Neural integrated fuzzy controller (NiF-T) and real-time implementation of a ball balancing beam (BBB)

A controller with blend of neural networks and fuzzy logic is proposed for a nonlinear control problem. Fuzzy logic membership functions are utilized to fuzzify input parameters; neural network interpolates the fuzzy rule set; after defuzzification, the output is used to train a smaller size of neural network; the weights of the later neural network can be adjusted to fine tune the controller. This controller successfully balances balls with one third of the required 27 rules. With learning capability, it approaches its goal more frequently in general.