Research and Implementation of Intelligent Control System for Grassland Grazing Robotic Vehicle
In response to the complex animal husbandry environment, wide livestock range, and labor shortage in Inner Mongolia grasslands, this study designed an intelligent control system for robotic vehicles used in natural grazing grassland environments. The control system consists of software and hardware...
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MDPI AG
2023-07-01
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Series: | Electronics |
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Online Access: | https://www.mdpi.com/2079-9292/12/14/3078 |
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author | Hongyuan Zhang Mingjuan Han Yajie Mi Jile Xin Wei Fan Ding Han |
author_facet | Hongyuan Zhang Mingjuan Han Yajie Mi Jile Xin Wei Fan Ding Han |
author_sort | Hongyuan Zhang |
collection | DOAJ |
description | In response to the complex animal husbandry environment, wide livestock range, and labor shortage in Inner Mongolia grasslands, this study designed an intelligent control system for robotic vehicles used in natural grazing grassland environments. The control system consists of software and hardware components and motion control algorithms. Based on the application characteristics of different mechanisms of the robotic vehicle, the motion control of the robotic vehicle is decomposed into longitudinal speed control and lateral steering control. The longitudinal speed control adopts the traditional Proportional-Integral-Differential (PID) control method. Since the hardware composition and internal angle calculation method of the steering system are complex and prone to deviations caused by external terrain, a lateral adaptive fuzzy PID controller was constructed with lateral deviation and deviation change rate as input variables and parameters <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><msub><mi>K</mi><mi>p</mi></msub></mrow></semantics></math></inline-formula>, <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><msub><mi>K</mi><mi>i</mi></msub></mrow></semantics></math></inline-formula>, and <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><msub><mi>K</mi><mi>d</mi></msub></mrow></semantics></math></inline-formula> as outputs. The field test results show that when the longitudinal speed was set to 0.5 m/s, the adjustment time was 1.95 s, and the steady-state error was about 0. When the longitudinal speed was the same, the lateral adaptive fuzzy PID controller reduced the rise time by 0.77 s compared to traditional control methods, reduced overshoot and steady-state error by 2%, and quickly recovered to a steady state after being disturbed. The following test results show that the designed intelligent control system can achieve real-time tracking of targets and that the motion controllers can effectively control speed and steering angle. Therefore, the intelligent control system designed in this paper can effectively achieve stable and real-time control of the robotic vehicle. |
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language | English |
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spelling | doaj.art-3e9a38308e1d4eb2b1412188381280782023-11-18T19:05:31ZengMDPI AGElectronics2079-92922023-07-011214307810.3390/electronics12143078Research and Implementation of Intelligent Control System for Grassland Grazing Robotic VehicleHongyuan Zhang0Mingjuan Han1Yajie Mi2Jile Xin3Wei Fan4Ding Han5College of Electronic Information Engineering, Inner Mongolia University, Hohhot 010021, ChinaCollege of Electronic Information Engineering, Inner Mongolia University, Hohhot 010021, ChinaCollege of Electronic Information Engineering, Inner Mongolia University, Hohhot 010021, ChinaCollege of Electronic Information Engineering, Inner Mongolia University, Hohhot 010021, ChinaCollege of Electronic Information Engineering, Inner Mongolia University, Hohhot 010021, ChinaCollege of Electronic Information Engineering, Inner Mongolia University, Hohhot 010021, ChinaIn response to the complex animal husbandry environment, wide livestock range, and labor shortage in Inner Mongolia grasslands, this study designed an intelligent control system for robotic vehicles used in natural grazing grassland environments. The control system consists of software and hardware components and motion control algorithms. Based on the application characteristics of different mechanisms of the robotic vehicle, the motion control of the robotic vehicle is decomposed into longitudinal speed control and lateral steering control. The longitudinal speed control adopts the traditional Proportional-Integral-Differential (PID) control method. Since the hardware composition and internal angle calculation method of the steering system are complex and prone to deviations caused by external terrain, a lateral adaptive fuzzy PID controller was constructed with lateral deviation and deviation change rate as input variables and parameters <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><msub><mi>K</mi><mi>p</mi></msub></mrow></semantics></math></inline-formula>, <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><msub><mi>K</mi><mi>i</mi></msub></mrow></semantics></math></inline-formula>, and <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><msub><mi>K</mi><mi>d</mi></msub></mrow></semantics></math></inline-formula> as outputs. The field test results show that when the longitudinal speed was set to 0.5 m/s, the adjustment time was 1.95 s, and the steady-state error was about 0. When the longitudinal speed was the same, the lateral adaptive fuzzy PID controller reduced the rise time by 0.77 s compared to traditional control methods, reduced overshoot and steady-state error by 2%, and quickly recovered to a steady state after being disturbed. The following test results show that the designed intelligent control system can achieve real-time tracking of targets and that the motion controllers can effectively control speed and steering angle. Therefore, the intelligent control system designed in this paper can effectively achieve stable and real-time control of the robotic vehicle.https://www.mdpi.com/2079-9292/12/14/3078grassland grazing robotic vehicleintelligent control systemadaptive fuzzy PID controlintelligent animal husbandry |
spellingShingle | Hongyuan Zhang Mingjuan Han Yajie Mi Jile Xin Wei Fan Ding Han Research and Implementation of Intelligent Control System for Grassland Grazing Robotic Vehicle Electronics grassland grazing robotic vehicle intelligent control system adaptive fuzzy PID control intelligent animal husbandry |
title | Research and Implementation of Intelligent Control System for Grassland Grazing Robotic Vehicle |
title_full | Research and Implementation of Intelligent Control System for Grassland Grazing Robotic Vehicle |
title_fullStr | Research and Implementation of Intelligent Control System for Grassland Grazing Robotic Vehicle |
title_full_unstemmed | Research and Implementation of Intelligent Control System for Grassland Grazing Robotic Vehicle |
title_short | Research and Implementation of Intelligent Control System for Grassland Grazing Robotic Vehicle |
title_sort | research and implementation of intelligent control system for grassland grazing robotic vehicle |
topic | grassland grazing robotic vehicle intelligent control system adaptive fuzzy PID control intelligent animal husbandry |
url | https://www.mdpi.com/2079-9292/12/14/3078 |
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