Comparison between Genetic Programming and Dynamic Models for Compact Electrohydraulic Actuators

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@Article{bamshad:2022:Machines,

• author = "Hamid Bamshad and Seongwon Jang and Hyemi Jeong and Jaesung Lee and Hyunseok Yang",
• title = "Comparison between Genetic Programming and Dynamic Models for Compact Electrohydraulic Actuators",
• journal = "Machines",
• year = "2022",
• volume = "10",
• number = "10",
• pages = "Article No. 961",
• keywords = "genetic algorithms, genetic programming",
• ISSN = "2075-1702",
• URL = "https://www.mdpi.com/2075-1702/10/10/961",
• DOI = "doi:10.3390/machines10100961",
• abstract = "A compact electrohydraulic actuator (C-EHA) is an innovative hydraulic system with a wide range of applications, particularly in automation, robotics, and aerospace. The actuator provides the benefits of hydraulics without the expense and space requirements of full-sized hydraulic systems and in a much cleaner manner. However, this actuator is associated with some disadvantages, such as a high level of nonlinearity, uncertainty, and a lack of studies. The development of a robust controller requires a thorough understanding of the system behaviour as well as an accurate dynamic model of the system; however, finding an accurate dynamic model of a system is not always straightforward, and it is considered a significant challenge for engineers, particularly for a C-EHA because the critical parameters inside cannot be accessed. Our research aims to evaluate and confirm the ability of genetic programming (GP) to model a nonlinear system for a C-EHA. In our paper, we present and develop a GP model for the C-EHA system. Furthermore, our study presents a dynamic model of the system for comparison with the GP model. As a result, by using this actuator in the 1-DOF arm system and conducting experiments, we confirmed that the GP model has a better performance with less positional error compared with the proposed dynamic model. The model can be used to conduct further studies, such as designing controllers or system simulations.",
• notes = "also known as \cite{machines10100961}",

}

Genetic Programming entries for Hamid Bamshad Seongwon Jang Hyemi Jeong Jaesung Lee Hyunseok Yang

Citations