithm underperformed on the first simulation series. Therefore, the
paper proposes a new mutation operator having adaptive Gaussian standard deviation of
genes' values variation.