Optimal Design of Agricultural Mobile Robot Suspension System Based on NSGA-III and TOPSIS

Zhanghao Qu, Peng Zhang, Yaohua Hu, Huanbo Yang, Taifeng Guo, Kaili Zhang and Junchang Zhang ()
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Zhanghao Qu: College of Mechanical and Electronic Engineering, Northwest A&F University, Xianyang 712100, China
Peng Zhang: College of Mechanical and Electronic Engineering, Northwest A&F University, Xianyang 712100, China
Yaohua Hu: College of Optical, Mechanical, and Electrical Engineering, Zhejiang A&F University, Hangzhou 311300, China
Huanbo Yang: College of Mechanical and Electronic Engineering, Northwest A&F University, Xianyang 712100, China
Taifeng Guo: College of Mechanical and Electronic Engineering, Northwest A&F University, Xianyang 712100, China
Kaili Zhang: College of Mechanical and Electronic Engineering, Northwest A&F University, Xianyang 712100, China
Junchang Zhang: College of Mechanical and Electronic Engineering, Northwest A&F University, Xianyang 712100, China

Agriculture, 2023, vol. 13, issue 1, 1-20

Abstract: The stability of vehicles is influenced by the suspension system. At present, there are many studies on the suspension of traditional passenger vehicles, but few are related to agricultural mobile robots. There are structural differences between the suspension system of agricultural mobile robots and passenger vehicles, which requires structural simplification and modelling concerning suspension of agricultural mobile robots. This study investigates the optimal design for an agricultural mobile robot’s suspension system designed based on a double wishbone suspension structure. The dynamics of the quarter suspension system were modelled based on Lagrange’s equation. In our work, the non-dominated sorting genetic algorithm III (NSGA-III) was selected for conducting multi-objective optimization of the suspension design, combined with the Technique for Order Preference by Similarity to the Ideal Solution (TOPSIS) to choose the optimal combination of parameters in the non-dominated solution set obtained by NSGA-III. We compared the performance of NSGA-III with that of other multi-objective evolutionary algorithms (MOEAs). Compared with the second-scoring solution, the score of the optimal solution obtained by NSGA-III increased by 4.92%, indicating that NSGA-III has a significant advantage in terms of the solution quality and robustness for the optimal design of the suspension system. This was verified by simulation in Adams that our method, which utilizes multibody dynamics, NSGA-III and TOPSIS, is feasible to determine the optimal design of a suspension system for an agricultural mobile robot.

Keywords: multi-objective evolutionary algorithms; double wishbone mechanisms; multibody dynamics; pareto solution set (search for similar items in EconPapers)
JEL-codes: Q1 Q10 Q11 Q12 Q13 Q14 Q15 Q16 Q17 Q18 (search for similar items in EconPapers)
Date: 2023
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

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