emotional learning based intelligent controller for mimo peripheral milling process

During the milling process, one of the most important factors in reducing tool life expectancy and quality of workpiece is the chattering phenomenon due to self-excitation. the milling process is considered as a mimo strongly coupled nonlinear plant with time delay terms in cutting forces. we stabilize the plant using two independent emotional learning-based intelligent controller (elic) in parallel. control inputs are considered as forces ux and uy in two directions x and y, which are applied by the piezoelectrics. the elic consists of three elements; critic, tsk controller and the learning element. the results of the elic have been compared with a sliding mode controller (smc). the simulation for the nominal plant shows better performance of the elic in iae and itse values at least 86% in the x-direction and 79% in the y-direction. similar simulation for an uncertain plant also shows an improvement of at least 89% in the x-direction and 97% in the y-direction.