Superiority of using interval type-2 fuzzy PID controller over the conventional type-1 fuzzy controller in a chlorine flow control system

2017 ◽  
Author(s):  
Negar Moghadam ◽  
Fereidoon Shabaninia ◽  
Hamidreza Abbasi
Keyword(s):  
Control System ◽  
Pid Controller ◽  
Fuzzy Controller ◽  
Fuzzy Pid ◽  
Fuzzy Pid Controller ◽  
Flow Control System ◽  
Interval Type ◽  
Conventional Type

Design and Implementation of Fuzzy PID Controller for Brushless DC Motor Control System

2013 ◽  
Vol 432 ◽  
pp. 472-477
Author(s):  
Wei Fan ◽  
Tao Chen
Keyword(s):  
Control System ◽  
Digital Signal Processor ◽  
Pid Controller ◽  
Fuzzy Controller ◽  
Digital Signal ◽  
Dc Motor ◽  
Brushless Dc Motor ◽  
Fuzzy Pid ◽  
Brushless Dc ◽  
Fuzzy Pid Controller

This paper presents a robust fuzzy proportional-integral-derivative (PID) controller for brushless DC motor (BLDCM) control system. The hardware circuit of the BLDCM control system is designed and implemented using a digital signal processor (DSP) TMS320LF2407A and a monolithic BLDCM controller MC33035 as the core. Furthermore, a fuzzy PID controller, which combines the advantages of good robustness of fuzzy controller and high precision of conventional PID controller, is employed in the hardware system, thereby yielding a digital, intelligent BLDCM control system. Experimental results have shown that the control system can run steadily and control accurately, and have convincingly demonstrated the usefulness of the proposed fuzzy PID controller in BLDCM control system.

Fuzzy Controller Design for Multi-Legged Robot

2011 ◽  
Vol 383-390 ◽  
pp. 7345-7350
Author(s):  
Zhi Yong Tang ◽  
Hai Xiao Zhong ◽  
Zhong Cai Pei ◽  
Yan Hao Bu
Keyword(s):  
Control System ◽  
Real Time ◽  
Pid Controller ◽  
Fuzzy Controller ◽  
Controller Design ◽  
High Accuracy ◽  
Dynamics Analysis ◽  
Legged Robot ◽  
Fuzzy Pid ◽  
Fuzzy Pid Controller

In this paper, we propose a mechanical structure for multi-legged robot. Referring the request of control system, we also made a proper choice on driving means. After dynamics analysis on a single leg of the robot, we make a simulation using ADAMS and get how the torque of each joint is changing when the robot is walking. The model of DC motor is established for the control system. Fuzzy PID controller was used to get real-time response and high accuracy of control system.

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