Stability Control of Inverted Pendulum Using Fuzzy Logic and Genetic Neural Networks

In this study, fuzzy logic is first proposed for nonlinear inverted-pendulum mechanism real time stability control. This kind of control can be observed as a coarse control action as fuzzy logic is rather easily applied. However, choosing the correct set of rules and scale factors is not an easy task in order to fine-tune the fuzzy controller for optimum performance. in this case, genetic algorithm and neural networks are used for fine improvement of the two controllers to overcome nonlinearity and unknown dynamics in the system.. Finally, the simulation experiments results show the superiority of the optimal controller.