PSO training of the Neural Network application for a controller of the line tracing car

Abstract

In this research, a fuzzy controller system is useful as a key technique to design a machine controller because a fuzzy system can be designed by fuzzy sets, which can be represented using linguistic descriptions of natural language. Those natural languages are able capture human knowledge in fuzzy rules. A fuzzy controller system consists of fuzzy rules and involved techniques. Recently, the research of the fuzzy control has controlled various machines. We verified that fuzzy control can be applicable to a line tracing car control, which is running at a high speed. In our research, designers took a huge amount of time to adjust and setup the fuzzy controller. In order to apply the Neural Network (NN) controller, we designed a simple network system, and setup a PSO_VC and parameters. The PSO_VC (a PSO with Velocity Control) is a speed control strategy for all moving particles on the PSO. In order to configure the NN, a very powerful and quick PSO_VC is used. The PSO_VC is able to adjust all weights and threshold levels. In this paper we present the performances of accurate control and compare results between fuzzy controller and the NN controller.