Operations Research, Systems Engineering and Industrial Engineering Commons^™

A Comparison Of Fam And Cmac For Nonlinear Control, Arit Thammano, Cihan H. Dagli

Engineering Management and Systems Engineering Faculty Research & Creative Works

This article compares a neural network-based controller, both local and global networks, with fuzzy associative memories (FAM) on a nonlinear problem. CMAC and FAM are chosen as representatives of local generalization networks. CMAC controller is trained off-line, therefore, it can response to the incoming input immediately. CMAC can interpolate its memory and give a reasonable control signal even the input has not been trained on. Backpropagation is picked as a representative of global generalization networks. All three systems are studied on a simple simulated control problem. This preliminary research will be adapted later to control the laser cutting machine. A …