ANFIS modelling of a twin rotor system using particle swarm optimisation and RLS

Toha, Siti Fauziah and Tokhi, M. O. (2010) ANFIS modelling of a twin rotor system using particle swarm optimisation and RLS. In: 2010 IEEE 9th International Conference on Cybernetic Intelligent Systems (CIS), 1 - 2 September 2010 , University of Reading Reading, U.K..

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Abstract

Artificial intelligence techniques, such as neural networks and fuzzy logic have shown promising results for modelling of nonlinear systems whilst traditional approaches are rather insufficient due to difficulty in modelling of highly nonlinear components in the system. A laboratory set-up that resembles the behaviour of a helicopter, namely twin rotor multiinput multi-output system (TRMS) is used as an experimental rig in this research. An adaptive neuro-fuzzy inference system (ANFIS) tuned by particle swarm optimization (PSO) algorithm is developed in search for non-parametric model for the TRMS. The antecedent parameters of the ANFIS are optimized by a PSO algorithm and the consequent parameters are updated using recursive least squares (RLS). The results show that the proposed technique has better convergence and better performance in modeling of a nonlinear process. The identified model is justified and validated in both time domain and frequency domain

Item Type:	Conference or Workshop Item (Full Paper)
Additional Information:	4680/7120
Uncontrolled Keywords:	Twin rotor system, adaptive neuro-fuzzy inference system , particle swarm optimisation, recursive least squares
Subjects:	T Technology > TA Engineering (General). Civil engineering (General)
Kulliyyahs/Centres/Divisions/Institutes (Can select more than one option. Press CONTROL button):	Kulliyyah of Engineering Kulliyyah of Engineering > Department of Mechatronics Engineering
Depositing User:	Dr. Siti Fauziah Toha
Date Deposited:	11 Jun 2012 10:12
Last Modified:	09 Oct 2012 08:59
URI:	http://irep.iium.edu.my/id/eprint/7120

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