Publications Scientifiques
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Item Experimental investigation of evolving cloud-based fuzzy control of a pilot thermal exchanger under a decentralized framework(Elsevier, 2023) Lamraoui, Oualid; Habbi, HaceneRelying 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.Item Fuzzy distributed control of the forced Burgers-Fisher equation under periodic boundary conditions(IEEE, 2020) Raab, Sadia; Habbi, Hacene; Maidi, Ahmed; Belharet, KarimThis 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 conditionsItem Late-lumping fuzzy boundary geometric control of nonlinear partial differential systems(Wiley, 2020) Raab, Sadia; Habbi, Hacene; Maidi, AhmedIn 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 simulationsItem Multivariable control of a drum-type boiler system through LQG fuzzy emulation(IEEE, 2015) Lamraoui, Oualid; Habbi, HaceneItem Swarm bee colony optimization for heat exchanger distributed dynamics approximation with application to leak detection(IGI Global, 2018) Boudouaoui, Yassine; Habbi, Hacene; Harfouchi, FatimaItem A cooperative learning strategy with multiple search mechanisms for improved artificial bee colony optimization(IEEE, 2015) Harfouchi, Fatima; Habbi, HaceneArtificial 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 variantsItem A cooperative learning artificial bee colony algorithm with multiple search mechanisms(IOS Press, 2016) Harfouchi, Fatima; Habbi, HaceneItem Self-generated fuzzy systems design using artificial bee colony optimization(Elsevier, 2015) Habbi, Hacene; Boudouaoui, Yassine; Karaboga, Dervis; Ozturk, CelalItem A complete procedure for leak detection and diagnosis in a complex heat exchanger using data-driven fuzzy models(Elsevier, 2009) Habbi, Hacene; Kinnaert, Michel; Zelmat, MimounItem H-infinity fuzzy emulator design for multivariable control of drum boiler-turbine unit(Institute of Electrical and Electronics Engineers, 2015) Lamraoui, Oualid; Habbi, Hacene