Browsing by Author "Habbi, Hacene"

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Now showing 1 - 15 of 15
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    A cooperative learning artificial bee colony algorithm with multiple search mechanisms
    (IOS Press, 2016) Harfouchi, Fatima; Habbi, Hacene
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    A cooperative learning strategy with multiple search mechanisms for improved artificial bee colony optimization
    (IEEE, 2015) Harfouchi, Fatima; Habbi, Hacene
    Artificial bee colony (ABC) optimization is a swarm based stochastic search strategy inspired by the foraging behavior of honeybees. Due to its simplicity and promising optimization capability, the ABC concept has devoted special interest with an increasing number of applications to scientific and engineering optimization problems. As an open research field, many researchers attempted to improve the performance of ABC algorithm through new algorithmic frameworks or by introducing modifications on the basic model. This paper presents an improved version of ABC algorithm based on a cooperative learning strategy with modified search mechanisms incorporated at both employed and onlooker levels. The proposed approach referred to as CLABC (Cooperative learning ABC) is tested on benchmark functions for numerical optimization. The results demonstrate the good performance and convergence of the proposed algorithm over other existing ABC variants
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    Data-driven fuzzy models for nonlinear identification of a complex heat exchanger
    (Elsevier, 2011) Habbi, Hacene; Kidouche, Madjid; Zelmat, Mimoun
    This paper presents and discusses experimental results on nonlinear model identification method applied to a real pilot thermal plant. The aim of this work is to develop a moderately complex model with interpretable structure for a complex parallel flow heat exchanger which is the main component of the thermal plant using a fuzzy clustering technique. The proposed Takagi–Sugeno-type (TS) fuzzy rule-based model is derived through an iterative fuzzy clustering algorithm using a set of input–output measurements. It is shown that the identified multivariable fuzzy rule-based model captures well the key dynamical properties of the physical plant over a wide operating range and under varying operating conditions. For validation, the model is run in parallel and series-parallel configurations to the real process. The experimental results show clearly the high performance of the proposed fuzzy model in achieving good prediction of the main process variables
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    Experimental investigation of evolving cloud-based fuzzy control of a pilot thermal exchanger under a decentralized framework
    (Elsevier, 2023) Lamraoui, Oualid; Habbi, Hacene
    Relying on the Robust Evolving Cloud-based Control (RECCo) protocol, a decentralized evolving fuzzy control scheme is presented in this paper for a strongly interacting thermal exchanger process and for the first time experimentally investigated on the real pilot plant. Loop pairing information is first derived based on experimental analysis of the process dynamics. Accordingly, independent RECCo-controlled loops of system temperature are arranged in functional blocks without any prior decoupling or process modelling. The evolvable fuzzy controller structure is learned concurrently relying on data streams only. Simulation and experiments are carried out to support the design procedure and verify the control performance. The results show reasonable tracking performance under different scenarios.
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    Finite-horizon optimal LQ control design using artificial bee colony programming
    (Institute of Electrical and Electronics Engineers, 2025) Boudouaoui, Yassine; Habbi, Hacene; Maidi, Ahmed; Belharet, Karim
    Designing optimal control laws in closed analytical form is still showing challenging computational issues. This may even hold for moderately complex problems like the linear quadratic (LQ) control problem with finite horizon. This paper introduces a novel approach to LQ controller design based on artificial bee colony programming (ABCP). Solution to the matrix Riccati differential equation (MRDE) derived for the optimal control problem subject to linear dynamical system model is determined by means of ABCP method. Aiming at this, preparatory steps have been set and analyzed as essential part of the ABCP-based MRDE solver. The effectiveness of the proposed solver is investigated on a typical LQ control problem and compared to existing methods in literature. Evidence of superiority is shown through numerical evaluation of the method convergence and solution accuracy
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    Fuzzy distributed control of the forced Burgers-Fisher equation under periodic boundary conditions
    (IEEE, 2020) Raab, Sadia; Habbi, Hacene; Maidi, Ahmed; Belharet, Karim
    This paper presents a novel control design methodology for a class of distributed parameter systems (DPSs) described by the nonlinear Burgers-Fisher equation model. The proposed approach is built upon a fuzzy Burgers-Fisher equation model of T-S type which is derived to approximate the nonlinear DPS dynamics over the spatio-temporal dimension. Relying on the geometric control theory, a complete control design procedure is developed based on the constructed fuzzy Burgers-Fisher equation model with distributed control. The resulting fuzzy distributed controller is infinite dimensional showing good stabilizing effect and performs considerably well within the specified operating conditions
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    Fuzzy model-based fault detection and diagnosis for a pilot heat exchanger
    (Taylor & Francis, 2011) Zelmat, Mimoun; Kinnaert, Michel; Habbi, Hacene
    This article addresses the design and real-time implementation of a fuzzy model-based fault detection and diagnosis (FDD) system for a pilot co-current heat exchanger. The design method is based on a three-step procedure which involves the identification of data-driven fuzzy rule-based models, the design of a fuzzy residual generator and the evaluation of the residuals for fault diagnosis using statistical tests. The fuzzy FDD mechanism has been implemented and validated on the real co-current heat exchanger, and has been proven to be efficient in detecting and isolating process, sensor and actuator faults
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    H-infinity fuzzy emulator design for multivariable control of drum boiler-turbine unit
    (Institute of Electrical and Electronics Engineers, 2015) Lamraoui, Oualid; Habbi, Hacene
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    Identification et surveillance de processus dynamiques complexes par logique floue. Application à un échangeur de chaleur
    (2007) Habbi, Hacene
    L’objectif visé dans cette thèse est de présenter et valider une approche d’identification et de surveillance pour les processus dynamiques complexes en se basant sur la logique floue. Par souci d’applications industrielles, l’accent a été exclusivement mis sur des systèmes non linéaires. Les systèmes non linéaires étant beaucoup plus difficiles à analyser que les systèmes linéaires, leur identification et surveillance sont loin d’être aussi développées et complètes. En général, les fonctions de surveillance sont étroitement liées aux méthodes d’identification qui permettent d’obtenir le modèle de référence et la conception des algorithmes de surveillance. De ce fait, le modèle identifié doit être suffisamment représentatif et moins conservatif pour permettre la détection et le diagnostic des défauts considérés, et assez flexible que possible pour ne pas nuire à la conception et l’implémentation de l’algorithme de surveillance. Ainsi, notre contribution s’inscrit au cœur de cette problématique. En fait, nous avons pu développer une procédure complète pour la détection et l’isolation de défauts basée sur les modèles flous et l’appliquer avec succès à un échangeur de chaleur qui constitue l’élément principal d’une installation pilote du laboratoire SAAS de l’Université Libre de Bruxelles. La démarche n’était guère aisée car il a fallu donner une justification pratique à l’approche théorique en commençant tout d’abord par répondre à l’une des principales interrogations, que nous nous sommes posées, et qui concerne la capacité de l’approximation d’un modèle flou, notamment pour le cas de l’échangeur de chaleur qui fait bien partie de la classe des systèmes à paramètres distribués. Pour ce faire, il a fallu valider l’algorithme de surveillance basé sur la manipulation de ces modèles flous afin d’apporter une justification de plus aux succès de la logique floue rencontrés au niveau des applications. Comme le montrent clairement les résultats expérimentaux obtenus, il a été démontré que les modèles flous élaborés peuvent efficacement reproduire le comportement dynamique de n’importe quel processus sur un sous-ensemble compact avec un degré de précision donné. Ces modèles sont ensuite utilisés pour la synthèse d’une procédure complète de détection et d’isolation de défauts avec une concentration particulière sur le problème de fuite d’eau. Les algorithmes développés ont été implémentés et mis en oeuvre avec succès sur l’installation pilote
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    Late-lumping fuzzy boundary geometric control of nonlinear partial differential systems
    (Wiley, 2020) Raab, Sadia; Habbi, Hacene; Maidi, Ahmed
    In this article, a fuzzy boundary geometric controller that stabilizes a class of nonlinear distributed parameter systems (DPSs) is proposed. The design procedure relies on the use of Takagi‐Sugeno (T‐S) type fuzzy partial differential equation (PDE) model, which approximates the dynamical behavior of the nonlinear DPS. The T‐S fuzzy PDE model is constructed through “fuzzy blending” of local linear PDE models of infinite characteristic indexes. This is a challenging task in the design procedure of fuzzy PDE model‐based boundary controller in the framework of the well‐established geometric control theory. To overcome this constraint, it is proposed in this article to resort to the concept of extended operator in order to transform the T‐S fuzzy PDE model with boundary control to an equivalent fuzzy PDE model with punctual control and finite characteristic index. Based on the developed fuzzy model, a fuzzy boundary geometric controller is derived and sufficient conditions of exponential stability of the resulting closed‐loop system are established by employing the Lyapunov direct method. The stabilizing performance of the proposed fuzzy PDE model‐based boundary geometric controller is evaluated on benchmark control problems and compared with other existing control methods via numerical simulations
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    Modélisation et commande d'un boiler-turbine par logique floue
    (2000) Habbi, Hacene
    During the last decade, significant change of direction in the devlopment of control theory and its application has attracted great attention from both the academic and industrial communities. The concept of "Intelligent control" has been suggested as an alternative approach to conventional control techniques for complex control, Systems. Many people have devoted a great deal of time and effort to both theoretical research and implementation technique for intelligent control Systems, trying to make an "obvious Link" between the classic control theory and fuzzy logic theory in which can be treated at the same time symbolic and numeric knowledge base, with for main objective a wide use of fuzzy logic control theory in industrial application. However, it is well known that, on the one hand the real processes apprehension is in general imperfect because of their too big complexity, on the other hand their functional representation must preserve information sufficiently for being efficiently used in control system desing. It is why fuzzy logic is one of the most useful approaches in complex Systems control because it represents a means of both collecting symbolic knowledge and expertise and dealing with uncertainties in the process of control, that witch very few other methodologies allow
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    Multivariable control of a drum-type boiler system through LQG fuzzy emulation
    (IEEE, 2015) Lamraoui, Oualid; Habbi, Hacene
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    Self-generated fuzzy systems design using artificial bee colony optimization
    (Elsevier, 2015) Habbi, Hacene; Boudouaoui, Yassine; Karaboga, Dervis; Ozturk, Celal
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    Swarm bee colony optimization for heat exchanger distributed dynamics approximation with application to leak detection
    (IGI Global, 2018) Boudouaoui, Yassine; Habbi, Hacene; Harfouchi, Fatima