摘要
为解决智能灌溉系统中水泵运行的不稳定问题,基于人群搜索优化算法(Seeker optimization algorithm,SOA)实现了PID(Proportion integration differentiation)参数的自动优化。该优化算法能够有效解决智能灌溉系统水泵控制中的非线性、时变性和滞后性等问题。为验证SOA优化PID控制的实际效果,与PSO(Particle swarm optimization)算法和GA(Genetic algorithms)算法优化的PID控制进行比较。仿真实验结果表明,基于SOA优化的PID控制响应时间短、超调量小,稳态过程没有振荡。因此,适用于智能灌溉系统中的水泵控制。
The control of water pump water supply is an important part of the intelligent irrigation control system. The water supply in the water supply process is beneficial to the development of crop roots and the absorption of minerals in the soil within the optimal control range. In the intelligent irrigation control,due to the nonlinear,time-varying and hysteresis problems of the pump control,the traditional proportion integration differentiation( PID) control is difficult to achieve good control effects. In order to solve the instability problem of pump control in intelligent irrigation system,based on the traditional PID control algorithm,the seeker optimization algorithm( SOA) was used to optimize PID control. The results showed that the optimal control algorithm can effectively solve the problems of nonlinearity,time-varying and hysteresis in the control of intelligent irrigation pumps. In order to verify the actual effect of SOA optimization PID control,it was compared with particle swarm optimization( PSO) optimized PID control and genetic algorithms( GA) optimized PID control. The experimental simulation results showed that the PID control based on SOA optimization had the shortest response time,smallest overshoot,and no oscillation in the steady state process. Therefore,it was suitable for pump control in intelligent irrigation systems.
作者
许景辉
王雷
谭小强
王一琛
赵钟声
邵明烨
XU Jinghui;WANG Lei;TAN Xiaoqiang;WANG Yichen;ZHAO Zhongsheng;SHAO Mingye(Key Laboratory of Agricultural Soil and Water Engineering in Arid and Semiarid Areas,Ministry of Education,Northwest A&F University,Yangling,Shaanxi 712100,China;College of Water Resources and Architectural Engineering,Northwest A&F University,Yangling,Shaanxi 712100,China;College of Mechanical and Electronic Engineering,Northwest A&F University,Yangling,Shaanxi 712100,China)
出处
《农业机械学报》
EI
CAS
CSCD
北大核心
2020年第4期261-267,共7页
Transactions of the Chinese Society for Agricultural Machinery
基金
国家重点研发计划项目(2017YFC0403203)
陕西水利科技计划项目(2014slkj-18)。
