Quick-response PID (Proportion Integration Differentiation) adjustment method
By using a fast-response PID control method, the problem of temperature oscillation in the refrigeration system was solved, achieving faster response and higher accuracy. Temperature fluctuation was optimized to ±0.5℃, and the low-temperature range was controlled within ±0.2℃.
Patent Information
- Application Number
- CN202511640817.X
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2025-11-11
- Publication Date
- 2026-02-10
AI Technical Summary
Traditional PID control exhibits hysteresis in refrigeration systems, leading to temperature oscillations and making it difficult to achieve rapid response and precise regulation.
A fast-response PID control method is adopted, including system preheating and initial data acquisition, dynamic limit calculation, improved real-time control, iterative optimization and hysteresis compensation. Overshoot is suppressed by dynamic limit and convergence is accelerated by mean feedback, thereby optimizing temperature fluctuations.
Temperature fluctuation was optimized from ±1.5℃ to ±0.5℃, and the low-temperature range was controlled within ±0.2℃, improving the response speed and accuracy of the refrigeration system.
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Figure CN121498286A_ABST
Abstract
Description
TECHNICAL FIELD
[0001] The present application relates to the technical field of PID regulation, in particular to a PID regulation method with fast response. BACKGROUND
[0002] In the field of refrigeration system control, the hot gas bypass valve is the core actuator for realizing stepless regulation of refrigeration load. The traditional control method realizes 0-100% refrigeration capacity regulation by adjusting the on-off duty ratio (typical period: 10 seconds) of the liquid supply electromagnetic valve and the hot gas bypass valve: when the opening time of the liquid supply valve accounts for 100%, full load refrigeration is realized, and when the opening time accounts for 50%, the refrigeration capacity is 50%. However, such a system has significant technical bottlenecks.
[0003] Generally, after the action of the traditional liquid supply electromagnetic valve, the temperature starts to change after a delay of 5-8 seconds, and the temperature still drops by 0.5-1℃ after the valve is closed. The temperature needs to be maintained at a high temperature for 1-3 seconds after the valve is opened. This hysteresis characteristic causes the traditional PID control to produce a continuous oscillation of ±1.5℃, and even if the proportional coefficient is reduced from 10000 to 6000, the fluctuation cannot be eliminated.
[0004] Based on this, the present application provides a PID regulation method with fast response to solve the above-mentioned technical problems. SUMMARY
[0005] The present application aims to provide a PID regulation method with fast response to solve the problems mentioned in the background.
[0006] To achieve the above-mentioned purpose, the present application provides the following technical solutions: The present application provides a PID regulation method with fast response, comprising the following steps: S1. System preheating and initial data acquisition: S2. Dynamic amplitude limiting calculation: S3. Then perform improved PID real-time control: S4. Iterative optimization every 10 control periods: S5. Finally, implement special compensation for system hysteresis problems.
[0007] Preferably, the step S1 comprises the following steps: S11. Start with full-range PID mode, 0-65535 output range, continuous operation for 10 control periods, 10 seconds / period; S12. Real-time record the PID output value, liquid supply temperature feedback value and actual opening time of the electromagnetic valve of each period, and store these data in a ring buffer; S13. Calculate the mean value of the PID output Ū as the reference value, and establish a temperature-valve opening time mapping model.
[0008] Preferably, the step S2 comprises the following steps: S21. Calculate the dynamic amplitude range based on the initial collected Ū value in step S1: The upper limit is: ; The lower limit is: ; S22. Introduce a compensation factor β according to the supply temperature, take 0.95 to enhance low-temperature control when the temperature is <20℃, otherwise take 1.0, generate the corrected amplitude parameter and pass it to the next stage.
[0009] Preferably, the step S3 comprises the following steps: S31. Use the PID algorithm containing energy compensation, see formula (1): ; In the formula, is the PID output signal; is the deviation between the set temperature and the measured temperature; is the proportional coefficient; is the integral time constant; is the derivative time constant; S32. Take the generated by step S2 as the primary amplitude range, when e(t)>2℃, start the secondary protection mechanism to automatically expand the amplitude by ±20%, and finally output the PWM duty cycle: ; S33. Continuously record the valve opening time data during the control process to provide a basis for subsequent optimization.
[0010] Preferably, the step S4 comprises the following steps: S41. Obtain the new PID output sequence to calculate the mean value When , update the reference value and recalculate the amplitude range; S42. Dynamically adjust the parameters according to the control effect, when , decrease the α value, when the temperature overshoots, increase the Bias value, form a closed-loop feedback from the execution layer to the optimization layer.
[0011] Preferably, the step S5 comprises the following steps: S51. Based on the initial collected Figure 5 / 6 data, construct a prediction model to calculate the delay time: ; S52. When the target temperature changes , additional feedforward compensation output: ; wherein, , at the same time the dead zone range adopts open / close control instead of PID; S53. The compensation signal is directly superimposed to the main control loop, and the τ value is recalibrated every 30 periods.
[0012] Compared with the prior art, the present application has the beneficial effects that: The present application realizes the optimization of temperature fluctuation from ±1.5℃ to ±0.5℃, and the low temperature area can be controlled within ±0.2℃, through the complete linkage chain of initial data acquisition, amplitude calculation, real-time control, period optimization, lag compensation and real-time control, through dynamic amplitude suppression, mean value feedback acceleration convergence and lag compensation response, and solves the problems existing in the traditional technology. BRIEF DESCRIPTION OF DRAWINGS
[0013] Figure 1 PID output program segment diagram of the present application; Figure 2 supply liquid temperature fluctuation diagram A of the present application; Figure 3 supply liquid temperature and supply liquid electromagnetic valve opening time diagram of the present application; Figure 4 PID upper limit and lower limit value program segment diagram of the present application; Figure 5 supply liquid temperature fluctuation diagram B of the present application. DETAILED DESCRIPTION
[0014] The technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative labor fall within the scope of protection of the present application.
[0015] Embodiment 1, please refer to Figures 1 to 5 The present application proposes a fast response PID adjustment method, comprising the following steps: S1. System preheating and initial data acquisition: S2. Dynamic amplitude calculation: S3. Then execute improved PID real-time control: S4. Iterative optimization every 10 control periods: S5. Finally, special compensation is implemented for system lag problem.
[0016] Further, step S1 comprises the following steps: S11. At startup, it adopts full-range PID mode with an output range of 0-65535 and runs continuously for 10 control cycles, 10 seconds / cycle. S12. Record the PID output value, liquid supply temperature feedback value and actual opening time of the solenoid valve in real time for each cycle, and store these data in the ring buffer. S13. Calculate the average PID output Ū as the baseline value, and at the same time establish a temperature valve opening time mapping model.
[0017] Furthermore, step S2 includes the following steps: S21. Calculate the dynamic limiting range based on the Ū value initially acquired in step S1: The upper limit is: ; The lower limit is: ; S22. Introduce a compensation factor β based on the liquid supply temperature. When the temperature is <20℃, take 0.95 to enhance low temperature control; otherwise, take 1.0. Generate the corrected limiting parameters and pass them to the next stage.
[0018] Furthermore, step S3 includes the following steps: S31. A PID algorithm with energy compensation is adopted, as shown in equation (1): ; In the formula, For PID output signals; To account for the deviation between the set temperature and the measured temperature; This is the proportionality coefficient; The integral time constant; The differential time constant; S32. The product generated in step S2 As the primary limiting range, when e(t) > 2℃, the secondary protection mechanism is activated to automatically extend the limiting by ±20%, ultimately outputting the PWM duty cycle: ; S33. Continuously record valve opening time data during the control process to provide a basis for subsequent optimization.
[0019] Furthermore, step S4 includes the following steps: S41. Obtain the new PID output sequence and calculate the mean. ,when Update the baseline value And recalculate the limiting range; S42. Dynamically adjust parameters based on control effectiveness for 5 consecutive cycles. The α value is decreased when temperature overshoot occurs, and the Bias value is increased when temperature overshoot occurs, forming a closed-loop feedback from the execution layer to the optimization layer.
[0020] Furthermore, step S5 includes the following steps: S51. Based on initial acquisition Figure 5 / 6. Use data to build a predictive model and calculate latency: ; S52. When the target temperature changes Additional feedforward compensation output: ; in, At the same time The dead zone range is replaced by on / off control instead of PID; S53. The compensation signal is directly superimposed onto the main control loop, and the τ value is recalibrated every 30 cycles.
[0021] Example 2: In practical applications, the present invention uses a PLC as the core control element. After PID calculation, the PLC outputs a PWM wave to adjust the duty cycle of the liquid supply solenoid valve and the hot gas bypass valve. PID control uses the liquid supply temperature as the control objective and calculates the output using proportional, integral, and derivative terms. Its classic formula is... ; U(t): PID output signal; e(t): The deviation between the set temperature and the measured temperature; K p : Proportional coefficient; T i Integration time constant; T d： Differential time constant; In practical control design, the integral equation is transformed into a difference equation, and the formula is appropriately modified according to the actual control requirements. ; The formula amplifies and reduces the integral time constant and the derivative time constant respectively, and adds energy compensation bias according to the actual control situation to make up for the fixed energy loss when the system enters steady state. The PLC sampling cycle is 1 second. The liquid supply temperature sensor (TS1) converts the collected temperature signal into a current signal. The current signal enters the PLC through AI1 as the feedback value of the main circuit. Combined with the given target value, the controller performs PID calculations to generate an output signal, thereby completing the temperature control. In the program segment, 44110 is the target value, 40409 is the feedback value, and the PID output value 40690 changes dynamically according to the deviation and the magnitude of the deviation change. The program segment is as follows: Figure 1 ; Based on actual test results, in the initial adjustment phase, with a proportional coefficient of 10000 and an integral coefficient of 50, the supply liquid temperature fluctuated significantly, oscillating within a range of ±1.5℃. Even after reducing the proportional coefficient to minimize oscillation, the temperature fluctuation consistently failed to meet requirements. Figure Five It can be seen that even when the liquid supply solenoid valve is completely closed, the liquid supply temperature will still drop by 0.5 to 1°C, and when the liquid supply valve opening time reaches its maximum value, the liquid supply temperature will still remain at a high temperature for a period of time. This shows that the refrigeration system has a large lag. To achieve more precise liquid supply temperature control, the upper and lower limits of the PID output need to be limited to obtain higher accuracy. The relationship between liquid supply temperature and running time is as follows: Figure 2 The relationship between the liquid supply temperature and the opening time of the liquid supply solenoid valve is as follows: Figure 3 ; The experimental results show that the liquid supply temperature and the solenoid valve opening time have a basically linear relationship. The solenoid valve opening time can be expressed as a function of the running time, u=g(t), and the liquid supply temperature can be expressed as a function of the solenoid valve opening time. The function expression for the liquid supply temperature and operating time is T=ψ(t), that is... According to the experimental results, u and T can both be approximated as linear functions. Integrating both sides of equation (1) with respect to the running time, we get... Let a and b be the start and end times within a cycle, respectively. According to the experimental results, the temperature fluctuation is basically symmetrical with respect to the set value. Dividing both sides of the formula by ba, ; ; ξ、 It is the average value of the liquid supply temperature within the integral cycle, which is approximately the liquid supply temperature setpoint, and ζ is the average value of the solenoid valve opening time. To reduce fluctuations in the liquid supply temperature, reducing the upper and lower limits of the PID output is an effective approach. Since it is an approximately linear function, ζ×(1+15%) is used as the upper limit of the PID and ζ×(1-15%) is used as the lower limit of the PID. In the initial state, the PID output's upper and lower limits are set to full scale (0-65535). To improve the accuracy of the average opening time of the liquid supply solenoid valve, the program samples for 10 cycles. The PLC records the PID output values within these 10 cycles, and after 10 cycles, the average is calculated, resulting in an output average of 45035. The average calculation program segment is as follows: Figure 4 ; Please see Figure 5The improved PID control method of this invention, before calculating the integral upper and lower limits, resulted in large temperature fluctuations (±1.5℃). After limiting the integral upper and lower limits by calculating the average value over 10 cycles, the temperature control accuracy is within ±0.5℃, and the temperature fluctuation is as follows: Figure 5 ; Within the range of 10 to 30°C, the fluctuation of the liquid supply temperature can be controlled within ±0.2°C. This is because the lower the liquid supply temperature, the closer it is to the minimum design value range of the refrigeration system. In summary, hot gas bypass is mainly used to regulate the cooling load. Electromagnetic hot gas bypass can achieve stepless adjustment of the cooling load from 0 to 100%. When the liquid supply solenoid valve is closed and the hot gas solenoid valve is open, the compressor is essentially in an unloaded state, and the refrigerant circulates in the compressor's exhaust-return port. The refrigerant does not flow through the evaporator, i.e., no cooling effect is produced. Based on this principle, this invention adjusts the opening and closing times of the liquid supply solenoid valve and the hot gas solenoid valve to meet the actual cooling capacity requirements. With a 10-second cycle, if the liquid supply solenoid valve is fully open within 10 seconds, the achieved cooling capacity is 10 / 10 = 100%; if the liquid supply solenoid valve is open for 5 seconds and the hot gas solenoid valve is closed for 5 seconds, the current achieved cooling capacity is 5 / 10 = 50%. By adjusting the duty cycle of opening and closing in this way, stepless adjustment of the cooling capacity from 0 to 100% can be achieved.
[0022] Through the above steps, this invention achieves an optimized temperature fluctuation from ±1.5℃ to ±0.5℃ by using a complete linkage chain of initial data acquisition, amplitude limiting calculation, real-time control, cycle optimization, lag compensation, and real-time control. It also achieves this by using dynamic amplitude limiting to suppress overshoot, mean feedback to accelerate convergence, and lag compensation to improve response. The low-temperature range can be controlled within ±0.2℃.
[0023] In the description of this specification, references to terms such as "an embodiment," "example," "specific example," etc., indicate that a specific feature, structure, material, or characteristic described in connection with that embodiment or example is included in at least one embodiment or example of the invention. In this specification, illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples.
[0024] The preferred embodiments of the present invention disclosed above are merely illustrative of the invention. These preferred embodiments do not exhaustively describe all details, nor do they limit the invention to the specific implementations described. Clearly, many modifications and variations can be made based on the content of this specification. This specification selects and specifically describes these embodiments to better explain the principles and practical applications of the invention, thereby enabling those skilled in the art to better understand and utilize the invention. The invention is limited only by the claims and their full scope and equivalents.
Claims
1. A fast-response PID control method, characterized in that, Includes the following steps: S1. Perform system preheating and initial data acquisition; S2. Perform dynamic amplitude limiting calculation; S3. Then execute the improved PID real-time control; S4. Iterative optimization is performed every 10 control cycles; S5. Finally, implement special compensation for system lag issues.
2. The fast-response PID control method according to claim 1, characterized in that, Step S1 includes the following steps: S11. At startup, it adopts full-range PID mode with an output range of 0-65535 and runs continuously for 10 control cycles, 10 seconds / cycle. S12. Record the PID output value, liquid supply temperature feedback value and actual opening time of the solenoid valve in real time for each cycle, and store these data in the ring buffer. S13. Calculate the average PID output Ū as the baseline value, and at the same time establish a temperature valve opening time mapping model.
3. The fast-response PID control method according to claim 1, characterized in that, Step S2 includes the following steps: S21. Calculate the dynamic limiting range based on the Ū value initially acquired in step S1: The upper limit is: ; The lower limit is: ; S22. Introduce a compensation factor β based on the liquid supply temperature. When the temperature is <20℃, take 0.95 to enhance low temperature control; otherwise, take 1.
0. Generate the corrected limiting parameters and pass them to the next stage.
4. The fast-response PID control method according to claim 1, characterized in that, Step S3 includes the following steps: S31. A PID algorithm with energy compensation is adopted, as shown in equation (1): ； In the formula, For PID output signals; To account for the deviation between the set temperature and the measured temperature; This is the proportionality coefficient; The integral time constant; The differential time constant; S32. The product generated in step S2 As the primary limiting range, when e(t) > 2℃, the secondary protection mechanism is activated to automatically extend the limiting by ±20%, ultimately outputting the PWM duty cycle: ； S33. Continuously record valve opening time data during the control process to provide a basis for subsequent optimization.
5. The fast-response PID control method according to claim 1, characterized in that, Step S4 includes the following steps: S41. Obtain the new PID output sequence and calculate the mean. ,when Update the baseline value And recalculate the limiting range; S42. Dynamically adjust parameters based on control effectiveness for 5 consecutive cycles. The α value is decreased when temperature overshoot occurs, and the Bias value is increased when temperature overshoot occurs, forming a closed-loop feedback from the execution layer to the optimization layer.
6. The fast-response PID control method according to claim 1, characterized in that, Step S5 includes the following steps: S51. Based on the initially collected data from Figures 5 and 6, construct a prediction model and calculate the delay time: ； S52. When the target temperature changes Additional feedforward compensation output: ； in, At the same time The dead zone range is replaced by on / off control instead of PID; S53. The compensation signal is directly superimposed onto the main control loop, and the τ value is recalibrated every 30 cycles.