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    Enhancing the transient performances and stability of three-tank liquid level using a modified pid controller
    (Revue roumaine des sciences techniques — Série électrotechnique et énergétique, 2025) Idir, Abdelhakim; Nesri, Mokhtar; Belhouchet, Khaled; Guedida, Sifelislam; Canale, Laurent
    Managing liquid levels in industrial tanks is crucial, especially for precise component mixing. Traditional PID controllers, though widely used, often exhibit slow settling times and excessive overshoot, which can affect system performance. This study proposes a fractionalized order PID (FrOPID) controller optimized using the Modified Artificial Hummingbird Algorithm (MAHA) to enhance stability and response in a three-tank system. The controller’s effectiveness is evaluated under varying valve coefficient (Kv) and tank cross-sectional area conditions. A comparative analysis with advanced metaheuristic-optimized PID controllers confirms the superiority of the MAHA/FrOPID in terms of accuracy, response speed, and robustness, making it a highly efficient solution for liquid level control.
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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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    A comparative study between fractionalized and fractional order PID controllers for control of a stable system based on particle swarm optimization algorithm
    (Wydawnictwo SIGMA-NOT, 2023) Idir, Abdelhakim; Berrabah, Fouad; Laurent, Canale
    Most industrial applications use integer-order proportional integral derivative (IOPID) controllers due to well-known characteristics such as simplicity and ease of implementation. However, because of their nonlinear nature and the underlying iso-damping feature of fractional-order operators, fractional-order PID (FOPID) and fractionalized-order PID (FrOPID) controllers outperform the IOPID controllers. In this study, three different controllers based on particle swarm optimization are used to regulate a stable system. While a FrOPID controller only has to optimize four parameters and a normal PID controller only needs to optimize three parameters, a FOPID controller requires the optimization of five parameters. Set-point tracking, and better disturbance rejection are obtained with the fractional PID controller, whereas fractionalized PID outperforms the other controllers in terms of noise attenuation
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    Enhanced backstepping control for disturbances rejection in quadrotors
    (2022) Saibi, Ali; Belaidi, Hadjira; Boushaki, Razika; Recham, Zine Eddine; Amrouche, Hafid
    This work studies the issue of quadrotor trajectory tracking control in presence of disturbances and model uncertainties. The paper starts by extracting the kinematics and dynamics models of the quadrotor. This results in the motion equations, which eventually serve as a blueprint for creating the suggested smart flight control scheme. Secondly, an enhanced backstepping controller (BSC) is developed and tested to keep the quadrotor tracking the desired trajectory both in steady state and in presence of disturbances. Finally, BSC beside two other controllers: sliding mode controller (SMC) and proportional derivative controller (PDC) are implemented in MATLAB/Simulink and the obtained results are compared and conclusions are extracted. Therefore, it is established that PDC is not robust to disturbances as noise will be amplified due to the derivative term. Whereas, although SMC is robust to parameter variations and disturbances; however, it is not continuous which may affect the actuators due to the increased gains which may saturate them. In contrast, BSC requires too many tuning parameters; however, it ensures Lyapunov Stability and does not depend on the system as it does not involve cancelling system nonlinearity. Moreover, BSC results are 1017 better than the results of the two other controllers.
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    PID and Novel Approach of PI Fuzzy Logic Controllers for Active Surge in Centrifugal Compressor
    (Springer, 2013) Chetate, Boukhmis; Zamoum, R.; Fegriche, A.; Boummdine, Mohand Said
    The operating range of aerodynamic compressors is usually limited by a phenomenon known as surge. Active surge control has showed the ability to extend the operating range significantly. This study presents a solution to this problem based on classical PID regulator and a new PI fuzzy logic approach with three lines of protection. The fuzzy controller is designed to avoid the surge instability on a given compressormodel. Simulation studies showpromising results at different operating points compared to the results obtained using PID controller
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    Active surge control of the recycle compression system by hybrid adaptive controller
    (IEEE, 2019) Aribi, Yacine; Zammoum Boushaki, Razika; Loubar, Hocine
    Centrifugal compressors are a Type of widely used compression systems for industrial gases. Practically, centrifugal and axial compressors often suffer huge and irreversible damages due to a major non-stability feature widely known as surge. In this paper, a control strategy is proposed in order to avoid falling into surge and to recover the system from deep surge state. An auto-tuned, PID-Based, model free approach based on Multi-stage Fuzzy Inference system is used to provide a real-time tuning for PID parameters in order to achieve optimal control for the Compression system’s recycle valve. The proposed control solution comes to prevent the system from falling into surge and shows promising results while recovering the system back into stability and maintaining stable operating point. Furthermore, a stable and robust, model free control, has been achieved for deep surge control
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    An Improved Robust Fractionalized PID Controller for a Class of Fractional-Order Systems with Measurement Noise
    (INASS, 2018) Bensafia, Yassine; Khettab, Khatir; Idir, Abdelhakim
    Recently, many research works have focused on fractional order control (FOC) and fractional systems. It has proven to be a good mean for improving the plant dynamics with respect to response time and disturbance rejection. In this paper we propose a new approach for robust control by fractionalizing an integer order integrator in the classical PID control scheme and we use the Sub-optimal Approximation of fractional order transfer function to design the parameters of PID controller, after that we study the performance analysis of fractionalized PID controller over integer order PID controller. The implementation of the fractionalized terms is realized by mean of well-established numerical approximation methods. Illustrative simulation examples show that the disturbance rejection is improved by 50%. This approach can also be generalized to a wide range of control methods
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    Continuous firefly algorithm for optimal tuning of PID controller in AVR system
    (2014) Bendjeghaba, Omar
    This paper presents a tuning approach based on Continuous firefly algorithm (CFA) to obtain the proportional-integralderivative (PID) controller parameters in Automatic Voltage Regulator system (AVR). In the tuning processes the CFA is iterated to reach the optimal or the near optimal of PID controller parameters when the main goal is to improve the AVR step response characteristics. Conducted simulations show the effectiveness and the efficiency of the proposed approach. Furthermore the proposed approach can improve the dynamic of the AVR system. Compared with particle swarm optimization (PSO), the new CFA tuning method has better control system performance in terms of time domain specifications and setpoint tracking
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    Artificial neural network control of the recycle compression system
    (2014) Zammoum Boushaki, Razika; Chetate, Boukhmis; Zamoum, Y.
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    Adaptive fuzzy inference control of the recycle compression system
    (Praise Worthy Prize, 2014) Zammoum Boushaki, Razika; Zamoum, Y.; Chetate, Boukhmis