基于模糊PID的变量液体施肥控制系统
|
摘要
变量液体施肥控制系统具有大惯性、非线性和参数时变的特点,采用传统的PID控制方法很难实现准确的控制。为此,在建立电动执行器的数学模型的基础上,采用自适应模糊PID对液体肥流量进行自动控制,并利用Mat Lab对变量液体施肥控制系统进行建模和仿真及实验验证。仿真与实验结果表明:变量液体施肥控制系统采仿真时,自适应模糊PID控制系统的动态静态指标明显高于常规PID控制;系统超调量、调整时间明显改善,即超调量为1.5%,系统进入稳态所需时间为0.86s。变量液体施肥控制系统实验时,PID控制变量液体施肥系统的响应时间为1.6s,超调量为7.8%。模糊PID控制变量液体施肥系统的响应时间为0.8s,超调量为0,使施肥量更有效地保持在给定范围。该方法可为变量液体施肥控制提供一种有效的控制方法。
According to the variable flow characteristic of the control system of liquid fertilizer,the traffic system has the characteristics of large inertia,nonlinear and parameter time-varying,the traditional PID control method is difficult to achieve accurate control,so this article on the basis of establishing the mathematical model of electric actuator,using adaptive fuzzy PID automatic control was carried out on the liquid flow.Using MATLAB Simulink and Fuzzy tools for adaptive Fuzzy PID variable liquid fertilizer control system modeling and simulation.The simulation and experimental results show that the dynamic and static index of adaptive fuzzy PID control system is significantly higher than that of conventional PID control when the variable liquid fertilization control system is simulated.In the system overshoot,the adjustment time is obviously improved,the overshoot amount is 1.5 %,and the time required for the system to enter the steady state is 0.8 6s.The response time of the PID control variable liquid fertilization system is 1.6 seconds and the overshoot is 7.8 % when the variable liquid fertiliz er control system is used.The response time of the fuzzy PID control variable liquid fertilizer system is 0.8 seconds and the overshoot is zero,so that the amount of fertilizer keep in a given range more effectively.This method provides an effective control method for the control of variable liquid fertilizer application.
According to the variable flow characteristic of the control system of liquid fertilizer,the traffic system has the characteristics of large inertia,nonlinear and parameter time-varying,the traditional PID control method is difficult to achieve accurate control,so this article on the basis of establishing the mathematical model of electric actuator,using adaptive fuzzy PID automatic control was carried out on the liquid flow.Using MATLAB Simulink and Fuzzy tools for adaptive Fuzzy PID variable liquid fertilizer control system modeling and simulation.The simulation and experimental results show that the dynamic and static index of adaptive fuzzy PID control system is significantly higher than that of conventional PID control when the variable liquid fertilization control system is simulated.In the system overshoot,the adjustment time is obviously improved,the overshoot amount is 1.5 %,and the time required for the system to enter the steady state is 0.8 6s.The response time of the PID control variable liquid fertilization system is 1.6 seconds and the overshoot is 7.8 % when the variable liquid fertiliz er control system is used.The response time of the fuzzy PID control variable liquid fertilizer system is 0.8 seconds and the overshoot is zero,so that the amount of fertilizer keep in a given range more effectively.This method provides an effective control method for the control of variable liquid fertilizer application.
引文
[1]郭娜,胡静涛.基于Smith-模糊PID控制的变量喷药系统设计及试验[J].农业工程学报,2014,30(8):56-64.
[2]于合龙,赵新子,陈桂芬,等.基于改进的BP神经网络集成的作物精准施肥模型[J].农业工程学报,2010,26(12):193-198.
[3]袁媛,李淼,李录久,等.基于智能计算的施肥模型算法研究[J].农业工程学报,2008,24(12):116-119.
[4]梁春英,吕鹏,纪建伟,等.基于遗传算法的电液变量施肥控制系统PID参数优化[J].农业机械学报,2013,44(S1):89-93,88.
[5]苑进,刘勤华,刘雪美,等.配比变量施肥中多肥料掺混模拟与掺混腔结构优化[J].农业机械学报,2014,45(6):125-132.
[6]李勇,赵军,谢叶伟,等.针对农户地块的施肥决策支持系统的设计与实现[J].农业工程学报,2010,26(13):192-196.
[7]刘浩蓬,龙长江,万鹏,等.植保四轴飞行器的模糊PID控制[J].农业工程学报,2015,31(1):71-77.
[8]李琳,周国雄.基于逆模型解耦的绿茶烘焙变论域模糊控制[J].农业工程学报,2014,30(7):258-267.
[9]鲁植雄,郭兵,高强.拖拉机耕深模糊自动控制方法与试验研究[J].农业工程学报,2013,29(23):23-29.
[10]焦俊,孔文,王强,等.基于输入模糊化的农用履带机器人自适应滑模控制[J].农业机械学报,2015,46(6):14-19,13.
[11]宁小波,陈进,李耀明,等.联合收获机前进速度模糊控制系统多目标遗传优化[J].农业机械学报,2015,46(5):68-74.
[12]苗中华,李闯,韩科立,等.基于模糊PID的采棉机作业速度最优控制算法与试验[J].农业机械学报,2015,46(4):9-14,27.
[13]张闻宇,丁幼春,廖庆喜,等.拖拉机液压转向变论域模糊控制器设计与试验[J].农业机械学报,2015,46(3):43-50.
[2]于合龙,赵新子,陈桂芬,等.基于改进的BP神经网络集成的作物精准施肥模型[J].农业工程学报,2010,26(12):193-198.
[3]袁媛,李淼,李录久,等.基于智能计算的施肥模型算法研究[J].农业工程学报,2008,24(12):116-119.
[4]梁春英,吕鹏,纪建伟,等.基于遗传算法的电液变量施肥控制系统PID参数优化[J].农业机械学报,2013,44(S1):89-93,88.
[5]苑进,刘勤华,刘雪美,等.配比变量施肥中多肥料掺混模拟与掺混腔结构优化[J].农业机械学报,2014,45(6):125-132.
[6]李勇,赵军,谢叶伟,等.针对农户地块的施肥决策支持系统的设计与实现[J].农业工程学报,2010,26(13):192-196.
[7]刘浩蓬,龙长江,万鹏,等.植保四轴飞行器的模糊PID控制[J].农业工程学报,2015,31(1):71-77.
[8]李琳,周国雄.基于逆模型解耦的绿茶烘焙变论域模糊控制[J].农业工程学报,2014,30(7):258-267.
[9]鲁植雄,郭兵,高强.拖拉机耕深模糊自动控制方法与试验研究[J].农业工程学报,2013,29(23):23-29.
[10]焦俊,孔文,王强,等.基于输入模糊化的农用履带机器人自适应滑模控制[J].农业机械学报,2015,46(6):14-19,13.
[11]宁小波,陈进,李耀明,等.联合收获机前进速度模糊控制系统多目标遗传优化[J].农业机械学报,2015,46(5):68-74.
[12]苗中华,李闯,韩科立,等.基于模糊PID的采棉机作业速度最优控制算法与试验[J].农业机械学报,2015,46(4):9-14,27.
[13]张闻宇,丁幼春,廖庆喜,等.拖拉机液压转向变论域模糊控制器设计与试验[J].农业机械学报,2015,46(3):43-50.