title: Comparative study of a learning fuzzy PID controller and a self-tuning controller.
abstract: The self-organising fuzzy controller is an extension of the rule-based fuzzy controller with an additional learning capability. The self-organising fuzzy (SOF) is used as a master controller to readjust conventional PID gains at the actuator level during the system operation, copying the experience of a human operator. The application of the self-organising fuzzy PID (SOF-PID) controller to a 2-link non-linear revolute-joint robot-arm is studied using path tracking trajectories at the setpoint. For the purpose of comparison, the same experiments are repeated by using the self-tuning controller subject to the same data supplied at the setpoint. For the path tracking experiments, the output trajectories of the SOF-PID controller followed the specified path closer and smoother than the self-tuning controller.
authors.affiliation: Department of Computing, Information Systems and Mathematics, London Guildhall University, UK. kazemian@lgu.ac.uk
authors.forename: H B
authors.initials: HB
authors.lastname: Kazemian
mesh_terms: D000465:Algorithms; D001185:Artificial Intelligence; D017143:Fuzzy Logic; D016571:Neural Networks, Computer; D012371:Robotics