An adaptive approach for the fault tolerant control of a nonlinear system
by K. Sudha; V. Thulasi Bai
International Journal of Automation and Control (IJAAC), Vol. 11, No. 2, 2017

Abstract: In this paper hybridisation between two optimisation methods such as modified bacterial foraging optimisation algorithm (MBFOA) and adaptive neuro fuzzy inference system (ANFIS) is presented for determining the optimal proportional-integral (PI) controller parameters, for fault tolerant control (FTC) in an wind energy conversion system (WECS). Initially, detection and diagnosis of fault is performed by the ANFIS. The wind turbine actual output performance and the estimated output values are given as an input to the ANFIS. The residuals, which are the outputs of ANFIS is used for deciding, whether the signal is a fault signal or a non-fault signal, which utilises the knowledge-based computation technique. By using the step size modified bacterial foraging optimisation algorithm-based FTC, the gain parameters are optimised based on the occurrence of fault. Then the proposed hybrid fault tolerant control model is implemented in the MATLAB/SIMULINK platform and the effectiveness is analysed by comparing with the other techniques. The comparison results demonstrate the superiority of the proposed approach and confirm its potential in controlling the fault in a WECS.

Online publication date: Thu, 23-Mar-2017

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