An interval type-2 Fuzzy PD controller for ball and beam system

Farooq, Umar; Asad, Muhammad Usman

doi:10.1109/ic4.2013.6653749

Cited by 3 publications

(1 citation statement)

References 9 publications

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“…Some of the combinations recently found from literatures are fuzzy PI+PD, fuzzy PI+D and fuzzy PD+I. Sometimes, not every PID gain needs to be fuzzified [18] [19]. Based on their findings, in some cases, these structures were better than the conventional PID.…”

Section: Literature Reviewsmentioning

confidence: 97%

Design and Evaluation of Self-Tuning Fuzzy PID Controller with Reference Model for Ball and Beam Mechanism

Tajjudin¹,

Pezol²,

Rahiman³

2022

IJETAE

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—Fuzzy Logic controller is one of the popular techniques in control system. However, the accuracy depends on numbers and the design of membership functions. Further, the output does not always fulfill specific design requirements. In this study, Fuzzy PID controller with first-order reference model had been designed and evaluated. The proposed new structure is able to guide fuzzy mechanism to produce desired output response as specified by the first-order model such as the time constant, rise time and settling time. The study was implemented on a ball and beam system to control the position of the ball while rolling on a beam. The control of a ball and beam system is challenging because it is an open-loop unstable system as the ball will continuously moves on the beam without control. The study also compares the results acquired from Fuzzy PID and Fuzzy PI plus PD against the proposed Fuzzy PID with first-order reference model controller. The evaluation covers for a pole starting from 0 until 1.0 for the first-order model. As a results, the proposed controller is able to produce an output response as specified where the fastest response was acquired when pole is set to 0.9. Whereas the Fuzzy PID and Fuzzy PI plus PD always produce the same transient response during step input test.

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Section: Literature Reviewsmentioning

confidence: 97%

Design and Evaluation of Self-Tuning Fuzzy PID Controller with Reference Model for Ball and Beam Mechanism

Tajjudin¹,

Pezol²,

Rahiman³

2022

IJETAE

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A review on interval type-2 fuzzy logic applications in intelligent control

Castillo

Melín

2014

Information Sciences

255

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Soft-Computing Control of Ball and Beam System

Kharola

Patil

2018

International Journal of Applied Evolutionary Computation

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This article derives a mathematical model and compares different soft-computing techniques for control of a highly dynamic ball and beam system. The techniques which were incorporated for control of proposed system were fuzzy logic, proportional-integral-derivative (PID), adaptive neuro fuzzy inference system (ANFIS) and neural networks. Initially, a fuzzy controller has been developed using seven gaussian shape membership functions. The article illustrates briefly both learning ability and parameter estimation properties of ANFIS and neural controllers. The results of PID controller were collected and used for training of ANFIS and Neural controllers. A Matlab simulink model of a ball and beam system has been derived for simulating and comparing different controllers. The performances of controllers were measured and compared in terms of settling time and steady state error. Simulation results proved the superiority of ANFIS over other control techniques.

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An interval type-2 Fuzzy PD controller for ball and beam system

Cited by 3 publications

References 9 publications

Design and Evaluation of Self-Tuning Fuzzy PID Controller with Reference Model for Ball and Beam Mechanism

Design and Evaluation of Self-Tuning Fuzzy PID Controller with Reference Model for Ball and Beam Mechanism

A review on interval type-2 fuzzy logic applications in intelligent control

Soft-Computing Control of Ball and Beam System

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