A neuro-fuzzy combiner for multiobjective control

This paper proposes a neuro-fuzzy combiner (NFC) with supervised learning capability for solving multiobjective control problems. The proposed NFC can combine n existing low-level controllers in a hierarchical way to form a multiobjective fuzzy controller. It is assumed that each low-level (fuzzy or nonfuzzy) controller has been well designed to serve a particular objective. The role of the NFC is to fuse the n actions decided by the n low-level controllers and determine a proper action acting on the environment (plant) at each time step. Hence, the NFC can combine low-level controller and achieve multiple objectives (goals) at once. Here a NFC can be designed by proposed architecture and supervised learning scheme. Computer simulations have been conducted to illustrate the performance and applicability of the proposed architecture and learning scheme.