Adaptive tuning of fuzzy membership functions for non-linear optimization using gradient descent method

摘要: This paper presents an adaptive fuzzy tuner for the optimization of non-linear, multi-variable problems. The gradient-descent method is used to adaptively tune bases membership functions in logic optimization. performance with tuning tested comparison without functions. It shown that provides better by converging optimal value lesser time and fewer iterations. A multi-variable, non-linear problem as illustrative example demonstrate improved performance. scheme has also been incorporated into Generalized Intelligent Grinding Advisory System (GIGAS II) results show even very complex problems such manufacturing processes, can be obtained.