Self-Organising Fuzzy Logic Control with a New On-Line Particle Swarm Optimisation-based Supervisory Layer

M. Ehtiawesh, M. Mahfouf

2014

Abstract

The Self-Organising Fuzzy Logic Control (SOFLC) which is an extended version of the Fuzzy logic controller was designed to make Fuzzy controllers work with less dependency on previous knowledge. Since the introduction of the SOFLC, only a few attempts have been made to create a performance index table that is responsible for the corrections of the low-level control ‘adaptable’ according to the dynamics of the process under control. In this paper a new dynamic supervisory layer is proposed which enables the controller to adapt its structure on-line to any given certain performance criteria. In this mechanism, the controller starts from an empty rule-base and uses an on-line Particle Swarm Optimisation (PSO) algorithm to adapt the cells of the performance index (PI) table while issuing control actions to the low-level fuzzy rule-base. The Simulation results achieved when the proposed scheme was tested on a non-linear muscle relation process showed that it is superior to the standard SOFLC scheme in terms of accurate tracking and efficient fuzzy rule-base elicitation (a conservative number of fuzzy rules)

References

  1. Linkens, D. A. and Nyongesa, H. O. (1995), Genetic algorithms for fuzzy control part 2: online system development and application. IEE Proceedings: Control Theory and Applications, 142, 177-185.
  2. Lu, Q. and Mahfouf, M. (2005), A new efficient selforganising fuzzy logic control (SOFLC) algorithm using a dynamic performance index table. 16th IFAC World Congress, Prague, Czech Republic, pp. 40-45.
  3. Mahfouf, M. and Linkens, D. A. (1998), Generalised. Predictive Control and Bioengineering, London:Taylor and Francis.
  4. Mahfouf, M., King, O., Denai, M., Ross, J. J. and LU, Q. (2011), A hierarchical self-organising fuzzy logicbased on-line advisor for the management of cardiac septic patients. 18th IFAC World Congress, Milano, Italy, pp.575-580.
  5. OI, A., Nakazawa, C., Matsui, T., Fujiwara, H., Matsumoto, K. and Nishida, H. (2008), PID optimal tuning method by Particle Swarm Optimisation. SICE Annual Conference, 3470-3473.
  6. Procyk, T. J and Mamdani. E. H. (1979), A linguistic self-organising process controller, Automatica, 15(1), pp 15-3.
  7. Zadeh, L.A.(1965), Fuzzy sets. Information and Control, 1965. 8(3): pp. 338-353.
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Paper Citation


in Harvard Style

Ehtiawesh M. and Mahfouf M. (2014). Self-Organising Fuzzy Logic Control with a New On-Line Particle Swarm Optimisation-based Supervisory Layer . In Proceedings of the International Conference on Fuzzy Computation Theory and Applications - Volume 1: FCTA, (IJCCI 2014) ISBN 978-989-758-053-6, pages 95-102. DOI: 10.5220/0005033200950102


in Bibtex Style

@conference{fcta14,
author={M. Ehtiawesh and M. Mahfouf},
title={Self-Organising Fuzzy Logic Control with a New On-Line Particle Swarm Optimisation-based Supervisory Layer},
booktitle={Proceedings of the International Conference on Fuzzy Computation Theory and Applications - Volume 1: FCTA, (IJCCI 2014)},
year={2014},
pages={95-102},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005033200950102},
isbn={978-989-758-053-6},
}


in EndNote Style

TY - CONF
JO - Proceedings of the International Conference on Fuzzy Computation Theory and Applications - Volume 1: FCTA, (IJCCI 2014)
TI - Self-Organising Fuzzy Logic Control with a New On-Line Particle Swarm Optimisation-based Supervisory Layer
SN - 978-989-758-053-6
AU - Ehtiawesh M.
AU - Mahfouf M.
PY - 2014
SP - 95
EP - 102
DO - 10.5220/0005033200950102