Identification and Control of Nonlinear Systems using Soft Computing Techniques - Volume 1 Number 1 (Apr. 2011) - ijmo
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General Information
Prof. Adrian Olaru
University Politehnica of Bucharest, Romania
I'm happy to take on the position of editor in chief of IJMO. It's a journal that shows promise of becoming a recognized journal in the area of modelling and optimization. I'll work together with the editors to help it progress.
IJMO 2011 Vol.1(1): 24-28 ISSN: 2010-3697
DOI: 10.7763/IJMO.2011.V1.5

Identification and Control of Nonlinear Systems using Soft Computing Techniques

Wahida Banu.R. S. D, Shakila Banu. A. Manoj. D

Abstract—The inverted pendulum is a highly nonlinear and open-loop unstable system. This means that standard linear techniques cannot model the nonlinear dynamics of the system, Inverted pendulum system is often used as a benchmark for verifying the performance and effectiveness of a new control method because of the simplicities of the structure. In this paper an accurate model of the inverted pendulum system, a neural network controller and ANFIS (Adaptive Neuro-Fuzzy Inference System) controller to stabilize the system have been developed. A control law that removes some of the nonlinearities from the process and allows the process to exhibit its dynamics has been developed. This aids in stabilizing the nonlinear pendulum. The quality of the data input has also been improved, since only limited number of variables that can be measured accurately are included in the system identification Simulation results establishes that the proposed controller has good set point tracking and disturbance rejection properties.

Index Terms—Inverted Pendulum, Neural Network, ANFIS, Nonlinear system control.

Dr. R. S. D. Wahida Banu, Government Engineering College, Salem, Tamilnadu, India (email:
A. Shakila Banu, SethuInstitute of technology, Kariapatti, Tamilnadu, India (email:
D. Manoj, Sethu Institute of Technology, Kariapatti, Tamilnadu, India (email:


Cite: Wahida Banu. R. S. D, Shakila Banu. A. Manoj. D, "Identification and Control of Nonlinear Systems using Soft Computing Techniques," International Journal of Modeling and Optimization vol. 1, no. 1, pp. 24-28, 2011.

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