Enhanced Arithmetic Optimization Algorithm for Parameter Estimation of PID Controller

The Proportional-Integral-Derivative (PID) controller is a key component in most engineering applications. The main disadvantage of PID is the selection of the best values for its parameters using traditional methods that do not achieve the best response. In this work, the recently released empirica...

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Published inArabian journal for science and engineering Vol. 48; no. 2; pp. 2191 - 2205
Main Author Issa, Mohamed
Format Journal Article
LanguageEnglish
Published Berlin/Heidelberg Springer Berlin Heidelberg 01.02.2023
Springer Nature B.V
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ISSN2193-567X
1319-8025
2191-4281
DOI10.1007/s13369-022-07136-2

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Abstract The Proportional-Integral-Derivative (PID) controller is a key component in most engineering applications. The main disadvantage of PID is the selection of the best values for its parameters using traditional methods that do not achieve the best response. In this work, the recently released empirical identification algorithm that is the Arithmetic Optimization Algorithm (AOA) was used to determine the best values of the PID parameters. AOA was selected due to its effective exploration ability. Unfortunately, AOA cannot achieve the best parameter values due to its poor exploitation of search space. Hence, the performance of the AOA exploit is improved by combining it with the Harris Hawk Optimization (HHO) algorithm which has an efficient exploit mechanism. In addition, avoidance of trapping in the local lower bounds of AOA–HHO is enhanced by the inclusion of perturbation and mutation factors. The proposed AOA–HHO algorithm is tested when choosing the best values for PID parameters to control two engineering applications namely DC motor regulation and three fluid level sequential tank systems. AOA–HHO has superiority over AOA and comparative algorithms.
AbstractList The Proportional-Integral-Derivative (PID) controller is a key component in most engineering applications. The main disadvantage of PID is the selection of the best values for its parameters using traditional methods that do not achieve the best response. In this work, the recently released empirical identification algorithm that is the Arithmetic Optimization Algorithm (AOA) was used to determine the best values of the PID parameters. AOA was selected due to its effective exploration ability. Unfortunately, AOA cannot achieve the best parameter values due to its poor exploitation of search space. Hence, the performance of the AOA exploit is improved by combining it with the Harris Hawk Optimization (HHO) algorithm which has an efficient exploit mechanism. In addition, avoidance of trapping in the local lower bounds of AOA–HHO is enhanced by the inclusion of perturbation and mutation factors. The proposed AOA–HHO algorithm is tested when choosing the best values for PID parameters to control two engineering applications namely DC motor regulation and three fluid level sequential tank systems. AOA–HHO has superiority over AOA and comparative algorithms.
Author Issa, Mohamed
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  email: Mamohamedali@eng.zu.edu.eg
  organization: Computer and Systems Department, Faculty of Engineering, Zagazig University, Faculty of Computer Science, NAHDA University in Beni-Suef
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Cites_doi 10.1109/ACCESS.2019.2902306
10.1109/IKT54664.2021.9685429
10.1016/j.asoc.2021.107197
10.1007/978-3-030-70542-8_28
10.1007/978-3-030-56689-0_8
10.1016/j.eswa.2018.01.019
10.1016/j.neucom.2015.11.018
10.1109/ACCESS.2019.2905961
10.5772/652
10.1109/ICCPCT.2016.7530150
10.4018/978-1-5225-2229-4.ch018
10.1007/s00500-020-04842-7
10.1007/s00500-018-3586-y
10.31814/stce.huce(nuce)2022-16(2)-03
10.1016/j.compchemeng.2019.106656
10.1007/978-3-030-69744-0_21
10.1007/s12652-022-03724-0
10.1016/j.asoc.2020.106683
10.1007/s13369-022-06605-y
10.1016/j.engappai.2022.104753
10.1016/j.eswa.2021.116432
10.1016/j.asoc.2015.10.041
10.1007/s00542-018-3920-4
10.1109/ISMSIT.2019.8932907
10.3390/electronics10222834
10.1109/4235.585893
10.1016/j.eswa.2017.02.035
10.1145/2001858.2002123
10.1016/j.asoc.2017.06.033
10.1109/SIS.2007.367959
10.1007/s00366-020-01028-5
10.1002/9780470496916
10.1115/1.4019264
10.1016/j.rser.2016.03.049
10.3390/pr9071155
10.1016/j.future.2019.02.028
10.1007/978-3-319-74690-6_11
10.1109/TEC.2003.821821
10.1016/j.asej.2018.07.005
10.1016/j.cma.2020.113609
10.1016/j.matcom.2021.08.016
10.1109/UPEC50034.2021.9548204
10.1007/s12065-022-00711-4
10.1016/j.energy.2019.116025
10.1371/journal.pone.0255703
10.1016/j.ins.2019.04.022
10.1109/ACCESS.2021.3085529
10.1016/j.eswa.2019.112976
10.1016/j.knosys.2015.12.022
10.1007/978-3-030-02357-7_20
10.1007/s00500-020-05349-x
10.1016/j.enconman.2020.113211
10.3390/rs11121421
10.1016/j.eswa.2021.116063
10.1016/j.eswa.2019.113103
10.1007/s10489-021-03125-4
10.3390/s19163590
10.1016/j.knosys.2015.07.006
10.1016/j.jclepro.2019.118778
10.1109/TMAG.2011.2176108
10.3906/elk-1612-277
10.1109/MPS52805.2021.9492572
10.1155/2022/3987494
10.1016/j.ijepes.2015.11.010
10.1016/j.est.2022.104343
10.1016/j.asoc.2015.03.035
10.1155/2021/9114113
10.3390/math9182321
10.1109/ACCESS.2022.3146374
10.1007/s10489-016-0848-1
10.3390/pr9101774
10.1007/s00500-022-06873-8
10.1109/ACCESS.2019.2921545
10.1007/978-3-030-04792-4_8
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Issue 2
Keywords Arithmetic optimization algorithm (AOA)
PID controller
Harris Hawk optimization algorithm (HHO)
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References RamachandranMA hybrid grasshopper optimization algorithm and harris hawks optimizer for combined heat and power economic dispatch problemEng. Appl. Artif. Intell.2022111
IssaMA biological sub-sequences detection using integrated BA-PSO based on infection propagation mechanism: Case study COVID-19Expert Syst. Appl.2022189
JordehiARParameter estimation of solar photovoltaic (PV) cells: A reviewRenew. Sustain. Energy Rev.201661354371
ChenHParameters identification of photovoltaic cells and modules using diversification-enriched Harris hawks optimization with chaotic driftsJ. Clean. Prod.2020244
Abd ElazizMImproving image thresholding by the type II fuzzy entropy and a hybrid optimization algorithmSoft. Comput.202024191488514905
KharrichMAn improved arithmetic optimization algorithm for design of a microgrid with energy storage system: case study of El Kharga Oasis, EgyptJ. Energy Storage202251104343
PremkumarMA new arithmetic optimization algorithm for solving real-world multiobjective CEC-2021 constrained optimization problems: diversity analysis and validationsIEEE Access202198426384295
RazmjooyNSpeed control of a DC motor using pid controller based on improved whale optimization algorithmMetaheuristics and Optimization in Computer and Electrical Engineering2021Springer153167
Issa, M.; Hassanien, A.E.: Multiple sequence alignment optimization using meta-heuristic techniques. In: Handbook of Research on Machine Learning Innovations and Trends. IGI Global. p. 409–423 (2017)
EkinciSHekimoğluBIzciDOpposition based Henry gas solubility optimization as a novel algorithm for PID control of DC motorEng Sci Technol Int J2021242331342
LiuHDingGWangBBare-bones particle swarm optimization with disruption operatorAppl. Math. Comput.201423810612232096201334.90213
Kennedy: Particle swarm optimization. Neural Netw (1995)
ZhangQChaos-induced and mutation-driven schemes boosting salp chains-inspired optimizersIEEE Access201973124331261
KhodadadiNSnaselVMirjaliliSDynamic arithmetic optimization algorithm for truss optimization under natural frequency constraintsIEEE Access2022101618816208
ZhengRDeep ensemble of slime mold algorithm and arithmetic optimization algorithm for global optimizationProcesses20219101774
Mahboob, A.S.; Moghaddam, M.R.O.; Yousefi. S.: AOV-IDS: arithmetic optimizer with voting classifier for intrusion detection system. In: 2021 12th International Conference on Information and Knowledge Technology (IKT). IEEE (2021)
Bora, T.C.; L.d.S. Coelho, and L. Lebensztajn, Bat-inspired optimization approach for the brushless DC wheel motor problem. IEEE Transactions on magnetics, 2012. 48(2): p. 947–950.
Singh, N. et al.;: HSSAHHO: a novel hybrid Salp swarm-Harris hawks optimization algorithm for complex engineering problems. J Ambient Intell Humanized Comput, p. 1–37 (2022)
Wang, H. et al.: Opposition-based particle swarm algorithm with Cauchy mutation. In: 2007 IEEE Congress on Evolutionary Computation. IEEE (2007)
WolpertDHMacreadyWGNo free lunch theorems for optimizationIEEE Trans. Evol. Comput.1997116782
GaingZ-LA particle swarm optimization approach for optimum design of PID controller in AVR systemIEEE Trans. Energy Convers.2004192384391
Abd Elaziz, M. et al.: IoT workflow scheduling using intelligent arithmetic optimization algorithm in fog computing. Comput. Intel. Neurosci (2021)
Ziegler, J.G.; Nichols, N.B.: Optimum settings for automatic controllers. Trans. ASME 64(11) (1942)
Zellagui, M. et al. Arithmetic optimization algorithm for optimal installation of DSTATCOM into distribution system based on various voltage stability indices. In: 2021 9th International Conference on Modern Power Systems (MPS). IEEE (2021)
AgarwalJAnalysis of grey wolf optimizer based fractional order PID controller in speed control of DC motorMicrosyst. Technol.2018241249975006
ZhangYBoosted binary Harris hawks optimizer and feature selectionEng. Comput.202137437413770
Issa, M. et al. Pairwise Global Sequence Alignment Using Sine-Cosine Optimization Algorithm. In: International Conference on Advanced Machine Learning Technologies and Applications. Springer (2018)
Talbi E.-G.: Metaheuristics: From Design to Implementation. vol. 74. John Wiley & Sons, London (2009)
ZhangXGaussian mutational chaotic fruit fly-built optimization and feature selectionExpert Syst. Appl.2020141
BendjeghabaOContinuous firefly algorithm for optimal tuning of PID controller in AVR systemJ. Electr. Eng.201465144
HamidzadehJFeature selection by using chaotic cuckoo optimization algorithm with levy flight, opposition-based learning and disruption operatorSoft. Comput.202125429112933
AgarwalJParmarGGuptaRApplication of sine cosine algorithm in optimal control of DC motor and robustness analysisWulfenia J201724117795
Harwit, M.: Astrophysical Concepts. Springer Science & Business Media, Berlin (2006)
Mahajan, S. et al.: Hybrid Aquila optimizer with arithmetic optimization algorithm for global optimization tasks. Soft Comput, p. 1–19 (2022)
Issa, M.: Sequence analysis algorithms for bioinformatics application. GRIN Verlag (2014)
Issa, M.; Abd Elaziz, M.: Analyzing COVID-19 virus based on enhanced fragmented biological Local Aligner using improved ions motion optimization algorithm. Appl Soft Comput, p. 106683 (2020)
ChatterjeeSMukherjeeVPID controller for automatic voltage regulator using teaching–learning based optimization techniqueInt. J. Electr. Power Energy Syst.201677418429
Abbassi, A. et al.: Improved arithmetic optimization algorithm for parameters extraction of photovoltaic solar cell single-diode model. Arab. J. Sci. Eng.; p. 1–17 (2022)
MoharamAEl-HosseiniMAAliHADesign of optimal PID controller using hybrid differential evolution and particle swarm optimization with an aging leader and challengersAppl. Soft Comput.201638727737
SapreSMiniSOpposition-based moth flame optimization with Cauchy mutation and evolutionary boundary constraint handling for global optimizationSoft. Comput.2019231560236041
IssaMPID controller tuning parameters using meta-heuristics algorithms: comparative analysisMachine Learning Paradigms: Theory and Application2019Springer413430
Malibari, A.A. et al.: Arithmetic optimization with retinanet model for motor imagery classification on brain computer interface. J. Healthcare Eng. (2022)
Ekinci, S. et al.: Speed control of DC motor using improved sine cosine algorithm based PID controller. In: 2019 3rd International Symposium on Multidisciplinary Studies and Innovative Technologies (ISMSIT). IEEE (2019)
Ogata, K.; Yang, Y.: Modern control engineering. Vol. 4. Prentice hall India, Prentice (2002)
AbualigahLA novel evolutionary arithmetic optimization algorithm for multilevel thresholding segmentation of covid-19 ct imagesProcesses2021971155
Do, D.T. et al.: A hybrid arithmetic optimization algorithm and differential evolution for optimization of truss structures subjected to frequency constraints. J. Sci. Technol. Civil Eng. (STCE)-HUCE (2022)
NematollahiAFRahiminejadAVahidiBA novel physical based meta-heuristic optimization method known as lightning attachment procedure optimizationAppl. Soft Comput.201759596621
IssaMSamnAPassive vehicle suspension system optimization using Harris Hawk Optimization algorithmMath. Comput. Simul.2022191328345430945407431708
Mansour, T.: PID Control: Implementation and Tuning. BoD–Books on Demand (2011)
Hao, W.-K. et al.: Arithmetic optimization algorithm based on elementary function disturbance for solving economic load dispatch problem in power system. Appl. Intell.; p. 1–27 (2022)
Roy, A.; Srivastava, S.: Design of optimal PIλDδ controller for speed control of DC motor using constrained particle swarm optimization. In 2016 International Conference on Circuit, Power and Computing Technologies (ICCPCT). IEEE (2016)
EweesAABoosting arithmetic optimization algorithm with genetic algorithm operators for feature selection: case study on cox proportional hazards modelMathematics20219182321
AgushakaJOEzugwuAEAdvanced arithmetic optimization algorithm for solving mechanical engineering design problemsPLoS ONE2021168
BansalJCFarswanPA novel disruption in biogeography-based optimization with application to optimal power flow problemAppl. Intell.2017463590615
BaoXJiaHLangCA novel hybrid harris hawks optimization for color image multilevel thresholding segmentationIEEE Access201977652976546
IssaMASCA-PSO: Adaptive sine cosine optimization algorithm integrated with particle swarm for pairwise local sequence alignmentExpert Syst. Appl.2018995670
Garzon Rivera, O.D. et al.: Application of the Arithmetic Optimization Algorithm to Solve the Optimal Power Flow Problem in Direct Current Networks. Available at SSRN, 4069702.
WangG-GOpposition-based krill herd algorithm with Cauchy mutation and position clampingNeurocomputing2016177147157
FathyAOptimal parameter identification of triple-junction photovoltaic panel based on enhanced moth search algorithmEnergy2019188
HeidariAAHarris hawks optimization: algorithm and applicationsFutur. Gener. Comput. Syst.201997849872
MirjaliliSSCA: a sine cosine algorithm for solving optimization problemsKnowl.Based Syst.201696120133
MirjaliliSMoth-flame optimization algorithm: a novel nature-inspired heuristic paradigmKnowl.Based Syst.201589228249
NeggazNBoosting salp swarm algorithm by sine cosine algorithm and disrupt operator for feature selectionExpert Syst. Appl.2020145
SalgotraRSinghUApplication of mutation operators to flower pollination algorithmExp. Syst. Appl.201779112129
IssaMHelmiATwo layer hybrid scheme of IMO and PSO for optimization of local aligner: COVID-19 as a case studyArtificial Intelligence for COVID-192021Springer363381
Pan, J.-S. et al.: A Multi-objective ions motion optimization for robot path planning. In: International conference on engineering research and applications. Springer (2018)
KhubalkarSModeling and control of a permanent-magnet brushless DC motor drive using a fractional order proportional-integral-derivative controllerTurk. J. Electr. Eng. Comput. Sci.201725542234241
IssaMExpeditious Covid-19 similarity measure tool b
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A Fathy (7136_CR72) 2019; 188
H Liu (7136_CR67) 2014; 238
JO Agushaka (7136_CR52) 2021; 16
7136_CR66
7136_CR21
7136_CR25
7136_CR53
S Mirjalili (7136_CR9) 2015; 89
Y Zhang (7136_CR57) 2021; 37
L Abualigah (7136_CR36) 2021; 376
D Potnuru (7136_CR30) 2019; 10
X Bao (7136_CR59) 2019; 7
H Jia (7136_CR75) 2019; 11
Q Zhang (7136_CR74) 2019; 7
R Zheng (7136_CR50) 2021; 9
X Zhang (7136_CR78) 2020; 141
H Chen (7136_CR58) 2020; 244
7136_CR18
O Bendjeghaba (7136_CR31) 2014; 65
M Kharrich (7136_CR42) 2022; 51
JC Bansal (7136_CR70) 2017; 46
N Khodadadi (7136_CR39) 2022; 10
Z-L Gaing (7136_CR23) 2004; 19
7136_CR13
7136_CR55
7136_CR6
7136_CR10
7136_CR54
7136_CR3
7136_CR4
7136_CR1
7136_CR15
AA Ewees (7136_CR51) 2021; 9
7136_CR2
M Issa (7136_CR11) 2018; 99
7136_CR14
7136_CR82
7136_CR81
S Sapre (7136_CR80) 2019; 23
M Premkumar (7136_CR37) 2021; 9
R Salgotra (7136_CR73) 2017; 79
7136_CR41
J Agarwal (7136_CR32) 2018; 24
7136_CR40
G-G Wang (7136_CR79) 2016; 177
M Issa (7136_CR12) 2021; 104
DH Wolpert (7136_CR35) 1997; 1
C Zhong (7136_CR65) 2022; 192
L Abualigah (7136_CR38) 2021; 9
M Abd Elaziz (7136_CR71) 2020; 24
A Moharam (7136_CR34) 2016; 38
AR Jordehi (7136_CR20) 2016; 61
EH Houssein (7136_CR60) 2020; 133
M Issa (7136_CR24) 2021
A Sharma (7136_CR49) 2021; 10
7136_CR46
7136_CR45
7136_CR44
AA Heidari (7136_CR56) 2019; 97
7136_CR43
7136_CR48
M Issa (7136_CR22) 2022; 191
7136_CR47
Y Liu (7136_CR62) 2020; 223
J Hamidzadeh (7136_CR68) 2021; 25
S Ekinci (7136_CR27) 2021; 24
M Ramachandran (7136_CR63) 2022; 111
J Agarwal (7136_CR83) 2017; 24
S Chatterjee (7136_CR33) 2016; 77
Y Xu (7136_CR76) 2019; 492
7136_CR77
B Hekimoğlu (7136_CR84) 2019; 7
References_xml – reference: AbualigahLA novel evolutionary arithmetic optimization algorithm for multilevel thresholding segmentation of covid-19 ct imagesProcesses2021971155
– reference: AbualigahLThe arithmetic optimization algorithmComput. Methods Appl. Mech. Eng.2021376419929907340412
– reference: LiuHDingGWangBBare-bones particle swarm optimization with disruption operatorAppl. Math. Comput.201423810612232096201334.90213
– reference: AgushakaJOEzugwuAEAdvanced arithmetic optimization algorithm for solving mechanical engineering design problemsPLoS ONE2021168
– reference: Talbi E.-G.: Metaheuristics: From Design to Implementation. vol. 74. John Wiley & Sons, London (2009)
– reference: SalgotraRSinghUApplication of mutation operators to flower pollination algorithmExp. Syst. Appl.201779112129
– reference: Roy, A.; Srivastava, S.: Design of optimal PIλDδ controller for speed control of DC motor using constrained particle swarm optimization. In 2016 International Conference on Circuit, Power and Computing Technologies (ICCPCT). IEEE (2016)
– reference: IssaMPerformance optimization of pid controller based on parameters estimation using meta-heuristic techniques: a comparative studyMetaheuristics in Machine Learning: Theory and Applications2021Springer691709
– reference: PotnuruDMaryKABabuCSExperimental implementation of flower pollination algorithm for speed controller of a BLDC motorAin Shams Eng. J.2019102287295
– reference: EweesAABoosting arithmetic optimization algorithm with genetic algorithm operators for feature selection: case study on cox proportional hazards modelMathematics20219182321
– reference: NeggazNBoosting salp swarm algorithm by sine cosine algorithm and disrupt operator for feature selectionExpert Syst. Appl.2020145
– reference: Pan, J.-S. et al.: A Multi-objective ions motion optimization for robot path planning. In: International conference on engineering research and applications. Springer (2018)
– reference: ChatterjeeSMukherjeeVPID controller for automatic voltage regulator using teaching–learning based optimization techniqueInt. J. Electr. Power Energy Syst.201677418429
– reference: Mansour, T.: PID Control: Implementation and Tuning. BoD–Books on Demand (2011)
– reference: MoharamAEl-HosseiniMAAliHADesign of optimal PID controller using hybrid differential evolution and particle swarm optimization with an aging leader and challengersAppl. Soft Comput.201638727737
– reference: GaingZ-LA particle swarm optimization approach for optimum design of PID controller in AVR systemIEEE Trans. Energy Convers.2004192384391
– reference: ZhangYBoosted binary Harris hawks optimizer and feature selectionEng. Comput.202137437413770
– reference: Wang, H. et al.: Opposition-based particle swarm algorithm with Cauchy mutation. In: 2007 IEEE Congress on Evolutionary Computation. IEEE (2007)
– reference: Hansen, N.; Auger. A.: CMA-ES: evolution strategies and covariance matrix adaptation. In: Proceedings of the 13th annual conference companion on Genetic and evolutionary computation (2011)s
– reference: Ziegler, J.G.; Nichols, N.B.: Optimum settings for automatic controllers. Trans. ASME 64(11) (1942)
– reference: Khalilpour, M. et al.: Optimal control of DC motor using invasive weed optimization (IWO) algorithm. In: Majlesi Conference on Electrical Engineering, Majlesi New Town, Isfahan, Iran (2011)
– reference: JavidyBHatamlouAMirjaliliSIons motion algorithm for solving optimization problemsAppl. Soft Comput.2015327279
– reference: Zellagui, M. et al. Arithmetic optimization algorithm for optimal installation of DSTATCOM into distribution system based on various voltage stability indices. In: 2021 9th International Conference on Modern Power Systems (MPS). IEEE (2021)
– reference: IssaMASCA-PSO: Adaptive sine cosine optimization algorithm integrated with particle swarm for pairwise local sequence alignmentExpert Syst. Appl.2018995670
– reference: ZhengRDeep ensemble of slime mold algorithm and arithmetic optimization algorithm for global optimizationProcesses20219101774
– reference: SapreSMiniSOpposition-based moth flame optimization with Cauchy mutation and evolutionary boundary constraint handling for global optimizationSoft. Comput.2019231560236041
– reference: MirjaliliSSCA: a sine cosine algorithm for solving optimization problemsKnowl.Based Syst.201696120133
– reference: BaoXJiaHLangCA novel hybrid harris hawks optimization for color image multilevel thresholding segmentationIEEE Access201977652976546
– reference: RazmjooyNSpeed control of a DC motor using pid controller based on improved whale optimization algorithmMetaheuristics and Optimization in Computer and Electrical Engineering2021Springer153167
– reference: Aydemir, S.B.: A novel arithmetic optimization algorithm based on chaotic maps for global optimization. Evol Intell, p. 1–16 (2022)
– reference: EkinciSHekimoğluBIzciDOpposition based Henry gas solubility optimization as a novel algorithm for PID control of DC motorEng Sci Technol Int J2021242331342
– reference: Abd Elaziz, M. et al.: IoT workflow scheduling using intelligent arithmetic optimization algorithm in fog computing. Comput. Intel. Neurosci (2021)
– reference: KharrichMAn improved arithmetic optimization algorithm for design of a microgrid with energy storage system: case study of El Kharga Oasis, EgyptJ. Energy Storage202251104343
– reference: Issa, M.; Abd Elaziz, M.: Analyzing COVID-19 virus based on enhanced fragmented biological Local Aligner using improved ions motion optimization algorithm. Appl Soft Comput, p. 106683 (2020)
– reference: SharmaAA Novel opposition-based arithmetic optimization algorithm for parameter extraction of PEM fuel cellElectronics202110222834
– reference: IssaMPID controller tuning parameters using meta-heuristics algorithms: comparative analysisMachine Learning Paradigms: Theory and Application2019Springer413430
– reference: ZhangXGaussian mutational chaotic fruit fly-built optimization and feature selectionExpert Syst. Appl.2020141
– reference: Hao, W.-K. et al.: Arithmetic optimization algorithm based on elementary function disturbance for solving economic load dispatch problem in power system. Appl. Intell.; p. 1–27 (2022)
– reference: WangG-GOpposition-based krill herd algorithm with Cauchy mutation and position clampingNeurocomputing2016177147157
– reference: JiaHDynamic harris hawks optimization with mutation mechanism for satellite image segmentationRemote sensing201911121421
– reference: Bora, T.C.; L.d.S. Coelho, and L. Lebensztajn, Bat-inspired optimization approach for the brushless DC wheel motor problem. IEEE Transactions on magnetics, 2012. 48(2): p. 947–950.
– reference: Malibari, A.A. et al.: Arithmetic optimization with retinanet model for motor imagery classification on brain computer interface. J. Healthcare Eng. (2022)
– reference: Ogata, K.; Yang, Y.: Modern control engineering. Vol. 4. Prentice hall India, Prentice (2002)
– reference: BansalJCFarswanPA novel disruption in biogeography-based optimization with application to optimal power flow problemAppl. Intell.2017463590615
– reference: KhodadadiNSnaselVMirjaliliSDynamic arithmetic optimization algorithm for truss optimization under natural frequency constraintsIEEE Access2022101618816208
– reference: Ahmadi, B. et al.: The Arithmetic optimization algorithm for optimal energy resource planning. In 2021 56th International Universities Power Engineering Conference (UPEC). IEEE (2021)
– reference: AgarwalJAnalysis of grey wolf optimizer based fractional order PID controller in speed control of DC motorMicrosyst. Technol.2018241249975006
– reference: ChenHParameters identification of photovoltaic cells and modules using diversification-enriched Harris hawks optimization with chaotic driftsJ. Clean. Prod.2020244
– reference: Ekinci, S. et al.: Speed control of DC motor using improved sine cosine algorithm based PID controller. In: 2019 3rd International Symposium on Multidisciplinary Studies and Innovative Technologies (ISMSIT). IEEE (2019)
– reference: Do, D.T. et al.: A hybrid arithmetic optimization algorithm and differential evolution for optimization of truss structures subjected to frequency constraints. J. Sci. Technol. Civil Eng. (STCE)-HUCE (2022)
– reference: AgarwalJParmarGGuptaRApplication of sine cosine algorithm in optimal control of DC motor and robustness analysisWulfenia J201724117795
– reference: Abbassi, A. et al.: Improved arithmetic optimization algorithm for parameters extraction of photovoltaic solar cell single-diode model. Arab. J. Sci. Eng.; p. 1–17 (2022)
– reference: Issa, M.: Sequence analysis algorithms for bioinformatics application. GRIN Verlag (2014)
– reference: IssaMA biological sub-sequences detection using integrated BA-PSO based on infection propagation mechanism: Case study COVID-19Expert Syst. Appl.2022189
– reference: Abd ElazizMImproving image thresholding by the type II fuzzy entropy and a hybrid optimization algorithmSoft. Comput.202024191488514905
– reference: LiuYHorizontal and vertical crossover of Harris hawk optimizer with Nelder-Mead simplex for parameter estimation of photovoltaic modelsEnergy Convers. Manage.2020223
– reference: Kennedy: Particle swarm optimization. Neural Netw (1995)
– reference: Issa, M.; Hassanien, A.E.: Multiple sequence alignment optimization using meta-heuristic techniques. In: Handbook of Research on Machine Learning Innovations and Trends. IGI Global. p. 409–423 (2017)
– reference: HeidariAAHarris hawks optimization: algorithm and applicationsFutur. Gener. Comput. Syst.201997849872
– reference: FathyAOptimal parameter identification of triple-junction photovoltaic panel based on enhanced moth search algorithmEnergy2019188
– reference: MirjaliliSMoth-flame optimization algorithm: a novel nature-inspired heuristic paradigmKnowl.Based Syst.201589228249
– reference: IssaMHelmiATwo layer hybrid scheme of IMO and PSO for optimization of local aligner: COVID-19 as a case studyArtificial Intelligence for COVID-192021Springer363381
– reference: BuiDTA novel swarm intelligence—Harris hawks optimization for spatial assessment of landslide susceptibilitySensors201919163590
– reference: BendjeghabaOContinuous firefly algorithm for optimal tuning of PID controller in AVR systemJ. Electr. Eng.201465144
– reference: ZhongCLiGComprehensive learning Harris hawks-equilibrium optimization with terminal replacement mechanism for constrained optimization problemsExpert Syst. Appl.2022192
– reference: HousseinEHA novel hybrid Harris hawks optimization and support vector machines for drug design and discoveryComput. Chem. Eng.2020133
– reference: Issa, M. et al. Pairwise Global Sequence Alignment Using Sine-Cosine Optimization Algorithm. In: International Conference on Advanced Machine Learning Technologies and Applications. Springer (2018)
– reference: NematollahiAFRahiminejadAVahidiBA novel physical based meta-heuristic optimization method known as lightning attachment procedure optimizationAppl. Soft Comput.201759596621
– reference: JordehiARParameter estimation of solar photovoltaic (PV) cells: A reviewRenew. Sustain. Energy Rev.201661354371
– reference: PremkumarMA new arithmetic optimization algorithm for solving real-world multiobjective CEC-2021 constrained optimization problems: diversity analysis and validationsIEEE Access202198426384295
– reference: HekimoğluBOptimal tuning of fractional order PID controller for DC motor speed control via chaotic atom search optimization algorithmIEEE Access201973810038114
– reference: IssaMExpeditious Covid-19 similarity measure tool based on consolidated SCA algorithm with mutation and opposition operatorsAppl. Soft Comput.2021104
– reference: Harwit, M.: Astrophysical Concepts. Springer Science & Business Media, Berlin (2006)
– reference: WolpertDHMacreadyWGNo free lunch theorems for optimizationIEEE Trans. Evol. Comput.1997116782
– reference: ZhangQChaos-induced and mutation-driven schemes boosting salp chains-inspired optimizersIEEE Access201973124331261
– reference: Singh, N. et al.;: HSSAHHO: a novel hybrid Salp swarm-Harris hawks optimization algorithm for complex engineering problems. J Ambient Intell Humanized Comput, p. 1–37 (2022)
– reference: XuYEnhanced Moth-flame optimizer with mutation strategy for global optimizationInf. Sci.20194921812033941398
– reference: IssaMSamnAPassive vehicle suspension system optimization using Harris Hawk Optimization algorithmMath. Comput. Simul.2022191328345430945407431708
– reference: Garzon Rivera, O.D. et al.: Application of the Arithmetic Optimization Algorithm to Solve the Optimal Power Flow Problem in Direct Current Networks. Available at SSRN, 4069702.
– reference: HamidzadehJFeature selection by using chaotic cuckoo optimization algorithm with levy flight, opposition-based learning and disruption operatorSoft. Comput.202125429112933
– reference: KhubalkarSModeling and control of a permanent-magnet brushless DC motor drive using a fractional order proportional-integral-derivative controllerTurk. J. Electr. Eng. Comput. Sci.201725542234241
– reference: Mahajan, S. et al.: Hybrid Aquila optimizer with arithmetic optimization algorithm for global optimization tasks. Soft Comput, p. 1–19 (2022)
– reference: Mahboob, A.S.; Moghaddam, M.R.O.; Yousefi. S.: AOV-IDS: arithmetic optimizer with voting classifier for intrusion detection system. In: 2021 12th International Conference on Information and Knowledge Technology (IKT). IEEE (2021)
– reference: RamachandranMA hybrid grasshopper optimization algorithm and harris hawks optimizer for combined heat and power economic dispatch problemEng. Appl. Artif. Intell.2022111
– volume: 7
  start-page: 31243
  year: 2019
  ident: 7136_CR74
  publication-title: IEEE Access
  doi: 10.1109/ACCESS.2019.2902306
– ident: 7136_CR48
  doi: 10.1109/IKT54664.2021.9685429
– volume: 104
  year: 2021
  ident: 7136_CR12
  publication-title: Appl. Soft Comput.
  doi: 10.1016/j.asoc.2021.107197
– start-page: 691
  volume-title: Metaheuristics in Machine Learning: Theory and Applications
  year: 2021
  ident: 7136_CR24
  doi: 10.1007/978-3-030-70542-8_28
– start-page: 153
  volume-title: Metaheuristics and Optimization in Computer and Electrical Engineering
  year: 2021
  ident: 7136_CR28
  doi: 10.1007/978-3-030-56689-0_8
– volume: 99
  start-page: 56
  year: 2018
  ident: 7136_CR11
  publication-title: Expert Syst. Appl.
  doi: 10.1016/j.eswa.2018.01.019
– volume: 177
  start-page: 147
  year: 2016
  ident: 7136_CR79
  publication-title: Neurocomputing
  doi: 10.1016/j.neucom.2015.11.018
– ident: 7136_CR13
– volume: 65
  start-page: 44
  issue: 1
  year: 2014
  ident: 7136_CR31
  publication-title: J. Electr. Eng.
– volume: 7
  start-page: 38100
  year: 2019
  ident: 7136_CR84
  publication-title: IEEE Access
  doi: 10.1109/ACCESS.2019.2905961
– ident: 7136_CR2
  doi: 10.5772/652
– ident: 7136_CR25
  doi: 10.1109/ICCPCT.2016.7530150
– ident: 7136_CR6
– ident: 7136_CR14
  doi: 10.4018/978-1-5225-2229-4.ch018
– volume: 24
  start-page: 14885
  issue: 19
  year: 2020
  ident: 7136_CR71
  publication-title: Soft. Comput.
  doi: 10.1007/s00500-020-04842-7
– volume: 23
  start-page: 6023
  issue: 15
  year: 2019
  ident: 7136_CR80
  publication-title: Soft. Comput.
  doi: 10.1007/s00500-018-3586-y
– ident: 7136_CR55
  doi: 10.31814/stce.huce(nuce)2022-16(2)-03
– volume: 133
  year: 2020
  ident: 7136_CR60
  publication-title: Comput. Chem. Eng.
  doi: 10.1016/j.compchemeng.2019.106656
– start-page: 363
  volume-title: Artificial Intelligence for COVID-19
  year: 2021
  ident: 7136_CR16
  doi: 10.1007/978-3-030-69744-0_21
– ident: 7136_CR29
– ident: 7136_CR64
  doi: 10.1007/s12652-022-03724-0
– ident: 7136_CR10
  doi: 10.1016/j.asoc.2020.106683
– ident: 7136_CR46
  doi: 10.1007/s13369-022-06605-y
– volume: 111
  year: 2022
  ident: 7136_CR63
  publication-title: Eng. Appl. Artif. Intell.
  doi: 10.1016/j.engappai.2022.104753
– volume: 192
  year: 2022
  ident: 7136_CR65
  publication-title: Expert Syst. Appl.
  doi: 10.1016/j.eswa.2021.116432
– volume: 38
  start-page: 727
  year: 2016
  ident: 7136_CR34
  publication-title: Appl. Soft Comput.
  doi: 10.1016/j.asoc.2015.10.041
– volume: 24
  start-page: 4997
  issue: 12
  year: 2018
  ident: 7136_CR32
  publication-title: Microsyst. Technol.
  doi: 10.1007/s00542-018-3920-4
– ident: 7136_CR81
  doi: 10.1109/ISMSIT.2019.8932907
– volume: 24
  start-page: 77
  issue: 11
  year: 2017
  ident: 7136_CR83
  publication-title: Wulfenia J
– volume: 10
  start-page: 2834
  issue: 22
  year: 2021
  ident: 7136_CR49
  publication-title: Electronics
  doi: 10.3390/electronics10222834
– volume: 1
  start-page: 67
  issue: 1
  year: 1997
  ident: 7136_CR35
  publication-title: IEEE Trans. Evol. Comput.
  doi: 10.1109/4235.585893
– volume: 79
  start-page: 112
  year: 2017
  ident: 7136_CR73
  publication-title: Exp. Syst. Appl.
  doi: 10.1016/j.eswa.2017.02.035
– ident: 7136_CR82
  doi: 10.1145/2001858.2002123
– volume: 59
  start-page: 596
  year: 2017
  ident: 7136_CR8
  publication-title: Appl. Soft Comput.
  doi: 10.1016/j.asoc.2017.06.033
– ident: 7136_CR77
  doi: 10.1109/SIS.2007.367959
– volume: 37
  start-page: 3741
  issue: 4
  year: 2021
  ident: 7136_CR57
  publication-title: Eng. Comput.
  doi: 10.1007/s00366-020-01028-5
– ident: 7136_CR4
  doi: 10.1002/9780470496916
– ident: 7136_CR3
  doi: 10.1115/1.4019264
– volume: 61
  start-page: 354
  year: 2016
  ident: 7136_CR20
  publication-title: Renew. Sustain. Energy Rev.
  doi: 10.1016/j.rser.2016.03.049
– volume: 9
  start-page: 1155
  issue: 7
  year: 2021
  ident: 7136_CR38
  publication-title: Processes
  doi: 10.3390/pr9071155
– volume: 97
  start-page: 849
  year: 2019
  ident: 7136_CR56
  publication-title: Futur. Gener. Comput. Syst.
  doi: 10.1016/j.future.2019.02.028
– ident: 7136_CR15
  doi: 10.1007/978-3-319-74690-6_11
– volume: 19
  start-page: 384
  issue: 2
  year: 2004
  ident: 7136_CR23
  publication-title: IEEE Trans. Energy Convers.
  doi: 10.1109/TEC.2003.821821
– volume: 238
  start-page: 106
  year: 2014
  ident: 7136_CR67
  publication-title: Appl. Math. Comput.
– volume: 10
  start-page: 287
  issue: 2
  year: 2019
  ident: 7136_CR30
  publication-title: Ain Shams Eng. J.
  doi: 10.1016/j.asej.2018.07.005
– volume: 376
  year: 2021
  ident: 7136_CR36
  publication-title: Comput. Methods Appl. Mech. Eng.
  doi: 10.1016/j.cma.2020.113609
– volume: 191
  start-page: 328
  year: 2022
  ident: 7136_CR22
  publication-title: Math. Comput. Simul.
  doi: 10.1016/j.matcom.2021.08.016
– ident: 7136_CR47
  doi: 10.1109/UPEC50034.2021.9548204
– ident: 7136_CR54
  doi: 10.1007/s12065-022-00711-4
– volume: 188
  year: 2019
  ident: 7136_CR72
  publication-title: Energy
  doi: 10.1016/j.energy.2019.116025
– volume: 16
  issue: 8
  year: 2021
  ident: 7136_CR52
  publication-title: PLoS ONE
  doi: 10.1371/journal.pone.0255703
– volume: 492
  start-page: 181
  year: 2019
  ident: 7136_CR76
  publication-title: Inf. Sci.
  doi: 10.1016/j.ins.2019.04.022
– volume: 9
  start-page: 84263
  year: 2021
  ident: 7136_CR37
  publication-title: IEEE Access
  doi: 10.1109/ACCESS.2021.3085529
– volume: 141
  year: 2020
  ident: 7136_CR78
  publication-title: Expert Syst. Appl.
  doi: 10.1016/j.eswa.2019.112976
– volume: 96
  start-page: 120
  year: 2016
  ident: 7136_CR5
  publication-title: Knowl.Based Syst.
  doi: 10.1016/j.knosys.2015.12.022
– start-page: 413
  volume-title: Machine Learning Paradigms: Theory and Application
  year: 2019
  ident: 7136_CR19
  doi: 10.1007/978-3-030-02357-7_20
– ident: 7136_CR44
– volume: 25
  start-page: 2911
  issue: 4
  year: 2021
  ident: 7136_CR68
  publication-title: Soft. Comput.
  doi: 10.1007/s00500-020-05349-x
– volume: 223
  year: 2020
  ident: 7136_CR62
  publication-title: Energy Convers. Manage.
  doi: 10.1016/j.enconman.2020.113211
– volume: 11
  start-page: 1421
  issue: 12
  year: 2019
  ident: 7136_CR75
  publication-title: Remote sensing
  doi: 10.3390/rs11121421
– volume: 189
  year: 2022
  ident: 7136_CR17
  publication-title: Expert Syst. Appl.
  doi: 10.1016/j.eswa.2021.116063
– volume: 145
  year: 2020
  ident: 7136_CR69
  publication-title: Expert Syst. Appl.
  doi: 10.1016/j.eswa.2019.113103
– ident: 7136_CR43
  doi: 10.1007/s10489-021-03125-4
– volume: 19
  start-page: 3590
  issue: 16
  year: 2019
  ident: 7136_CR61
  publication-title: Sensors
  doi: 10.3390/s19163590
– volume: 89
  start-page: 228
  year: 2015
  ident: 7136_CR9
  publication-title: Knowl.Based Syst.
  doi: 10.1016/j.knosys.2015.07.006
– volume: 244
  year: 2020
  ident: 7136_CR58
  publication-title: J. Clean. Prod.
  doi: 10.1016/j.jclepro.2019.118778
– ident: 7136_CR18
  doi: 10.1109/TMAG.2011.2176108
– volume: 25
  start-page: 4223
  issue: 5
  year: 2017
  ident: 7136_CR26
  publication-title: Turk. J. Electr. Eng. Comput. Sci.
  doi: 10.3906/elk-1612-277
– ident: 7136_CR40
  doi: 10.1109/MPS52805.2021.9492572
– ident: 7136_CR45
  doi: 10.1155/2022/3987494
– volume: 77
  start-page: 418
  year: 2016
  ident: 7136_CR33
  publication-title: Int. J. Electr. Power Energy Syst.
  doi: 10.1016/j.ijepes.2015.11.010
– volume: 51
  start-page: 104343
  year: 2022
  ident: 7136_CR42
  publication-title: J. Energy Storage
  doi: 10.1016/j.est.2022.104343
– volume: 32
  start-page: 72
  year: 2015
  ident: 7136_CR7
  publication-title: Appl. Soft Comput.
  doi: 10.1016/j.asoc.2015.03.035
– ident: 7136_CR1
– ident: 7136_CR41
  doi: 10.1155/2021/9114113
– volume: 9
  start-page: 2321
  issue: 18
  year: 2021
  ident: 7136_CR51
  publication-title: Mathematics
  doi: 10.3390/math9182321
– ident: 7136_CR66
– volume: 10
  start-page: 16188
  year: 2022
  ident: 7136_CR39
  publication-title: IEEE Access
  doi: 10.1109/ACCESS.2022.3146374
– volume: 24
  start-page: 331
  issue: 2
  year: 2021
  ident: 7136_CR27
  publication-title: Eng Sci Technol Int J
– volume: 46
  start-page: 590
  issue: 3
  year: 2017
  ident: 7136_CR70
  publication-title: Appl. Intell.
  doi: 10.1007/s10489-016-0848-1
– volume: 9
  start-page: 1774
  issue: 10
  year: 2021
  ident: 7136_CR50
  publication-title: Processes
  doi: 10.3390/pr9101774
– ident: 7136_CR53
  doi: 10.1007/s00500-022-06873-8
– volume: 7
  start-page: 76529
  year: 2019
  ident: 7136_CR59
  publication-title: IEEE Access
  doi: 10.1109/ACCESS.2019.2921545
– ident: 7136_CR21
  doi: 10.1007/978-3-030-04792-4_8
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Snippet The Proportional-Integral-Derivative (PID) controller is a key component in most engineering applications. The main disadvantage of PID is the selection of the...
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SubjectTerms Algorithms
Arithmetic
Computer Engineering and Computer Science
Controllers
D C motors
Electric motors
Engineering
Humanities and Social Sciences
Lower bounds
Mathematical analysis
multidisciplinary
Mutation
Optimization
Optimization algorithms
Parameter estimation
Perturbation
Proportional integral derivative
Research Article-Computer Engineering and Computer Science
Science
Title Enhanced Arithmetic Optimization Algorithm for Parameter Estimation of PID Controller
URI https://link.springer.com/article/10.1007/s13369-022-07136-2
https://www.ncbi.nlm.nih.gov/pubmed/36042895
https://www.proquest.com/docview/2774560122
https://pubmed.ncbi.nlm.nih.gov/PMC9411853
Volume 48
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