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Article type: Research Article
Authors: Sun, Ruixiaa | Xiao, Pingb; c; * | Tang, Weia; d | Chen, Longa | Chen, Dandana
Affiliations: [a] School of Electrical Engineering, Anhui Polytechnic University, Wuhu, China | [b] School of Mechanical Engineering, Anhui Polytechnic University, Wuhu, China | [c] School of Engineering, University of Bridgeport, Bridgeport, CT, USA | [d] Anhui Province Key Laboratory of Intelligent Car Wire-Controlled Chassis System, Anhui Polytechnic University, Wuhu, China
Correspondence: [*] Corresponding author. Ping Xiao, E-mail: [email protected].
Abstract: In order to further enhance energy conservation and emission reduction, the header lifting structure of a harvester is studied. First, a double electric pushrod structure is used to replace the oil cylinder and air cylinder lifting structure of a traditional header to reduce fuel consumption and harmful gas emission. Furthermore, a mathematical model and a simulation model of the electric pushrod are established. To enhance the control effect of the header lifting structure, an improved version of the traditional gray wolf optimization (GWO) algorithm is designed. The nonlinear convergence factor, Kent chaotic mapping and convergence surrounding and spiral updating operations are introduced to increase the convergence speed and optimization accuracy of this algorithm. The improved GWO (IGWO) algorithm is applied to optimize the proportional-integral-derivative (PID) controller of the double pushrod coordinated control system. Then, a new IGWO-PID control algorithm is also designed. The cross-coupling control strategy of header’s double pushrods is then studied. Results of the simulation and bench test show that the IGWO-PID control algorithm and the cross-coupling control strategy can effectively enhance controlling effect of the harvester header. The left and right pushrods can achieve good synchronous and coordinated movements.
Keywords: Harvester header, electric pushrod, IGWO-PID control algorithm, cross-coupled collocated control
DOI: 10.3233/JIFS-231193
Journal: Journal of Intelligent & Fuzzy Systems, vol. 46, no. 2, pp. 4941-4953, 2024
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