Development of fuzzy-logic-based self tuning PI controller for servomotor

Wahyunggoro, O. and Saad, N.B. (2008) Development of fuzzy-logic-based self tuning PI controller for servomotor. In: UNSPECIFIED.

Full text not available from this repository.
Official URL: https://www.scopus.com/inward/record.uri?eid=2-s2....

Abstract

Direct Current (DC) servomotors are widely used in robot manipulator applications. Servomotors use feedback controller to control either the speed or the position or both, and the basic continuous feedback control is PID controller. This paper discusses the modeling and simulation of DC servomotor control built using MATLAB/Simulink, and the analysis of controller performance, namely a PID controller, PI controller, fuzzy-scheduled PID controler, and a fuzzy-logic-based self tuning PI controller on the system. The singleton fuzzification is used as a fuzzifier. The center average is used as a defuzzifier. Two control modes are applied in sequential to the plant: speed control, and then position control. Simulation results show that fuzzy-logic-based self tuning PI controller has the best performance compared to conventional PID controller and fuzzy-scheduled PID controler. © 2008 IEEE.

Item Type: Conference or Workshop Item (UNSPECIFIED)
Additional Information: cited By 11; Conference of 2008 10th International Conference on Control, Automation, Robotics and Vision, ICARCV 2008 ; Conference Date: 17 December 2008 Through 20 December 2008; Conference Code:75841
Uncontrolled Keywords: Continuous feedback controls; Control modes; Controller performance; DC servomotor controls; Defuzzifier; Direct-currents; Feedback controllers; Fuzzification; MATLAB /simulink; Modeling and simulations; PI controller; PID controllers; Robot manipulators; Self-tuning PI controllers; Simulation results, Computer vision; Controllers; Electric control equipment; Feedback; Feedback control; Fuzzy sets; Proportional control systems; Robot applications; Robotics; Robots; Servomotors; Three term control systems; Tuning; Two term control systems, Fuzzy logic
Depositing User: Mr Ahmad Suhairi UTP
Date Deposited: 09 Nov 2023 15:16
Last Modified: 09 Nov 2023 15:16
URI: https://khub.utp.edu.my/scholars/id/eprint/381

Actions (login required)

View Item
View Item