Publications Internationales

Permanent URI for this collectionhttps://dspace.univ-boumerdes.dz/handle/123456789/13

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Author: search.filters.author.Grouni, Said

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Now showing 1 - 10 of 10
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    A Single-Neuron-Based Temperature Control of a Continuous Stirred Tank Reactor
    (Springer Nature, 2024) Ladjouzi, Samir; Grouni, Said
    In this paper, a new technique to determine the best values of a PID controller is presented. The proposed scheme is based on using a single-neuron controller which its weights represent the PID parameters. Weight’s adjustment is accomplished with a recent meta-heuristic algorithm called the DragonFly Algorithm. To show the effectiveness of our method, we have applied it to control a Continuous Stirred Tank Reactor. The obtained results are compared with several algorithms: the Ziegler–Nichols, Genetic Algorithm, and Particle Swarm Optimization.
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    Improved sensorless backstepping controller using extended Kalman filter of a permanent magnet synchronous machine
    (2022) Kirad, Abderrahmen; Grouni, Said; Soufi, Youcef
    This paper deals with an improved backstepping control strategy for sensorless control of a permanent magnet synchronous motor (PMSM) based on field-oriented control (FOC), using a backstepping controller to improve its performances. However, this control requires the precise knowledge of some machine’s variables which could not be available. In electric drives control, sensors are generally used as the main devices for feedback information. Some practical constraints could affect the system performances, due to the lack of measurement material or maintenance difficulties caused by the dysfunction or faults of the used sensors such as: encoder or resolver sensors of speed-position. In this paper, a sensorless control is proposed based on a dynamic backstepping method and an extended Kalman filter (EKF) which uses the state space formulation with a set of mathematical equations to recursively estimate future observations and minimizes the mean square error of the estimated variables (rotor speed position and torque) to design controllers for nonlinear systems. The proposed control scheme achieves the asymptotically uniformed stability. The effectiveness of this method is illustrated by the stabilization and tracking numerical examples and the obtained simulation results show the effectiveness and the feasibility of the proposed controller using Lyapunov approach.
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    Quadcopter nonsingular finite-time adaptive robust saturated command-filtered control system under the presence of uncertainties and input saturation
    (Springer Science and Business Media B.V., 2021) Eliker, Karam; Grouni, Said; Tadjine, Mohamed; Zhang, Weidong
    The nonsingular finite-time adaptive robust saturated command-filtered control problem for quadcopter unmanned aerial vehicles is investigated in this paper. Firstly, an adaptive robust command-filtered control, based on backstepping command-filtered and nonsingular fast terminal sliding mode control, is developed. Secondly, the parametric and nonparametric uncertainties are estimated by using a small number of adaptive laws. Also, a projector function is used to ensure the estimation of quadcopter parameters within an admissible set. Thirdly, error compensating signals are employed to tackle the undesirable effect of command filters. Finally, saturation compensator signals are developed to deal with the adverse effect of saturation in the system. The proposed control strategy can cope with the “explosion of complexity” and “singularity” problems. In addition, it can alleviate the chattering phenomenon and satisfy practical finite-time stability. The numerical simulation results and comparison display the effectiveness of the proposed technique over the other control methods
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    PID controller parameters adjustment using a single memory neuron
    (Elsevier, 2020) Ladjouzi, Samir; Grouni, Said
    The work presented in this paper presents the use of a single memory neuron to find optimal gains for a PID controller. The adopted strategy with the principal equations is discussed. The efficiency of the proposed method is shown for two usual problems which frequently occur in the industry: a single tank and a boiler and heat exchanger applications. A comparison with the Ziegler–Nichols method is presented in order to prove the effectiveness of our approach
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    New improved hybrid MPPT based on neural network-model predictive control-kalman filter for photovoltaic system
    (2020) Kacimi, Nora; Grouni, Said; Idir, Abdelhakim; Boucherit, Mohamed Seghir
    In this paper, new hybrid maximum power point tracking strategy for photovoltaic systems has been proposed. The proposed technique for control based on a novel combination of an artificial neural network with an improved model predictive control using Kalman Filter. In this paper the Kalman Filter is used to estimate the converter state vector for minimized the cost function then predict the future value to track the maximum power point with fast changing weather parameters. The proposed control technique can track the in fast changing irradiance conditions and a small overshoot. Finally, the system is simulated in the MATLAB/Simulink environment. Several tests under stable and variable environmental conditions are made for the four algorithms, and results show a better performance of the proposed compared to conventional perturb and observation neural network based proprtional integral control and neural network based model predictive control in terms of response time, efficiency and steady-state oscillations
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    Application of predictive controller tuning and a comparison study in terms of PID controllers
    (Elseier, 2016) Ramdani, Ammar; Grouni, Said; Soufi, Youcef
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    Advanced control algorithm : applications to industrial processes
    (2015) Ramdani, Ammar; Grouni, Said; Traïche, M.
    As in the most industrial systems, a control of the input of the systems including a classic regulator is a key point. The Proportional-Integral-Derivative controllers are commonly used in many industrial control systems and appeared suitable to stable the control of the majority of real processes. But in some cases like a non-minimum-phase plant or a plant with a dead-time proceed to a thin regulating of coefficients until to get a system respecting the conditions specified. It is possible also to present a problem of overtaking with the increase of the gain or seems impotent for systems having a big delay and the use of sophisticated process controllers is required. Model predictive control is an important branch of automatic control theory, it refers to a class of control algorithms in which a process model is used to predict and optimize the process performance. MPC has been widely applied in industry. Dynamic Matrix Control Algorithm belongs to the family of Model predictive control Algorithms where these algorithms only differ between themselves in the model that represents the process, disruptions and the function of cost. In this paper the study of the Dynamic Matrix Control Algorithm are interested while applying him on processes of water heating and mechanical rotations of steering mirrors in a Light Detection and Ranging system as a second application. The objective of this work consists of solving the problem of prediction of the output and input of the process by fixing a horizon finished N, and while considering the present state like initial state, to optimize a cost function on this interval, while respecting constraints. Therefore, the future reference is known and the system behavior must be predictable by an appropriate model. It results an optimal sequence of N control of it among which alone the first value will be applied effectively. As the time advances, the horizon of prediction slips and a new problem of optimization is to solve while considering the state of the system updating. In summary, every moment, it is necessary to elaborate an optimal control sequence in open loop, refined systematically by the present measure arrival
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    Predictive functional control approach, study and simulation
    (2015) Ramdani, Ammar; Grouni, Said; Bouallegue, K.
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    Dynamic angle stability of an industrial turbo generator connected in power system
    (AIP Publishing, 2014) Grouni, Said; Hallak, M.; Aibeche, Abderrazak; Ramdani, Ammar; Bouallegue, K.
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