Teaching Fuzzy Logic Control Based on a Robotic Implementation

Advanced control concepts present a teaching challenge - even at master level students benefit from these concepts being implemented and demonstrated on real hardware, rather than simply modeling the plant, applying control strategy and tuning. This paper provides reference materials (both theoretical and test results), to be used in control teaching and assessment using a laboratory experiment, with a real-time single board computer based robotic vehicle (National Instruments Robotics Starter Kit). This paper explores the practical implementation of the ACC system through use of a real-time single board computer based robotic vehicle (National Instruments Robotics Starter Kit). The ACC algorithm based on fuzzy PID control is deployed on a field programmable gate array (FPGA), included in the robot's architecture. This robotic vehicle is programmed using a graphical programming language (LabVIEW). A Kalman filter is used to estimate the unmeasured parameters while implementing the control algorithm in the hardware (the real robot). The results obtained are compared for the simulation model and the real robot, respectively. The experiment demonstrates clear correlation between theoretical expectations and real-life system performance and at the same time offers a novel idea how to deliver this advanced control concept in an applied and visual manner.