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

Abstract

The application provides a fluid pulsation control method, device and system based on a time delay parameter model. The method comprises the following steps: obtaining a hysteresis phase parameter of a control valve at a target frequency of fluid pulsation based on the target frequency; determining a model parameter of a secondary channel estimation model based on the hysteresis phase parameter of the control valve at the target frequency and a basic delay of the secondary channel; obtaining a reference signal based on the target frequency of the fluid pulsation, inputting the reference signal into the secondary channel estimation model, and obtaining a reference signal filtered by the secondary channel estimation model; and adjusting an adaptive parameter based on a reference control error of the fluid pulsation and the reference signal filtered by the secondary channel estimation model, and realizing active control. The method can ensure that an adaptive fluid pulsation control algorithm is applicable to stable control in a time-varying scene.

Description

TECHNICAL FIELD

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

[0002] In a fluid pulsation control scheme based on the bypass overflow principle, a bypass branch can be arranged on a main pipeline between a hydraulic pump and an actuator, and a control valve is installed on the bypass branch, and then the control valve generates a secondary pulsation wave to offset the original pressure wave in the main pipeline, so as to reduce the fluid pulsation in the main pipeline and achieve the purpose of fluid pulsation suppression.

[0003] In related technologies, the pulsation frequency of the fluid can be obtained, a reference signal is constructed according to the pulsation frequency of the fluid, and then a control signal of the control valve is determined according to the reference signal and the identification excitation signal, and the control signal of the control valve is used to control the control valve to generate a secondary pulsation wave. However, the adaptive filter for identification and the notch filter for control are coupled, which affects the stability of the adaptive fluid pulsation control algorithm, and the parameters of the identification filter and the notch filter need to be adjusted repeatedly, which is not good in practicability. SUMMARY

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

[0005] obtaining a first reference signal and a second reference signal based on a target frequency of fluid pulsation, the first reference signal and the second reference signal being 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 an adaptive parameter based on the reference signal filtered by the secondary channel estimation model and a control error of fluid pulsation;

[0008] The model parameter determination method of the secondary channel estimation model comprises: obtaining a lag phase parameter of the control valve at the target frequency based on the target frequency of fluid pulsation, and determining the model parameter 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.

[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 obtaining module configured to obtain a first reference signal and a second reference signal based on a target frequency of fluid pulsation, the first reference signal and the second reference signal being orthogonal;

[0011] an adjusting module, configured to input the first reference signal and the second reference signal into the 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 the fluid pulsation;

[0012] an identifying module, configured to obtain a lag phase parameter of the control valve at the target frequency based on a target frequency of the fluid pulsation, and determine a model parameter of the secondary channel estimation model based on the lag phase parameter of the control valve at the target frequency and a basic delay of the secondary channel.

[0013] According to another aspect of the present application, a fluid pulsation active control system is provided, comprising a control valve, a pressure sensor and an active controller, a first end of the control valve is connected to a pipeline, a second end of the control valve is connected to an oil tank, the pressure sensor and the control valve are both in communication connection with the active controller, and the active controller is configured to execute the method according to the exemplary embodiments of the present application.

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

[0015] a processor; and

[0016] a memory storing a program;

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

[0018] According to another aspect of the present application, a non-transitory computer readable storage medium is provided, which stores computer instructions for causing a computer to perform the method according to the exemplary embodiments of the present application.

[0019] According to another aspect of the present application, a computer program product is provided, comprising a computer program which, when executed by a processor, implements the method according to the exemplary embodiments of the present application.

[0020] In one or more technical solutions provided in 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 parameter of the control valve at the target frequency, and determines the model parameters of the secondary channel estimation model (i.e. the time delay parameter model) through offline identification, so that the predicted model parameters of the secondary channel estimation model are not affected by the trap filter. In this case, based on the control error of the reference signal filtered by the secondary channel estimation model and the fluid pulsation, the control stability of the adaptive fluid pulsation control algorithm can be improved after adjusting the adaptive parameters, so that the adaptive fluid pulsation control algorithm is suitable for stable control in time-varying scenarios. BRIEF DESCRIPTION OF DRAWINGS

[0021] In the following description of exemplary embodiments in conjunction with the accompanying drawings, more details, features and advantages of the present application are described. In the drawings:

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

[0023] Figure 2 A flowchart 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 flowchart of a model parameter determination method of a secondary channel estimation model according to an embodiment of the present application is shown;

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

[0026] Figure 5 A schematic diagram of the simulation verification results of online identification of a secondary channel in the related art is shown;

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

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

[0029] Figure 8 A functional module schematic diagram 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] Figure 9 A schematic diagram of a chip according to an exemplary embodiment of the present application is shown;

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

[0032] Embodiments of the present application will be described in more detail with reference to the drawings. While the present application is shown in the drawings and described as being implemented in one or more specific embodiments, it will be understood that the present application can be embodied in various forms and should not be limited to the embodiments set forth in the description. Rather, these embodiments are provided as non-limiting examples of the present application so that a thorough and complete understanding can be obtained. It is to be understood that the figures and examples of the present application are merely illustrative and are not to be construed as limiting the scope of the present application.

[0033] It should be understood that each of the steps in the method embodiments of the present application can be performed in a different order and / or in parallel. In addition, the method embodiments can include additional steps and / or omit performing the steps shown. The scope of the present application is not limited in this respect.

[0034] As used herein, the term "includes" and its variants are to be read to be analogous to "comprising," namely "including but not limited to." The term "based on" is to be read as "based, at least in part, on." The term "one embodiment" means "at least one embodiment"; the term "another embodiment" means "at least one additional embodiment"; the term "some embodiments" means "at least some embodiments." Related definitions will be given in the description below. It should be noted that the concepts "first," "second," etc. mentioned in the present application are merely used to distinguish different apparatuses, modules or units, and are not intended to limit the order or interdependence of the functions performed by these apparatuses, modules or units.

[0035] It should be noted that the terms "a" and "an" and "the" and "said" used in the present application are used in the sense of "at least one" unless explicitly indicated otherwise. It should be understood that "one," "multiple," or "a plurality of" as referred to in the present application are illustrative and not limiting, and those skilled in the art will understand that "one" or "a" should be interpreted as "one or more" unless the context clearly indicates otherwise.

[0036] Figure 1 An example schematic diagram of a fluid pulsation active control system showing a bypass spill principle is shown. As 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 an overflow pipeline and a 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 at a position of the hydraulic pipeline between the control valve 105 and the throttle valve 106, the outlet of the control valve 105 is also connected to a bypass pipeline, the bypass pipeline is connected to the inlet of the oil tank 101, and the active controller 108 is electrically connected to the pressure sensor 107 and the control valve 105 respectively.

[0037] In specific implementation, as shown in the figure, Figure 1 Under the drive of the motor 103, the plunger pump 102 rotates, so that the plunger pump 102 sucks low-pressure oil liquid from the oil tank 101 and sends the low-pressure oil liquid into the hydraulic pipeline, and the low-pressure oil liquid returns to the oil tank 101 through the throttle valve 106; the overflow valve 104 can control the pressure in the hydraulic pipeline to be not higher than a set pressure, thereby playing a safety protection role; the active controller 108 can obtain the pressure signal at the position through the pressure sensor 107, take the pressure signal as a control error of fluid pulsation, update the parameters required in the fluid pulsation active control process, and enable the control valve 105 to serve as an actuator for active control when the fluid pulsation active control signal controls the control valve 105, so as to control the oil liquid flow in the bypass pipeline.

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

[0039] In fluid pulsation active suppression based on the overflow principle, the delay characteristic is an important property of the secondary channel. At present, most hydraulic system fluid pulsation active control adopts a filtered-X least mean square (FXLMS) algorithm. The FXLMS needs to use a secondary channel estimation model, and the phase shift error between the secondary channel estimation model and the secondary channel determines whether the FXLMS algorithm can be stable, so online identification and offline identification can be used to model the secondary channel.

[0040] When the secondary channel is modeled in an online identification manner, the online identification scheme is relatively complex, the calculation amount is large, the hardware performance requirement is high, and there is coupling between online identification and active control, that is, there is coupling between the identification excitation signal and the notch filter, thereby affecting the convergence of the adaptive fluid pulsation active control algorithm and causing the problem of unstable control. When the secondary channel is modeled in an offline identification manner, in the case of time-varying secondary channel, there may be a problem of large estimation error of the secondary channel model, which leads to invalidation of active control.

[0041] The inventors find that when the phase shift error between the estimated model of the secondary channel and the real model of the secondary channel is greater than 90°, the FXLMS algorithm diverges. For a certain target frequency, the phase shift of the estimated model of the secondary channel and the real model of the secondary channel corresponds to the delay time, so as long as the phase shift error of the secondary channel within 90° can be identified, and the corresponding delay model is used as the estimated model of the secondary channel, the algorithm can maintain convergence. The delay time of the secondary channel includes two parts of basic delay and phase difference delay, the basic delay reflects the static delay characteristics of the secondary channel, and 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 the model parameters of the estimated model of the secondary channel, which can determine the model parameters of the estimated model of the secondary channel using an offline identification manner, so that the model parameters of the estimated model of the secondary channel are not affected by the notch filter, thereby improving the control stability of the adaptive fluid pulsation active control algorithm. The method can be executed by an electronic device or a chip applied to an electronic device.

[0043] Figure 2 A flowchart of the fluid pulsation control method based on the time delay parameter model of the embodiment of the present application is shown. As shown in Figure 2 The fluid pulsation control method based on the time delay parameter model of the embodiment of the present application can include:

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

[0045] In actual application, 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 period, then determine the amplitude-frequency spectrum of fluid pulsation based on the pressure signals of multiple sampling points of fluid pulsation in the non-suppressed state, and determine the target frequency of fluid pulsation based on the amplitude-frequency spectrum of fluid pulsation, which is the fluid pulsation frequency corresponding to the maximum fluid pulsation amplitude in the amplitude-frequency spectrum of fluid pulsation.

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

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

[0048] active control, thereby improving the fluid pulsation control effect.

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

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

[0051] In actual application, the reference signal filtered by the secondary channel estimation model of the embodiment of the present application can include the first reference signal filtered by the secondary channel estimation model and the second reference signal filtered by the secondary channel estimation model.

[0052] Exemplarily, the first reference signal can 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 can 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 of the embodiment of the present application is actually a time delay parameter model, Figure 3 A flowchart of a model parameter determination method of the secondary channel estimation model of the embodiment of the present application is shown. As shown in Figure 3 The model parameter determination method of the secondary channel estimation model of the embodiment of the present application can include:

[0054] Step 301: acquiring the hysteresis phase parameter of the control valve at the target frequency on the basis of the target frequency of the 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 sweep frequency 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 the reference, and is positioned as the lag phase of the control valve at the target frequency.

[0056] Step 302: determining the model parameter 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 actual application, the embodiment of the present application can determine the delay deviation of the secondary channel based on the lag phase parameter of the control valve at the target frequency and the target frequency, and then determine the model parameter 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 lag phase parameter of the control valve at the target frequency includes the lag phase of the control valve at the target frequency, the lag 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, represents the lag phase of the control valve at the target frequency.

[0059] For example, the embodiment of the present application can input the test signal into the secondary channel, obtain the test result of the secondary channel, determine the 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, and if the candidate delay of the secondary channel meets the screening condition of the basic delay, determine that the candidate delay of the secondary channel is the basic delay of the secondary channel.

[0060] When the test signal can be a step signal and 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. The screening condition of the basic delay can be that the candidate delay of the secondary channel is greater than a preset delay, so as to improve the accuracy of the basic delay.

[0061] In some embodiments, the embodiment 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 parameter 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 Td , the basic delay of the secondary channel is represented as Δ, then the total delay of the secondary channel

[0062] The secondary channel estimation model of the embodiment of the present application can be expressed in the form of a finite impulse response, i.e., the secondary channel estimation model is expressed as: n represents a model parameter 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: the first reference signal of the continuous three fluid pulsation sampling points can be obtained, and then the first reference signal of the continuous three fluid pulsation sampling points is convoluted with the model parameter of the secondary channel estimation model, so as to obtain the first reference signal of the current pulsation sampling point filtered by the secondary channel estimation model. The second reference signal of the continuous three fluid pulsation sampling points is convoluted with the model parameter of the secondary channel estimation model, so as to obtain the second reference signal of the current fluid pulsation sampling point filtered by the secondary channel estimation model.

[0064] Step 203: adjusting the adaptive parameter based on the reference signal filtered by the secondary channel estimation model and the control error of the fluid pulsation. 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 essentially the target parameter of the notch filter.

[0065] For example, 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 of the nth fluid pulsation sampling point, the control error e(n) of the fluid pulsation of the nth fluid pulsation sampling point is determined, where e(n) = d(n)-y'(n).

[0066] The target parameter of the notch filter of the embodiment of the present application can 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 one, and the first weight coefficient of the notch filter can be expressed as formula two:

[0067]

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

[0069] Since the model parameter determination process of the secondary channel estimation model does not exist the coupling between the online identification and the active control, the first weight coefficient and the second weight coefficient of the notch filter can be updated by using the first reference signal and the second reference signal filtered by the secondary channel estimation model, so that the stability of the adaptive fluid pulsation active control algorithm can be ensured.

[0070] In an optional manner, the present application provides a fluid pulsation active control system, which can include 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 an oil tank, and the pressure sensor and the control valve are in communication connection with the active controller. The active controller can execute the fluid pulsation control method based on the time delay parameter model of the embodiments of the present application.

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

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

[0073] In practical applications, the digital-to-analog converter, the hydraulic impedance, the pressure sensor and the analog-to-digital converter of the embodiment of the present application have dynamics and phase difference delay. The phase difference delay of the digital-to-analog converter, the pressure sensor and the 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 shift of the hydraulic impedance is within 90°, so that the phase shift error of the secondary channel estimation model and the secondary channel shown in the figure is within 90°, and therefore the stability of the adaptive fluid pulsation control algorithm of the embodiment of the present application is relatively good. Figure 4 The phase shift error of the secondary channel shown in the figure is within 90°, and therefore the stability of the adaptive fluid pulsation control algorithm of the embodiment of the present application is relatively good.

[0074] The mainstream adaptive notch control algorithm based on FXLMS is verified by joint simulation of Amesim and Simulink.

[0075] Figure 5 The simulation verification result schematic diagram of the online identification of the secondary channel in the related art is shown. As shown in the figure Figure 5 When the adaptive fluid pulsation active control starts at 4s, the control is stable after about 2s.

[0076] Figure 6 The simulation verification result schematic diagram of the offline identification method of the embodiment of the present application is shown. As shown in the figure Figure 6 When the adaptive fluid pulsation active control starts at 4s, the control is stable after about 0.2s, and has a faster convergence speed.

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

[0078] In one or more of the 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 parameter of the control valve at the target frequency, and determines the model parameters of the secondary channel estimation model (i.e., the delay parameter model) through offline identification. In this way, the predicted model parameters of the secondary channel estimation model are not affected by the trap filter. In this case, based on the control error of the fluid pulsation and the reference signal filtered by the secondary channel estimation model, the control stability of the adaptive fluid pulsation control algorithm can be improved after adjusting the adaptive parameters, so that the adaptive fluid pulsation control algorithm is suitable for stable control in a time-varying scene.

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

[0080] The embodiments of the present application can divide the functional units of the electronic device according to the above method examples, for example, each functional module can be divided corresponding to each function, or two or more functions can be integrated in one processing module. The above integrated module can be realized in the form of hardware or in the form of software function module. It should be noted that the division of the module in the embodiments of the present application is illustrative, and is only a logical function division. Actual implementation can have another division method.

[0081] In the case of dividing each functional module corresponding to each function, the example embodiments of the present application provide a fluid pulsation control device based on a delay parameter model, which can be applied to the chip of the electronic device for the electronic device. Figure 8 A functional module schematic block diagram of the fluid pulsation control device based on a delay parameter model according to the example embodiments of the present application is shown. As shown in Figure 8 The fluid pulsation control device based on a delay parameter model 800 includes:

[0082] The acquisition module 801 is configured to acquire a first reference signal and a second reference signal based on a target frequency of fluid pulsation, and the first reference signal and the second reference signal are orthogonal.

[0083] The adjusting module 802 is 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 the fluid pulsation.

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

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

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

[0087] As a possible implementation, the identification module 803 is configured to determine a delay deviation of the secondary channel based on the lag phase parameter of the control valve at the target frequency and the target frequency, and determine the model parameter 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, the lag phase parameter of the control valve at the target frequency is a 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 configured to determine an 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 parameter of the secondary channel estimation model based on the actual delay of the secondary channel and the target frequency.

[0090] As a possible implementation, 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 the secondary channel.

[0091] Figure 9 A schematic block diagram of a chip according to an example embodiment of the present application is shown. As shown in FIG. 1, the chip includes a processor 100, a memory 200, a communication interface 300, and a bus 400.Figure 9 As shown, the chip 900 includes one or more (including two) processors 901 and a communication interface 902. The communication interface 902 can perform the data transmission and reception steps in the above method, and the processor 901 can perform the data processing steps in the above method.

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

[0093] In some implementations, such as Figure 9 As shown, processor 901 executes corresponding operations by calling operation instructions stored in memory (which may be stored in the operating system). Processor 901 controls the processing operations of any terminal device; processor can also be called a central processing unit (CPU). Memory 903 may include read-only memory and random access memory, and provides instructions and data to processor 901. A portion of memory 903 may also include NVRAM. For example, in applications, memory, communication interfaces, and other components are coupled together via a bus system, which may include, in addition to a data bus, a power bus, a control bus, and a status signal bus, etc. However, for clarity, in... Figure 9 The general designated all buses as Bus System 904.

[0094] The method disclosed by the embodiments of the present application can be applied to a processor or implemented by the processor. The processor can be an integrated circuit chip having a signal processing capability. In the implementation process, the steps of the method can be completed by an integrated logic circuit or an instruction in the form of software in the processor. The processor can be a general-purpose processor, a digital signal processor (DSP), an ASIC, a field-programmable gate array (FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components. Each method, step and logic block diagram in the embodiments of the present application can be implemented or executed. The general-purpose processor can be a microprocessor or the processor can also be any conventional processor. The steps of the method applied in conjunction with the embodiments of the present application can be directly embodied as a hardware code processor for execution, or a combination of hardware and software modules in the code processor for execution. The software module can be located in a random access memory, a flash memory, a read-only memory, a programmable read-only memory or an electrically erasable programmable memory, a register, or other mature storage media in the art. The storage medium is located in the storage, and the processor reads the information in the storage and combines the hardware to complete the steps of the above method.

[0095] The exemplary embodiments of the present application further provide an electronic device, including: at least one processor; and a memory connected with the at least one processor in communication. The memory stores a computer program capable of being executed by the at least one processor, and the computer program, when executed by the at least one processor, is configured to cause the electronic device to perform the method according to the embodiments of the present application.

[0096] The exemplary embodiments of the present application further provide a non-transitory computer readable storage medium storing a computer program, and the computer program, when executed by a processor of a computer, is configured to cause the computer to perform the method according to the embodiments of the present application.

[0097] The exemplary embodiments of the present application further provide a computer program product, including a computer program, and the computer program, when executed by a processor of a computer, is configured to cause the computer to perform the method according to the embodiments of the present application.

[0098] Reference Figure 10An example of a hardware device that can be employed in the implementation of the present application is now described with reference to the block diagram of an electronic device 1000 that can serve as a server or client of the present application, which is an example of a hardware device that can be applied to aspects of the present application. The electronic device is intended to represent various forms of digital electronic computer devices such as laptops, desktops, workstations, personal digital assistants, servers, blade servers, mainframes, and other appropriate computers. The electronic device can also represent various forms of mobile devices such as personal digital assistants, cellular telephones, smart phones, wearable devices, and other similar computing devices. The components shown here, their connections and relationships, and their functions, are meant to be examples only, and are not meant to limit implementations of the present application described and / or claimed in this document.

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

[0100] As shown in Figure 10 , various components in the electronic device 1000 are connected to the I / O interface 1005, including an input unit 1006, an output unit 1007, the 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 can receive inputted digital or character information, as well as generate key signal inputs related to user settings and / or function controls 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 magnetic 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™ device, a WiFi device, a WiMax device, a cellular communication device, and / or the like.

[0101] As shown in Figure 10As shown, the computing unit 1001 can be various general purpose and / or special purpose processing components having 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 specialized artificial intelligence (AI) computing chips, various computing units running machine learning model algorithms, a digital signal processor (DSP), and any suitable processor, controller, microcontroller, or the like. The computing unit 1001 performs various methods and processes described above. For example, in some embodiments, the methods of the example embodiments of the present application can be implemented as a computer software program tangibly embodied in a machine readable medium, such as the storage unit 1008. In some embodiments, portions or all of the computer program can be loaded and / or installed onto the electronic device 1000 via the ROM 1002 and / or the communication unit 1009. In some embodiments, the computing unit 1001 can be configured to perform the methods of the example embodiments of the present application by way of other any suitable means, such as by way of firmware.

[0102] Program code for carrying out methods of the present application can be written in any combination of one or more programming languages. The program code can be provided to a processor or controller of a general purpose computer, special purpose computer, or other programmable data processing apparatus to produce a machine, such that the program code, when executed by the processor or controller, produces a means for implementing the functions / acts specified in the flowcharts and / or block diagrams. The program code can be retrieved from a machine readable medium or from a propagated signal. The machine readable medium can be a storage medium, such as a magnetic, optical, or semiconductor storage. The machine readable medium can be a distributed network, so that the program code is stored on a plurality of different storage mediums and / or propagated signals.

[0103] In the context of the present application, a machine readable medium can be a tangible medium that can contain or store the program for use by or in connection with an instruction execution system, apparatus, or device. The machine readable medium can be a machine readable signal medium or a machine readable storage medium. A machine readable medium can include but is not limited to an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any suitable combination of the foregoing. More specific examples of the machine readable storage medium will include one or more lines of electrical connections, portable computer disks, hard disk, random access memory (RAM), read only memory (ROM), erasable programmable read only memory (EPROM or Flash memory), optical fibers, portable compact disc read only memories (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination of the foregoing.

[0104] As used in this application, the terms "machine-readable medium" and "computer- readable medium" refer to any computer program product, apparatus and / or device (e.g., magnetic discs, optical disks, memory, Programmable Logic Devices (PLDs)) used to provide 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 used to provide machine instructions and / or data to a programmable processor.

[0105] To provide for interaction with a user, the systems and techniques described here 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 a pointing device (e.g., a mouse or a trackball) by which the user can provide input to the computer. Other kinds of devices can be used to provide for interaction with a user as well; for example, 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, speech, or tactile input.

[0106] The systems and techniques described here can be implemented in a computing system that includes a back end component (e.g., as a data server), or that includes a middleware component (e.g., an application server), or that includes a front end component (e.g., a client computer having a graphical user interface or a Web browser through which a user can interact with an implementation of the systems and techniques described here), or any combination of such back end, middleware, or front end components. The components of the system can 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] The computing system can include clients and servers. A client and server are generally remote from each other and typically interact through a communication network. The relationship of client and server arises by virtue of computer programs running on the respective computers and having a client-server relationship to each other.

[0108] In the above embodiments, all or part of the embodiments can be implemented by software, hardware, firmware or any combination thereof. When implemented by software, all or part of the embodiments can be implemented in the form of a computer program product. The computer program product includes one or more computer programs or instructions. When the computer programs or instructions are loaded and executed on a computer, all or part of the processes or functions described in the embodiments of the present application are performed. The computer can be a general purpose computer, a special purpose computer, a computer network, a terminal, user equipment or other programmable apparatus. The computer programs or instructions can be stored in a computer readable storage medium or transferred from one computer readable storage medium to another computer readable storage medium, for example, the computer programs or instructions can be transferred from one website site, computer, server or data center to another website site, computer, server or data center through wired or wireless manner. The computer readable storage medium can be any available medium that can be accessed by a computer or a data storage device such as a server, data center and the like integrated with one or more available media. The available media can be a magnetic medium, for example, a floppy disk, a hard disk, a magnetic tape; or an optical medium, for example, a digital video disc (digital video disc, DVD); or a semiconductor medium, for example, a solid state drive (solid state drive, SSD).

[0109] Although the present application is described in conjunction with specific features and embodiments thereof, it is evident that many alternatives, modifications and variations will be apparent to those skilled in the art in light of the foregoing description. Accordingly, it is intended to embrace all alternatives, modifications and variations that fall within the scope of the present application. Obviously, various modifications and changes are possible in the present application without departing from the scope and spirit of the application. Accordingly, it is intended to embrace all such modifications and changes that fall within the scope of the appended claims and their equivalents.

Claims

1. A method for controlling fluid pulsation based on a time delay parameter model, characterized by, The method comprises: obtaining a first reference signal and a second reference signal based on a target frequency of fluid pulsation, the first reference signal and the second reference signal being 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 an adaptive parameter based on the reference signal filtered by the secondary channel estimation model and a control error of fluid pulsation; wherein the method for determining the model parameter of the secondary channel estimation model comprises: obtaining a lag phase parameter of a control valve at the target frequency based on the target frequency of fluid pulsation, and determining the model parameter of the secondary channel estimation model based on the lag phase parameter of the control valve at the target frequency and a basic delay of the secondary channel.

2. The method of claim 1, wherein, The method for obtaining the lag phase parameter of the control valve at the target frequency based on the target frequency of fluid pulsation comprises: obtaining phase-frequency characteristic information of the control valve; determining the lag phase parameter of the control valve at the target frequency based on the phase-frequency characteristic curve of the control valve.

3. The method of claim 1, wherein, 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 time of obtaining 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, determining that the candidate delay of the secondary channel is the basic delay of the secondary channel.

4. The method of claim 1, wherein, The method for determining the model parameter 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 the secondary channel based on the lag phase parameter of the control valve at the target frequency and the target frequency; determining the model parameter of the secondary channel estimation model based on the delay deviation of the secondary channel and the basic delay of the secondary channel.

5. The method of claim 4, wherein, 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 of claim 4, wherein, The method for determining the model parameter 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 the basic delay of the secondary channel; determining the model parameter of the secondary channel estimation model based on the actual delay of the secondary channel and the target frequency.

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

8. A fluid pulsation control device based on a time delay parameter model, characterized by, The method comprises: an obtaining module configured to obtain a first reference signal and a second reference signal based on a target frequency of fluid pulsation, the first reference signal and the second reference signal being orthogonal; an adjusting 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; adjust an adaptive parameter based on the reference signal filtered by the secondary channel estimation model and a control error of fluid pulsation; The identification module is configured to acquire a lag phase parameter of the control valve at the target frequency based on a target frequency of the fluid pulsation, and determine a model parameter of a secondary channel estimation model based on the lag phase parameter of the control valve at the target frequency and a basic delay of the secondary channel.

9. A fluid pulsation active control system, characterized by, The method comprises: The control valve, the pressure sensor and the active controller, the first end of the control valve is connected with the pipeline, the second end of the control valve is connected with the oil tank, the pressure sensor and the control valve are both in communication connection with the active controller, and the active controller is used for executing the method in any one of claims 1-7.

10. An electronic device, comprising: The method comprises: A processor; And A memory for storing programs; Wherein, the program includes instructions, which, when executed by the processor, cause the processor to execute the method according to any one of claims 1-7.

11. A non-transitory computer readable storage medium, comprising: The non-transitory computer readable storage medium stores computer instructions for causing the computer to execute the method according to any one of claims 1-7.

Images