A PID parameter self-tuning algorithm for temperature control

Abstract

The present invention aims to provide a PID parameter self-tuning algorithm for temperature control that can effectively avoid large overshoots, ensure temperature stability, and have a fast tuning speed. The present invention performs self-tuning when starting temperature control of the device, records the times to reach the temperature limit and the target temperature during full-power regulation of the temperature, and after reaching the target temperature, executes a variable excitation output to the temperature control module according to the excitation function to gradually change the temperature in the controlled environment. Subsequently, the actual temperature limit value of the controlled environment after reaching the target temperature and the time to return to the temperature limit are collected. According to the actual temperature limit value, the maximum excitation, the temperature limit, t0, t1, t2, and the control period TC of the controller, combined with the Ziegler-Nichols method, the PID control parameters are calculated. The present invention is applied to the technical field of PID control.

Description

Technical Field

[0001] The present invention is applied to the technical field of PID control, and particularly relates to a PID parameter self-tuning algorithm for temperature control. Background Art

[0002] For products or places that are sensitive to environmental temperature, in order to ensure that the items in the products or places will not change in form or deteriorate due to temperature changes, it is necessary to strictly control the temperature of the place. For example, places with strict temperature control requirements such as barns and greenhouses, and also structures for melting and heat preservation of raw materials in injection molding equipment. Most current temperature control devices basically use PID controllers for automatic temperature adjustment to ensure that the temperature of the place is relatively constant.

[0003] The acquisition of various parameters of the existing temperature PID control mainly includes step open-loop self-tuning method, step closed-loop self-tuning method, relay self-tuning method, and relay feedback self-tuning method.

[0004] Among them, the step open-loop self-tuning method is to apply a step to the input and wait until the steady state is reached (the process variable remains unchanged). This method assumes that the user can model any process as a first-order lag and pure dead time. The step open-loop self-tuning method tests the dead time Td, time constant T, and process gain K values of the controller, and multiplies them according to the formula of heuristic method; for example, most PIDs use the Ziegler-Nichols method. The step closed-loop self-tuning method is similar to the step open-loop method and reaches the steady state faster than the step open-loop method. As Figure 1 shown, the relay self-tuning method is to use a setpoint relay experiment to determine the information required for tuning the controller. The relay feedback self-tuning method is a variant of the closed-loop step test, but it is more effective for systems with large time constants.

[0005] In the above methods, large overshoots will occur in the open-loop and relay algorithms, which may cause danger in high-temperature control occasions. At the same time, the open-loop and relay algorithms will suddenly cancel the excitation (or apply the reverse maximum excitation) during tuning, resulting in noise caused by system mutations. In addition, the relay algorithm has a long tuning time and requires at least two cycles to stabilize. Summary of the Invention

[0006] The technical problem to be solved by the present invention is to overcome the deficiencies of the prior art, and provide a PID parameter self-tuning algorithm for temperature control that can effectively avoid large overshoots, ensure temperature stability, and has a fast tuning speed.

[0007] The technical solution adopted by the present invention is as follows: The present invention includes the following steps:

[0008] Step S1. Set the target temperature T and the temperature threshold Tthr ;

[0009] Step S2. Perform self-tuning;

[0010] In the initial stage of self-tuning in Step S3, initialize the time t to 0, and the device outputs the maximum excitation E Max to the temperature control module, thereby controlling the actual temperature A in the controlled environment to change towards the target temperature T;

[0011] In Step S4, when the actual temperature A reaches the temperature threshold T thr record the current time as time t0;

[0012] In Step S5, when the actual temperature A reaches the target temperature T, record the current time as time t1;

[0013] In Step S6, the device executes to output a variable excitation E to the temperature control module according to the excitation function to change the temperature in the controlled environment, and collect the extreme value T of the actual temperature A after time t1 ext ; The excitation function is , where t is the current time;

[0014] In Step S7, when the actual temperature A returns to the temperature threshold T at time t0 thr record the current time as time t2;

[0015] In Step S8, according to the extreme value T of the actual temperature ext , the maximum excitation E Max , the temperature threshold T thr , t0, t1, t2 and the control period TC, combined with the Ziegler-Nichols method, calculate the PID control parameters.

[0016] As can be seen from the above solution, by using the function described in Step S6 as the excitation function, the excitation signal of the temperature control module can be adjusted in a timely manner, thereby effectively suppressing the large overshoot of the temperature during the execution of self-tuning, resulting in the actual temperature exceeding the set upper or lower limit, ensuring that the items or raw materials in the controlled scenario will not be damaged or deteriorated. At the same time, using this excitation function can complete parameter tuning within one control period, thereby ensuring that the temperature is relatively constant during the tuning process and ensuring the temperature control effect. In addition, it can also achieve no mutation during the tuning process, which is beneficial to filtering the disturbance when collecting the actual temperature.

[0017] A preferred solution is that the temperature threshold T thr includes the upper temperature limit T Max and the lower temperature limit T min ; When the requirement of the controlled environment is to increase the temperature, the temperature threshold T in Step S4 thr is the lower temperature limit T min; When the requirement of the controlled environment is to cool down, the temperature threshold T in step S4 thr is the upper temperature limit T Max .

[0018] A preferred solution is that the Ziegler-Nichols method in step S8 is to calculate the ultimate gain KU and the oscillation period TU according to the obtained parameters, and select the calculation coefficients of the proportional parameter Kc, the integral action parameter Ti, and the derivative action parameter Td according to the temperature change rate of the controlled environment; where the ultimate gain KU satisfies , and the oscillation period TU satisfies .

[0019] A preferred solution is that the deformed form of the excitation function according to the controlled scenario and the device hardware parameters is , where , … are calculation coefficients, which are determined according to the controlled scenario and the device hardware parameters. Description of the Drawings

[0020] Figure 1 is the working principle diagram of the existing relay self-tuning method;

[0021] Figure 2 is the excitation signal change diagram of Embodiment 1 of the present invention;

[0022] Figure 3 is the temperature change diagram of Embodiment 1 of the present invention. Detailed Embodiments

[0023] Embodiment 1:

[0024] In this embodiment, the temperature control mode is heating control. The temperature of the controlled scenario decreases with time. The device includes a temperature sensor for detecting the real-time temperature A in the controlled environment and a heating device for increasing the temperature in the controlled environment. The heating device is controlled by a PID controller or a P controller or a PI controller for the heating power, and the heating power is adjusted by adjusting the output excitation signal; the PID algorithm parameters are adjusted through the PID parameter self-tuning algorithm to make the temperature fluctuation smaller when maintaining a constant temperature.

[0025] As Figure 2 and Figure 3 shown, the PID parameter self-tuning algorithm includes the following steps:

[0026] Step S1. Determine the temperature requirement in the environment according to the controlled environment and the physical or chemical properties of the items in the environment. Communicate with the device through a computer to obtain the target temperature T, the upper temperature limit T Max and the lower temperature limit Tmin Setting;

[0027] Step S2. Start the self-tuning of the PID controller;

[0028] In the initial stage of self-tuning, initialize the time t to 0, and at this time, the device outputs the maximum excitation E Max to the temperature control module, and the temperature control module heats up the controlled environment at full power, thereby gradually increasing the actual temperature A in the controlled environment;

[0029] Step S4. When the temperature sensor detects that the actual temperature A at the current time reaches the lower temperature limit T min the system records the current time as time t0 and maintains full-power heating;

[0030] Step S5. When the temperature sensor detects that the actual temperature A at the current time reaches the target temperature T, the system records the current time as time t1 and stops full-power heating and switches to the variable temperature mode;

[0031] In the variable temperature mode, the device executes to output a variable excitation E to the temperature control module according to the excitation function, so that the power of the temperature control module gradually decreases. During this period, the temperature in the controlled environment will be affected by the afterheat of the temperature control module and maintain a short-term temperature increase and then become a temperature decrease, and the system monitors the temperature change of the actual temperature A after time t1 in real time and obtains the maximum value A of the real-time temperature during the temperature change process Max ;

[0032] The excitation function is , where t is the current time;

[0033] Step S7. When the actual temperature A drops back to the lower temperature limit T min the system records the current time as time t2;

[0034] Step S8. According to the maximum value A of the actual temperature Max , the maximum excitation E Max , the lower temperature limit T min , t0, t1, t2 and the control period TC of the PID controller, combined with the Ziegler-Nichols method, calculate the PID control parameters.

[0035] In this embodiment, the control period TC of the PID controller is an inherent parameter of the selected PID controller and is determined according to the parameter table corresponding to the selected PID controller model.

[0036] The Ziegler-Nichols method described in step S8 is a method for tuning a PID controller and exploring its control parameters. The debugging method is as follows: First, set the integral and derivative gains to 0, and then gradually increase the proportional gain from zero until the limit gain KU is reached. At this time, the controller output value oscillates at a constant value. The limit gain KU and the oscillation period TU are used to set the proportional, integral, and derivative gains according to the following table for different types.

[0037] The temperature of the controlled environment is regulated by the temperature control module through the excitation function, and then the above parameters are obtained. The limit gain KU and the oscillation period TU are calculated through the above parameters. The limit gain KU satisfies , and the oscillation period TU satisfies .

[0038] As shown in Table 1, the calculation coefficients of the proportional parameter Kc, the integral action parameter Ti, and the derivative action parameter Td are selected according to the temperature change rate of the controlled environment and the type of the controller.

[0039]

[0040] For example, in the scenario of heating and melting injection molding raw materials, the calculation coefficients corresponding to fast performance are selected to meet the scenario with a relatively fast temperature change. For scenarios with a relatively slow temperature change, such as barn temperature control, the calculation coefficients corresponding to normal performance or slow performance are selected.

[0041] The values of the proportional parameter Kc, the integral action parameter Ti, and the derivative action parameter Td are calculated through the selected calculation coefficients and output to the PID controller to perform the temperature control of the controlled environment, thereby ensuring that the temperature in the controlled environment is relatively constant.

[0042] Example 2:

[0043] In this embodiment, the difference between this embodiment and Embodiment 1 is that the deformation formula of the excitation function according to the controlled scenario and the device hardware parameters is , where , … are calculation coefficients, which are determined according to the controlled scenario and the device hardware parameters.

[0044] In different temperature control modules and controlled scenarios, different hardware parameters will result in different temperature change rates. In order to adapt to different temperature change rates and the control period TC of different controllers, the deformation formula of the above excitation function is used to adjust the change curve when the temperature drops, and then the PID parameters that can meet the temperature stability of the corresponding scenario are obtained.

[0045] Although the embodiments of the present invention are described in terms of actual solutions, they do not constitute a limitation on the meaning of the present invention. For those skilled in the art, modifications to its implementation solutions according to this specification and combinations with other solutions are obvious.

Claims

1. A PID parameter self-tuning algorithm for temperature control, characterized in that: It includes the following steps: Step S1. Set the target temperature T and the temperature threshold T thr ; Step S2: Execute self-tuning; Step S3. In the initial stage of self-tuning, the initialization time t is 0, and the device outputs the maximum excitation E Max To the temperature control module, and then control the actual temperature A in the controlled environment to change towards the target temperature T; Step S4. When the actual temperature A reaches the temperature threshold T thr When , the current time is recorded as time t0; Step S5. When the actual temperature A reaches the target temperature T, the current time is recorded as time t1; Step S6. The device outputs a variable excitation E to the temperature control module according to the excitation function to change the temperature in the controlled environment, and collects the extreme value T of the actual temperature A after time t1. ext ; The activation function is , where t is the current moment; Step S7: When the actual temperature A returns to the temperature threshold T at time t0 thr When , the current time is recorded as time t2; Step S8. According to the extreme value T of the actual temperature ext , maximum incentive E Max , temperature threshold T thr , t0, t1, t2 and control period TC, combined with the Ziegler-Nichols method, the PID control parameters are calculated.

2. A PID parameter self-tuning algorithm for temperature control according to claim 1, characterized in that: The temperature threshold T thr Including upper temperature limit T Max And the lower limit temperature T min When the controlled environment requires heating, the temperature threshold T in step S4 thr is the lower limit of temperature T min When the controlled environment requires cooling, the temperature threshold T in step S4 thr The upper temperature limit T Max .

3. A PID parameter self-tuning algorithm for temperature control according to claim 1, characterized in that: The Ziegler-Nichols method in step S8 is to calculate the limit gain KU and the oscillation period TU according to the obtained parameters, and select the calculation coefficients of the proportional parameter Kc, the integral action parameter Ti and the differential action parameter Td according to the temperature change rate of the controlled environment; wherein the limit gain KU satisfies , the oscillation period TU satisfies .

4. A PID parameter self-tuning algorithm for temperature control according to claim 1, characterized in that: The variant of the activation function according to the controlled scenario and device hardware parameters is: ,in , … To calculate the coefficient, it is determined based on the controlled scenario and device hardware parameters.

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