Title :
Self-tuning PD+I fuzzy logic controller with minimum number of rules
Author :
Teng, F.C. ; Lotfi, A. ; Tsoi, A.C.
Author_Institution :
Polytech. Univ. of Puerto Rico, San Juan
Abstract :
A novel 9 rules self-tuning PD+I fuzzy logic controller applicable for a class of nonlinear plants is proposed in this paper. The controller comprises of three separate fuzzy logic controllers with each uses minimum number of rules and the output scaling factor is tuned automatically depending on the tracking error dynamic conditions. The controller is applied to a two-link revolute robot for the tracking control. Simulation results show that the robustness and tracking performance of the proposed controller is comparable to standard PD+I fuzzy logic controller at low and medium speed motions. However, the performance of the proposed new design far exceeds the standard design at high speed motions.
Keywords :
adaptive control; control system synthesis; fuzzy control; manipulators; nonlinear control systems; self-adjusting systems; three-term control; error dynamic condition tracking; nonlinear plant; output scaling factor; self-tuning PDI fuzzy logic controller; two-link revolute robotic manipulator; Adaptive control; Automatic control; Control systems; Fuzzy logic; Industrial control; Manipulators; Motion control; Nonlinear control systems; Robotics and automation; Three-term control; PD+ I fuzzy logic controller; minimum number of rules; self-tuning output scaling factor;
Conference_Titel :
Systems, Man and Cybernetics, 2007. ISIC. IEEE International Conference on
Conference_Location :
Montreal, Que.
Print_ISBN :
978-1-4244-0990-7
Electronic_ISBN :
978-1-4244-0991-4
DOI :
10.1109/ICSMC.2007.4413665