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Kinetic Mechanical Engineering, 2023, 4(2); doi: 10.38007/KME.2023.040201.

Optimal Control Strategy of Construction Machinery Motor Considering Genetic Algorithm


Aghenta Lawrence

Corresponding Author:
Aghenta Lawrence

BIHER, BIST, Dept Comp Sci & Engn, Chennai, Tamil Nadu, India


Genetic algorithm is a global search optimization method, which has high efficiency and robustness in solving the control problems of complex systems. This paper first introduces the basic theory of genetic algorithm, coding method, fitness function design principle and other basic theoretical knowledge, then analyzes and studies them according to the model, establishes a simple and fast mathematical equation to solve the motor position and speed distribution law, and constructs a multi-objective optimization problem with robustness and efficiency based on the standard normal form system dynamic characteristic parameter self-tuning network. The test results show that the genetic algorithm can get an optimal solution when setting PID parameters, and the time to find the global optimal value is fast.


Genetic Algorithm, Construction Machinery, Machine Optimization, Control Strategy

Cite This Paper

Aghenta Lawrence. Optimal Control Strategy of Construction Machinery Motor Considering Genetic Algorithm. Kinetic Mechanical Engineering (2023), Vol. 4, Issue 2: 1-9. https://doi.org/10.38007/KME.2023.040201.


[1] Elena L. Kulida:Genetic Algorithm for Solving the Problem of Optimizing Aircraft Landing Sequence and Times. Autom. Remote. Control. 83(3): 426-436 (2021). https://doi.org/10.1134/S0005117922030109

[2] A. Jameer Basha, S. Aswini, S. Aarthini, Yunyoung Nam, Mohamed Abouhawwash:Genetic-Chicken Swarm Algorithm for Minimizing Energy in Wireless Sensor Network. Comput. Syst. Sci. Eng. 44(2): 1451-1466 (2023). 

[3]  K. Jagadeesh, A. Rajendran:Improved Model for Genetic Algorithm-Based Accurate Lung Cancer Segmentation and Classification. Comput. Syst. Sci. Eng. 45(2): 2017-2032 (2023). 

[4] yed Mahdi Homayouni, Dalila B. M. M. Fontes, José Fernando Gonçalves:A multistart biased random key genetic algorithm for the flexible job shop scheduling problem with transportation. Int. Trans. Oper. Res. 30(2): 688-716 (2023). 

[5] M. Mythreyee, A. Nalini:Genetic Algorithm Based Smart Grid System for Distributed Renewable Energy Sources. Comput. Syst. Sci. Eng. 45(1): 819-837 (2023). 

[6] Maryam Majidi, Rahil Mahdian Toroghi:A combination of multi-objective genetic algorithm and deep learning for music harmony generation. Multim. Tools Appl. 82(2): 2419-2435 (2023). 

[7] Antonio Alexandre Moura Costa, Felipe Barbosa Araújo Ramos, Mirko Barbosa Perkusich, Ademar França de Sousa Neto, Luiz Silva, Felipe Cunha, Thiago Rique, Hyggo O. Almeida, Angelo Perkusich:A Genetic Algorithm-Based Approach to Support Forming Multiple Scrum Project Teams. IEEE Access 10: 68981-68994 (2021). 

[8] Yang Cao, Wei Feng, Yinghui Quan, Wenxing Bao, Gabriel Dauphin, Yijia Song, Aifeng Ren, Mengdao Xing:A Two-Step Ensemble-Based Genetic Algorithm for Land Cover Classification. IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens. 16: 409-418 (2023). 

[9] Nazeeh Ghatasheh, Ismail Al-Taharwa, Khaled Aldebei:Modified Genetic Algorithm for Feature Selection and Hyper Parameter Optimization: Case of XGBoost in Spam Prediction. IEEE Access 10: 84365-84383 (2021).

[10] Bahram Mahjoob Karambasti, Mohamad Naghashzadegan, Maryam Ghodrat, Ghadir Ghorbani, Roy B. V. B. Simorangkir, Ali Lalbakhsh:Optimal Solar Greenhouses Design Using Multiobjective Genetic Algorithm. IEEE Access 10: 73728-73742 (2021). 

[11] Karima Khadir, Nawal Guermouche, Amal Guittoum, Thierry Monteil:A Genetic Algorithm-Based Approach for Fluctuating QoS Aware Selection of IoT Services. IEEE Access 10: 17946-17965 (2021). 

[12]  Pintu Kumar Ram, Pratyay Kuila:GAAE: a novel genetic algorithm based on autoencoder with ensemble classifiers for imbalanced healthcare data. J. Supercomput. 79(1): 541-572 (2023). 

[13]  Elena L. Kulida:Genetic Algorithm for Solving the Problem of Optimizing Aircraft Landing Sequence and Times. Autom. Remote. Control. 83(3): 426-436 (2022).

[14]  Zahra Fattahi, Javad Behnamian:Location and transportation of intermodal hazmat considering equipment capacity and congestion impact: elastic method and sub-population genetic algorithm. Ann. Oper. Res. 316(1): 303-341 (2022). 

[15]  Manuel Luna, Ignacio Llorente, Angel Cobo:Determination of feeding strategies in aquaculture farms using a multiple-criteria approach and genetic algorithms. Ann. Oper. Res. 314(2): 551-576 (2022).

[16] Gagan Deep Singh, Manish Prateek, Sunil Kumar, Madhushi Verma, Dilbag Singh, Heung-No Lee:Hybrid Genetic Firefly Algorithm-Based Routing Protocol for VANETs. IEEE Access 10: 9142-9151 (2021). 

[17] Atefeh Taghavi, Reza Ghanbari, Khatere Ghorbani-Moghadam, Alireza Davoodi, Ali Emrouznejad:A genetic algorithm for solving bus terminal location problem using data envelopment analysis with multi-objective programming. Ann. Oper. Res. 309(1): 259-276 (2022). 

[18] Li Li, Tian Qiu, Tichang Jia, Chen Chen:Stepping quantum genetic algorithm-based LQR control strategy for lateral vibration of high-speed elevator. Autom. 70(7): 623-634 (2022).