Adaptive fuzzy parameter scheduling scheme for GSA based optimal proportional integral derivative and lag-lead control of a DC attraction type levitation system
by Mrinal Kanti Sarkar; Subrata Banerjee; Sakti Prasad Ghoshal; Tapas Kumar Saha
International Journal of Automation and Control (IJAAC), Vol. 6, No. 2, 2012

Abstract: Magnetic levitation system is inherently unstable and strongly nonlinear in nature. Fixed optimal gain controllers designed at some nominal operating conditions fail to provide the best control performance over a wide range of off-nominal operating conditions. In this paper, an adaptive fuzzy parameter scheduling scheme for Gravitational Search Algorithm (GSA) based optimal Proportional Integral Derivative (PID) and Lag-Lead controllers has been proposed to control a single actuator based DC Attraction type Levitation System (DCALS). A Takagi-Sugeno (T-S) fuzzy inference system is used in the proposed controllers. The inference system is extremely well suited to the task of smoothly interpolating linear gains across the input space when a strongly non-linear DCALS moves around in its operating space. Simulation results show that both proposed adaptive fuzzy PID and Lag-Lead controllers offer better performance than fixed gain controllers at different operating conditions.

Online publication date: Fri, 07-Nov-2014

The full text of this article is only available to individual subscribers or to users at subscribing institutions.

 
Existing subscribers:
Go to Inderscience Online Journals to access the Full Text of this article.

Pay per view:
If you are not a subscriber and you just want to read the full contents of this article, buy online access here.

Complimentary Subscribers, Editors or Members of the Editorial Board of the International Journal of Automation and Control (IJAAC):
Login with your Inderscience username and password:

    Username:        Password:         

Forgotten your password?


Want to subscribe?
A subscription gives you complete access to all articles in the current issue, as well as to all articles in the previous three years (where applicable). See our Orders page to subscribe.

If you still need assistance, please email subs@inderscience.com