CN112099540B - Sand concentration control method based on stepping type single neuron PID control algorithm - Google Patents
Sand concentration control method based on stepping type single neuron PID control algorithm Download PDFInfo
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Abstract
The invention provides a sand concentration control method based on a stepping type single neuron PID control algorithm, which comprises the following steps: the microprocessor calculates the fixed step length of the current stage according to the deviation between the sand concentration value set in the current stage and the sand concentration value set in the previous stage, and then calculates the sand concentration value set in each step according to the fixed step length; the microprocessor calculates the set rotating speed of the auger device in each step according to the actual suction flow and the set sand concentration value in each step; the microprocessor calculates an output value by adopting a single neuron self-adaptive PID control algorithm to control the actual rotating speed of the packing auger device and calculates the actual rotating speed and sand conveying amount of the packing auger device; the microprocessor calculates an actual sand concentration value according to the actual suction flow and the actual sand conveying amount; and when the actual sand concentration value reaches the set sand concentration value of a certain step, adding a fixed step length to the set sand concentration value, and repeating the steps until the actual sand concentration value reaches the set sand concentration value.
Description
[ technical field ] A method for producing a semiconductor device
The invention relates to the technical field of PID control algorithms, in particular to a sand concentration control method based on a stepping type single neuron PID control algorithm.
[ background of the invention ]
The sand mixing equipment is one of the main matching equipment for oil field fracturing and sand prevention operation, and is used for mixing, stirring and conveying the sand carrying liquid. During construction, according to technological requirements, the sand-carrying liquid with different sand concentrations is conveyed in stages, and the control precision of the concentration is one of the main factors for determining the success or failure of the fracturing operation. The traditional automatic control system of the sand mulling vehicle adopts a PID control instruction carried by a PLC controller as a control algorithm, and adjusts the rotating speed of an auger device by using an output control value to realize different sand concentration control.
In view of this, it is actually necessary to provide a novel sand concentration control method based on a step-by-step single neuron PID control algorithm to overcome the above-mentioned drawbacks.
[ summary of the invention ]
The invention aims to provide a sand concentration control method based on a stepping type single neuron PID control algorithm, wherein the actual sand concentration value of the method adopts a fixed step length to gradually approach the set sand concentration value, and meanwhile, the integral, proportion and differential control of PID respectively adopts different learning rates by utilizing the self-learning and self-adaptive capacity of a single neuron so as to respectively adjust different weight coefficients, thereby achieving the purpose of improving the control precision.
In order to achieve the purpose, the invention provides a sand concentration control method based on a stepping type single neuron PID control algorithm, which comprises the following steps:
setting the total suction volume Sk, the sand density rho, the sand concentration value Ck, the distribution proportion range Ra of the packing auger device and the sand conveying factor F of the packing auger device in multiple stages, calculating the fixed step length of the current stage by the microprocessor according to the deviation between the sand concentration value set in the current stage and the sand concentration value set in the previous stage, and calculating the sand concentration value set in each step according to the fixed step length;
the microprocessor calculates the set rotating speed of the auger device in each step according to the actual suction flow and the set sand concentration value in each step; the microprocessor calculates an output value by adopting a single neuron self-adaptive PID control algorithm to control the actual rotating speed of the packing auger device and calculates the actual rotating speed and sand conveying amount of the packing auger device;
the microprocessor calculates an actual sand concentration value according to the actual suction flow and the actual sand conveying amount; and when the actual sand concentration value reaches the set sand concentration value of a certain step, increasing a fixed step length for the set sand concentration value, and repeating the steps until the actual sand concentration value reaches the set sand concentration value.
Preferably, ra 0. Ltoreq. Ra 1; the method comprises the following steps of setting parameters of the packing auger device on an upper computer and calculating the actual rotating speed of the packing auger device:
aug with the lowest rotation speed Minu which can be detected by a rotation speed sensor of the input auger device,
the highest rotating speed Maxu. Aug can be detected by a rotating speed sensor of the input auger device,
the minimum current Minv. Aug can be detected by a rotating speed sensor of the input auger device,
the maximum current Maxv.Aug which can be detected by a rotating speed sensor of the input auger device,
receiving a current signal Sig.Aug transmitted to a microprocessor by a rotating speed sensor of the packing auger device,
the microprocessor calculates the actual rotating speed R = (Maxu. Aug-Minu. Aug) ÷ (Maxv. Aug-Minv. Aug) × (Sig. Aug-Minv. Aug) + Minu. Aug of the auger device according to the parameters.
Preferably, the parameters of the rotating speed controller of the auger device are input to the upper computer, and the parameters are as follows:
the lowest output control voltage MinCntrl. Aug of the pair twist device is input into the rotating speed controller,
the highest output control voltage maxcntrl. Aug of the input speed controller pair auger device,
input control parameters K and eta of single neuron self-adaptive PID control algorithm i 、η p 、η d Where K is the proportionality coefficient of the neuron, η i Is a differential learning rate, η p For integrating the learning rate, η d For integrating the learning rate, K>0。
Preferably, the parameters of the air inlet flow sensor of the auger device are input to the upper computer, and the actual sand conveying amount is calculated, and the method comprises the following steps:
the lowest flow rate mini.suc that can be detected by the suction flow sensor is input,
the highest flow rate maxu.suc that can be detected by the suction flow sensor is input,
the minimum current minv.Suc that can be detected by the suction flow sensor is input,
the maximum current maxv.suc that can be detected by the suction flow sensor is input,
receives the current signal sig.Suc transmitted to the microprocessor by the suction flow sensor,
the microprocessor calculates the actual suction flow rate S, S = (maxu.suc-minu.suc) ÷ (maxv.suc-minv.suc) × (sig.suc-minv.suc) + minu.suc based on the above parameters.
Preferably, the microprocessor executes the algorithm in the following steps:
judging whether the sucked sand volume reaches the set suction total volume Sk, if not, jumping to the step S405, if so, entering the k +1 stage from the k stage, changing the set sand concentration value from Ck to Ck +1, and continuing downwards;
dividing the process into 10 steps, wherein the fixed step length of each step is delta C = (Ck + 1-Ck)/10, and continuing to perform the process;
increasing the set sand concentration value by one step Ck = Ck + Δ C, and continuing downwards;
calculating the set rotating speed of the auger device according to the set sand concentration value, wherein the set rotating speed Rk1= Ra Ck S/F of the auger device, and the set rotating speed Rk2= (1-Ra) × Ck S/F of the next auger device continue downwards;
adjusting the actual rotating speed of the first auger device and the second auger device by adopting a single neuron self-adaptive PID control algorithm, and continuing to move downwards;
the microprocessor judges whether the set rotating speeds of the first auger device and the second auger device respectively deviate from the actual rotating speeds of the first auger device and the second auger device, if yes, the step S403 is skipped, and if not, the process continues downwards;
the microprocessor judges whether the current actual set sand concentration is equal to the stage set sand concentration, if not, the step S503 is skipped, and if so, the process continues downwards;
the microprocessor judges whether the operation is finished, if not, the step goes to step S400, and if so, the operation is finished.
Preferably, when the actual sand concentration value of the rotating speed controller of the auger device reaches the set sand concentration value, the scanning period of the microprocessor is set to 300ms;
the microprocessor calculates the set value of the packing auger device according to the set sand concentration value Ck, the sand conveying factor F, the suction actual flow S and the distribution proportion range Ra of the stage kThe rotation speed Rk1= Ra Ck S/F, the microprocessor calculates the signal error e (k) = Rk1-R1 of the packing auger device according to the set rotation speed Rk1 of the packing auger device and the actual rotation speed R of the packing auger device, and inputs the signal error e (k) = Rk1-R1 into the control parameter w of the neuron self-adaptive PID control algorithm i (k)、x i (k) U (k) calculating the output range of the control signal of the packing auger device, wherein w i (k) To correspond to x i (k) U (k) is a control signal of the packing auger device;
the specific steps of the microprocessor executing the algorithm to calculate the output range of the control signal of the packing auger device are as follows:
the first scan cycle, k =1,
u(k)＝0，u(k-1)＝0，w 1 (k)＝1，w 2 (k)＝1，w 3 (k)＝1，w 1 (k-1)＝1，w 2 (k-1)＝1，w 3 (k-1)＝1；
the (k) th scanning period is,
x 1 (k)＝e(k)，x 2 (k)＝e(k)–e(k-1)，x 3 (k)＝e(k)–2×e(k-1)+e(k-2)，z(k)＝e(k)
w 1 (k)＝w 1 (k-1)+η i *u(k)*z(k)*x 1 (k)；
w 2 (k)＝w 2 (k–1)+η p *u(k)*z(k)*x 2 (k)；
w 3 (k)＝w 3 (k-1)+η d *u(k)*z(k)*x 3 (k)；
w 1 ′(k)＝w 1 (k)÷|w 1 (k)+w 2 (k)+w 3 (k)|；
w 2 ′(k)＝w 2 (k)÷|w 1 (k)+w 2 (k)+w 3 (k)|；
w 3 ′(k)＝w 3 (k)÷|w 1 (k)+w 2 (k)+w 3 (k)|；
u(k)＝u(k-1)+K*(w 1 ′(k)*x 1 (k)+w 2 ′(k)*x 2 (k)+w 3 ′(k)*x 3 (k))；
MinCntrl.Aug<＝u(k)<＝MaxCntrl.Aug。
compared with the prior art, the sand concentration control method based on the stepping type single neuron PID control algorithm has the advantages that: the actual sand concentration value of the method adopts a fixed step length to gradually approach the set sand concentration value, and meanwhile, the integral, proportion and differential control of the PID by utilizing the self-learning and self-adaptive capacity of a single neuron respectively adopts different learning rates so as to respectively adjust different weight coefficients, thereby achieving the effect of improving the control precision.
[ detailed description ] embodiments
In order to make the objects, technical solutions and advantageous effects of the present invention more apparent, the present invention is further described in detail with reference to the following detailed description. It should be understood that the detailed description and specific examples, while indicating the preferred embodiment of the invention, are intended for purposes of illustration only and are not intended to limit the scope of the invention.
The invention provides a sand concentration control method based on a stepping type single neuron PID control algorithm, which comprises the following steps:
setting the total suction volume Sk, the sand density rho, the sand concentration value Ck, the distribution proportion range Ra of the packing auger device and the sand conveying factor F of the packing auger device in multiple stages, calculating the fixed step length of the current stage by the microprocessor according to the deviation between the sand concentration value set in the current stage and the sand concentration value set in the previous stage, and calculating the sand concentration value set in each step according to the fixed step length;
the microprocessor calculates the set rotating speed of the auger device in each step according to the actual suction flow and the set sand concentration value in each step; the microprocessor calculates an output value by adopting a single neuron self-adaptive PID control algorithm to control the actual rotating speed of the auger device, and calculates the actual rotating speed and sand conveying amount of the auger device (sand conveying amount = the actual rotating speed multiplied by sand density of the auger device);
the microprocessor calculates an actual sand concentration value according to the actual suction flow and the actual sand conveying amount; and when the actual sand concentration value reaches the set sand concentration value of a certain step, increasing a fixed step length for the set sand concentration value, and repeating the steps until the actual sand concentration value reaches the set sand concentration value.
Preferably, ra is 0. Ltoreq. Ra.ltoreq.1; the method comprises the following steps of setting parameters of the auger device on an upper computer and calculating the actual rotating speed of the auger device, and specifically comprises the following steps:
aug with the lowest rotation speed Minu which can be detected by a rotation speed sensor of the input auger device,
the highest rotating speed Maxu. Aug can be detected by a rotating speed sensor of the input auger device,
the minimum current Minv. Aug can be detected by a rotating speed sensor of the input auger device,
the maximum current Maxv.Aug which can be detected by a rotating speed sensor of the input auger device,
receiving a current signal Sig.Aug transmitted to a microprocessor by a rotating speed sensor of the packing auger device,
the microprocessor calculates the actual rotating speed R = (Maxu. Aug-Minu. Aug) ÷ (Maxv. Aug-Minv. Aug) × (Sig. Aug-Minv. Aug) + Minu. Aug of the auger device according to the parameters.
Preferably, the parameters of the rotating speed controller of the auger device are input to the upper computer, and the parameters are as follows:
the lowest output control voltage MinCntrl. Aug of the pair twist device is input into the rotating speed controller,
the highest output control voltage maxcntrl. Aug of the input speed controller pair auger device,
control parameters K and eta of input single neuron self-adaptive PID control algorithm i 、η p 、η d Where K is the proportionality coefficient of the neuron, η i Is the differential learning rate, eta p For integrating the learning rate, η d For integrating the learning rate, K>0。
Preferably, the parameters of the air inlet flow sensor of the auger device are input to the upper computer, and the actual sand conveying amount is calculated, and the method comprises the following steps:
the lowest flow rate mini.suc that can be detected by the suction flow sensor is input,
the highest flow rate maxu.suc that can be detected by the suction flow sensor is input,
the minimum current minv.Suc that can be detected by the suction flow sensor is input,
the maximum current maxv.suc that can be detected by the suction flow sensor is input,
receives the current signal sig.Suc transmitted to the microprocessor by the suction flow sensor,
the microprocessor calculates the actual suction flow rate S, S = (maxu.suc-minu.suc) ÷ (maxv.suc-minv.suc) × (sig.suc-minv.suc) + minu.suc based on the above parameters.
Preferably, the microprocessor executes the algorithm as follows:
judging whether the sucked sand volume reaches the set suction total volume Sk, if not, jumping to the step S405, if so, entering the k +1 stage from the k stage, changing the set sand concentration value from Ck to Ck +1, and continuing downwards;
dividing the process into 10 steps, wherein the fixed step length of each step is delta C = (Ck + 1-Ck)/10, and continuing to operate downwards;
increasing the set sand concentration value by one step Ck = Ck + Δ C, and continuing downwards;
calculating the set rotating speed of the auger device according to the set sand concentration value, wherein the set rotating speed Rk1 of the auger device is = Ra Ck S/F, and the set rotating speed Rk2 of the next auger device is = (1-Ra) Ck S/F, and continuing to move downwards;
adjusting the actual rotating speeds of the first auger device and the second auger device by adopting a single neuron self-adaptive PID control algorithm, and continuing to operate downwards;
the microprocessor judges whether the set rotating speeds of the first auger device and the second auger device respectively deviate from the actual rotating speeds of the first auger device and the second auger device, if so, the step S403 is skipped, and if not, the process is continued downwards;
the microprocessor judges whether the current actual set sand concentration is equal to the stage set sand concentration, if not, the step S503 is skipped, and if so, the process continues downwards;
the microprocessor judges whether the operation is finished, if not, the step goes to step S400, and if so, the operation is finished.
Preferably, when the actual sand concentration value of the rotating speed controller of the auger device reaches the set sand concentration value, the scanning period of the microprocessor is set to 300ms;
the microprocessor calculates the set rotating speed Rk1= Ra Ck S/F of the auger device according to the set sand concentration value Ck, the sand conveying factor F, the sucked actual flow S and the distribution proportion range Ra of the stage k, calculates the signal error e (k) = Rk1-R1 of the auger device according to the set rotating speed Rk1 of the auger device and the actual rotating speed R of the auger device, and inputs the control parameter w of the neuron self-adaptive PID control algorithm i (k)、x i (k) U (k) calculating the output range of the control signal of the packing auger device, wherein w i (k) To correspond to x i (k) U (k) is a control signal of the auger device;
the specific steps of the microprocessor executing the algorithm to calculate the output range of the control signal of the auger device are as follows:
the first scan cycle, k =1,
u(k)＝0，u(k-1)＝0，w 1 (k)＝1，w 2 (k)＝1，w 3 (k)＝1，w 1 (k-1)＝1，w 2 (k-1)＝1，w 3 (k-1)＝1；
the (k) th scanning period is,
x 1 (k)＝e(k)，x 2 (k)＝e(k)–e(k-1)，x 3 (k)＝e(k)–2×e(k-1)+e(k-2)，z(k)＝e(k)
w 1 (k)＝w 1 (k-1)+η i *u(k)*z(k)*x 1 (k)；
w 2 (k)＝w 2 (k–1)+η p *u(k)*z(k)*x 2 (k)；
w 3 (k)＝w 3 (k-1)+η d *u(k)*z(k)*x 3 (k)；
w 1 ′(k)＝w 1 (k)÷|w 1 (k)+w 2 (k)+w 3 (k)|；
w 2 ′(k)＝w 2 (k)÷|w 1 (k)+w 2 (k)+w 3 (k)|；
w 3 ′(k)＝w 3 (k)÷|w 1 (k)+w 2 (k)+w 3 (k)|；
u(k)＝u(k-1)+K*(w 1 ′(k)*x 1 (k)+w 2 ′(k)*x 2 (k)+w 3 ′(k)*x 3 (k))；
MinCntrl.Aug<＝u(k)<＝MaxCntrl.Aug。
the actual sand concentration value of the method adopts a fixed step length to gradually approach the set sand concentration value, and meanwhile, the integral, proportion and differential control of the PID by utilizing the self-learning and self-adaptive capacity of the single neuron can respectively adopt different learning rates so as to respectively adjust different weight coefficients, thereby achieving the effect of improving the control precision.
The invention is not limited to only that described in the specification and embodiments, and thus additional advantages and modifications will readily occur to those skilled in the art, and it is not intended to be limited to the specific details, representative apparatus, and examples shown and described herein, without departing from the spirit and scope of the general concept as defined by the appended claims and their equivalents.
Claims (4)
1. A sand concentration control method based on a stepping type single neuron PID control algorithm is characterized by comprising the following steps:
s100: setting the total suction volume Sk, the sand density rho, the sand concentration value Ck, the distribution proportion range Ra of the packing auger device and the sand conveying factor F of the packing auger device in multiple stages, calculating the fixed step length of the current stage by the microprocessor according to the deviation between the sand concentration value set in the current stage and the sand concentration value set in the previous stage, and calculating the sand concentration value set in each step according to the fixed step length;
s101: the microprocessor calculates the set rotating speed of the auger device in each step according to the actual suction flow and the set sand concentration value in each step; the microprocessor calculates an output value by adopting a single neuron self-adaptive PID control algorithm to control the actual rotating speed of the packing auger device and calculates the actual rotating speed and sand conveying amount of the packing auger device;
s102: the microprocessor calculates an actual sand concentration value according to the actual suction flow and the actual sand conveying amount; when the actual sand concentration value reaches the sand concentration value set in a certain step, increasing a fixed step length for the set sand concentration value, and repeating the steps until the actual sand concentration value reaches the set sand concentration value;
ra is more than or equal to 0 and less than or equal to 1; the method comprises the following steps of setting parameters of the packing auger device on an upper computer and calculating the actual rotating speed of the packing auger device:
s200: aug with the lowest rotation speed Minu which can be detected by a rotation speed sensor of the input auger device,
s201: the highest rotating speed Maxu. Aug can be detected by a rotating speed sensor of the input auger device,
s202: the minimum current Minv. Aug which can be detected by a rotating speed sensor of the packing auger device is input,
s203: the maximum current Maxv.Aug which can be detected by a rotating speed sensor of the input auger device,
s204: receiving a current signal Sig.Aug transmitted to a microprocessor by a rotating speed sensor of the packing auger device,
s205: the microprocessor calculates the actual rotating speed R = (Maxu.Aug-Minu.Aug) ÷ (Maxv.Aug-Minv.Aug) × (Sig.Aug-Minv.Aug) + Minu.Aug of the auger device according to the parameters;
the parameters of a rotating speed controller of the auger device are input on the upper computer, and are as follows:
the lowest output control voltage MinCntrl. Aug of the pair twist device is input into the rotating speed controller,
the highest output control voltage maxcntrl. Aug of the input speed controller pair auger device,
input control parameters K and eta of single neuron self-adaptive PID control algorithm i 、η p 、η d Where K is the proportionality coefficient of the neuron, η i Is a differential learning rate, η p For integrating the learning rate, η d For integral learning rate, K>0。
2. The sand concentration control method based on the stepping single-neuron PID control algorithm as claimed in claim 1, wherein the parameters of the air inlet flow sensor of the auger device are input on the upper computer and the actual sand conveying amount is calculated, comprising the steps of:
s300: the lowest flow rate mini.suc that can be detected by the suction flow sensor is input,
s301: the highest flow rate maxu.suc that can be detected by the suction flow sensor is input,
s302: the minimum current minv.Suc that can be detected by the suction flow sensor is input,
s303: the maximum current maxv.suc that can be detected by the suction flow sensor is input,
s304: receives the current signal sig.Suc transmitted to the microprocessor by the suction flow sensor,
s305: the microprocessor calculates the actual suction flow rate S, S = (maxu.suc-minu.suc) ÷ (maxv.suc-minv.suc) × (sig.suc-minv.suc) + minu.suc based on the above parameters.
3. The sand concentration control method based on a stepwise single neuron PID control algorithm as claimed in claim 2, wherein the microprocessor executes the algorithm according to the following steps:
s400: judging whether the sucked sand volume reaches the set suction total volume Sk, if not, jumping to the step S405, if so, entering the k +1 stage from the k stage, changing the set sand concentration value from Ck to Ck +1, and continuing downwards;
s401: dividing the process into 10 steps, wherein the fixed step length of each step is delta C = (Ck + 1-Ck)/10, and continuing to operate downwards;
s402: increasing the set sand concentration value by one step Ck = Ck + Δ C, and continuing downwards;
s403: calculating the set rotating speed of the auger device according to the set sand concentration value, wherein the set rotating speed Rk1= Ra Ck S/F of the auger device, and the set rotating speed Rk2= (1-Ra) × Ck S/F of the next auger device continue downwards;
s404: adjusting the actual rotating speeds of the first auger device and the second auger device by adopting a single neuron self-adaptive PID control algorithm, and continuing to operate downwards;
s405: the microprocessor judges whether the set rotating speeds of the first auger device and the second auger device respectively deviate from the actual rotating speeds of the first auger device and the second auger device, if yes, the step S403 is skipped, and if not, the process continues downwards;
s406: the microprocessor judges whether the current actual set sand concentration is equal to the stage set sand concentration, if not, the step S503 is skipped, and if so, the process continues downwards;
s407: the microprocessor judges whether the operation is finished, if not, the step goes to step S400, and if so, the operation is finished.
4. The sand concentration control method based on the stepping single-neuron PID control algorithm according to claim 3, characterized in that: when the actual sand concentration value of a rotating speed controller of the auger device reaches the set sand concentration value, setting the scanning period of the microprocessor to 300ms;
the microprocessor sucks actual flow S and distribution ratio range Ra according to the set sand concentration value Ck and the sand conveying factor F of the stage k, calculates the set rotating speed Rk1= Ra Ck S/F of the auger device, calculates the signal error e (k) = Rk1-R1 of the auger device according to the set rotating speed Rk1 of the auger device and the actual rotating speed R of the auger device, and inputs the control parameter w of the neuron self-adaptive PID control algorithm i (k)、x i (k) U (k) calculating the output range of the control signal of the packing auger device, wherein w i (k) To correspond to x i (k) U (k) is a control signal of the packing auger device;
the specific steps of the microprocessor executing the algorithm to calculate the output range of the control signal of the packing auger device are as follows:
the first scan cycle, k =1,
u(k)＝0，u(k-1)＝0，w 1 (k)＝1，w 2 (k)＝1，w 3 (k)＝1，w 1 (k-1)＝1，w 2 (k-1)＝1，w 3 (k-1)＝1；
the (k) th scanning period is,
x 1 (k)＝e(k)，x 2 (k)＝e(k)-e(k-1)，x 3 (k)＝e(k)-2×e(k-1)+e(k-2)，z(k)＝e(k)；
w 1 (k)＝w 1 (k-1)+η i *u(k)*z(k)*x 1 (k)；
w 2 (k)＝w 2 (k-1)+η p *u(k)*z(k)*x 2 (k)；
w 3 (k)＝w 3 (k-1)+η d *u(k)*z(k)*x 3 (k)；
w 1 ′(k)＝w 1 (k)÷|w 1 (k)+w 2 (k)+w 3 (k)|；
w 2 ′(k)＝w 2 (k)÷|w 1 (k)+w 2 (k)+w 3 (k)|；
w 3 ′(k)＝w 3 (k)÷|w 1 (k)+w 2 (k)+w 3 (k)|；
u(k)＝u(k-1)+K*(w 1 ′(k)*x 1 (k)+-w 2 ′(k)*x 2 (k)+-w 3 ′(k)*x 3 (k))；
MinCntrl.Aug<＝u(k)<＝MaxCntrl.Aug。
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| CN101706662A (en) * | 2009-10-30 | 2010-05-12 | 四机赛瓦石油钻采设备有限公司 | Control system of crushing set and control method thereof |
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| 基于PWM和自适应算法的超声波电机控制研究;周莉;《安徽理工大学学报（自然科学版）》;20200531;正文第22-26页 * |
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