Design of Multi Agent Adaptive Neuro-Fuzzy Based Intelligent Controllers for Multi-Objective Nonlinear System

In this paper, we describe a multi agent controller for meeting different criteria, based on emotional learning. Our proposed controller is motivated by the affective and emotional faculties in human begins, which constantly evaluate the current states with respect to the achievement of the desired goals. For meeting different criteria, the controller consists of several critic agents that each agent tries to meet its goal. The combination of emotions of these agents applies on the controller in order to adapt the learning coefficients to achieve predefined criteria and goals. Our proposed controller, also continuously evaluate the current states from critic agents and incremental achievement or disachievement of the set objectives, and self tune its control action accordingly. The controller is based on intelligent neurofuzzy architecture that suitable for online training algorithms. The effectiveness of the total multi agent emotional control system (MEAC) is demonstrated trough examples in which the proposed system is used for reducing control effort and tracking error simultaneously. The contribution of critic’s emotions in multi criteria satisfaction is highlighted through these examples. Key-Words: Multi-agent systems, Multiobjective, Neural Network, Fuzzy logic, Nonlinear systems