Fusion of Modified Bat Algorithm Soft Computing and Dynamic Model Hard Computing to Online Self-Adaptive Fuzzy Control of Autonomous Mobile Robots

This paper presents a fusion methodology of modified bat algorithm (BA) soft computing and dynamic model hard computing to online self-adaptive fuzzy control of autonomous mobile robots in a field-programmable gate array (FPGA) chip. This fusion approach, called fusion of BA fuzzy control (FBAFC), gains the benefits of BA, online fuzzy control, dynamic model, Taguchi method, and FPGA technique. The FPGA realization of the proposed FBAFC fusion method is more effective in practice for challenging real-world embedded applications by using system-on-a-programmable-chip (SoPC) technology. Experimental results and comparative works are conducted to illustrate the merits of the proposed SoPC-based FBAFC optimal controller over other existing methods for mobile robots.