Interval type-2 fuzzy neural network for ball and beam systems
Wei-Shou Chan, Chun‐Yi Lee, Chia-Wen Chang, Yeong‐Hwa Chang · 2010
An interval type-2 fuzzy neural network (IT2FNN) is developed for the position control of ball-and-beam systems to confront the noise. A T2FNN consists of a type-2 fuzzy linguistic process as the antecedent part and multi-layer neural network as the consequent part. The developed IT2FNN combines the merits of an interval type-2 fuzzy logic system and a neural network. Furthermore, the parameter-learning of the IT2FNN, which is based on the gradient decent method using adaptation law, is performed on line. Simulation results show that the dynamic behaviors of the proposed IT2FNN control system are more effective and robust with regard to uncertainties than the interval type-2 fuzzy logic control scheme.