A self-tuning fuzzy PID-type controller design for unbalance compensation in an active magnetic bearing

Chen, Kuan‐Yu; Tung, Pi Cheng; Tsai, Mong-Tao; Fan, Yi-Hua

doi:10.1016/j.eswa.2008.10.055

Cited by 86 publications

(47 citation statements)

References 16 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…The first conventional proportional-integral-derivative controllers are used in many industrial applications due to its design simplicity, ease of operation and robust performance characteristics [32]. While, second Fuzzy logic based technique is governed by implementing operator's experience and knowledge about the system in controller.…”

Section: Different Control Algorithmsmentioning

confidence: 99%

Passenger seat vibration control of a semi-active quarter car system with hybrid Fuzzy–PID approach

Singh

Aggarwal

2015

Int. J. Dynam. Control

View full text Add to dashboard Cite

In this paper, semi-active quarter car system with three degrees of freedom is considered for modeling and evaluation of passenger ride comfort. Experimental results of magneto-rheological shock absorber are modeled using polynomial model. The considered algorithms in semi-active quarter car suspension system include PID controller, fuzzy logic controller, hybrid fuzzy-PID controller and hybrid fuzzy-PID controller with coupled rules. Simulation responses of the controlled semi-active and uncontrolled quarter car systems are compared under bump type of road excitation in time domain. Simulation results demonstrate that the semi-active suspension system having hybrid fuzzy-PID controller with coupled rules provide best performance in controlling the passenger seat acceleration and displacement response compared to uncontrolled and other controlled cases.

show abstract

Section: Different Control Algorithmsmentioning

confidence: 99%

Passenger seat vibration control of a semi-active quarter car system with hybrid Fuzzy–PID approach

Singh

Aggarwal

2015

Int. J. Dynam. Control

View full text Add to dashboard Cite

show abstract

“…But the fuzzy is a nonlinear control and the output of the controller has the static error (Guo, Zhou, & Cui, 2004). Then fuzzy PID control which combines the traditional PID control and the fuzzy control algorithm may become a solution (Chen, Tung, Tsai, & Fan, 2009;Huang & Shi, 2006;Soyguder, Karakose, & Alli, 2009;Vagelatos, Rigatos, & Tzafestas, 2001). However, the design of fuzzy rules depends largely on the experience of experts or input-output data (Truong, Ahn, Kim, & Yoon, 2007).…”

Section: Introductionmentioning

confidence: 98%

Force control for press machines using an online smart tuning fuzzy PID based on a robust extended Kalman filter

Truong

Ahn

2011

Expert Systems with Applications

View full text Add to dashboard Cite

“…the parameters tuning is more difficult especially when wind force which changes rapidly and randomly is the the load of magnetic bearing Many experts and engineers have been dedicated to the research of selfadjusting parameters. They combined fuzzy-control of intelligent control with traditional PID control and called it fuzzy-PID control [9]. In order to get better dynamic and static performance indicators of the system, this paper introduces the thought of variable universe [10] and suggests gives a brand-new PID control method variable universe fuzzy-PID control.…”

Section: Introductionmentioning

confidence: 99%

Variable Universe Fuzzy PID Control Strategy of Permanent Magnet Biased Axial Magnetic Bearing Used in Magnetic Suspension Wind Power Generator

Zhang

Mei

Yuan

2012

Intelligent Robotics and Applications

View full text Add to dashboard Cite

Abstract. Improvements of wind power generator in energy utilization rate, electric generation efficiency and reliability can be achieved when maglev technology is applied. This paper presents a maglev horizontal axis wind power generator with two radial permanent magnet bearings and one permanent magnet biased axial magnetic bearing. The structure and working principle of the maglev wind power generator and axial magnetic bearing are presented. The finite element simulations of electromagnetic field in the axial magnetic bearing are performed by ANSYS, and the current stiffness and displacement stiffness are obtained. In order to fit the rapidity and randomness of wind load, the axial displacement of the rotor is controlled based on the variable universe fuzzy PID control strategy. The simulation of the control system is performed in MATLAB.

show abstract

A self-tuning fuzzy PID-type controller design for unbalance compensation in an active magnetic bearing

Cited by 86 publications

References 16 publications

Passenger seat vibration control of a semi-active quarter car system with hybrid Fuzzy–PID approach

Passenger seat vibration control of a semi-active quarter car system with hybrid Fuzzy–PID approach

Force control for press machines using an online smart tuning fuzzy PID based on a robust extended Kalman filter

Variable Universe Fuzzy PID Control Strategy of Permanent Magnet Biased Axial Magnetic Bearing Used in Magnetic Suspension Wind Power Generator

Contact Info

Product

Resources

About