Fertilization Control System Research in Orchard Based on the PSO-BP-PID Control Algorithm

Article Computer Science, Artificial Intelligence

Drag coefficient modeling of heterogeneous connected platooning vehicles via BP neural network and PSO algorithm

Qianyue Luo et al.

Summary: This paper investigates the modeling and estimation of the drag coefficient for connected platooning vehicles (CPVs) and proposes an effective estimation method. Numerical analysis and an optimization algorithm are employed to validate the accuracy of the model.

NEUROCOMPUTING (2022)

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Article Engineering, Chemical

Control System of Liquid Fertilizer Variable-Rate Fertilization Based on Beetle Antennae Search Algorithm

Jinbin Bai et al.

Summary: A control system for variable-rate fertilization of liquid fertilizer based on beetle antennae search algorithm was proposed to solve the problems of low precision and uneven flow of field liquid fertilizer applicator. The system achieved high precision and uniform flow by optimizing the parameters of PID. The control effect of the system was validated through bench test.

PROCESSES (2022)

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Article Agronomy

Design and Experimental Testing of a Control System for a Solid-Fertilizer-Dissolving Device Based on Fuzzy PID

Xiuhua Song et al.

Summary: A closed-loop control system based on fuzzy PID was designed and tested to overcome the poor uniformity issue of solid-fertilizer-dissolving devices. The system used an STM32 to detect electrical conductivity and adjust fertilizer and water flow rates in real-time. The control system demonstrated good stability, speed, and accuracy, improving the fertilization uniformity of the solid-fertilizer-dissolving device. This study lays the foundation for further research on fertilization control systems and provides a reference for precise and intelligent fertigation development.

AGRICULTURE-BASEL (2022)

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Article Chemistry, Multidisciplinary

An Improved PID Controller for the Compliant Constant-Force Actuator Based on BP Neural Network and Smith Predictor

Guojin Pei et al.

Summary: A compliant constant-force actuator based on the cylinder is an important tool for robot contact operations, and the traditional PID method may not work well due to the nonlinearity and time delay of the pneumatic system. The proposed improved PID control method combining BP neural network and the Smith predictor shows better performance in shortening maximum overshoot and adjustment time, as validated through MATLAB simulation and experiments.

APPLIED SCIENCES-BASEL (2021)

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Article Engineering, Chemical

Adaptive PID Control and Its Application Based on a Double-Layer BP Neural Network

Ming-Li Zhang et al.

Summary: This paper proposes a method using double-layer BP neural networks to learn the law of PID control parameters, which was verified to be effective through simulation and experiment. It provides theoretical and experimental basis for the selection of control parameters, and can be extended to similar controllers, showing engineering application value.

PROCESSES (2021)

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Article Automation & Control Systems