Intelligent vision-based fuzzy control system

For better performance, the implementation of a controller for a nonlinear plant may use adaptive concepts. Adaptive controllers with self adjustment capabilities possess many advantages over conventional methods. Many adaptive fuzzy controllers have been considered, which are generally referred to as self-organizing controllers. One advantage of fuzzy controllers is their simple computation requirements and it is important for this simplicity to be retained in comparison with more algorithmic-based controllers. In this paper, a fuzzy logic controller is implemented in a 2-DOF varying-damper system for vibration reduction. In the metal forming problem, an optical camera is utilized as the sensor, a servo motor with a forming mechanism as the actuator, microprocessor as the CPU, as well as the data acquisition and conversion boards as communication unit. The integration of hardware elements is managed by a fuzzy logic algorithm that was written in C++. The data and disturbance measured by the sensor is processed by the CPU, allowing the controller to utilize primary and secondary errors between the desired output and the actual response to conduct decision making. Results from simulation and testing are presented.