An efficient artificial bee colony algorithm with application to nonlinear predictive control

Sahed, Oussama Ait; Kara, Kamel; Benyoucef, Abou soufyane; Hadjili, Mohamed Laid

doi:10.1080/03081079.2015.1086344

Cited by 15 publications

(2 citation statements)

References 47 publications

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“…Several reports about this application have been found in Refs. [27,28]. In this paper, a famous artificial bee colony (ABC) algorithm is introduced to optimize the parameters in LADRC.…”

Section: Parameter Tuningmentioning

confidence: 99%

Dynamical Modelling and Robust Control for an Unmanned Aerial Robot Using Hexarotor with 2-DOF Manipulator

Ding

2019

International Journal of Aerospace Engineering

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The robust control issues in trajectory tracking of an unmanned aerial robot (UAR) are challenging tasks due to strong parametric uncertainties, large nonlinearities, and high couplings in robot dynamics. This paper investigates the dynamical modelling and robust control of an aerial robot using a hexarotor with a 2-degrees-of-freedom (DOF) manipulator in a complex aerial environment. Firstly, the kinematic model and dynamic model of the aerial robot are developed by the Euler-Lagrange method. Afterwards, a linear active disturbance rejection control is designed for the robot to achieve a high-accuracy trajectory tracking goal under heavy lumped disturbances. In this control scheme, the modelling uncertainties and external disturbances are estimated by a linear extended state observer, and the high tracking precision is guaranteed by a proportion-differentiation (PD) feedback control law. Meanwhile, an artificial intelligence algorithm is applied to adjust the control parameters and ensure that the state variables of the robot converge to the references smoothly. Furthermore, it requires no detailed knowledge of the bounds on unknown dynamical parameters. Lastly, numerical simulations and experiments validate the efficiency and advantages of the proposed method.

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“…Several reports about this application have been found in Refs. [27,28]. In this paper, a famous artificial bee colony (ABC) algorithm is introduced to optimize the parameters in LADRC.…”

Section: Parameter Tuningmentioning

confidence: 99%

Dynamical Modelling and Robust Control for an Unmanned Aerial Robot Using Hexarotor with 2-DOF Manipulator

Ding

2019

International Journal of Aerospace Engineering

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“…The system has multiple input-multiple output (MIMO) characteristics consisting of four inputs (fuel, air, water flow, and steam demand) and four outputs (pressure, oxygen, steam flow and level in the drum) and also there are a dual fuel (oil/gas) fired unit for heating and generating electric power [12,13].…”

Section: System Structure 21 Steam Generator Modelmentioning

confidence: 99%

Performance of PSO Based Classical and Intelligent Controllers for Water Level Control of a Steam Generator

Altaş¹,

Ozkop²

2017

deufmd

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Abstract:In this paper, different controller techniques based on particle swarm optimization (PSO) algorithm are proposed to control the water level of a steam generator with multiple inputmultiple output (MIMO) characteristics. The techniques employed are classical proportional+integral+derivative (PID) control, fuzzy logic control (FLC) and fuzzy tuned proportional-integral control (FTPIC). Gains of PID controller and parameters of FLC (the core and the boundaries of triangular membership functions in input and output spaces) are optimized by the PSO. Validations of the proposed PSO based PID control (PSO-PID), PSO based fuzzy logic control (PSO-FLC) and PSO based fuzzy tuned PI control (PSO-FTPIC) techniques are done with numerical simulation in using MATLAB. The simulation results show that the PSO-PID provides better performance for controlling the water level of a steam generator compared to the others. Buhar Generatörünün Su Seviyesi Denetimi için PSO Temelli Klasik veAkıllı Denetleyicilerin Performansı Keywords Denetim, Bulanık Mantık, Parçacık Sürü, Optimizasyon, ÇGÇÇ Özet: Bu çalışmada çok giriş-çok çıkış (ÇGÇÇ) özelliğine sahip buhar generatörünün su seviyesi denetimi için parçacık sürü optimizasyonu (PSO) algoritmasına dayanan farklı kontrol teknikleri önerilmektedir. Bu teknikler, klasik oransal-integraltürevsel (PID) denetim, bulanık mantık denetim (BMD) ve bulanık ayarlı oransal-integral denetimdir. PID denetleyicilerin kazançları ve BMD'nin parametreleri (giriş ve çıkıştaki üçgen üyelik fonksiyonların merkezleri ve sınırları) PSO tarafından en uygun hale getirilmektedir. Önerilen PSO temelli PID denetim (PSO-PID), PSO temelli bulanık mantık denetim (PSO-BMD) ve PSO temelli bulanık ayarlı PI denetim (PSO-BAPI) tekniklerinin gerçeklemesi, MATLAB kullanılarak sayısal benzetim ile doğrulanmaktadır. Benzetim sonuçları, buhar generatörünün su seviyesi denetim için PSO-PID tekniğini diğerlerine göre daha iyi performans sergilediğini göstermektedir.

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Artificial Bee Colony Algorithms in Control Systems, Robotics, and Automation

Singh,

Godiyal,

Saroha

et al. 2024

Springer Tracts in Nature-Inspired Computing

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An efficient artificial bee colony algorithm with application to nonlinear predictive control

Cited by 15 publications

References 47 publications

Dynamical Modelling and Robust Control for an Unmanned Aerial Robot Using Hexarotor with 2-DOF Manipulator

Dynamical Modelling and Robust Control for an Unmanned Aerial Robot Using Hexarotor with 2-DOF Manipulator

Performance of PSO Based Classical and Intelligent Controllers for Water Level Control of a Steam Generator

Artificial Bee Colony Algorithms in Control Systems, Robotics, and Automation

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