Control of a cart system using genetic algorithm

So far many researches have studied to control a cart system with a pole on the top of itself (forwards we call it simply a cart system) which is movable only to the directions to which a cart moves, using neural networks and genetic algorithms. Especially which it wag solved by genetic algorithms, it was possible to control a cart system more robustly than ordinary methods using neural networks but it had problems too, i.e., the control time to be achieved was short and the processing time for it was long. However we could control a cart system using standard genetic algorithm longer than ordinary neural network methods (for example error backpropagation) and could see that robust control was possible. Computer simulation was performed through the personal computer and the results showed the possibility of real time control because the cpu time which was occupied by processes was relatively short.