Robust PID controller design based on multi-objective Particle Swarm Optimization approach

Madiouni, Riadh

doi:10.1109/icemis.2017.8273039

Cited by 3 publications

(4 citation statements)

References 18 publications

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“…The healthier and lifeless populations are too large, and the size of the sick population falloffs over time, so starting with a certain iteration, the newly sick population will be lower than the one that is already present. In agreement with the objective COVID-19 function in equation, the effectiveness of each row will be examined (8). Poor performance identifies the susceptible to death afflicted population.…”

Section: Covid-19 Optimizationmentioning

confidence: 99%

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A COVID-19 Based on Fractional Order Integral-Tilt Derivative Controller for Nonlinear Servomechanism Model

Shamseldin,

Salah,

Mohamed

et al. 2023

International Journal of Electrical Engineering and Computer Science

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In this research, a new one-axis servomechanism investigation is presented, taking into account parameter fluctuation and system uncertainty. Additionally, a novel method for very effective TID control was created to accurately monitor a chosen profile. A comparative study between the suggested control method and the well-known controllers (PID and Nonlinear PID) is also included. The COVID-19 optimization technique was used to discover the best control parameters. Through the online simulation, the servomechanism system's settings were modified at random within a predetermined range. As nonlinearity resources (friction, backlash, environmental influences), these parameters fluctuate and contribute to system uncertainty. It had been completed and looked at to compare the linear and nonlinear models. The results demonstrate that the suggested controller is capable of tracking the number of operational points with high accuracy, a short rising time, and little overrun.

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Section: Covid-19 Optimizationmentioning

confidence: 99%

“…The sliding mode technique has the advantage that it provides strong tracking performance over a variety of position command operating locations. On the other hand, chattering phenomena can make it challenging to improve control accuracy and, in uncommon circumstances, can result in system instability [7]; [8].…”

Section: Introductionmentioning

confidence: 99%

A COVID-19 Based on Fractional Order Integral-Tilt Derivative Controller for Nonlinear Servomechanism Model

Shamseldin,

Salah,

Mohamed

et al. 2023

International Journal of Electrical Engineering and Computer Science

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“…Ordinary people and super-spreaders can both follow and find solutions in different ways. As a result, individuals are more likely to travel, allowing them to disseminate the sickness to potential alternative solutions [56], [57]. The third step is population modernization.…”

Section: Covid-19 Optimizationmentioning

confidence: 99%

Adaptive Controller with PID, FOPID, and NPID Compensators for Tracking Control of Electric – Wind Vehicle

Shamseldin

2022

Journal of Robotics and Control

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This paper presents a new combination between the Model Reference Adaptive Control (MRAC) with several types of PID’s controllers (PID, Fractional order PID (FOPID), and Nonlinear PID (NPID)) optimized using a new Covid-19 algorithm. The proposed control techniques had been applied on a new model for an electric-wind vehicle, which can catch the wind that blows in the opposite direction of a moving vehicle to receive wind; a wind turbine is installed on the vehicle’s front. The generator converts wind energy into electricity and stores it into a backup battery to switch it when the primary battery is empty. The simulation results prove that the new model of electric–wind vehicles will save power and allow the vehicle to continue moving while the other battery charges. In addition, a comparative study between different types of control algorithms had been developed and investigated to improve the vehicle dynamic response. The comparison shows that the MRAC with the NPID compensator can absorb the nonlinearity (air resistance and wheel friction) where it has a minimum overshoot, rise time, and settling time (35 seconds) among other control techniques compensators (PID and FOPID).

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“…Madiouni (7) presented MOPSO algorithm based PID controller for various non-linear problems and proved its performances better than the non-dominated sorting genetic algorithm II in terms of better computation time. Ram and Chidambaram (8) proposed steady state gain matrix (SSGM) based centralized PI controller design for a multivariable process and validated its performance compared with controller design based on gain, time delay and time constant.…”

Section: Introductionmentioning

confidence: 99%

Design of centralized controller for multivariable process using MOPSO algorithm

Sivagurunathan¹

2021

IJST

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Objective: To estimate centralized PID controller parameters for 4 outputs and 5 inputs crude distillation non-square system with RHP zeros process. Methods/Analysis: The Multi-Objective Particle Swam Optimization (MOPSO) algorithm is applied to determine the PID controller parameters for the considered distillation column process. Findings: The performance of the proposed controller is compared with two centralized controller schemes, Davison's and Tanttu and Lieslehto methods. The Integral Square Error (ISE), Integral Absolute Error (IAE) and Integral of Time Absolute Error (ITAE) are chosen as performance indices. The simulation results prove that MOPSO tuned centralized controller gives the best performance when compared to other analytical techniques for both set point tracking and in disturbance rejection environment. Novelty: In practice, conventional PID controllers are tuned using classical methods, which require complex numerical calculations. In this paper, an attempt is made to fine tune the PID controller for a MIMO process using Multi Objective optimization technique and obtained challenging results as compared to conventional methods.

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Robust PID controller design based on multi-objective Particle Swarm Optimization approach

Cited by 3 publications

References 18 publications

A COVID-19 Based on Fractional Order Integral-Tilt Derivative Controller for Nonlinear Servomechanism Model

A COVID-19 Based on Fractional Order Integral-Tilt Derivative Controller for Nonlinear Servomechanism Model

Adaptive Controller with PID, FOPID, and NPID Compensators for Tracking Control of Electric – Wind Vehicle

Design of centralized controller for multivariable process using MOPSO algorithm

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