Fluid pulsation control method, device and system based on time delay parameter model

Abstract

The invention provides a fluid pulsation control method, device and system based on a time delay parameter model, and the method comprises the steps: obtaining a lagging phase parameter of a control valve at a target frequency based on the target frequency of fluid pulsation, and obtaining the lagging phase parameter of the control valve at the target frequency based on the lagging phase parameter of the control valve at the target frequency and the basic time delay of a secondary channel; determining model parameters of the secondary channel estimation model, obtaining a reference signal based on the target frequency of the fluid pulsation, inputting the reference signal into the secondary channel estimation model to obtain a reference signal filtered by the secondary channel estimation model, and determining the target frequency of the fluid pulsation based on the reference signal filtered by the secondary channel estimation model and a reference control error of the fluid pulsation. And self-adaptive parameters are adjusted to realize active control. The method can ensure that the adaptive fluid pulsation control algorithm is suitable for stable control in a time-varying scene.

Description

Technical Field

[0001] The present application relates to the field of hydraulic control technology, and in particular to a fluid pulsation control method, device and system based on a time-delay parameter model. Background Art

[0002] In the fluid pulsation control scheme based on the bypass overflow principle, a bypass branch can be set on the main line between the hydraulic pump and the actuator, and a control valve can be installed on the bypass branch. The control valve is then controlled to generate a secondary pulsation wave, so that the secondary pulsation wave and the original pressure wave in the main line can be offset against each other, thereby reducing the fluid pulsation in the main line and achieving the purpose of fluid pulsation suppression.

[0003] In the related technology, the pulsation frequency of the fluid can be obtained, a reference signal can be constructed according to the pulsation frequency of the fluid, and then the control signal of the control valve can be determined according to the reference signal and the identification excitation signal. Then, the control signal of the control valve is used to control the control valve to generate a secondary pulsation wave. However, there is coupling between the adaptive filter used for identification and the notch filter used for control, which affects the stability of the adaptive fluid pulsation control algorithm. It is necessary to repeatedly adjust the parameters of the identification filter and the notch filter, which has poor practicality. Summary of the invention

[0004] According to one aspect of the present application, a fluid pulsation control method based on a time delay parameter model is provided, comprising:

[0005] Acquire a first reference signal and a second reference signal based on a target frequency of fluid pulsation, wherein the first reference signal and the second reference signal are orthogonal;

[0006] Inputting the first reference signal and the second reference signal into a secondary channel estimation model to obtain a reference signal filtered by the secondary channel estimation model;

[0007] Adjusting adaptive parameters based on the reference signal filtered by the secondary channel estimation model and the control error of the fluid pulsation;

[0008] Among them, the method for determining the model parameters of the secondary channel estimation model includes: obtaining the lag phase parameters of the control valve at the target frequency based on the target frequency of the fluid pulsation, and determining the model parameters of the secondary channel estimation model based on the lag phase parameters of the control valve at the target frequency and the basic delay of the secondary channel.

[0009] According to another aspect of the present application, a fluid pulsation control device based on a time delay parameter model is provided, comprising:

[0010] An acquisition module, configured to acquire a first reference signal and a second reference signal based on a target frequency of fluid pulsation, wherein the first reference signal and the second reference signal are orthogonal;

[0011] An adjustment module, configured to input the first reference signal and the second reference signal into a secondary channel estimation model to obtain a reference signal filtered by the secondary channel estimation model; and adjust an adaptive parameter based on the reference signal filtered by the secondary channel estimation model and a control error of fluid pulsation;

[0012] The identification module is used to obtain the lag phase parameters of the control valve at the target frequency based on the target frequency of the fluid pulsation, and determine the model parameters of the secondary channel estimation model based on the lag phase parameters of the control valve at the target frequency and the basic delay of the secondary channel.

[0013] According to another aspect of the present application, a fluid pulsation active control system is provided, including: a control valve, a pressure sensor and an active controller, the first end of the control valve is connected to a pipeline, the second end of the control valve is connected to a fuel tank, the pressure sensor and the control valve are both communicatively connected to the active controller, and the active controller is used to execute the method described in this exemplary embodiment.

[0014] According to another aspect of the present application, there is provided an electronic device, including:

[0015] processor; and,

[0016] A memory for storing programs;

[0017] The program includes instructions, which, when executed by the processor, cause the processor to perform the method described in the present application.

[0018] According to another aspect of the present application, a non-transitory computer-readable storage medium is provided, wherein the non-transitory computer-readable storage medium stores computer instructions, wherein the computer instructions are used to cause the computer to execute the method according to the exemplary embodiment of the present application.

[0019] According to another aspect of the present application, a computer program product is provided, including a computer program, and when the computer program is executed by a processor, the method described in the exemplary embodiments of the present application is implemented.

[0020] In one or more technical solutions provided by the present application, the model parameter determination process of the secondary channel estimation model does not involve online identification, but is based on the basic delay of the secondary channel, combined with the lag phase parameters of the control valve at the target frequency, and the model parameters of the secondary channel estimation model (i.e., the delay parameter model) are determined by offline identification, so that the model parameters of the secondary channel estimation model predicted are not affected by the notch filter. In this case, based on the reference signal filtered by the secondary channel estimation model and the control error of the fluid pulsation, after adjusting the adaptive parameters, the control stability of the adaptive fluid pulsation control algorithm can be improved, so that the adaptive fluid pulsation control algorithm is suitable for stable control in time-varying scenarios. BRIEF DESCRIPTION OF THE DRAWINGS

[0021] Further details, features and advantages of the present application are claimed in the following description of exemplary embodiments in conjunction with the accompanying drawings, in which:

[0022] Figure 1 An example schematic diagram of a fluid pulsation control system based on a bypass overflow principle is shown;

[0023] Figure 2 A schematic flow chart of a fluid pulsation control method based on a time delay parameter model according to an embodiment of the present application is shown;

[0024] Figure 3 A schematic diagram showing a flow chart of a method for determining model parameters of a secondary channel estimation model according to an embodiment of the present application;

[0025] Figure 4 A schematic diagram of a secondary channel framework of an embodiment of the present application is shown;

[0026] Figure 5 A schematic diagram showing simulation verification results of online identification of secondary channels in the related art;

[0027] Figure 6 A schematic diagram showing simulation verification results of the offline identification method according to an embodiment of the present application is shown;

[0028] Figure 7 A schematic diagram showing simulation verification results of an embodiment of the present application under time-varying working conditions is shown;

[0029] Figure 8 A schematic block diagram of functional modules of a fluid pulsation control device based on a time-delay parameter model according to an exemplary embodiment of the present application is shown;

[0030] Fig. 9 A schematic block diagram of a chip according to an exemplary embodiment of the present application is shown;

[0031] Fig.10 A structural block diagram of an exemplary electronic device that can be used to implement the embodiments of the present application is shown. DETAILED DESCRIPTION

[0032] The embodiments of the present application will be described in more detail below with reference to the accompanying drawings. Although certain embodiments of the present application are shown in the accompanying drawings, it should be understood that the present application can be implemented in various forms and should not be construed as being limited to the embodiments described herein. Instead, these embodiments are provided to provide a more thorough and complete understanding of the present application. It should be understood that the drawings and embodiments of the present application are only for exemplary purposes and are not intended to limit the scope of protection of the present application.

[0033] It should be understood that the various steps described in the method implementation of the present application can be performed in different orders and / or performed in parallel. In addition, the method implementation may include additional steps and / or omit the steps shown. The scope of the present application is not limited in this respect.

[0034] The term "including" and its variations used in this document are open inclusions, that is, "including but not limited to". The term "based on" means "based at least in part on". The term "one embodiment" means "at least one embodiment"; the term "another embodiment" means "at least one other embodiment"; the term "some embodiments" means "at least some embodiments". Relevant definitions of other terms will be given in the description below. It should be noted that the concepts of "first", "second", etc. mentioned in this application are only used to distinguish different devices, modules or units, and are not used to limit the order or interdependence of the functions performed by these devices, modules or units.

[0035] It should be noted that the modifications of "one" and "plurality" mentioned in the present application are illustrative rather than restrictive, and those skilled in the art should understand that unless otherwise clearly indicated in the context, it should be understood as "one or more".

[0036] Figure 1 An example schematic diagram of a fluid pulsation active control system based on a bypass overflow principle is shown. Figure 1As shown, the fluid pulsation active control system 100 can include an oil tank 101, a plunger pump 102, a motor 103, an overflow valve 104, a control valve 105, a throttle valve 106, a pressure sensor 107, and an active controller 108. The motor 103 is connected to the plunger pump 102, the outlet of the oil tank 101 is connected to the inlet of the plunger pump 102, the outlet of the plunger pump 102 is connected to the inlet of the overflow valve 104 and the inlet of the control valve 105 respectively, and the outlet of the control valve 105 is connected to the inlet of the oil tank 101 through the throttle valve 106. Here, the outlet of the plunger pump 102 can be connected to the overflow pipeline and the hydraulic pipeline respectively, the overflow valve 104 is arranged on the overflow pipeline, and the control valve 105 and the throttle valve 106 are arranged on the hydraulic pipeline. The pressure sensor 107 can be arranged in the hydraulic pipeline between the control valve 105 and the throttle valve 106. The outlet of the control valve 105 is also connected to the bypass pipeline, and the bypass pipeline is connected to the inlet of the oil tank 101. The active controller 108 is electrically connected to the pressure sensor 107 and the control valve 105 respectively.

[0037] When implementing it, Figure 1 As shown, driven by the motor 103, the plunger pump 102 rotates, so that the plunger pump 102 draws low-pressure oil from the oil tank 101 and sends the low-pressure oil into the hydraulic pipeline, and the low-pressure oil returns to the oil tank 101 through the throttle valve 106; the overflow valve 104 can control the pressure in the hydraulic pipeline not to exceed the set pressure, thereby playing a safety protection role; the active controller 108 can obtain the pressure signal of the position through the pressure sensor 107, and use it as the control error of the fluid pulsation, and update the parameters required in the active control process of the fluid pulsation, so that when the fluid pulsation active control signal controls the control valve 105, the control valve 105 can be used as an active control actuator to control the oil flow of the bypass pipeline.

[0038] The above-mentioned control valve can be a servo valve or other control valves. Taking the servo valve as an example, the pulsation frequency of the oil can be obtained, and a reference signal can be constructed according to the pulsation frequency of the oil. Then, the reference signal is input into a notch filter, and the reference signal is weighted and summed using the weight coefficient in the notch filter to obtain the control signal of the servo valve. Then, the control signal of the servo valve is used to control the servo valve to generate a secondary pulsation wave.

[0039] In the active suppression of fluid pulsation based on the overflow principle, the delay characteristic is an important property of the secondary channel. At present, the active control of fluid pulsation in hydraulic systems mostly adopts the narrowband (Filtered-X Least Mean Square, FXLMS) algorithm. FXLMS requires the use of a secondary channel estimation model, and the secondary channel estimation model and the phase offset error of the secondary channel determine whether the FXLMS algorithm can be stable. Therefore, the secondary channel can be modeled using both online identification and offline identification.

[0040] When the online identification method is used to model the secondary channel, the online identification scheme is relatively complex, the amount of calculation is large, and the hardware performance requirements are high. In addition, there is coupling between the online identification and active control, that is, there is a coupling problem between the identification excitation signal and the notch filter, which affects the convergence of the adaptive fluid pulsation active control algorithm and leads to unstable control. When the offline identification method is used to model the secondary channel, the offline identification method may have a large estimation error of the secondary channel model when the secondary channel is time-varying, resulting in failure of active control.

[0041] The inventors found that when the phase offset error between the secondary channel estimation model and the secondary channel true model is greater than 90°, the FXLMS algorithm diverges. For a certain target frequency, the phase offset and delay time of the secondary channel estimation model and the secondary channel true model correspond one to one. Therefore, as long as the delay time of the secondary channel with a phase offset error within 90° can be identified and the corresponding delay model is used as the secondary channel estimation model, the algorithm can maintain convergence. The delay time of the secondary channel includes two parts: basic delay and phase difference delay. The basic delay reflects the static delay characteristics of the secondary channel, while the phase difference delay reflects the dynamic delay characteristics of the secondary channel.

[0042] The embodiment of the present application provides a method for determining model parameters of a secondary channel estimation model, which can use an offline identification method to determine the model parameters of the secondary channel estimation model, so that the model parameters of the secondary channel estimation model are not affected by the notch filter, thereby improving the control stability of the adaptive fluid pulsation active control algorithm. The method here can be executed by an electronic device or a chip applied to an electronic device.

[0043] Figure 2 FIG. 1 is a flow chart showing a method for controlling fluid pulsation based on a time delay parameter model according to an embodiment of the present application. Figure 2 As shown, the fluid pulsation control method based on the time delay parameter model of the embodiment of the present application may include:

[0044] Step 201: Acquire a first reference signal and a second reference signal based on a target frequency of fluid pulsation, wherein the first reference signal and the second reference signal are orthogonal.

[0045] In practical applications, the exemplary embodiment of the present application can obtain the pressure signals of multiple sampling points of fluid pulsation in a non-suppressed state within a preset time period, and then determine the amplitude-frequency spectrum of the fluid pulsation based on the pressure signals of multiple sampling points of the fluid pulsation in a non-suppressed state, and determine the target frequency of the fluid pulsation based on the amplitude-frequency spectrum of the fluid pulsation, which is the fluid pulsation frequency corresponding to the maximum fluid pulsation amplitude in the amplitude-frequency spectrum of the fluid pulsation.

[0046] Exemplarily, when the fluid pulsation is in a non-suppressed state, the control valve does not control the fluid pulsation. In this case, the pressure sensor is used to obtain pressure signals of multiple sampling points (such as 4096) in a preset period of time, and then the multiple historical signals are subjected to Fast Fourier Transform (FFT) to obtain the amplitude-spectrum diagram of the fluid pulsation. The amplitude-spectrum diagram of the fluid pulsation can actually represent the corresponding relationship between the fluid pulsation amplitude and the fluid pulsation frequency. Therefore, the amplitude-spectrum diagram of the fluid pulsation can be obtained by analyzing the amplitude-spectrum diagram of the fluid pulsation, and the fluid pulsation frequency corresponding to the maximum fluid pulsation amplitude can be obtained.

[0047] When the target frequency of fluid pulsation is the fluid pulsation frequency corresponding to the maximum fluid pulsation amplitude, the fluid pulsation control signal determined based on the target frequency of fluid pulsation can better control the fluid pulsation.

[0048] Active control is performed to improve the fluid pulsation control effect.

[0049] When the target frequency of fluid pulsation is f, the first reference signal x1(n) of the nth fluid pulsation sampling point is cos(2πfnΔt), and the second reference signal x2(n) of the nth fluid pulsation sampling point is sin(2πfnΔt), where n represents the fluid pulsation sampling number and Δt represents the sampling period.

[0050] Step 202: Input the first reference signal and the second reference signal into a secondary channel estimation model to obtain a reference signal filtered by the secondary channel estimation model.

[0051] In practical applications, the reference signal filtered by the secondary channel estimation model in the embodiment of the present application may include a first reference signal filtered by the secondary channel estimation model and a second reference signal filtered by the secondary channel estimation model.

[0052] Exemplarily, the first reference signal may be input into the secondary channel estimation model to obtain the first reference signal filtered by the secondary channel estimation model, and the second reference signal may be input into the secondary channel estimation model to obtain the second reference signal filtered by the secondary channel estimation model.

[0053] The secondary channel estimation model in the embodiment of the present application is actually a delay parameter model. Figure 3 FIG. 1 is a flow chart showing a method for determining model parameters of a secondary channel estimation model according to an embodiment of the present application. Figure 3 As shown, the method for determining the model parameters of the secondary channel estimation model in the embodiment of the present application may include:

[0054] Step 301: Obtaining a hysteresis phase parameter of a control valve at a target frequency based on a target frequency of fluid pulsation.

[0055] The embodiment of the present application can obtain the phase-frequency characteristic information of the control valve, and then determine the lag phase parameter of the control valve at the target frequency based on the phase-frequency characteristic curve of the control valve. For example, when the lag phase parameter of the control valve at the target frequency is the lag phase of the control valve at the target frequency, a frequency sweep experiment can be performed on the dynamic element in the control valve to obtain the phase-frequency characteristic curve, and then the lag phase corresponding to the target frequency is obtained from the phase-frequency characteristic curve with the target frequency as a reference, and it is positioned as the lag phase of the control valve at the target frequency.

[0056] Step 302: Determine the model parameters of the secondary channel estimation model based on the lag phase parameter of the control valve at the target frequency and the basic delay of the secondary channel.

[0057] In practical applications, the embodiments of the present application can determine the delay deviation of the secondary channel based on the lag phase parameters of the control valve at the target frequency and the target frequency, and then determine the model parameters of the secondary channel estimation model based on the delay deviation of the secondary channel and the basic delay of the secondary channel.

[0058] In some embodiments, when the hysteresis phase parameter of the control valve at the target frequency includes the hysteresis phase of the control valve at the target frequency, the hysteresis phase of the control valve at the target frequency is positively correlated with the delay deviation of the secondary channel. For example, the delay deviation of the secondary channel can be expressed as f represents the target frequency, Indicates the lag phase of the control valve at the target frequency.

[0059] Exemplarily, an embodiment of the present application may input a test signal into a secondary channel to obtain a test result of the secondary channel, determine a candidate delay of the secondary channel based on the time when the test result of the secondary channel is obtained and the time when the test signal is input, and if the candidate delay of the secondary channel meets the screening condition of the basic delay, determine the candidate delay of the secondary channel as the basic delay of the secondary channel.

[0060] When the test signal can be a step signal, the test result of the secondary channel is the step response of the secondary channel, the input time of the step signal and the acquisition time of the step response of the secondary channel can be recorded, and then the candidate delay of the secondary channel is determined based on the difference between the input time of the step signal and the acquisition time of the step response of the secondary channel. Here, the screening condition of the basic delay can be that the candidate delay of the secondary channel is greater than the preset delay, thereby improving the accuracy of the basic delay.

[0061] In some embodiments, the embodiments of the present application can determine the actual delay of the secondary channel based on the delay deviation of the secondary channel and the basic delay of the secondary channel, and determine the model parameters of the secondary channel estimation model based on the actual delay of the secondary channel and the target frequency. Let the total delay of the secondary channel be expressed as Td , the basic delay of the secondary channel is expressed as Δ, then the total delay of the secondary channel is

[0062] The secondary channel estimation model of the embodiment of the present application can be expressed in the form of a finite impulse response, that is, the secondary channel estimation model is expressed as: n represents the model parameters of the secondary channel estimation model, For example, when T d =0.0011s, f=2000Hz, then n=2. At this time, the secondary channel estimation model is:

[0063] When the secondary channel estimation model is expressed as: When the first reference signals of three consecutive fluid pulsation sampling points are obtained, the first reference signals of the three consecutive fluid pulsation sampling points are convolved with the model parameters of the secondary channel estimation model to obtain the first reference signal of the current pulsation sampling point after filtering by the secondary channel estimation model, and the second reference signals of the three consecutive fluid pulsation sampling points are convolved with the model parameters of the secondary channel estimation model to obtain the second reference signal of the current fluid pulsation sampling point after filtering by the secondary channel estimation model.

[0064] Step 203: Based on the reference signal filtered by the secondary channel estimation model and the control error of the fluid pulsation, the adaptive parameter is adjusted. Here, the control error of the fluid pulsation of the embodiment of the present application is determined by the historical pressure signal of the fluid pulsation and the historical response signal of the secondary channel. The adaptive parameter here is actually the target parameter of the notch filter.

[0065] Exemplarily, the fluid pulsation control signal y(n) of the nth fluid pulsation sampling point can be input into the secondary channel to obtain the response signal y'(n) of the secondary channel of the nth fluid pulsation sampling point, and based on the response signal y'(n) of the secondary channel of the nth fluid pulsation sampling point and the original pressure signal d(n) of the fluid pulsation at the nth fluid pulsation sampling point, the control error e(n) of the fluid pulsation at the nth fluid pulsation sampling point is determined, where e(n)=d(n)-y'(n).

[0066] The target parameters of the notch filter of the embodiment of the present application may include a first weight coefficient of the notch filter and a second weight coefficient of the notch filter. At this time, the first weight coefficient of the notch filter can be determined based on the first reference signal filtered by the secondary channel estimation model and the control error of the fluid pulsation, and the second weight coefficient of the notch filter can be determined based on the second reference signal filtered by the secondary channel estimation model and the control error of the fluid pulsation. For example, the first weight coefficient of the notch filter can be expressed as Formula 1, and the second weight coefficient of the notch filter can be expressed as Formula 2:

[0067]

[0068] Wherein, w1(n) represents the first weight coefficient of the notch filter at the nth fluid pulsation sampling point, w1(n+1) represents the first weight coefficient of the notch filter at the n+1th fluid pulsation sampling point, w2(n) represents the second weight coefficient of the notch filter at the nth fluid pulsation sampling point, w2(n+1) represents the second weight coefficient of the notch filter at the n+1th fluid pulsation sampling point, μ2 represents the second step factor, represents the first reference signal of the nth fluid pulsation sampling point after filtering by the secondary channel estimation model, represents the second reference signal of the nth fluid pulsation sampling point after filtering by the secondary channel estimation model, and e(n) represents the control error of the fluid pulsation at the nth fluid pulsation sampling point.

[0069] Since there is no coupling between online identification and active control in the model parameter determination process of the secondary channel estimation model, the embodiment of the present application utilizes the first reference signal and the second reference signal filtered by the secondary channel estimation model to update the first weight coefficient and the second weight coefficient of the notch filter, thereby ensuring the stability of the adaptive fluid pulsation active control algorithm.

[0070] In an optional manner, the present application provides a fluid pulsation active control system, which may include a control valve, a pressure sensor, and an active controller, wherein the first end of the control valve is connected to a pipeline, the second end of the control valve is connected to an oil tank, and the pressure sensor and the control valve are both communicatively connected to the active controller. The active controller may execute the fluid pulsation control method based on the time delay parameter model of the embodiment of the present application.

[0071] In an optional manner, the secondary channel of the embodiment of the present application can be applied to an active control system for fluid pulsation in a hydraulic pipeline. Figure 4 FIG. 2 shows a schematic diagram of a secondary channel of an embodiment of the present application. Figure 4 As shown, the fluid pulsation active control signal is input into the control valve, and the control valve can convert the fluid pulsation active control signal into a control signal through a digital-to-analog converter 401, and use the control signal to control an actuator 402 (such as a valve) to adjust the flow of the bypass pipeline, so that the hydraulic impedance 403 in the bypass pipeline changes. In this process, there is a propagation delay 404 in the pressure change. Therefore, when the pressure signal is collected by the pressure sensor 405, the pressure signal collected by the pressure sensor 405 is also delayed, and the pressure signal collected by the pressure sensor 405 is essentially the control error of the fluid pulsation, and the pressure sensor 405 can convert the collected pressure signal into a digital signal through the analog-to-digital converter 406.

[0072] For example, in the embodiment of the present application, the fluid pulsation active control signal can be set as a step signal, and the step signal is input into Figure 4 The secondary channel shown in FIG. Figure 4 The analog-to-digital converter shown can output the step response of the secondary channel.

[0073] In practical applications, the digital-to-analog converter, hydraulic impedance, pressure sensor and analog-to-digital converter of the embodiment of the present application have dynamics and phase delay. The phase delay of the digital-to-analog converter, pressure sensor and analog-to-digital converter is generally very small and can be ignored. According to the "lumped parameter model theory" of the hydraulic system, the phase offset of the hydraulic impedance is within 90°, so that the secondary channel estimation model and Figure 4 The phase offset error of the secondary channel is shown to be within 90°, so the stability of the adaptive fluid pulsation control algorithm of the embodiment of the present application is relatively good.

[0074] The mainstream FXLMS-based adaptive notch control algorithm is used for verification in Amesim and Simulink joint simulation.

[0075] Figure 5 FIG. 1 is a schematic diagram showing the simulation verification results of online identification of secondary channels in the related art. Figure 5 As shown, when the adaptive fluid pulsation active control starts at 4 seconds, the control becomes stable after about 2 seconds.

[0076] Figure 6 FIG. 2 shows a schematic diagram of simulation verification results of the offline identification method of the present application embodiment. Figure 6 As shown in the figure, when the adaptive fluid pulsation active control starts at 4 seconds, the control becomes stable after about 0.2 seconds, with a faster convergence speed.

[0077] Figure 7 The following is a schematic diagram showing the simulation verification results of the embodiment of the present application under time-varying working conditions. Figure 7 As shown, during the variable pressure process, when the offline identification method of the embodiment of the present application is used, the adaptive fluid pulsation active control can remain stable.

[0078] In one or more technical solutions provided in the embodiments of the present application, the model parameter determination process of the secondary channel estimation model does not involve online identification, but is based on the basic delay of the secondary channel, combined with the lag phase parameters of the control valve at the target frequency, and the model parameters of the secondary channel estimation model (i.e., the delay parameter model) are determined by offline identification, so that the model parameters of the secondary channel estimation model predicted are not affected by the notch filter. In this case, based on the reference signal filtered by the secondary channel estimation model and the control error of the fluid pulsation, after adjusting the adaptive parameters, the control stability of the adaptive fluid pulsation control algorithm can be improved, so that the adaptive fluid pulsation control algorithm is suitable for stable control in time-varying scenarios.

[0079] The above mainly introduces the solution provided by the embodiment of the present application from the perspective of an electronic device. It is understandable that, in order to realize the above functions, the electronic device includes a hardware structure and / or software module corresponding to the execution of each function. Those skilled in the art should easily realize that, in combination with the units and algorithm steps of each example described in the embodiment applied for herein, the present application can be implemented in the form of hardware or a combination of hardware and computer software. Whether a function is executed in the form of hardware or computer software driving hardware depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to exceed the scope of the present application.

[0080] The embodiment of the present application can divide the functional units of the electronic device according to the above method example. For example, each functional module can be divided corresponding to each function, or two or more functions can be integrated into one processing module. The above integrated module can be implemented in the form of hardware or in the form of software functional modules. It should be noted that the division of modules in the embodiment of the present application is schematic and is only a logical function division. There may be other division methods in actual implementation.

[0081] In the case of dividing each functional module according to each function, an exemplary embodiment of the present application provides a fluid pulsation control device based on a time delay parameter model, and the fluid pulsation control device based on a time delay parameter model can be a chip applied to an electronic device. Figure 8 FIG. 1 shows a schematic block diagram of functional modules of a fluid pulsation control device based on a time delay parameter model according to an exemplary embodiment of the present application. Figure 8 As shown, the fluid pulsation control device 800 based on the time delay parameter model includes:

[0082] An acquisition module 801 is used to acquire a first reference signal and a second reference signal based on a target frequency of fluid pulsation, wherein the first reference signal and the second reference signal are orthogonal;

[0083] An adjustment module 802 is used to input the first reference signal and the second reference signal into a secondary channel estimation model to obtain a reference signal filtered by the secondary channel estimation model; and adjust an adaptive parameter based on the reference signal filtered by the secondary channel estimation model and a control error of fluid pulsation;

[0084] The identification module 803 is used to obtain the lag phase parameters of the control valve at the target frequency based on the target frequency of the fluid pulsation, and determine the model parameters of the secondary channel estimation model based on the lag phase parameters of the control valve at the target frequency and the basic delay of the secondary channel.

[0085] As a possible implementation manner, the identification module 803 is used to obtain phase-frequency characteristic information of the control valve; based on the phase-frequency characteristic curve of the control valve, determine the lag phase parameter of the control valve at the target frequency.

[0086] As a possible implementation method, the identification module 803 is also used to input a test signal into a secondary channel to obtain a test result of the secondary channel; determine a candidate delay of the secondary channel based on the acquisition time of the test result of the secondary channel and the input time of the test signal; if the candidate delay of the secondary channel is greater than a preset delay, determine the candidate delay of the secondary channel as the basic delay of the secondary channel.

[0087] As a possible implementation method, the identification module 803 is used to determine the delay deviation of the secondary channel based on the lag phase parameters of the control valve at the target frequency and the target frequency; and determine the model parameters of the secondary channel estimation model based on the delay deviation of the secondary channel and the basic delay of the secondary channel.

[0088] As a possible implementation manner, the lag phase parameter of the control valve at the target frequency is the lag phase of the control valve at the target frequency, and the lag phase of the control valve at the target frequency is positively correlated with the delay deviation of the secondary channel.

[0089] As a possible implementation, the identification module 803 is used to determine the actual delay of the secondary channel based on the delay deviation of the secondary channel and the basic delay of the secondary channel; and determine the model parameters of the secondary channel estimation model based on the actual delay of the secondary channel and the target frequency.

[0090] As a possible implementation manner, the reference control error of the fluid pulsation is determined by a historical pressure signal of the fluid pulsation and a historical response signal of a secondary channel.

[0091] Fig. 9 Schematic block diagram of a chip according to an exemplary embodiment of the present application is shown. Fig. 9 As shown, the chip 900 includes one or more than two (including two) processors 901 and a communication interface 902. The communication interface 902 can perform the data sending and receiving steps in the above method, and the processor 901 can perform the data processing steps in the above method.

[0092] Optional, such as Fig. 9 As shown, the chip 900 also includes a memory 903, which may include a read-only memory and a random access memory, and provides operation instructions and data to the processor. A portion of the memory may also include a non-volatile random access memory (NVRAM).

[0093] In some embodiments, Fig. 9 As shown, the processor 901 performs corresponding operations by calling the operation instructions stored in the memory (the operation instructions may be stored in the operating system). The processor 901 controls the processing operations of any one of the terminal devices, and the processor may also be called a central processing unit (CPU). The memory 903 may include a read-only memory and a random access memory, and provides instructions and data to the processor 901. A portion of the memory 903 may also include NVRAM. For example, in an application, the memory, the communication interface, and the memory are coupled together through a bus system, wherein the bus system may include a power bus, a control bus, and a status signal bus in addition to a data bus. However, for the sake of clarity, in Fig. 9 Various buses are labeled as bus system 904.

[0094] The method disclosed in the above embodiment of the present application can be applied to a processor or implemented by a processor. The processor may be an integrated circuit chip with signal processing capabilities. In the implementation process, each step of the above method can be completed by an integrated logic circuit of hardware in the processor or an instruction in the form of software. The above processor may be a general-purpose processor, a digital signal processor (digital signal processing, DSP), an ASIC, a field-programmable gate array (field-programmable gate array, FPGA) or other programmable logic devices, discrete gates or transistor logic devices, discrete hardware components. The various methods, steps and logic block diagrams of the application in the embodiment of the present application can be implemented or executed. The general-purpose processor may be a microprocessor or the processor may also be any conventional processor, etc. The steps of the method applied in conjunction with the embodiment of the present application can be directly embodied as a hardware decoding processor to be executed, or a combination of hardware and software modules in the decoding processor to be executed. The software module may be located in a mature storage medium in the field such as a random access memory, a flash memory, a read-only memory, a programmable read-only memory or an electrically erasable programmable memory, a register, etc. The storage medium is located in a memory, and the processor reads the information in the memory and completes the steps of the above method in combination with its hardware.

[0095] The exemplary embodiment of the present application also provides an electronic device, comprising: at least one processor; and a memory connected to the at least one processor in communication. The memory stores a computer program that can be executed by the at least one processor, and the computer program is used to cause the electronic device to perform the method according to the embodiment of the present application when executed by the at least one processor.

[0096] The exemplary embodiment of the present application further provides a non-transitory computer-readable storage medium storing a computer program, wherein the computer program, when executed by a processor of a computer, is used to cause the computer to perform a method according to an embodiment of the present application.

[0097] The exemplary embodiments of the present application further provide a computer program product, including a computer program, wherein when the computer program is executed by a processor of a computer, it is used to enable the computer to execute the method according to the embodiment of the present application.

[0098] refer to Fig.10, the structural block diagram of the electronic device 1000 that can be used as the server or client of the present application will now be described, which is an example of a hardware device that can be applied to various aspects of the present application. The electronic device is intended to represent various forms of digital electronic computer equipment, such as laptop computers, desktop computers, workbenches, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device can also represent various forms of mobile devices, such as personal digital processing, cellular phones, smart phones, wearable devices and other similar computing devices. The components shown herein, their connections and relationships, and their functions are only examples, and are not intended to limit the implementation of the present application described and / or required herein.

[0099] like Fig.10 As shown, the electronic device 1000 includes a computing unit 1001, which can perform various appropriate actions and processes according to a computer program stored in a read-only memory (ROM) 1002 or a computer program loaded from a storage unit 1008 into a random access memory (RAM) 1003. In the RAM 1003, various programs and data required for the operation of the device 1000 can also be stored. The computing unit 1001, the ROM 1002, and the RAM 1003 are connected to each other via a bus 1004. An input / output (I / O) interface 1005 is also connected to the bus 1004.

[0100] like Fig.10 As shown, multiple components in the electronic device 1000 are connected to the I / O interface 1005, including: an input unit 1006, an output unit 1007, a storage unit 1008, and a communication unit 1009. The input unit 1006 can be any type of device that can input information to the electronic device 1000, and the input unit 1006 can receive input digital or character information, and generate key signal input related to the user settings and / or function control of the electronic device. The output unit 1007 can be any type of device that can present information, and can include but is not limited to a display, a speaker, a video / audio output terminal, a vibrator, and / or a printer. The storage unit 1008 can include but is not limited to a disk, an optical disk. The communication unit 1009 allows the electronic device 1000 to exchange information / data with other devices through a computer network such as the Internet and / or various telecommunication networks, and can include but is not limited to a modem, a network card, an infrared communication device, a wireless communication transceiver, and / or a chipset, such as a Bluetooth TM device, a WiFi device, a WiMax device, a cellular communication device, and / or the like.

[0101] like Fig.10As shown, the computing unit 1001 can be various general and / or special processing components with processing and computing capabilities. Some examples of the computing unit 1001 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various dedicated artificial intelligence (AI) computing chips, various computing units running machine learning model algorithms, digital signal processors (DSPs), and any appropriate processors, controllers, microcontrollers, etc. The computing unit 1001 performs the various methods and processes described above. For example, in some embodiments, the method of the exemplary embodiment of the present application may be implemented as a computer software program, which is tangibly included in a machine-readable medium, such as a storage unit 1008. In some embodiments, part or all of the computer program can be loaded and / or installed on the electronic device 1000 via ROM 1002 and / or communication unit 1009. In some embodiments, the computing unit 1001 can be configured to perform the method of the exemplary embodiment of the present application by any other appropriate means (e.g., by means of firmware).

[0102] The program code for implementing the method of the present application can be written in any combination of one or more programming languages. These program codes can be provided to a processor or controller of a general-purpose computer, a special-purpose computer, or other programmable data processing device, so that the program code, when executed by the processor or controller, implements the functions / operations specified in the flow chart and / or block diagram. The program code can be executed entirely on the machine, partially on the machine, partially on the machine and partially on a remote machine as a stand-alone software package, or entirely on a remote machine or server.

[0103] In the context of the present application, a machine-readable medium may be a tangible medium that may contain or store a program for use by or in conjunction with an instruction execution system, device, or equipment. A machine-readable medium may be a machine-readable signal medium or a machine-readable storage medium. A machine-readable medium may include, but is not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, device, or equipment, or any suitable combination of the foregoing. A more specific example of a machine-readable storage medium may include an electrical connection based on one or more lines, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

[0104] As used herein, the terms "machine-readable medium" and "computer-readable medium" refer to any computer program product, apparatus, and / or device (e.g., disk, optical disk, memory, programmable logic device (PLD)) for providing machine instructions and / or data to a programmable processor, including a machine-readable medium that receives machine instructions as a machine-readable signal. The term "machine-readable signal" refers to any signal for providing machine instructions and / or data to a programmable processor.

[0105] To provide interaction with a user, the systems and techniques described herein can be implemented on a computer having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user; and a keyboard and pointing device (e.g., a mouse or trackball) through which the user can provide input to the computer. Other types of devices can also be used to provide interaction with the user; for example, the feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form (including acoustic input, voice input, or tactile input).

[0106] The systems and techniques described herein may be implemented in a computing system that includes back-end components (e.g., as a data server), or a computing system that includes middleware components (e.g., an application server), or a computing system that includes front-end components (e.g., a user computer with a graphical user interface or a web browser through which a user can interact with implementations of the systems and techniques described herein), or a computing system that includes any combination of such back-end components, middleware components, or front-end components. The components of the system may be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include: a local area network (LAN), a wide area network (WAN), and the Internet.

[0107] A computer system may include clients and servers. Clients and servers are generally remote from each other and usually interact through a communication network. The relationship of client and server is generated by computer programs running on respective computers and having a client-server relationship to each other.

[0108] In the above embodiments, it can be implemented in whole or in part by software, hardware, firmware or any combination thereof. When implemented by software, it can be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer programs or instructions. When the computer program or instruction is loaded and executed on a computer, the process or function described in the embodiment of the present application is executed in whole or in part. The computer may be a general-purpose computer, a special-purpose computer, a computer network, a terminal, a user device or other programmable device. The computer program or instruction may be stored in a computer-readable storage medium, or transmitted from one computer-readable storage medium to another computer-readable storage medium, for example, the computer program or instruction may be transmitted from one website site, computer, server or data center to another website site, computer, server or data center by wired or wireless means. The computer-readable storage medium may be any available medium that a computer can access or a data storage device such as a server or data center that integrates one or more available media. The available medium may be a magnetic medium, for example, a floppy disk, a hard disk, or a tape; it may also be an optical medium, for example, a digital video disc (DVD); it may also be a semiconductor medium, for example, a solid state drive (SSD).

[0109] Although the present application has been described in conjunction with specific features and embodiments thereof, it is obvious that various modifications and combinations may be made thereto without departing from the spirit and scope of the present application. Accordingly, this specification and the drawings are merely exemplary illustrations of the present application as defined by the appended claims, and are deemed to have covered any and all modifications, variations, combinations or equivalents within the scope of the present application. Obviously, those skilled in the art may make various modifications and variations to the present application without departing from the spirit and scope of the present application. Thus, if these modifications and variations of the present application fall within the scope of the claims of the present application and their equivalents, the present application is also intended to include these modifications and variations.

Claims

1. A fluid pulsation control method based on a time-delay parameter model, characterized in that: include: Acquire a first reference signal and a second reference signal based on a target frequency of fluid pulsation, wherein the first reference signal and the second reference signal are orthogonal; Inputting the first reference signal and the second reference signal into a secondary channel estimation model to obtain a reference signal filtered by the secondary channel estimation model; Adjusting adaptive parameters based on the reference signal filtered by the secondary channel estimation model and the control error of the fluid pulsation; Among them, the method for determining the model parameters of the secondary channel estimation model includes: obtaining the lag phase parameters of the control valve at the target frequency based on the target frequency of the fluid pulsation, and determining the model parameters of the secondary channel estimation model based on the lag phase parameters of the control valve at the target frequency and the basic delay of the secondary channel.

2. The method according to claim 1, characterized in that The step of obtaining the hysteresis phase parameter of the control valve at the target frequency based on the target frequency of the fluid pulsation comprises: Obtain the phase-frequency characteristic information of the control valve; Based on the phase-frequency characteristic curve of the control valve, a lag phase parameter of the control valve at a target frequency is determined.

3. The method according to claim 1, characterized in that The method further comprises: Inputting a test signal into the secondary channel to obtain a test result of the secondary channel; Determining a candidate delay of the secondary channel based on the acquisition time of the test result of the secondary channel and the input time of the test signal; If the candidate delay of the secondary channel is greater than the preset delay, the candidate delay of the secondary channel is determined as the basic delay of the secondary channel.

4. The method according to claim 1, characterized in that The determining of the model parameters of the secondary channel estimation model based on the lag phase parameter of the control valve at the target frequency and the basic delay of the secondary channel comprises: Determining a delay deviation of a secondary channel based on a lag phase parameter of the control valve at a target frequency and the target frequency; Model parameters of the secondary channel estimation model are determined based on the delay deviation of the secondary channel and the basic delay of the secondary channel.

5. The method according to claim 4, characterized in that The lag phase parameter of the control valve at the target frequency is the lag phase of the control valve at the target frequency, and the lag phase of the control valve at the target frequency is positively correlated with the delay deviation of the secondary channel.

6. The method according to claim 4, characterized in that The determining of the model parameters of the secondary channel estimation model based on the delay deviation of the secondary channel and the basic delay of the secondary channel comprises: Determining an actual delay of the secondary channel based on the delay deviation of the secondary channel and a basic delay of the secondary channel; Based on the actual delay of the secondary channel and the target frequency, model parameters of the secondary channel estimation model are determined.

7. The method according to any one of claims 1 to 6, characterized in that: The reference control error of the fluid pulsation is determined by a historical pressure signal of the fluid pulsation and a historical response signal of a secondary channel.

8. A fluid pulsation control device based on a time-delay parameter model, characterized in that: include: An acquisition module, configured to acquire a first reference signal and a second reference signal based on a target frequency of fluid pulsation, wherein the first reference signal and the second reference signal are orthogonal; An adjustment module, configured to input the first reference signal and the second reference signal into a secondary channel estimation model to obtain a reference signal filtered by the secondary channel estimation model; Adjusting adaptive parameters based on the reference signal filtered by the secondary channel estimation model and the control error of the fluid pulsation; The identification module is used to obtain the lag phase parameters of the control valve at the target frequency based on the target frequency of the fluid pulsation, and determine the model parameters of the secondary channel estimation model based on the lag phase parameters of the control valve at the target frequency and the basic delay of the secondary channel.

9. A fluid pulsation active control system, characterized in that: include: A control valve, a pressure sensor and an active controller, wherein the first end of the control valve is connected to a pipeline, the second end of the control valve is connected to an oil tank, the pressure sensor and the control valve are both communicatively connected to the active controller, and the active controller is used to execute the method described in any one of claims 1 to 7.

10. An electronic device, characterized in that: include: processor; as well as, A memory for storing programs; The program includes instructions, which, when executed by the processor, cause the processor to perform the method according to any one of claims 1 to 7.

11. A non-transitory computer-readable storage medium, characterized in that The non-transitory computer-readable storage medium stores computer instructions, and the computer instructions are used to cause the computer to execute according to the right <24P06121CN> The method according to any one of claims 1 to 7.

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