On the neuro-genetic approach for determining optimal control of a rotary crane

The aim of this paper considers the determination of optimal control trajectories of a complex process. The proposed method is based on the decomposition of the system into interconnected subsystems. We consider the cases where subsystems are linear in terms of their state and control vectors. For this reason, a neural network is identified which compute local gains. Genetic algorithms are used to optimize the networks weights. Simulation results show that the proposed approximations yield satisfactory performances.