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Authors: José Vieira 1 and Alexandre Mota 2

Affiliations: 1 Escola Superior de Tecnologia de Castelo Branco, Portugal ; 2 Universidade de Aveiro, Portugal

ISBN: 972-8865-12-0

Keyword(s): Adaptive control, Smith predictive control, Hammerstein models, neuro-fuzzy modelling, on-line identification, recursive least square and covariance matrix.

Related Ontology Subjects/Areas/Topics: Adaptive Signal Processing and Control ; Hybrid Dynamical Systems ; Informatics in Control, Automation and Robotics ; Nonlinear Signals and Systems ; Signal Processing, Sensors, Systems Modeling and Control ; System Identification

Abstract: This paper proposes an Adaptive Smith Predictor Controller (ASPC) based on Neuro-Fuzzy Hammerstein Models (NFHM) with on-line non-linear model parameters identification. The NFHM approach uses a zeroorder Takagi-Sugeno fuzzy model to approximate the non-linear static function that is tuned off-line using gradient decent algorithm and to identify the linear dynamic function it is used the Recursive Least Square estimation with Covariance Matrix Reset (RLSCMR). This algorithm has the capability of follow fast and slow dynamic parameter changes. The proposed ASPC has special capabilities to control non-linear systems that have gain, time delay and dynamic changes through time. The implementation of the ASPC is made in two steps: first, off-line estimation of the non-linear static parameters that will be used to “get linear” the non-linearity of the system and second, on-line identification of the linear dynamic parameters updating direct and inverse models used in the ASPC. As an illustr ative example, a gas water heater system is controlled with the ASPC. Finally, the control results are compared with the results obtained with the Smith Predictive Controller based in a Semi-Physical Model (SPMSPC). (More)

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Paper citation in several formats:
Vieira J.; Mota A. and (2004). ADAPTIVE SMITH PREDICTIVE CONTROL OF NON-LINEAR SYSTEMS USING NEURO-FUZZY HAMMERSTEIN MODELS.In Proceedings of the First International Conference on Informatics in Control, Automation and Robotics - Volume 3: ICINCO, ISBN 972-8865-12-0, pages 62-69. DOI: 10.5220/0001131900620069

@conference{icinco04,
author={José Vieira and Alexandre Mota},
title={ADAPTIVE SMITH PREDICTIVE CONTROL OF NON-LINEAR SYSTEMS USING NEURO-FUZZY HAMMERSTEIN MODELS},
booktitle={Proceedings of the First International Conference on Informatics in Control, Automation and Robotics - Volume 3: ICINCO,},
year={2004},
pages={62-69},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0001131900620069},
isbn={972-8865-12-0},
}

TY - CONF

JO - Proceedings of the First International Conference on Informatics in Control, Automation and Robotics - Volume 3: ICINCO,
TI - ADAPTIVE SMITH PREDICTIVE CONTROL OF NON-LINEAR SYSTEMS USING NEURO-FUZZY HAMMERSTEIN MODELS
SN - 972-8865-12-0
AU - Vieira, J.
AU - Mota, A.
PY - 2004
SP - 62
EP - 69
DO - 10.5220/0001131900620069

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