Fuzzy-PID Controller for Azimuth Position Control of Deep Space Antenna

In previous work, the performance of PID plus an adaptive neural network compensator (ANNC) was compared with the performance of a novel fuzzy adaptive PID algorithm, as applied to position control of one axis of a pneumatic gantry robot. The fuzzy PID controller was found to be superior. In this paper, a simplified non-adaptive fuzzy algorithm was applied to the control of both axes of the robot. Individual step results are first shown to confirm the validity of the simplified fuzzy PID controller. The fuzzy controller is then applied to a sinuosoidal tracking problem with and without a fuzzy PD tracking algorithm. Initial results are considered to be very promising. Future work requires developing an adaptive version of the controller in order to demonstrate robustness relative to changing tracking frequencies and changing supply pressures.

Download Full-text

Effect of fuzzy PID controller on feedback control systems based on wireless sensor network

International Journal of Electrical and Computer Engineering (IJECE) ◽

10.11591/ijece.v10i3.pp2416-2425 ◽

2020 ◽

Vol 10 (3) ◽

pp. 2416

Author(s):

Anas A. Hussien ◽

Mehdi J Marie ◽

Khalaf S. Gaeid

Keyword(s):

Control System ◽

Wireless Sensor Network ◽

Feedback Control ◽

Sensor Network ◽

Pid Controller ◽

Position Control ◽

Angular Position ◽

Wireless Sensor ◽

Fuzzy Pid ◽

Fuzzy Pid Controller

Wireless Networked control system (WNCS) has an important in all aspects of the life and in the research fields of Engineering. In this article, a real-time implementation of the wireless feedback control system (WFCS) is performed. The stability issue in the closed-loop control system still suffer from noise, disturbances, and need careful considerations to handle it. Three cases to discover the ability of a Fuzzy PID controller to maintain better angular position control system (PCS) is addressed and controlled by a personal computer through a wireless sensor network(WSN) constructed by ZigBee platforms. The practical issues related with the design and implementation of the wireless computerized control system (WCCS) is discussed and analyzed. The simulation results carried out with Matlab/Simulink 2018b. Different parameters effect such as maximum overshoot, sampling frequency, distance and delay time have been studied. These effects on overall system performance would be discussed. Improving the efficient use of ZigBee platform for WFCS. The simulation and experimental results prove the proposed algorithm in the field of wireless control system.

Download Full-text

AN OPTIMIZED PID CONTROLLER FOR DEEP SPACE ANTENNA DC MOTOR POSITION CONTROL USING MODIFIED ARTIFICIAL FISH SWARM ALGORITHM

Yanbu Journal of Engineering and Science ◽

10.53370/001c.24324 ◽

2021 ◽

Author(s):

Jibril Y. ◽

Salawudeen A. T. ◽

Salawu A. ◽

Zainab M.

Keyword(s):

Pid Controller ◽

Position Control ◽

Dc Motor ◽

Deep Space ◽

Space Antenna ◽

Artificial Fish Swarm Algorithm ◽

Artificial Fish Swarm ◽

Swarm Algorithm

Download Full-text

Research on the Application of the Fuzzy Control Algrithm in the HAPC System

Applied Mechanics and Materials ◽

10.4028/www.scientific.net/amm.220-223.157 ◽

2012 ◽

Vol 220-223 ◽

pp. 157-160

Author(s):

Jing Qing Ma ◽

Hai Bo Chen

Keyword(s):

Dynamic Response ◽

Pid Controller ◽

Position Control ◽

Pid Controllers ◽

Control Methods ◽

Fuzzy Pid ◽

Fuzzy Pid Controller ◽

Main Factors ◽

High Control ◽

Control Accuracy

The HAPC(Hydraulic Automatic Position Control) requires quick dynamic response and high control accuracy. Based on the research of the HAPC system, I build the HAPC mathematical model, then design both the Conventional PID controller and fuzzy PID controllers, simulate the two control methods using the MATLAB software, analyze the main factors which influence the results. The simulation results show that the fuzzy PID controller has the better effect in the dynamic response and the control accuracy than the former.

Download Full-text

Angular Position Control of 3-Cars Crane System Using Proposed Fuzzy-PID Controller

Recent Innovations in Mechatronics ◽

10.17667/riim.2020.1/4. ◽

2021 ◽

Vol 7 (1.) ◽

Author(s):

Şahin YILDIRIM

Keyword(s):

Real Time ◽

Simulation Study ◽

Pid Controller ◽

Position Control ◽

Angular Position ◽

The Other ◽

Fuzzy Pid ◽

Control Approach ◽

Fuzzy Pid Controller ◽

Simulation Results

This paper presents a novel control approach for 3 cars crane systems. Nowadays; some problems for carrying unpredicted loads of crane systems exist. On the other hand; long bar loads are very important to carry without touch on other materials in factories. In this simulation study, fuzzy based controllers were designed to control vibrations of 3 cars crane system. The simulation results are improved and show this kind of controllers will be employed in real time such systems.

Download Full-text

Development of Servo Drive Positioning Control System Using PID Controller and Fuzzy Logic Controller

Proceedings of Universities ELECTRONICS ◽

10.24151/1561-5405-2021-26-6-583-588 ◽

2021 ◽

Vol 26 (6) ◽

pp. 583-588

Author(s):

Zaw Myo Naing ◽

Keyword(s):

Fuzzy Logic ◽

Control System ◽

Pid Controller ◽

Fuzzy Logic Controller ◽

Position Control ◽

Settling Time ◽

Fuzzy Pid ◽

Servo Drive ◽

Positioning Control ◽

Fuzzy Pid Controller

Servo drives are one of the most widely utilized devices in various mechanical systems and industrial applications to provide precise position control. The study of servo driver produc-tiveness and performance index is the important task. In this work, PID controller and fuzzy log-ic controller (FLC) were developed to control the position of a DC servo drive. The MATLAB Simulink program was investigated and implemented to calculate the values of servo drive pa-rameters, and a scheme for simulating the operation of a servo drive using different controllers was presented. A mathematical model of a DC servo drive for a positioning control system has been proposed. The control characteristics of the PID controller, fuzzy logic controller and fuzzy PID controller are compared. The simulation results have shown that the PID controller allows for an overshoot of about 1 % with a settling time of about 4 sec. The use of the fuzzy PID con-troller reduces the maximum overshoot to 1 % and decreases the settling time to 2 sec. As a re-sult, the fuzzy PID controller allows for better performance and efficiency compared to other controllers.

Download Full-text