PD-Fuzzy Logic Controller Design for Position Control of Intelligent Pneumatic Actuator System

The purpose of this paper is to design a controller that can control the position of the cylinder pneumatic stroke. This work proposes two control approaches, Proportional-Integral-Derivative Fuzzy Logic (Fuzzy-PID) controller and Proportional-Derivative Fuzzy Logic (PD-Fuzzy) controller for a Servo-Pneumatic Actuator. The design steps of each controller implemented on MATLAB/Simulink are presented. A model based on position system identification is used for the controller design. Then, the simulation results are analyzed and compared to illustrate the performance of the proposed controllers. Finally, the controllers are tested with the real plant in real-time experiment to validate the results obtained by simulation. Results show that PD-Fuzzy controller offer better control compared to Fuzzy-PID. A Pneumatic Actuated Ball & Beam System (PABBS) is proposed as the application of the position controller. The mathematical model of the system is developed and tested simulation using Feedback controller (outer loop)-PD-Fuzzy controller (inner loop). Simulation result is presented to see the effectiveness of the obtained model and controller. Results show that the servo-pneumatic actuator can control the position of the Ball & Beam system using PD-Fuzzy controller.

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PID and Fuzzy Logic Controller Design for Balancing Robot Stabilization

Iraqi Journal of Computer Communication Control and System Engineering ◽

10.33103/uot.ijccce.18.1.1 ◽

2018 ◽

pp. 1-10

Keyword(s):

Fuzzy Logic ◽

Tilt Angle ◽

Pid Controller ◽

Fuzzy Logic Controller ◽

Position Control ◽

Controller Design ◽

Point Of View ◽

Relative Advantage ◽

Balancing Robot ◽

Time Required

This paper addresses the problem of position control and stabilization for the two wheeled balancing robot. A mathematical model is derived based on the robot’s position and tilt angle and a fuzzy logic control is proposed for the balancing robot control. The fuzzy logic controller performance is compared with a conventional PID controller to show the difference between them. Both controllers were tested on the balancing robot in simulation using MATLAB software and the results were put together for a comparative point of view. The simulations shows a relative advantage for the fuzzy logic controller over the conventional PID controller especially in reducing the time required for stabilization which takes about 2 seconds and almost without overshoot while in the PID case the robot will have about 10% overshoot in position and about 20 degrees in tilt angle.

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Position Tracking of Pneumatic Actuator with Loads by Using Predictive and Fuzzy Logic Controller

Advanced Materials Research ◽

10.4028/www.scientific.net/amr.903.259 ◽

2014 ◽

Vol 903 ◽

pp. 259-266

Author(s):

Ahmad Athif Mohd Faudzi ◽

Nu’man din Mustafa ◽

M. Asyraf Azman ◽

Khairuddin Osman

Keyword(s):

Fuzzy Logic ◽

External Load ◽

Fuzzy Logic Controller ◽

Position Control ◽

Fast Response ◽

High Accuracy ◽

Pneumatic Actuator ◽

Position Tracking ◽

Predictive Controller ◽

Simulation Results

This paper presented two control approaches for position control of a pneumatic actuator, which are Generalized Predictive Controller (GPC) and Proportional-Derivative Fuzzy Logic Controller (PD-Fuzzy). Both controllers are designed using MATLAB/Simulink platform. The simulation results are then validated with real-time experiment. In order to test the controller's performance, external load is used and the results for both controllers are compared and analyzed. Results for both controllers show high accuracy and fast response for position tracking.

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Fuzzy logic controller design for PUMA 560 robot manipulator

IAES International Journal of Robotics and Automation (IJRA) ◽

10.11591/ijra.v9i2.pp73-83 ◽

2020 ◽

Vol 9 (2) ◽

pp. 73

Author(s):

Abdel-Azim S. Abdel-Salam ◽

Ibrahim N. Jleta

Keyword(s):

Fuzzy Logic ◽

Fuzzy Logic Controller ◽

Position Control ◽

Controller Design ◽

Robot Manipulator ◽

Tracking Error ◽

Pid Controllers ◽

Fuzzy Logic Controllers ◽

Better Than ◽

Computed Torque

The dynamic model of the robot manipulator contain from equations, these equations are nonlinear and contained from variations parameters due to variations in load, friction, and disturbance. The conventional computed torque (PD and PID) controllers are not highly suitable for nonlinear, complex, time-variant systems with delay. In this paper, the fuzzy logic controllers (FLC) has been used because it is efficient tools for control of nonlinear and uncertain parameters systems. This paper aims to design a fuzzy logic controller for position control of a PUMA 560 robot manipulator. Based on simulation results we conclude that the performance of the fuzzy logic controller in term of position tracking error in case of disturbance or load is better than the conventional computed torque (PD-CTC and PID-CTC) controllers.

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Position Control of a Pneumatic Servo System Using Sliding Mode Control and Fuzzy Control: A Comparison

Volume 10: Mechanical Systems and Control, Parts A and B ◽

10.1115/imece2009-10747 ◽

2009 ◽

Author(s):

S. S. Dhami ◽

S. S. Bhasin ◽

P. B. Mahapatra

Keyword(s):

Fuzzy Logic ◽

Sliding Mode Control ◽

Fuzzy Logic Controller ◽

Position Control ◽

Sliding Mode ◽

Pneumatic Actuator ◽

Sliding Mode Controller ◽

Virtual Model ◽

Mode Control ◽

Actuation System

The performance comparison of fuzzy logic control and sliding mode control for position control of a pneumatic actuator for different operative conditions is presented in this article. A virtual model of a pneumatic actuation system is developed using comprehensive mathematical model of the system. A fuzzy logic controller and a sliding mode controller are developed for positioning the piston at different linear displacements for different loading conditions. The virtual model is employed for obtaining the transient and steady state positional response of the pneumatic actuator by implementing the two controllers one by one. The results show that fuzzy controller results in better piston positional response for combinations of lower payloads and smaller linear displacements, whereas sliding mode controller is more effective for combinations of higher payloads and larger displacements.

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