Lei Liu , Siyu Hou , Yuefeng Du , Guorun Li , Yucong Wang , Du Chen , Zhongxiang Zhu , Zhenghe Song , Xiaoyu Li
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引用次数: 0
Abstract
The cooperative operation between the self-propelled forage harvester and the trailer aims to achieve precise and automatic forage unloading. The discharge arm serves as the core structure for conveying forage, and the precision and speed of its motion control are crucial factors influencing the efficiency of forage harvesting. In this context, we proposed a trajectory tracking control method for the discharge arm based on an improved particle swarm optimization (IPSO)-PID controller. Firstly, we utilized the Denavit-Hartenberg (D-H) model of the discharge arm for a positive kinematics solution and the geometric resolution and linear fitting method for the inverse kinematics solution. Secondly, we employed the polynomial interpolation method for trajectory planning on the joint space of the discharge arm, and the PSO algorithm for time-optimal trajectory planning. Then, we designed an IPSO-PID trajectory tracking control algorithm and built an Amesim-Simulink co-simulation model for multiple simulation experiments. Finally, we conducted several performance tests of the discharge arm automatic control system in the workstation and the field, respectively. The experiment results indicate that the performance of the IPSO-PID controller exceeds that of all other controllers, which can meet the discharge arm’s motion control accuracy and speed requirements. Our research results are of great significance for improving the productivity and automation process of the self-propelled forage harvester and provide valuable references for research on automatic and precise control of material loading in other agricultural cooperative harvesting.
期刊介绍:
Computers and Electronics in Agriculture provides international coverage of advancements in computer hardware, software, electronic instrumentation, and control systems applied to agricultural challenges. Encompassing agronomy, horticulture, forestry, aquaculture, and animal farming, the journal publishes original papers, reviews, and applications notes. It explores the use of computers and electronics in plant or animal agricultural production, covering topics like agricultural soils, water, pests, controlled environments, and waste. The scope extends to on-farm post-harvest operations and relevant technologies, including artificial intelligence, sensors, machine vision, robotics, networking, and simulation modeling. Its companion journal, Smart Agricultural Technology, continues the focus on smart applications in production agriculture.