Spacecraft propulsion thrust noise suppression method and device

Abstract

The invention discloses a spacecraft propulsion thrust noise suppression method and device, and belongs to the technical field of spacecraft propulsion system regulation and control. The method comprises the following steps: establishing a valve needle coupling dynamic equation containing a fluid reaction force according to a hysteresis model used for representing a nonlinear relationship between piezoelectric ceramic input voltage and output displacement; the input voltage of expected displacement of the valve needle is calculated according to the valve needle coupling dynamic equation, the calculation result is applied to the piezoelectric ceramic stack, the obtained valve needle displacement is fed back to a preset active-disturbance-rejection control model, and the displacement compensation control quantity of the valve needle is output; and respectively carrying out parameter identification and gain updating processing on the valve needle coupling dynamic equation and the active-disturbance-rejection control model, and updating a displacement compensation control quantity according to a processing result and a real-time input voltage of the spacecraft so as to carry out real-time suppression on thrust noise of the spacecraft. According to the method, the problem of thrust fluctuation caused by the fact that a traditional linear model cannot accurately represent the hysteresis characteristic of the piezoelectric ceramic can be solved, and thrust noise is effectively reduced.

Description

Technical Field

[0001] The present invention relates to the technical field of spacecraft regulation and control, and in particular to a method and device for suppressing spacecraft propulsion thrust noise. Background Art

[0002] Micronewton-class propulsion systems are critical for spacecraft missions such as drag-free control and high-precision orbit maintenance. Traditional piezoelectric ceramic stack-driven valve needle systems use linear models to describe the valve needle dynamics. However, the inherent hysteresis and nonlinearity of piezoelectric materials lead to significant phase lag and amplitude errors between the input voltage and output displacement, which in turn cause thrust fluctuations.

[0003] In related technologies, classic closed-loop control algorithms and static feedforward compensation are difficult to adapt to the dynamic nonlinear characteristics of the propulsion system, resulting in limited thrust noise suppression effects; while complex finite element modeling methods have high computational costs and cannot meet real-time control requirements.

[0004] Based on this, there is an urgent need for a method and device for suppressing spacecraft propulsion thrust noise to solve the above technical problems. Summary of the Invention

[0005] The present invention provides a method and device for suppressing spacecraft propulsion thrust noise, which can effectively reduce thrust noise and significantly improve the accuracy of spacecraft attitude control. The technical solution is as follows:

[0006] In one aspect, a method for suppressing propulsion thrust noise of a spacecraft is provided, the method comprising:

[0007] Based on the hysteresis model used to characterize the nonlinear relationship between the input voltage and output displacement of piezoelectric ceramics, the valve needle coupling dynamic equation including the fluid reaction force is established;

[0008] The input voltage of the desired displacement of the valve needle is calculated according to the valve needle coupling dynamic equation, and the calculation result is applied to the piezoelectric ceramic stack. The obtained valve needle displacement is fed back to a preset active disturbance rejection control model, and the displacement compensation control amount of the valve needle is output;

[0009] Parameter identification and gain update processing are performed on the valve needle coupling dynamic equation and the active disturbance rejection control model respectively, and the displacement compensation control amount is updated according to the processing results and the real-time input voltage of the spacecraft to suppress the thrust noise of the spacecraft in real time.

[0010] In another aspect, a spacecraft propulsion thrust noise suppression device is provided, the device comprising:

[0011] A modeling module for establishing a valve needle coupling dynamic equation including fluid reaction force based on a hysteresis model used to characterize the nonlinear relationship between the input voltage and output displacement of piezoelectric ceramics;

[0012] a calculation module for calculating an input voltage for a desired displacement of the valve needle based on the valve needle coupling dynamic equation, applying the calculation result to the piezoelectric ceramic stack, and feeding the obtained valve needle displacement back to a preset active disturbance rejection control model to output a displacement compensation control variable for the valve needle;

[0013] A processing module is used to perform parameter identification and gain update processing on the valve needle coupling dynamic equation and the active disturbance rejection control model respectively, and update the displacement compensation control amount according to the processing results and the real-time input voltage of the spacecraft to suppress the thrust noise of the spacecraft in real time.

[0014] On the other hand, a computer device is provided, which includes a memory and a processor, wherein the memory is used to store a computer program, and the processor is used to execute the computer program stored in the memory to implement the steps of the above-mentioned spacecraft propulsion thrust noise suppression method.

[0015] On the other hand, a computer-readable storage medium is provided, wherein the storage medium stores a computer program, and when the computer program is executed by a processor, the steps of the above-mentioned method for suppressing spacecraft propulsion thrust noise are implemented.

[0016] On the other hand, a computer program product is provided, comprising a computer program, which, when executed by a processor, implements the steps of the above-mentioned method for suppressing spacecraft propulsion thrust noise.

[0017] The technical solution provided by the present invention can bring at least the following beneficial effects: the nonlinear relationship between the input voltage and output displacement of the piezoelectric ceramic is accurately described through a hysteresis model, and the valve needle dynamic equation including the fluid reaction force is constructed; then, a preset anti-disturbance control controller is used to generate a smooth command signal through a tracking differentiator, the total system disturbance is estimated in real time using an extended state observer, and the compensation control variable is generated through nonlinear state error feedback; finally, the hysteresis model parameters are identified online using the recursive least squares method, and the controller gain and observer bandwidth are dynamically adjusted to achieve adaptive optimization of the compensation control variable. This solves the problem of thrust fluctuation caused by the inability of traditional linear models to accurately characterize the hysteresis characteristics of piezoelectric ceramics, effectively reduces thrust noise, and significantly improves the accuracy of spacecraft attitude control. It has modular integration, low cost, strong robustness, and wide applicability. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0019] Figure 1 This is a flow chart of a method for suppressing spacecraft propulsion thrust noise provided by one embodiment of the present invention;

[0020] Figure 2 This is a comparison diagram of the hysteresis model provided by one embodiment of the present invention and the measured hysteresis curve;

[0021] Figure 3 This is a structural block diagram of an active disturbance rejection controller provided by an embodiment of the present invention;

[0022] Figure 4 This is a flow chart of an online parameter identification algorithm provided by one embodiment of the present invention;

[0023] Figure 5 This is a structural diagram of a spacecraft propulsion thrust noise suppression device provided by one embodiment of the present invention;

[0024] Figure 6 This is a hardware architecture diagram of a computer device provided by one embodiment of the present invention. DETAILED DESCRIPTION

[0025] In order to make the purpose, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of the present invention.

[0026] As mentioned earlier, the traditional piezoelectric ceramic stack-driven valve needle system uses a linear model to describe the valve needle dynamics. However, the inherent hysteresis nonlinearity of the piezoelectric material leads to significant phase lag and amplitude error between the input voltage and output displacement, which in turn causes thrust fluctuations.

[0027] Based on this, the concept of the present invention is to perform composite suppression of thrust noise through a hysteresis model and active disturbance rejection control, thereby taking into account the application needs of both thrust accuracy and real-time noise suppression.

[0028] The specific implementation of the above concept is described below.

[0029] Please refer to Figure 1 , an embodiment of the present invention provides a method for suppressing spacecraft propulsion thrust noise, the method comprising:

[0030] Step 100, establishing a valve needle coupling dynamic equation including fluid reaction force based on a hysteresis model used to characterize the nonlinear relationship between the input voltage and output displacement of the piezoelectric ceramic;

[0031] Step 102: Calculate the input voltage of the desired valve needle displacement based on the valve needle coupling dynamic equation, apply the calculated result to the piezoelectric ceramic stack, and feed the obtained valve needle displacement back to a preset active disturbance rejection control model to output a displacement compensation control variable of the valve needle.

[0032] In step 104, parameter identification and gain update processing are performed on the valve needle coupling dynamic equation and the active disturbance rejection control model respectively, and the displacement compensation control amount is updated according to the processing results and the real-time input voltage of the spacecraft to suppress the thrust noise of the spacecraft in real time.

[0033] In an embodiment of the present invention, a hysteresis model is used to accurately describe the nonlinear relationship between the input voltage and output displacement of piezoelectric ceramics, and a valve needle dynamics equation including the fluid reaction force is constructed. A preset anti-disturbance control controller is then used to generate a smooth command signal through a tracking differentiator. The extended state observer is used to estimate the total system disturbance in real time, and a compensating control variable is generated through nonlinear state error feedback. Finally, the recursive least squares method is combined to online identify the hysteresis model parameters, dynamically adjust the controller gain and observer bandwidth, and achieve adaptive optimization of the compensating control variable. This solves the problem of thrust fluctuations caused by the inability of traditional linear models to accurately characterize the hysteresis characteristics of piezoelectric ceramics, effectively reduces thrust noise, and significantly improves the accuracy of spacecraft attitude control. The system features modular integration, low cost, strong robustness, and wide applicability.

[0034] Described below Figure 1 How to perform the steps shown.

[0035] First, for step 100 , a valve needle coupling dynamic equation including the fluid reaction force is established based on a hysteresis model used to characterize the nonlinear relationship between the input voltage and output displacement of the piezoelectric ceramic.

[0036] Considering that traditional linear models cannot accurately characterize the hysteresis effect of piezoelectric ceramics, causing the controller design to deviate from the actual dynamics, the Bouc-Wen hysteresis model is used in the embodiment of the present invention to characterize the nonlinear relationship between the input voltage u(t) and the output displacement x(t) of the piezoelectric ceramic stack:

[0037] x(t)=du(t)+h(t)

[0038]

[0039] Among them, d is the linear proportional coefficient; du(t) is the linear displacement output; h(t) is the hysteresis displacement output; α, is the hysteresis loop shape control coefficient of the hysteresis model. The comparison between the hysteresis model and the measured hysteresis curve is shown in the figure below. Figure 2 shown.

[0040] Calculate the fluid reaction force F based on the flow field pressure gradient caused by the valve needle movement flow :

[0041]

[0042] Where, ρ is the propellant density; A is the cross-sectional area of ​​the flow channel; v is the flow velocity;

[0043] According to the hysteresis model and the fluid reaction force, the valve needle coupling dynamic model is established:

[0044]

[0045] Where m, c, and k are the equivalent mass, equivalent damping coefficient, and equivalent stiffness of the piezoelectric valve needle system, respectively; k p is the equivalent stiffness of the piezoelectric ceramic stack.

[0046] Then, for step 102, the input voltage of the desired valve needle displacement is calculated according to the valve needle coupling dynamic equation, and the calculation result is applied to the piezoelectric ceramic stack. The obtained valve needle displacement is fed back to the preset active disturbance rejection control model, and the displacement compensation control amount of the valve needle is output.

[0047] In the embodiment of the present invention, a third-order active disturbance rejection controller is designed, such as Figure 3 As shown in the figure, a smooth command signal is generated by a tracking differentiator (TD), the extended state observer (ESO) is used to estimate the total system disturbance (including hysteresis nonlinearity, fluid pulsation and unmodeled dynamics) in real time, and the compensation control variable is generated by nonlinear state error feedback (NLSEF).

[0048] Specifically, the tracking micro-molecule model is used to generate a target displacement signal v1(t) without overshoot and a differential v2(t) of the target displacement signal according to the target displacement instruction:

[0049]

[0050] Where R is the tracking speed factor;

[0051] The extended state observation submodel is used to estimate the system states z1, z2 and total disturbance z3 of the spacecraft propulsion system according to the output displacement:

[0052]

[0053] Where, β 01 , β 02 and β 03 are all observation gains; b0 is the control input coefficient;

[0054] Furthermore, for the extended state observation sub-model, its observer bandwidth w0 is set to 50-200 Hz and dynamically adjusted according to the main frequency band of the noise to meet β 01 =3ω o 、

[0055] The nonlinear state error feedback sub-model is used to calculate the state error according to the target displacement signal and the system state, and determine the displacement compensation control amount according to the calculation result:

[0056] State error:

[0057] e1=v1-z1

[0058] e2=ν2-z2

[0059] The output control quantity u0 is:

[0060] u0=β1f al (e1,λ1,τ)+β2f al (e2,λ2,τ)

[0061] Where, e1 and e2 are the state errors; λ1, λ2 and τ are nonlinear filter parameters; u is the displacement compensation control quantity; f al (·) is a nonlinear function with filtering function:

[0062]

[0063] The final displacement compensation control quantity is: u = u0-z3 / b; where b is the control gain.

[0064] Furthermore, for the nonlinear state error feedback sub-model, the nonlinear filter function parameters are set to λ1=0.5, λ2=0.25, and τ=0.01 to balance the response speed and anti-shake capability.

[0065] For step 104, parameter identification and gain update processing are performed on the valve needle coupling dynamic equation and the active disturbance rejection control model respectively, and the displacement compensation control amount is updated according to the processing results and the real-time input voltage of the spacecraft to suppress the thrust noise of the spacecraft in real time.

[0066] In the embodiment of the present invention, the recursive least squares method is used to identify the parameters α, And dynamically update the ESO bandwidth and NLSEF gain of ADRC to achieve collaborative optimization of the model and controller. The specific process is as follows Figure 4 shown.

[0067] In an embodiment of the present invention, the parameter identification processing of the hysteresis model includes the following steps: establishing a data set with a triangular wave excitation voltage with increasing amplitude as input and voltage response displacement data as output; using a particle swarm optimization algorithm to perform offline global parameter initial identification according to preset convergence conditions, and iteratively updating to obtain the initial parameters of the valve needle coupling dynamic equation; substituting the data set into the valve needle coupling dynamic equation composed of the initial parameters, and using the least squares method to perform online global parameter identification to obtain the optimal parameters whose adjacent iterative parameter changes are lower than a preset threshold.

[0068] Specifically, the piezoelectric ceramics are first excited by a triangular voltage with increasing amplitude, while displacement response data is simultaneously collected to construct a data set. A particle swarm optimization (PSO) algorithm is then used for offline global parameter initial identification. The population size and number of iterations are set, and the initial parameters are obtained with a model error of less than 3% as the convergence condition. The system then switches to online identification using the recursive least squares method, inputting the displacement-voltage data stream in real time. The parameters are continuously corrected by dynamically calculating the prediction error and updating the gain and covariance matrices until the parameter change between adjacent iterations falls below a threshold. The combination of PSO and recursive least squares ensures the physical rationality of the initial parameter values ​​while also enabling the tracking of the time-varying characteristics of the parameters.

[0069] In an embodiment of the present invention, the gain update of the active disturbance rejection control model includes the following steps: performing broadband adjustment on the extended state observation submodel according to the online global parameter identification results to improve the disturbance estimation accuracy; and updating the control gain of the nonlinear state error feedback submodel according to the online global parameter identification results to obtain a real-time control gain coefficient.

[0070] Specifically, the nonlinear parameters (α, ), and use the dynamically updated error covariance matrix and gain matrix to achieve parameter tracking; at the same time, the identification results are fed back to the ADRC controller, the bandwidth of the ESO (extended state observer) is dynamically adjusted to optimize the disturbance estimation accuracy, and the gain coefficient of the NLSEF (nonlinear state error feedback) is adaptively adjusted, finally forming a "parameter identification-controller parameter adjustment" closed loop, which improves the system's ability to suppress hysteresis nonlinearity and dynamic response performance.

[0071] Compared with the existing technology, the above-mentioned thrust noise suppression method has the following effects: (1) High-precision noise suppression: In the 0.001-1Hz frequency band, the thrust noise spectral density is reduced by 85%, reaching below 0.2μN / √Hz, that is, micro-newton-level thrust accuracy; (2) Strong robustness: ESO compensates for model uncertainty in real time, and the system remains stable under ±20% parameter perturbation; (3) Fast dynamic response: The step command tracking error convergence time is less than 10ms, and the overshoot is less than 2%; (4) Engineering applicability: The algorithm can be directly embedded in the existing FPGA controller without the need for additional hardware modification.

[0072] The effectiveness of the above method is demonstrated below with two examples.

[0073] Implementation Case 1: Model Parameter Calibration and Controller Configuration

[0074] Experimental platform construction: using commercial piezoelectric ceramic stacks, displacement resolution 0.1nm; microthruster flow channel cross-sectional area A = 0.1mm 2 The propellant is xenon (density ρ = 5.89 kg / m 3 ); the sampling frequency of the data acquisition system is 10kHz.

[0075] Bouc-Wen parameter identification: Apply a 0-100V triangle wave voltage and collect displacement response data; use the particle swarm optimization algorithm (PSO) to fit α = 0.85, The model error is 2.7%.

[0076] ADRC model parameter settings: the speed factor of the tracking micro-molecule model is R = 500, the observer bandwidth of the extended state observation sub-model is w0 = 150 Hz, and the corresponding gain β 01 =450,β 02 =67500,β 03 =3375000; nonlinear state error feedback gains β1=100, β2=50, λ1=0.5, λ2=0.25, τ=0.01.

[0077] Implementation Case 2: Noise Suppression Effect Verification

[0078] Open-loop test: When ADRC is not enabled, the 1Hz frequency band noise spectral density is tested. The 1Hz frequency band noise spectral density is 1.5μN / √Hz.

[0079] Closed-loop test: When ADRC is enabled, the noise spectral density in the 1Hz frequency band is tested and reduced to 0.2μN / √Hz; the total noise energy is reduced by 85%, and the control system bandwidth is extended to 200Hz.

[0080] Robustness verification: When the model parameter perturbation of ±20% is artificially introduced, the system can still operate stably and the noise suppression effect fluctuates by less than 5%.

[0081] Please refer to Figure 5 , an embodiment of the present invention provides a spacecraft propulsion thrust noise suppression device, the device comprising:

[0082] A modeling module 500 is used to establish a valve needle coupling dynamic equation including a fluid reaction force based on a hysteresis model used to characterize the nonlinear relationship between the input voltage and output displacement of the piezoelectric ceramic;

[0083] a calculation module 502 for calculating the input voltage of the desired valve needle displacement based on the valve needle coupling dynamic equation, applying the calculation result to the piezoelectric ceramic stack, and feeding the obtained valve needle displacement back to a preset active disturbance rejection control model to output a displacement compensation control variable of the valve needle;

[0084] The processing module 504 is used to perform parameter identification and gain update processing on the valve needle coupling dynamic equation and the active disturbance rejection control model respectively, and update the displacement compensation control amount according to the processing results and the real-time input voltage of the spacecraft to suppress the thrust noise of the spacecraft in real time.

[0085] In the embodiment of the present invention, when the modeling module 500 establishes the valve needle coupling dynamic equation including the fluid reaction force based on the hysteresis model used to characterize the nonlinear relationship between the input voltage and the output displacement of the piezoelectric ceramic, it is specifically configured to perform the following operations:

[0086] According to the hysteresis characteristics of piezoelectric ceramics, a hysteresis model is established to characterize the nonlinear relationship between input voltage u(t) and output displacement x(t):

[0087] x(t)=du(t)+h(t)

[0088]

[0089] Among them, d is the linear proportional coefficient; du(t) is the linear displacement output; h(t) is the hysteresis displacement output; α, is the hysteresis loop shape control coefficient of the hysteresis model;

[0090] Calculate the fluid reaction force F based on the flow field pressure gradient caused by the valve needle movement flow :

[0091]

[0092] Where, ρ is the propellant density; A is the cross-sectional area of ​​the flow channel; v is the flow velocity;

[0093] According to the hysteresis model and the fluid reaction force, the valve needle coupling dynamic model is established:

[0094]

[0095] Where m, c, and k are the equivalent mass, equivalent damping coefficient, and equivalent stiffness of the piezoelectric valve needle system, respectively; k p is the equivalent stiffness of the piezoelectric ceramic stack.

[0096] In an embodiment of the present invention, the active disturbance rejection control model includes a tracking micro-molecule model, an extended state observation sub-model, and a nonlinear state error feedback sub-model, wherein:

[0097] The tracking micro-molecule model is used to generate a target displacement signal v1(t) without overshoot and a differential v2(t) of the target displacement signal according to the target displacement instruction:

[0098]

[0099] Where R is the tracking speed factor;

[0100] The extended state observation submodel is used to estimate the system states z1, z2 and total disturbance z3 of the spacecraft propulsion system according to the output displacement:

[0101]

[0102] Where, β 01 , β 02 and β 03 are all observation gains; b0 is the control input coefficient;

[0103] The nonlinear state error feedback sub-model is used to calculate the state error according to the target displacement signal and the system state, and determine the displacement compensation control amount according to the calculation result:

[0104] u0=β1f al (e1,λ1,τ)+β2f al (e2,λ2,τ)

[0105] u=u0-z3 / b

[0106] Where, e1 and e2 are the state errors; f al (·) is a nonlinear function; λ1, λ2, and τ are all nonlinear filter parameters; u0 is the output control variable; u is the displacement compensation control variable; and b is the control gain.

[0107] In the embodiment of the present invention, the observation gains are set as follows:

[0108] β 01 =3ω o

[0109]

[0110] Where w0 is the observation bandwidth;

[0111] The nonlinear filtering parameters are set to be: λ1=0.5, λ2=0.25, τ=0.01 in sequence.

[0112] In an embodiment of the present invention, when performing parameter identification on the valve needle coupling dynamic equation, the processing module 504 is specifically used to perform the following operations: establishing a data set with a triangular wave excitation voltage with increasing amplitude as input and voltage response displacement data as output; using a particle swarm optimization algorithm to perform offline global parameter initial identification according to preset convergence conditions, and iteratively updating to obtain the initial parameters of the valve needle coupling dynamic equation; substituting the data set into the valve needle coupling dynamic equation composed of the initial parameters, and using the least squares method to perform online global parameter identification to obtain the optimal parameters with the change in parameters between adjacent iterations being lower than a preset threshold.

[0113] In an embodiment of the present invention, when executing the gain update of the active disturbance rejection control model, the processing module 504 is specifically used to perform the following operations: performing broadband adjustment on the extended state observation submodel according to the online global parameter identification result to improve the disturbance estimation accuracy; updating the control gain of the nonlinear state error feedback submodel according to the online global parameter identification result to obtain a real-time control gain coefficient.

[0114] It should be noted that the spacecraft propulsion thrust noise suppression device provided in the above embodiment is merely illustrated by the division of the aforementioned functional modules. In actual applications, the aforementioned functions can be assigned to different functional modules as needed, that is, the internal structure of the device can be divided into different functional modules to complete all or part of the functions described above. Furthermore, the spacecraft propulsion thrust noise suppression device provided in the above embodiment and the spacecraft propulsion thrust noise suppression method embodiment are based on the same concept. The specific implementation process is detailed in the method embodiment and will not be repeated here.

[0115] The embodiment of the present application also provides a computer device, please refer to Figure 6 The computer device includes a processor and a memory, wherein the memory stores at least one instruction, at least one program, code set or instruction set, and the at least one instruction, at least one program, code set or instruction set is loaded and executed by the processor to implement the spacecraft propulsion thrust noise suppression method provided by the above-mentioned method embodiments.

[0116] An embodiment of the present application also provides a computer-readable storage medium, on which is stored at least one instruction, at least one program, code set or instruction set, and the at least one instruction, at least one program, code set or instruction set is loaded and executed by a processor to implement the spacecraft propulsion thrust noise suppression method provided by the above-mentioned method embodiments.

[0117] An embodiment of the present application also provides a computer program product, which includes a computer program. A processor of a computer device reads the computer program from a computer-readable storage medium, and the processor executes the computer program, so that the computer device executes the spacecraft propulsion thrust noise suppression method described in any of the above embodiments.

[0118] For the convenience of description, the above systems or devices are described as being divided into various modules or units according to their functions. Of course, when implementing the present application, the functions of each unit can be implemented in the same or multiple software and / or hardware.

[0119] Through the description of the above embodiments, it can be seen that those skilled in the art can clearly understand that the present application can be implemented by means of software plus a necessary general hardware platform. Based on this understanding, the technical solution of the present application, or the part that contributes to the prior art, can be embodied in the form of a software product, which can be stored in a storage medium such as ROM / RAM, a magnetic disk, an optical disk, etc., and includes a number of instructions for enabling a computer device (which can be a personal computer, a server, or a network device, etc.) to execute the methods described in various embodiments of the present application or certain parts of the embodiments.

[0120] Finally, it should be noted that, in this document, relational terms such as first, second, third, and fourth are used only to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any actual relationship or order between these entities or operations. Moreover, the terms "comprises," "comprising," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus comprising a series of elements includes not only those elements, but also other elements not explicitly listed, or elements inherent to such process, method, article, or apparatus. In the absence of further limitations, an element defined by the phrase "comprising a ..." does not exclude the presence of additional identical elements in the process, method, article, or apparatus comprising the element.

[0121] The above is only a preferred embodiment of the present application. It should be pointed out that for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the principles of the present application. These improvements and modifications should also be regarded as the scope of protection of the present application.

Claims

1. A method for suppressing spacecraft propulsion thrust noise, characterized in that: The method comprises: Based on the hysteresis model used to characterize the nonlinear relationship between the input voltage and output displacement of piezoelectric ceramics, the valve needle coupling dynamic equation including the fluid reaction force is established; The input voltage of the desired displacement of the valve needle is calculated according to the valve needle coupling dynamic equation, and the calculation result is applied to the piezoelectric ceramic stack. The obtained valve needle displacement is fed back to a preset active disturbance rejection control model, and the displacement compensation control amount of the valve needle is output; Parameter identification and gain update processing are performed on the valve needle coupling dynamic equation and the active disturbance rejection control model respectively, and the displacement compensation control amount is updated according to the processing results and the real-time input voltage of the spacecraft to suppress the thrust noise of the spacecraft in real time.

2. The method according to claim 1, wherein The valve needle coupling dynamic equation including the fluid reaction force is established based on the hysteresis model used to characterize the nonlinear relationship between the input voltage and output displacement of the piezoelectric ceramic, including: According to the hysteresis characteristics of piezoelectric ceramics, a hysteresis model is established to characterize the nonlinear relationship between input voltage u(t) and output displacement x(t): x(t)=du(t)+h(t) Among them, d is the linear proportional coefficient; du(t) is the linear displacement output; h(t) is the hysteresis displacement output; α, is the hysteresis loop shape control coefficient of the hysteresis model; Calculate the fluid reaction force F based on the flow field pressure gradient caused by the valve needle movement flow : Where, ρ is the propellant density; A is the cross-sectional area of ​​the flow channel; v is the flow velocity; According to the hysteresis model and the fluid reaction force, the valve needle coupling dynamic model is established: Where m, c, and k are the equivalent mass, equivalent damping coefficient, and equivalent stiffness of the piezoelectric valve needle system, respectively; k p is the equivalent stiffness of the piezoelectric ceramic stack.

3. The method according to claim 1, wherein The active disturbance rejection control model includes a tracking micro-molecule model, an extended state observation sub-model and a nonlinear state error feedback sub-model, wherein: The tracking micro-molecule model is used to generate a target displacement signal ν1(t) without overshoot and a differential v2(t) of the target displacement signal according to the target displacement instruction: Where R is the tracking speed factor; The extended state observation submodel is used to estimate the system states z1, z2 and total disturbance z3 of the spacecraft propulsion system according to the output displacement: Where, β 01 , β 02 and β 03 are all observation gains; b0 is the control input coefficient; The nonlinear state error feedback sub-model is used to calculate the state error according to the target displacement signal and the system state, and determine the displacement compensation control amount according to the calculation result: u0=β1f al (e1,λ1,τ)+β2f al (e2,λ2,τ) u=u0-z3 / b Where, e1 and e2 are the state errors; f al (·) is a nonlinear function; λ1, λ2, and τ are all nonlinear filter parameters; u0 is the output control variable; u is the displacement compensation control variable; and b is the control gain.

4. The method according to claim 3, wherein The observation gains are set as follows: b 01 =3h o Where w0 is the observation bandwidth; The nonlinear filtering parameters are set to be: λ1=0.5, λ2=0.25, τ=0.01 in sequence.

5. The method according to claim 1, wherein Parameter identification is performed on the valve needle coupling dynamic equation, including: Establish a data set with a triangular wave excitation voltage with increasing amplitude as input and voltage response displacement data as output; Using a particle swarm optimization algorithm to perform offline global parameter initial identification according to a preset convergence condition, and iteratively updating to obtain initial parameters of the valve needle coupling dynamic equation; The data set is substituted into the valve needle coupling dynamic equation composed of initial parameters, and the least squares method is used to perform online global parameter identification to obtain the optimal parameters whose adjacent iterative parameter changes are lower than a preset threshold.

6. The method according to claim 5, wherein Performing a gain update on the active disturbance rejection control model includes: Based on the online global parameter identification results, the extended state observation submodel is adjusted to improve the disturbance estimation accuracy. The control gain of the nonlinear state error feedback sub-model is updated according to the online global parameter identification results to obtain the real-time control gain coefficient.

7. A spacecraft propulsion thrust noise suppression device, characterized in that: The device comprises: A modeling module for establishing a valve needle coupling dynamic equation including fluid reaction force based on a hysteresis model used to characterize the nonlinear relationship between the input voltage and output displacement of piezoelectric ceramics; a calculation module for calculating an input voltage for a desired valve needle displacement based on the valve needle coupling dynamic equation, applying the calculation result to the piezoelectric ceramic stack, and feeding the obtained valve needle displacement back to a preset active disturbance rejection control model to output a displacement compensation control variable for the valve needle; A processing module is used to perform parameter identification and gain update processing on the valve needle coupling dynamic equation and the active disturbance rejection control model respectively, and update the displacement compensation control amount according to the processing results and the real-time input voltage of the spacecraft to suppress the thrust noise of the spacecraft in real time.

8. A computer device, characterized in that: The computer device includes a memory and a processor, the memory is used to store a computer program, and the processor is used to execute the computer program stored in the memory to implement the steps of any one of the methods described in claims 1-6.

9. A computer-readable storage medium, characterized in that The storage medium stores a computer program, which, when executed by a processor, implements the steps of the method according to any one of claims 1 to 6.

10. A computer program product, characterized in that The method comprises a computer program, wherein when the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 6 are implemented.

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