WO2020140188A1 - 一种智能混肥控制方法及控制系统 - Google Patents

一种智能混肥控制方法及控制系统 Download PDF

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WO2020140188A1
WO2020140188A1 PCT/CN2019/000262 CN2019000262W WO2020140188A1 WO 2020140188 A1 WO2020140188 A1 WO 2020140188A1 CN 2019000262 W CN2019000262 W CN 2019000262W WO 2020140188 A1 WO2020140188 A1 WO 2020140188A1
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pid parameter
correction value
error
control
control method
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PCT/CN2019/000262
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French (fr)
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赵景波
朱敬旭辉
刘信潮
邱腾飞
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青岛理工大学
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    • GPHYSICS
    • G05CONTROLLING; REGULATING
    • G05BCONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
    • G05B11/00Automatic controllers
    • G05B11/01Automatic controllers electric
    • G05B11/36Automatic controllers electric with provision for obtaining particular characteristics, e.g. proportional, integral, differential
    • G05B11/42Automatic controllers electric with provision for obtaining particular characteristics, e.g. proportional, integral, differential for obtaining a characteristic which is both proportional and time-dependent, e.g. P. I., P. I. D.

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  • the invention relates to the technical field of water and fertilizer irrigation, in particular to an intelligent mixed fertilizer control method and control system.
  • the mixed fertilizer concentration of the intelligent water and fertilizer integrated machine is an important part of the entire control system as the controlled object.
  • the accuracy of the concentration control directly affects the growth and development of the plant, and it has a profound impact on the future development of agriculture in the direction of intelligence, precision, and automation. influences.
  • the mixed fertilizer system is one of the cores of the intelligent water and fertilizer integrated machine control system. It has the characteristics of large lag, strong time and strong nonlinearity. The ideal dynamic quality and accurate steady-state accuracy are the key indicators of the control system. The traditional control method It is difficult to resolve this contradiction.
  • the object of the present invention is to provide an intelligent mixed fertilizer control method and control system to achieve precise control of fertilizer concentration.
  • the control method includes:
  • the adaptive fuzzy control algorithm is used to determine the PID parameter correction value according to the error and the error change rate
  • the adaptive fuzzy control algorithm is used to determine the PID parameter correction value according to the error and the error change rate.
  • the specific formula is:
  • e(k) is the error at the kth time
  • ec(k) is the error change rate at the kth time
  • E is the blurring target value of the error e(k)
  • EC is the blurring rate of the error change rate ec(k) Target value
  • a and b are exponential coefficients
  • ⁇ e and ⁇ ec are tuning factors of input and output variables
  • ⁇ K p , ⁇ K i and ⁇ K d are the proportional coefficient correction value and integral coefficient correction in the PID parameter correction value, respectively Value and differential coefficient correction value.
  • the PID parameter at the next moment is determined according to the PID parameter at the current moment and the PID parameter correction value, and the specific formula is:
  • ⁇ K p , ⁇ K i and ⁇ K d are the proportional coefficient correction value, integral coefficient correction value and differential coefficient correction value in the PID parameter correction value
  • K p0 , K i0 and K d0 are the proportion in the PID parameter at the current time gain, integral gain and the differential coefficient
  • K p, K i and K d are the proportional coefficient in a next PID parameters in time, the integral coefficient and differential coefficient.
  • control increment is determined according to the PID parameter at the next moment, and the specific formula is:
  • K p , K i, and K d are the proportional coefficient, integral coefficient, and differential coefficient in the PID parameter at the next time, respectively.
  • the invention also provides an intelligent mixed fertilizer control system.
  • the control system includes a detection circuit, a controller and a solenoid valve; the detection circuit is used to detect the actual fertilizer concentration and send it to the controller; the controller application
  • the above intelligent mixed fertilizer control method controls the opening and closing of the solenoid valve.
  • the present invention discloses the following technical effects:
  • the invention discloses an intelligent mixed fertilizer control method and control system.
  • the control method includes: obtaining the actual fertilizer concentration; determining the error and the rate of error change according to the actual fertilizer concentration and the given fertilizer concentration; using an adaptive fuzzy control algorithm, Determine the PID parameter correction value according to the error and the error change rate; obtain the PID parameter at the current time; determine the PID parameter at the next time according to the PID parameter at the current time and the PID parameter correction value; according to the PID at the next time
  • the parameter determines the control increment; according to the control increment, the opening and closing of the solenoid valve is controlled.
  • the invention combines PID control and adaptive fuzzy control to control the fertilization concentration, and improves the accuracy of the mixed fertilizer control process.
  • FIG. 1 is a flowchart of an intelligent mixed fertilizer control method according to an embodiment of the present invention
  • FIG. 2 is a structural diagram of an intelligent mixed fertilizer control system according to an embodiment of the present invention.
  • the purpose of the present invention is to provide an intelligent mixed fertilizer control method and control system to achieve precise control of fertilizer concentration.
  • FIG. 1 is a flowchart of an intelligent mixed fertilizer control method according to an embodiment of the present invention. As shown in FIG. 1, the present invention discloses an intelligent mixed fertilizer control method.
  • the control method includes:
  • Step S1 Obtain the actual fertilization concentration c(k);
  • Step S2 Determine the error e(k) and the error change rate ec(k) according to the actual fertilizer concentration c(k) and the given fertilizer concentration r(k);
  • Step S3 adopt an adaptive fuzzy control algorithm to determine the PID parameter correction value according to the error and the error change rate;
  • Step S4 Obtain the PID parameter at the current moment
  • Step S5 Determine the PID parameter at the next moment according to the current PID parameter and the PID parameter correction value
  • Step S6 Determine the control increment u(k) according to the PID parameter at the next moment
  • Step S7 Control the opening and closing of the solenoid valve according to the control increment u(k), and return to "Step S1".
  • Step S3 The adaptive fuzzy control algorithm is adopted to determine the PID parameter correction value according to the error and the error change rate; specifically, the error e(k) and the error change rate ec(k) are passed Fuzzification, fuzzy reasoning and deblurring get the PID parameter correction value, the specific formula is:
  • e(k) is the error at the kth time
  • the basic domain is [- ⁇ e E, ⁇ c E]
  • E is the fuzzy target value of the error e(k)
  • ec(k) is the kth time
  • the basic domain of the error rate of change is [- ⁇ ec EC, ⁇ ec EC]
  • EC is the fuzzy target value of the error rate ec(k)
  • a and b are exponential coefficients
  • ⁇ e and ⁇ ec are both
  • ⁇ K p , ⁇ K i and ⁇ K d are the proportional coefficient correction value, integral coefficient correction value and differential coefficient correction value in the PID parameter correction value, respectively.
  • index coefficients a and b in this embodiment are both 0.8, and the fuzzy domain of each input and output variable can be adjusted to [-6, 6], so the specific formulas for quantization factor and scale factor are determined for:
  • ⁇ e, ⁇ ec, ⁇ ⁇ kp , ⁇ ⁇ ki input and output variables are ⁇ ⁇ kd tuning factor, K e, K ec respectively quantization factor, K ⁇ kp, K ⁇ ki, K ⁇ kd divided into scale factor.
  • Step S5 the PID parameter at the next moment is determined according to the PID parameter at the current moment and the PID parameter correction value, the previous moment is the kth moment, and the next moment is the k+1st moment;
  • the specific formula of the PID parameter at the moment is:
  • ⁇ K p , ⁇ K i and ⁇ K d are the proportional coefficient correction value, integral coefficient correction value and differential coefficient correction value in the PID parameter correction value
  • K p0 , K i0 and K d0 are the proportion in the PID parameter at the current time gain, integral gain and the differential coefficient
  • K p, K i and K d are the proportional coefficient in a next PID parameters in time, the integral coefficient and differential coefficient.
  • Step S6 The control increment is determined according to the PID parameter at the next moment, and the specific formula is:
  • ⁇ u(k) is the control increment
  • e(k) is the error at time k
  • e(k+1) is the error at time k+1
  • e(k-1) is the error at time k-1
  • K p , K i and K d are the proportional coefficient, integral coefficient and differential coefficient in the PID parameter at the next moment.
  • FIG. 2 is a structural diagram of an intelligent mixed fertilizer control system according to an embodiment of the present invention. As shown in FIG. 2, the present invention also provides an intelligent mixed fertilizer control system.
  • the control system includes a detection circuit 3, a controller 1, and a solenoid valve 2;
  • the detection circuit 3 is used to detect the actual fertilizer concentration and send it to the controller 1; the controller is applied to the above method to control the opening and closing of the solenoid valve 2.
  • the invention discloses an intelligent mixed fertilizer control method and control system.
  • the control method includes: obtaining an actual fertilizer concentration; determining an error and a rate of error change according to the actual fertilizer concentration and a given fertilizer concentration; using an adaptive fuzzy control algorithm, Determine the PID parameter correction value according to the error and the error change rate; obtain the PID parameter at the current time; determine the PID parameter at the next time according to the PID parameter at the current time and the PID parameter correction value; according to the PID at the next time
  • the parameter determines the control increment; according to the control increment controls the proportion of the opening and closing time of the solenoid valve to control the input amount of the raw fertilizer solution, and then the mixed concentration of the fertilizer solution, the purpose is to make the mixed fertilizer concentration slowly approach the target value.
  • the present invention combines PID control and adaptive fuzzy control to control the concentration of fertilization, which not only improves the accuracy of the control process of the mixed fertilizer, but also considers the initial rapidity, and considers the stability and rapidity of the middle section of the mixed fertilizer At the end of the mixed fertilizer, stability is considered. Therefore, the control method disclosed by the present invention has the advantages of strong robustness of fuzzy control, high PID control accuracy and fast response speed.

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Abstract

一种智能混肥控制方法及控制系统,控制方法包括:获取实际施肥浓度(S1);根据实际施肥浓度与给定施肥浓度确定误差以及误差变化率(S2);采用自适应模糊控制算法,根据误差和误差变化率确定PID参数修正值(S3);获取当前时刻PID参数(S4);根据当前时刻PID参数和PID参数修正值确定下一时刻PID参数(S5);根据下一时刻PID参数确定控制增量(S6);根据控制增量控制电磁阀(3)的打开和关闭(S7)。该控制方法将PID控制与自适应模糊控制相结合的方法进行控制施肥浓度,提高了混肥控制过程的准确性。

Description

一种智能混肥控制方法及控制系统
本申请要求于2019年1月2日提交中国专利局、申请号为201910001849.3、发明名称为“一种智能混肥控制系统水肥浓度控制器”的中国专利申请的优先权,其全部内容通过引用结合在本申请中。
技术领域
本发明涉及水肥灌溉技术领域,特别是涉及一种智能混肥控制方法及控制系统。
背景技术
智能水肥一体机的混肥浓度作为被控对象是整个控制系统的重要组成部分,浓度控制的精度直接影响植物的生长发育,更是对未来农业向智能化、精准化、自动化方向发展具有深远的影响。
混肥系统是智能水肥一体机控制系统的核心之一,具有滞后大、时变强、非线性大的特点,理想的动态品质和准确的稳态精度是控制系统的关键指标,传统的控制方法难以解决这种矛盾。
发明内容
基于此,本发明的目的是提供一种智能混肥控制方法及控制系统,以实现精确控制施肥浓度。
为实现上述目的,本发明提供了一种智能混肥控制方法,所述控制方法包括:
获取实际施肥浓度;
根据所述实际施肥浓度与给定施肥浓度确定误差以及误差变化率;
采用自适应模糊控制算法,根据所述误差和所述误差变化率确定PID参数修正值;
获取当前时刻PID参数;
根据所述当前时刻PID参数和所述PID参数修正值确定下一时刻PID参数;
根据所述下一时刻PID参数确定控制增量;
根据所述控制增量控制电磁阀的打开和关闭,并返回步骤“获取实际施肥浓度”。
可选的,所述采用自适应模糊控制算法,根据所述误差和所述误差变化率确定PID参数修正值,具体公式为:
Figure PCTCN2019000262-appb-000001
其中,e(k)为第k时刻的误差,ec(k)为第k时刻的误差变化率,E为误差e(k)的模糊化目标值,EC为误差变化率ec(k)的模糊化目标值,a和b分别为指数系数,α e和α ec均为输入输出变量的整定因子,ΔK p、ΔK i和ΔK d分别为PID参数修正值中的比例系数修正值、积分系数修正值和微分系数修正值。
可选的,所述根据所述当前时刻PID参数和所述PID参数修正值确定下一时刻PID参数,具体公式为:
Figure PCTCN2019000262-appb-000002
其中,ΔK p、ΔK i和ΔK d分别为PID参数修正值中的比例系数修正值、积分系数修正值和微分系数修正值,K p0、K i0和K d0分别为当前时刻PID参数中的比例系数、积分系数和微分系数,K p、K i和K d分别为下一时刻PID参数中的比例系数、积分系数和微分系数。
可选的,所述根据所述下一时刻PID参数确定控制增量,具体公式为:
Δu(k)=K p(e(k+1)-e(k))+K ie(k)+K d(e(k)-e(k-1));
其中,e(k)为第k时刻的误差,K p、K i和K d分别为下一时刻PID参数中的比例系数、积分系数和微分系数。
本发明还提供一种智能混肥控制系统,所述控制系统包括检测电路、控制器和电磁阀;所述检测电路用于检测实际施肥浓度,并发送至所述控制器;所述控制器应用于上述的智能混肥控制方法控制所述电磁阀的打开和关闭。
根据本发明提供的具体实施例,本发明公开了以下技术效果:
本发明公开一种智能混肥控制方法及控制系统,所述控制方法包括:获取实际施肥浓度;根据所述实际施肥浓度与给定施肥浓度确定误差以及误差变化率;采用自适应模糊控制算法,根据所述误差和所述误差变化率确定PID参数修正值;获取当前时刻PID参数;根据所述当前时刻PID参数和所述PID参数修正值确定下一时刻PID参数;根据所述下一时刻PID参数确定控制增量;根据所述控制增量控制电磁阀的打开和关闭。本发明将PID控制与自适应模糊控制相结合的方法进行控制施肥浓度,提高了混肥控制过程的准确性。
说明书附图
为了更清楚地说明本发明实施例或现有技术中的技术方案,下面将对实施例中所需要使用的附图作简单地介绍,显而易见地,下面描述中的附图仅仅是本发明的一些实施例,对于本领域普通技术人员来讲,在不付出创造性劳动性的前提下,还可以根据这些附图获得其他的附图。
图1为本发明实施例智能混肥控制方法流程图;
图2为本发明实施例智能混肥控制系统结构图;
其中,1、控制器,2、电磁阀,3、检测电路。
具体实施方式
下面将结合本发明实施例中的附图,对本发明实施例中的技术方案进行清楚、完整地描述,显然,所描述的实施例仅仅是本发明一部分实施例,而不是全部的实施例。基于本发明中的实施例,本领域普通技术人员在没有做出创造性劳动前提下所获得的所有其他实施例,都属于本发明保护的范围。
本发明的目的是提供一种智能混肥控制方法及控制系统,以实现精确控制施肥浓度。
为使本发明的上述目的、特征和优点能够更加明显易懂,下面结合附图和具体实施方式对本发明作进一步详细的说明。
图1为本发明实施例智能混肥控制方法流程图,如图1所示,本发明公开一种智能混肥控制方法,所述控制方法包括:
步骤S1:获取实际施肥浓度c(k);
步骤S2:根据所述实际施肥浓度c(k)与给定施肥浓度r(k)确定误差e(k)以及误差变化率ec(k);
步骤S3:采用自适应模糊控制算法,根据所述误差和所述误差变化率确定PID参数修正值;
步骤S4:获取当前时刻PID参数;
步骤S5:根据所述当前时刻PID参数和所述PID参数修正值确定下一时刻PID参数;
步骤S6:根据所述下一时刻PID参数确定控制增量u(k);
步骤S7:根据所述控制增量u(k)控制电磁阀的打开和关闭,并返回“步骤S1”。
下面对各个步骤进行详细论述:
步骤S3:所述采用自适应模糊控制算法,根据所述误差和所述误差变化率确定PID参数修正值;具体的,将所述误差e(k)和所述误差变化率ec(k)通过模糊化、模糊推理以及解模糊得到PID参数修正值,具体公式为:
Figure PCTCN2019000262-appb-000003
其中,e(k)为第k时刻的误差,其基本论域为[-α eE,α cE],E为误差e(k)的模糊化目标值,ec(k)为第k时刻的误差变化率,其基本论域为[-α ecEC,α ecEC],EC为误差变化率ec(k)的模糊化目标值,a和b分别为指数系数,α e和α ec均为输入输出变量的整定因子,ΔK p、ΔK i和ΔK d分别为PID参数修正值中的比例系数修正值、积分系数修正值和微分系数修正值。
根据实际经验和测试,本实施例中指数系数a和b的取值均为0.8,各个输入输出变量的模糊论域可以调整为[-6,6],因此确定量化因子和比例因子的具体公式为:
Figure PCTCN2019000262-appb-000004
Figure PCTCN2019000262-appb-000005
α e、α ec、β Δkp、β Δki和β Δkd均为输入输出变量的整定因子,K e、K ec分别为量化因子,K Δkp、K Δki、K Δkd分为比例因子。
步骤S5:所述根据所述当前时刻PID参数和所述PID参数修正值确定下一时刻PID参数,所述前时刻为第k时刻,所述下一时刻为第k+1时刻;确定下一时刻PID参数的具体公式为:
Figure PCTCN2019000262-appb-000006
其中,ΔK p、ΔK i和ΔK d分别为PID参数修正值中的比例系数修正值、积分系数修正值和微分系数修正值,K p0、K i0和K d0分别为当前时刻PID参数中的比例系数、积分系数和微分系数,K p、K i和K d分别为下一时刻PID参数中的比例系数、积分系数和微分系数。
步骤S6:所述根据所述下一时刻PID参数确定控制增量,具体公式为:
Δu(k)=K p(e(k+1)-e(k))+K ie(k)+K d(e(k)-e(k-1));
其中,Δu(k)为控制增量,e(k)为第k时刻的误差,e(k+1)为第k+1时刻的误差,e(k-1)为第k-1时刻的误差,K p、K i和K d分别为下一时刻PID参数中的比例系数、积分系数和微分系数。
图2为本发明实施例智能混肥控制系统结构图,如图2所示,本发明还提供一种智能混肥控制系统,所述控制系统包括检测电路3、控制器1和电磁阀2;所述检测电路3用于检测实际施肥浓度,并发送至所述控制器1;所述控制器应用于上述方法控制所述电磁阀2的打开和关闭。
本发明公开一种智能混肥控制方法及控制系统,所述控制方法包括:获取实际施肥浓度;根据所述实际施肥浓度与给定施肥浓度确定误差以及误差变化率;采用自适应模糊控制算法,根据所述误差和所述误差变化率确定PID参数修正值;获取当前时刻PID参数;根据所述当前时刻PID参数和所述PID参数修正值确定下一时刻PID参数;根据所述下一时刻PID参数确定控制增量;根据所述控制增量控制电磁阀的打开和关闭的时间比例来控制肥料原液的输入量,进而控制肥液混合浓度,目的是使混肥浓度慢慢逼近目标值。另外本发明将PID控制与自适应模糊控制相结合的方法进行控制施肥浓度,不仅提高了混肥控制过程的准确性,还虑了初期的快速性,考虑了混肥中段的稳定性和快速性,在混肥末段考虑的是稳定性,因此本发明公开的控制方法既具有模糊控制鲁棒性强的优点,又具有PID控制精度高,响应速度快的特点。
本说明书中各个实施例采用递进的方式描述,每个实施例重点说明的都是与其他实施例的不同之处,各个实施例之间相同相似部分互相参见即可。
本文中应用了具体个例对本发明的原理及实施方式进行了阐述,以上实施例的说明只是用于帮助理解本发明的方法及其核心思想;同时,对于本领域的一般技术人员,依据本发明的思想,在具体实施方式及应用范围上均会有改变之处。综上所述,本说明书内容不应理解为对本发明的限制。

Claims (5)

  1. 一种智能混肥控制方法,其特征在于,所述控制方法包括:
    获取实际施肥浓度;
    根据所述实际施肥浓度与给定施肥浓度确定误差以及误差变化率;
    采用自适应模糊控制算法,根据所述误差和所述误差变化率确定PID参数修正值;
    获取当前时刻PID参数;
    根据所述当前时刻PID参数和所述PID参数修正值确定下一时刻PID参数;
    根据所述下一时刻PID参数确定控制增量;
    根据所述控制增量控制电磁阀的打开和关闭,并返回步骤“获取实际施肥浓度”。
  2. 根据权利要求1所述的智能混肥控制方法,其特征在于,所述采用自适应模糊控制算法,根据所述误差和所述误差变化率确定PID参数修正值,具体公式为:
    Figure PCTCN2019000262-appb-100001
    其中,e(k)为第k时刻的误差,ec(k)为第k时刻的误差变化率,E为误差e(k)的模糊化目标值,EC为误差变化率ec(k)的模糊化目标值,a和b分别为指数系数,α e和α ec均为输入输出变量的整定因子,ΔK p、Δk i和ΔK d分别为PID参数修正值中的比例系数修正值、积分系数修正值和微分系数修正值。
  3. 根据权利要求1所述的智能混肥控制方法,其特征在于,所述根据所述当前时刻PID参数和所述PID参数修正值确定下一时刻PID参数,具体公式为:
    Figure PCTCN2019000262-appb-100002
    其中,ΔK p、ΔK i和ΔK d分别为PID参数修正值中的比例系数修正值、积分系数修正值和微分系数修正值,K p0、K i0和K d0分别为当前时刻PID参数中的比例系数、积分系数和微分系数,K p、K i和K d分别为下一时刻PID参数中的比例系数、积分系数和微分系数。
  4. 根据权利要求1所述的智能混肥控制方法,其特征在于,所述根据所述下一时刻PID参数确定控制增量,具体公式为:
    Δu(k)=K p(e(k+1)-e(k))+K ie(k)+K d(e(k)-e(k-1));
    其中,e(k)为第k时刻的误差,K p、K i和K d分别为下一时刻PID参数中的比例系数、积分系数和微分系数。
  5. 一种智能混肥控制系统,其特征在于,所述控制系统包括检测电路、控制器和电磁阀;所述检测电路用于检测实际施肥浓度,并发送至所述控制器;所述控制器应用于权利要求1-4任一项所述的智能混肥控制方法控制所述电磁阀的打开和关闭。
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