Parallel Cascade Fuzzy Inference System at the environment changes, case study: Automated Guide Vehicle Robot using ultrasonic sensor

Problems of environmental change often causes a system failure on a robot control. It occurs because the system is not capable of adapting to it problem. This paper presents a new design architecture of the Parallel Cascade Fuzzy Inference System as a solution to cope with the uncertainty of environmental change and applied on a case study of an Automated Guide Vehicle (AGV) Robot with ultrasonic sensors. In this systems, there are two systems, namely, Environment Change System and Control System. Parallel Cascade Fuzzy Inference System was tested in a simulated of different road scenario and continued to implementation of the Lego robot. From the results obtained, prove that the system is capable of adapting to the environmental change for the case study (AGV).