Design of an Automated System for Cattle-Feed Dispensing in Cattle-Cows

Quintanilla-Mosquera, Iraiz Lucero; Fierro, Jesus Eduardo Rosales; Ortiz-Zacarias, Jhon Rodrigo; Montero, Jhamir Beltran; Quijano, Sario Angel Chamorro; Huamanchahua, Deyby

doi:10.1109/uemcon53757.2021.9666491

Cited by 21 publications

(1 citation statement)

References 18 publications

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“…L. Peng et al developed an intelligent pig feeding system based on PLC, which has three parts: automatic feeding, environmental control, and an upper computer control interface; real-time control was achieved through the interface, which greatly improves the efficiency of pig feeding [3]. Mosquera et al developed an automatic feeding system for dairy cows based on PLC that used multiple sensors and robotic arms for precise feeding, while also optimizing the feed ratio based on the weight of the milk [4]. C. Long et al designed a mobile monitoring robot for livestock and poultry houses that monitored the breeding environment through various sensors and livestock using cameras and infrared temperature measuring devices.…”

Section: Introductionmentioning

confidence: 99%

Research and Implementation of Intelligent Control System for Grassland Grazing Robotic Vehicle

Zhang

Mei

et al. 2023

Electronics

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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 Kp, Ki, and Kd 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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Section: Introductionmentioning

confidence: 99%