Fuzzy neural controller

Abstract

The authors consider a fuzzy controller that processes fuzzy information. They discuss the model of the fuzzy controller, with fuzzy inputs for error and change in error, using a max-min neural network. A new learning algorithm, a modified delta rule, is derived. The generalization property of the neural net can be used to find a controller output for new fuzzy values of error and change in error. An example is presented showing the applicability of the fuzzy neural controller.<>