International Journal of Advanced and Applied Sciences

Int. j. adv. appl. sci.

EISSN: 2313-3724

Print ISSN: 2313-626X

Volume 4, Issue 8  (August 2017), Pages:  139-148

Title: Improving the performance indices of a dynamic system using adaptive learning controllers

Author(s):  Srinibash Swain 1, *, Partha Sarathi Khuntia 2


1Faculty of Electrical Engineering, Bijupattnaik University of Technology, Bhubaneswar, India
2Faculty of Electronics and Telecommunications Engineering, Bijupattnaik University of Technology, Bhubaneswar, India

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In this paper, the angle of attack of an aircraft is controlled by using soft computing techniques like Genetic Algorithm (GA), Fuzzy Model Reference Learning Controller (FMRLC) and Radial Basis Function Neural Controller (RBFNC) and the performance indices like Mean Square Error (MSE), Integral Square Error (ISE), and Integral Absolute Time Error (IATE) etc. of the dynamic system is improved. The result is compared with the conventional techniques like Tyreus-Luyben (TL), Ziegler-Nichols (ZN) and Interpolation Rule (IR) for tuning the PID controller. It was established that the errors by using soft computing techniques are very less as compared to the conventional techniques thereby improving the performance indices of the dynamic system. 

© 2017 The Authors. Published by IASE.

This is an open access article under the CC BY-NC-ND license (

Keywords: Angle of attack performance indices, Adaptive controller, Learning controller, Radial basis function

Article History: Received 13 February 2017, Received in revised form 12 July 2017, Accepted 17 July 2017

Digital Object Identifier:


Swain S and Khuntia PS (2017). Improving the performance indices of a dynamic system using adaptive learning controllers. International Journal of Advanced and Applied Sciences, 4(8): 139-148


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