An Evolutionary Optimal Fuzzy System With Information Fusion of Heterogeneous Distributed Computing and Polar-Space Dynamic Model for Online Motion Control of Swedish Redundant Robots

Abstract

This paper presents an evolutionary optimal fuzzy system with information fusion of heterogeneous distributed computing and polar-space dynamic model for online motion control of Swedish redundant robots. The intelligent fuzzy system incorporated with the parallel metaheuristic Bacteria Foraging Optimization (BFO)-Artificial Immune System (AIS), called FS-PBFOAIS and its field-programmable gate array (FPGA) realization to optimal polar-space online motion control of four-wheeled redundant mobile robots. This hybrid paradigm gains the benefits of Taguchi quality method, BFO, AIS, distributed processing, and FPGA technique. Experimental results are conducted to present effective optimization and high accuracy of the proposed FPGA-based FS-PBFOAIS tracking controller. Finally, the comparative works are provided to demonstrate the superiority of the FPGA-based FS-PBFOAIS polar-space redundant controller over other conventional control methods.