Temperature control method and system for low-temperature wind tunnel based on composite adaptive control

Abstract

The present invention belongs to the field of wind tunnel flow field control and discloses a low-temperature wind tunnel temperature control method and system based on composite adaptive control. The present invention combines three control strategies: feedforward control, model reference adaptive control, and PI control. This method not only provides feedforward control for the effects of known heat sources such as compressor heat generation and tunnel wall heat transfer in the wind tunnel, but also effectively estimates and offsets unmodeled real-time disturbances, while ensuring that the wind tunnel temperature steady-state value converges to the target value. In this process, the proposed method estimates the existing time lag and takes into account the effects of the actuator's own characteristics, enabling rapid and precise control of the low-temperature wind tunnel temperature.

Description

Technical Field

[0001] The present invention relates to the field of wind tunnel flow field control, and in particular to a low-temperature wind tunnel temperature control method and system based on composite adaptive control. Background Art

[0002] Low-temperature wind tunnels can significantly improve their ability to simulate high Reynolds number tests by lowering the total test temperature. This is achieved by injecting liquid nitrogen into the wind tunnel circuit through a liquid nitrogen injection system. During the vaporization process, the liquid nitrogen absorbs a large amount of heat, thereby lowering the test environment temperature in the wind tunnel.

[0003] Temperature control in cryogenic wind tunnels is achieved by regulating the amount of liquid nitrogen injected into the tunnel through a liquid nitrogen injection system. Increasing the amount of liquid nitrogen injected increases the downward trend in the tunnel airflow temperature, while decreasing the amount of liquid nitrogen injected increases the upward trend in the tunnel airflow temperature. The addition of the liquid nitrogen injection system creates a strong coupling between the control and operation of the cryogenic wind tunnel flow field parameters and demonstrates multivariable control characteristics. The tunnel temperature is primarily affected by liquid nitrogen vaporization and compressor performance. The injected liquid nitrogen absorbs heat during vaporization, balancing the heat generated by the compressor and counteracting the effects of heat transfer from the tunnel walls. Therefore, temperature control is dependent on both the liquid nitrogen injection system and the compressor system. However, the compressor system is the primary influencer of the wind tunnel's Mach number, and therefore is coupled to the wind tunnel's Mach number control during temperature control. Furthermore, when controlling wind tunnel pressure, changes in the gas pressure and density within the wind tunnel result in changes in the total gas mass within the wind tunnel. The same amount of liquid nitrogen injected can result in different temperature regulation effects, thus coupling temperature control with wind tunnel pressure control.

[0004] In view of this, the present invention is proposed. Summary of the Invention

[0005] The present invention aims to solve one of the technical problems in the related art at least to a certain extent.

[0006] To this end, the first technical solution adopted in the present invention is:

[0007] A temperature control method for a low-temperature wind tunnel based on composite adaptive control includes:

[0008] Based on the fluid dynamics characteristics of the wind tunnel, the transmission delay from liquid nitrogen injection into the wind tunnel to temperature sensor detection is calculated in real time;

[0009] Calculate the temperature impact caused by the actuator characteristics based on the input signal and output flow response characteristics of the liquid nitrogen valve and the transmission time lag;

[0010] Based on the compressor heat generation power and the tunnel wall heat transfer model, the feedforward control quantity to offset the thermal disturbance is calculated;

[0011] By referring to the tracking target temperature output by the reference model, the adaptive compensation amount is calculated using the error signal corrected by the temperature effect;

[0012] When the actual temperature deviates from the target threshold, the PI controller outputs the accelerated convergence control amount;

[0013] The feedforward control amount, the adaptive compensation amount and the accelerated convergence control amount are synthesized, and the physical injection amount is output to the liquid nitrogen system according to the saturation characteristics of the actuator and the transfer function model.

[0014] Preferably, the transmission time lag consists of the following three parts: a delay from the actuator to the sensor, an execution delay of the liquid nitrogen injection system, and a collection delay of the temperature sensor.

[0015] Preferably, the transmission time lag τ is calculated as follows:

[0016] ;

[0017] ;

[0018] in, is the actuator-to-sensor delay, is the execution delay of the liquid nitrogen injection system, is the acquisition delay of the temperature sensor, 、 、 、 、 They are the total pressure, temperature, Mach number, volume and flow rate of the wind tunnel.

[0019] Preferably, the calculation method of the temperature effect caused by the actuator characteristics is:

[0020] The difference between the actual liquid nitrogen injection amount and the theoretical liquid nitrogen injection amount is calculated in combination with the transmission time delay;

[0021] Dynamically determine the temperature control gain per kilogram of liquid nitrogen based on the current wind tunnel operating conditions;

[0022] The temperature influence caused by the actuator characteristics is obtained by dividing the difference by the temperature control gain.

[0023] Preferably, the calculation method of the feedforward control amount for offsetting thermal disturbance is:

[0024] Collect the compressor outlet temperature, compressor inlet temperature and pressure, and calculate the compressor heat generation power;

[0025] Collect the tunnel wall temperature and air flow temperature at key measuring points, and calculate the tunnel wall heat transfer power according to the convection heat transfer formula;

[0026] The feedforward control quantity to offset the thermal disturbance is obtained by integrating the heat generation power of the compressor and the heat transfer power of the cavity wall.

[0027] Preferably, the transfer function of the reference model is:

[0028] ,in , , represents the transfer function and s is the complex variable in the Laplace transform.

[0029] Preferably, the adaptive compensation amount is calculated as follows:

[0030] Calculate the error between the tracking target temperature output by the reference model and the actual wind tunnel temperature;

[0031] Introducing the temperature effect caused by the actuator characteristics to correct the error,

[0032] According to the correction error calculated in real time, the controller parameter structure is dynamically adjusted according to the preset adaptive law to minimize the correction error;

[0033] The adjusted and updated control law is the adaptive compensation.

[0034] Preferably, the physical injection amount μac1 is generated according to the following rules:

[0035] ,in, Represents the composite control quantity of feedforward control quantity, adaptive compensation quantity and accelerated convergence control quantity Perform rate limiting and stroke limiting, is the transfer function of the liquid nitrogen injection system.

[0036] The second technical solution adopted in the present invention is:

[0037] The temperature control system of the low-temperature wind tunnel based on composite adaptive control includes:

[0038] The first calculation module is used to calculate the transmission time delay from the injection of liquid nitrogen into the wind tunnel to the temperature sensor sensing in real time based on the fluid dynamic characteristics of the wind tunnel;

[0039] A second calculation module is used to calculate the temperature impact caused by the actuator characteristics based on the liquid nitrogen valve input signal and output flow response characteristics combined with the transmission time lag;

[0040] The third calculation module is used to calculate the feedforward control amount to offset the thermal disturbance based on the compressor heat generation power and the cavity wall heat transfer model;

[0041] A fourth calculation module is used to calculate an adaptive compensation amount by using the error signal corrected by the temperature effect through the tracking target temperature output by the reference model;

[0042] The first output module is used for the PI controller to output an accelerated convergence control amount when the actual temperature deviates from the target threshold;

[0043] The second output module is used to synthesize the feedforward control amount, the adaptive compensation amount and the accelerated convergence control amount, and output the physical injection amount to the liquid nitrogen system according to the saturation characteristics of the actuator and the transfer function model.

[0044] Compared with the prior art, the present invention has the following beneficial effects:

[0045] The present invention eliminates the mutual coupling between temperature and other flow field parameters, realizes temperature decoupling control, and the controller output can realize low-temperature wind tunnel temperature control to converge to the target temperature according to the designed reference model. Compared with traditional PID control, it greatly reduces debugging consumption and improves the intelligence of flow field control. BRIEF DESCRIPTION OF THE DRAWINGS

[0046] Figure 1 A schematic flow chart of a low-temperature wind tunnel temperature control method based on composite adaptive control provided in an embodiment of the present invention;

[0047] Figure 2 This is a schematic structural diagram of a low-temperature wind tunnel temperature control system based on composite adaptive control provided in an embodiment of the present invention. DETAILED DESCRIPTION

[0048] In order to make the purpose, technical solutions and advantages of the implementation of this application clearer, the technical solutions in the embodiments of this application will be described in more detail below in conjunction with the drawings in the embodiments of this application. In the drawings, the same or similar reference numerals throughout represent the same or similar elements or elements with the same or similar functions. The described embodiments are part of the embodiments of this application, not all of the embodiments. The embodiments described below with reference to the drawings are exemplary and are intended to be used to explain this application, and should not be understood as limitations on this application. Based on the embodiments in this application, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of this application.

[0049] refer to Figure 1 The first embodiment of the present invention provides a low-temperature wind tunnel temperature control method based on composite adaptive control, which specifically includes the following steps.

[0050] S101 calculates the transmission time delay from liquid nitrogen injection into the wind tunnel to temperature sensor perception in real time based on the fluid dynamics characteristics of the wind tunnel.

[0051] The purpose of this step is to actively estimate time lag. In existing solutions, time lag is considered a fixed value, but in actual control, time lag varies with flow. This invention updates time lag through online calculation to reduce or compensate for the impact of time lag on system performance, thereby improving the dynamic and steady-state performance of the system.

[0052] Specifically, the transmission time delay τ is composed of the following three parts: the delay from the actuator to the sensor, the execution delay of the liquid nitrogen injection system, and the acquisition delay of the temperature sensor. The calculation formula is:

[0053] ,

[0054] ,in, is the delay from the actuator to the sensor, which is the variable time lag. is the execution delay of the liquid nitrogen injection system, is a fixed time delay, is the acquisition delay of the temperature sensor, is a fixed time lag, 、 、 、 、 They are the total pressure, temperature, Mach number, volume and flow rate of the wind tunnel.

[0055] S102 , calculating the temperature impact caused by the actuator characteristics based on the input signal and output flow response characteristics of the liquid nitrogen valve and the transmission time lag.

[0056] This step calculates the temperature impact of the liquid nitrogen injection system's inherent characteristics—the temperature change caused by the inconsistency between the liquid nitrogen injection rate and the controller output due to the actuator's characteristics—and outputs this value to S104 and S106. Incorporating the temperature impact of the actuator's characteristics significantly improves model tracking accuracy.

[0057] The specific calculation method for the temperature effect caused by the actuator characteristics is:

[0058] Combined with the transmission time delay τ, the difference between the actual liquid nitrogen injection amount μ1 and the theoretical liquid nitrogen injection amount μ2 at time t is calculated as μ1(t-τ)-μ2;

[0059] Dynamically determine the temperature control gain g per kilogram of liquid nitrogen based on the current wind tunnel operating conditions;

[0060] The temperature effect ΔT caused by the actuator characteristics is obtained by dividing the difference by the temperature control gain, that is, ΔT=(μ1(t-τ)-μ2) / g.

[0061] The above temperature control gain g is updated in real time according to the working conditions and is more accurate than fixed gain compensation.

[0062] S103: Calculate a feedforward control variable to offset thermal disturbance based on the compressor heat generation power and the cavity wall heat transfer model.

[0063] This step is feedforward control, which uses the feedforward control quantity to offset the heat generated by the compressor and the heat transfer of the cave wall, thus solving the measurable disturbance.

[0064] Specifically, the calculation method of the feedforward control quantity to offset thermal disturbance is:

[0065] Collect the compressor outlet temperature, compressor inlet temperature and pressure, calculate the compressor power and convert it into the compressor heat generation power;

[0066] Collect the tunnel wall temperature and air flow temperature at key measuring points, and calculate the tunnel wall heat transfer power according to the convection heat transfer formula;

[0067] The heat generation power of the compressor and the heat transfer power of the tunnel wall are combined to obtain the feedforward control quantity to offset the thermal disturbance, that is, the liquid nitrogen flow rate required to offset the heat generation of the compressor and the heat transfer of the tunnel wall.

[0068] S104 , calculating an adaptive compensation amount by referring to the tracking target temperature output by the reference model and using the error signal corrected by the temperature effect.

[0069] This step is called model-referenced adaptive dynamic compensation control, and its purpose is to offset unmodeled disturbances in the wind tunnel (such as airflow pulsation and sensor noise) in real time, so that the actual temperature accurately tracks the ideal trajectory.

[0070] Specifically, the calculation method of the adaptive compensation amount is:

[0071] S104-1, establish a reference model of the controlled object.

[0072] The purpose of this step is to design a critically damped second-order reference model with optimized parameters (natural frequency 0.7, damping ratio 0.95). This model converts the set target temperature into a smooth transition curve, avoiding step changes and ensuring that the output temperature trajectory has an exponential convergence characteristic without overshoot. The transfer function of the reference model is, ,in , , ωn controls the convergence speed (the smaller the value, the slower), ε sets the critical damping (to avoid overshoot), represents the transfer function and s is the complex variable in the Laplace transform.

[0073] S104-2, calculating the error between the tracking target temperature output by the reference model and the actual wind tunnel temperature.

[0074] S104-3, introducing the temperature influence caused by the actuator characteristics to perform error correction.

[0075] The purpose of steps S104-2 and S104-3 is to calculate the corrected tracking error, e, as follows: e = Tt − Tc − ΔT, where Tc is the target temperature and Tt is the actual wind tunnel temperature. In this step, ΔT quantifies the temperature deviation caused by nonlinearities (such as deadband and saturation) in the liquid nitrogen valve. This interference is removed from the error, allowing the adaptive law to focus on the actual disturbance.

[0076] S104-3, based on the real-time calculated correction error, dynamically adjust the parameter structure of the controller according to a preset adaptive law to minimize the correction error.

[0077] The purpose of this step is to dynamically optimize the compensation parameters. Based on the correction error e, the control parameters are adjusted in real time through the adaptive law: when |e| is large, the compensation strength is quickly increased to quickly suppress the disturbance; when |e| is close to zero, the parameters are fine-tuned to avoid oscillation.

[0078] S104-4, the control law after adjustment and update is the adaptive compensation amount.

[0079] The purpose of this step is to output a disturbance compensation amount, namely an adaptive compensation amount, whose value is proportional to the estimated unmodeled disturbance intensity: if a positive disturbance is detected, the adaptive compensation amount is to increase the liquid nitrogen injection amount; if a negative disturbance is detected, the adaptive compensation amount is to reduce the injection amount.

[0080] S105 , when the actual temperature deviates from the target threshold, the PI controller outputs an accelerated convergence control variable.

[0081] When the actual wind tunnel temperature fails to converge to the target temperature for a long time, the PI control module is activated to output the control variable to accelerate convergence, compensating for the hysteresis of the adaptive control. This hierarchical strategy enables precise classification and processing of disturbance types.

[0082] S106 , synthesizing the feedforward control amount, the adaptive compensation amount, and the accelerated convergence control amount, and outputting the physical injection amount to the liquid nitrogen system according to the actuator saturation characteristics and the transfer function model.

[0083] Specifically, the synthetic control amount ( ) = feedforward control amount + adaptive compensation amount + accelerated convergence control amount. The composite control amount is corrected by the actuator characteristics and output as the physical injection amount μacl, which is generated according to the following rules:

[0084] ,in, Represents the composite control quantity of feedforward control quantity, adaptive compensation quantity and accelerated convergence control quantity Perform rate limiting and stroke limiting, is the transfer function of the liquid nitrogen injection system.

[0085] This embodiment of the present invention combines three control strategies: feedforward control, model-referenced adaptive control, and PI control. This approach not only provides feedforward control for known heat sources in the wind tunnel, such as compressor heat generation and wall heat transfer, but also effectively estimates and offsets unmodeled real-time disturbances, ensuring that the wind tunnel steady-state temperature converges to the target value. In this process, the proposed method estimates existing time lags and accounts for the effects of the actuator's inherent characteristics, enabling rapid and precise temperature control in low-temperature wind tunnels.

[0086] refer to Figure 2 The second embodiment of the present invention provides a low-temperature wind tunnel temperature control system 200 based on composite adaptive control, including a first calculation module 201, a second calculation module 202, a third calculation module 203, a fourth calculation module 204, a first output module 205, and a second output module 206. The functions of each module are described in detail as follows:

[0087] The first calculation module 201 is used to calculate the transmission time delay from liquid nitrogen injection to temperature sensor sensing in real time based on the wind tunnel fluid dynamics characteristics;

[0088] A second calculation module 202 is configured to calculate the temperature impact caused by the actuator characteristics based on the liquid nitrogen valve input signal and output flow response characteristics in combination with the transmission time lag;

[0089] The third calculation module 203 is used to calculate the feedforward control quantity for offsetting the thermal disturbance based on the heat generation power of the compressor and the heat transfer model of the cavity wall;

[0090] A fourth calculation module 204 is configured to calculate an adaptive compensation amount using the error signal corrected for temperature effects by using the tracking target temperature output by the reference model;

[0091] The first output module 205 is configured to cause the PI controller to output an accelerated convergence control variable when the actual temperature deviates from the target threshold;

[0092] The second output module 206 is used to synthesize the feedforward control amount, the adaptive compensation amount and the accelerated convergence control amount, and output the physical injection amount to the liquid nitrogen system according to the actuator saturation characteristics and the transfer function model.

[0093] Furthermore, the terms "first" and "second" are used for descriptive purposes only and should not be understood to indicate or imply relative importance or implicitly specify the quantity of the technical features indicated. Thus, features defined as "first" or "second" may explicitly or implicitly include at least one of these features.

[0094] Although the embodiments of the present invention have been shown and described above, it will be understood that the above embodiments are illustrative and are not to be construed as limitations on the present invention. A person skilled in the art may change, modify, replace and modify the above embodiments within the scope of the present invention.

Claims

1. A temperature control method for a low-temperature wind tunnel based on composite adaptive control, characterized in that: Include: Based on the fluid dynamics characteristics of the wind tunnel, the transmission delay from liquid nitrogen injection into the wind tunnel to temperature sensor detection is calculated in real time; Calculate the temperature impact caused by the actuator characteristics based on the input signal and output flow response characteristics of the liquid nitrogen valve and the transmission time lag; Based on the compressor heat generation power and the tunnel wall heat transfer model, the feedforward control quantity to offset the thermal disturbance is calculated; By referring to the tracking target temperature output by the reference model, the adaptive compensation amount is calculated using the error signal corrected by the temperature effect; When the actual temperature deviates from the target threshold, the PI controller outputs the accelerated convergence control amount; The feedforward control variable, adaptive compensation variable, and accelerated convergence control variable are synthesized, and the physical injection quantity is output to the liquid nitrogen injection system based on the actuator saturation characteristics and the transfer function model. The transmission time delay is composed of the following three parts: the delay from the actuator to the temperature sensor, the execution delay of the liquid nitrogen injection system, and the acquisition delay of the temperature sensor. The transmission time delay τ is calculated as follows: ； ； in, is the delay from the actuator to the temperature sensor, is the execution delay of the liquid nitrogen injection system, is the acquisition delay of the temperature sensor, 、 、 、 、 They are the total pressure, temperature, Mach number, volume and flow rate of the wind tunnel.

2. The temperature control method of a low-temperature wind tunnel based on composite adaptive control according to claim 1, characterized in that: The calculation method for the temperature effect caused by the actuator characteristics is: The difference between the actual liquid nitrogen injection amount and the theoretical liquid nitrogen injection amount is calculated in combination with the transmission time delay; Dynamically determine the temperature control gain per kilogram of liquid nitrogen based on the current wind tunnel operating conditions; The temperature influence caused by the actuator characteristics is obtained by dividing the difference by the temperature control gain.

3. The temperature control method of a low-temperature wind tunnel based on composite adaptive control according to claim 1, characterized in that: The calculation method of the feedforward control quantity to offset thermal disturbance is: Collect the compressor outlet temperature, compressor inlet temperature and pressure, and calculate the compressor heat generation power; Collect the tunnel wall temperature and air flow temperature at key measuring points, and calculate the tunnel wall heat transfer power according to the convection heat transfer formula; The feedforward control quantity to offset the thermal disturbance is obtained by integrating the heat generation power of the compressor and the heat transfer power of the cavity wall.

4. The temperature control method for a low-temperature wind tunnel based on composite adaptive control according to claim 1, characterized in that: The transfer function of the reference model is: ,in , , represents the transfer function and s is the complex variable in the Laplace transform.

5. The temperature control method for a low-temperature wind tunnel based on composite adaptive control according to claim 1 or 4, characterized in that: The calculation method of adaptive compensation is: Calculate the error between the tracking target temperature output by the reference model and the actual wind tunnel temperature; Introducing the temperature effect caused by the actuator characteristics to correct the error, According to the correction error calculated in real time, the controller parameter structure is dynamically adjusted according to the preset adaptive law to minimize the correction error; The adjusted and updated control law is the adaptive compensation.

6. The temperature control method of a low-temperature wind tunnel based on composite adaptive control according to claim 1, characterized in that: The physical injection amount μac1 is generated according to the following rules: ,in, Represents the composite control quantity of feedforward control quantity, adaptive compensation quantity and accelerated convergence control quantity Perform rate limiting and stroke limiting, is the transfer function of the liquid nitrogen injection system.

7. A low-temperature wind tunnel temperature control system based on compound adaptive control, configured to execute the low-temperature wind tunnel temperature control method based on compound adaptive control according to any one of claims 1 to 6, characterized in that: include: The first calculation module is used to calculate the transmission time delay from the injection of liquid nitrogen into the wind tunnel to the temperature sensor sensing in real time based on the fluid dynamic characteristics of the wind tunnel; A second calculation module is used to calculate the temperature impact caused by the actuator characteristics based on the liquid nitrogen valve input signal and output flow response characteristics combined with the transmission time lag; The third calculation module is used to calculate the feedforward control quantity for offsetting the thermal disturbance based on the heat generation power of the compressor and the heat transfer model of the cavity wall; A fourth calculation module is used to calculate an adaptive compensation amount by using the error signal corrected by the temperature effect through the tracking target temperature output by the reference model; The first output module is used for the PI controller to output an accelerated convergence control amount when the actual temperature deviates from the target threshold; The second output module is used to synthesize the feedforward control amount, the adaptive compensation amount and the accelerated convergence control amount, and output the physical injection amount to the liquid nitrogen injection system according to the saturation characteristics of the actuator and the transfer function model.

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