Adaptive Neuro-Fuzzy Model with Fuzzy Clustering for Nonlinear Prediction and Control
Keywords:ANFIS, Fuzzy Clustering, Air-fuel ratio
Nonlinear systems have more complex manner and profoundness than linear systems. Thus, their analyses are much more difficult. This paper presents the use of neuro-fuzzy networks as means of implementing algorithms suitable for nonlinear black-box prediction and control. In engineering applications, two attractive tools have emerged recently. These two attractive tools are: the artificial neural networks and the fuzzy logic system. One area of particular importance is the design of networks capable of modeling and predicting the behavior of systems that involve complex, multi-variable processes. To illustrate the applicability of the neuro-fuzzy networks, a case study involving air-fuel ratio is presented here. Air-fuel ratio represents complex, nonlinear and stochastic behavior. To monitor the engine conditions, an adaptive neuro-fuzzy inference system (ANFIS) is used to capture the nonlinear connections between the air-fuel ratio and control parameters such manifold air pressure, throttle position, manifold air temperature, engine temperature, engine speed, and injection opening time. This paper describes a fuzzy clustering method to initialize the ANFIS.
A. R. Sadeghian, â€œNonlinear Neuro-Fuzzy Prediction: Methodology, Design and Applicationsâ€, 2001.
C.J. Harris, M. Brown, K.M. Bossley, D.J. Mills, F. Ming,â€Advances in Neurofuzzy Algorithms for Real-time Modelling
and Controlâ€, Engineering Applications of Artificial Intelligence, Vol. 9, Issue 1, pp. 1-16, February 1996.
E. Gorrostiet, J.C. Pedraza, R.J. Carlos,â€Fuzzy Modelling of Systemsâ€, Proceedings of 11 th IEEE International
Conference on Methods and Models in Automation and Robotics MMAR 2005, 29 August- 1 September 2005,
Miedzyzdroje, Poland. ISBN 83-60140-85-5.
H. O. Wang, K. Tanaka, and M. F. Griffin, â€œAn approach to fuzzy control of nonlinear systems: stability and design
issuesâ€, IEEE Trans. on Fuzzy Systems, vol. 4, no. 1, pp. 14-23, Feburary 1996.
J.C. Bezdek, Pattern Recognition With Fuzzy Objective Function Algorithms, Plenum Press, New York, 1981.
J. Jang, â€œANFIS: Adaptive network-based fuzzy inference systemsâ€, IEEE Transactions on Systems, Man, and
Cybernetics 23, pp.665-685, 1993.
J. Lauber, T. M. Guerra, M. Dambrine,â€ Air-fuel ratio control in a gasoline engineâ€. International Journal of Systems
Science, Vol. 42, No. 2, pp. 277-286, 2011.
K.P. Mohanadas and S. Karimulla,â€œFuzzy and neuro-fuzzy modelling and control of nonlinear systemsâ€.
L.A. Zadeh, â€œFuzzy setsâ€, Information Control 8 pp.338â€“353, 1965.
L. Hong-Xing, C. L. Phillip Chen, â€œThe equivalence Between Fuzzy Logic and Feedforward Neural Networksâ€, IEEE
Trans. On Neural Networks, vol. 11, no. 2, March 2000.
M.S. Yang, C.H. Ko, â€œOn a class of fuzzy c-numbers clustering procedures for fuzzy dataâ€, Fuzzy Sets and Systems 84,
Robert fuller, Introduction to Neuro-Fuzzy Systems, springer, 2000.
How to Cite
- Papers must be submitted on the understanding that they have not been published elsewhere (except in the form of an abstract or as part of a published lecture, review, or thesis) and are not currently under consideration by another journal published by any other publisher.
- It is also the authors responsibility to ensure that the articles emanating from a particular source are submitted with the necessary approval.
- The authors warrant that the paper is original and that he/she is the author of the paper, except for material that is clearly identified as to its original source, with permission notices from the copyright owners where required.
- The authors ensure that all the references carefully and they are accurate in the text as well as in the list of references (and vice versa).
- Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under a Attribution-NonCommercial 4.0 International that allows others to share the work with an acknowledgement of the work's authorship and initial publication in this journal.
- Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgement of its initial publication in this journal.
- Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work (See The Effect of Open Access).
- The journal/publisher is not responsible for subsequent uses of the work. It is the author's responsibility to bring an infringement action if so desired by the author.