Spacecraft propulsion thrust noise suppression method and apparatus

Abstract

The application 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: according to a hysteresis model used for representing the nonlinear relationship between the input voltage of a piezoelectric ceramic and the output displacement, a valve needle coupling dynamic equation containing fluid reaction force is established; the input voltage of the expected 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 valve needle displacement is fed back to a preset active disturbance rejection control model, and a displacement compensation control amount of the valve needle is output; the valve needle coupling dynamic equation and the active disturbance rejection control model are subjected to parameter identification and gain updating processing respectively, and the displacement compensation control amount is updated according to the processing result and the real-time input voltage of the spacecraft, so that the thrust noise of the spacecraft is suppressed in real time. The application can solve the problem of thrust fluctuation caused by the fact that the traditional linear model cannot accurately represent the hysteresis characteristic of the piezoelectric ceramic, and effectively reduces the thrust noise.

Description

Technical Field

[0001] This invention relates to the field of spacecraft adjustment and control technology, and in particular to a method and apparatus for suppressing spacecraft propulsion thrust noise. Background Technology

[0002] Micro-Newton (MNY) propulsion systems are key components for performing tasks such as drag-free control and high-precision orbit maintenance of spacecraft. Traditional piezoelectric ceramic stack-driven valve needle systems describe valve needle dynamics using linear models, but the inherent hysteresis nonlinearity of piezoelectric materials leads to significant phase lag and amplitude errors between the input voltage and output displacement, resulting in thrust fluctuations.

[0003] In related technologies, classical closed-loop control algorithms and static feedforward compensation are difficult to adapt to the dynamic nonlinear characteristics of propulsion systems, 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] Therefore, there is an urgent need for a method and device for suppressing spacecraft propulsion noise to solve the above-mentioned technical problems. Summary of the Invention

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

[0006] On the one hand, a method for suppressing spacecraft propulsion thrust noise is provided, the method comprising:

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

[0008] The input voltage for the desired displacement of the valve needle is calculated based on 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 quantity of the valve needle is output.

[0009] The valve needle coupled dynamic equation and the active disturbance rejection control model are respectively subjected to parameter identification and gain update processing, and the displacement compensation control quantity 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] On the other hand, a spacecraft propulsion thrust noise suppression device is provided, the device comprising:

[0011] The modeling module is used to establish the valve needle coupling dynamic equation, which includes fluid reaction force, based on the hysteresis model used to characterize the nonlinear relationship between the input voltage and output displacement of piezoelectric ceramics.

[0012] The calculation module is used to calculate the input voltage of the desired displacement of the valve needle according to the valve needle coupling dynamic equation, and apply the calculation result 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 quantity of the valve needle is output.

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

[0014] On the other hand, a computer device is provided, the computer device including a memory and a processor, the memory for storing computer programs, and the processor for executing the computer programs stored in the memory to implement the steps of the spacecraft propulsion thrust noise suppression method described above.

[0015] On the other hand, a computer-readable storage medium is provided, wherein a computer program is stored therein, and when the computer program is executed by a processor, it implements the steps of the spacecraft propulsion thrust noise suppression method described above.

[0016] On the other hand, a computer program product is provided, including a computer program that, when executed by a processor, implements the steps of the spacecraft propulsion thrust noise suppression method described above.

[0017] The technical solution provided by this invention can bring at least the following beneficial effects: It accurately describes the nonlinear relationship between the input voltage and output displacement of the piezoelectric ceramic using a hysteresis model, and constructs a valve needle dynamic equation incorporating fluid reaction force; then, using a pre-set active disturbance rejection controller, a smooth command signal is generated through a tracking differentiator, and the total system disturbance is estimated in real time using an extended state observer, and a compensation control quantity 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 quantity. 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, significantly improves the attitude control accuracy of spacecraft, and features modular integration, low cost, strong robustness, and wide applicability. Attached Figure Description

[0018] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0019] Figure 1 This is a flowchart of a spacecraft propulsion thrust noise suppression method according to an embodiment of the present invention;

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

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

[0022] Figure 4 This is a flowchart of an online parameter identification algorithm provided in an embodiment of the present invention;

[0023] Figure 5 This is a structural diagram of a spacecraft propulsion thrust noise suppression device according to an embodiment of the present invention;

[0024] Figure 6 This is a hardware architecture diagram of a computer device provided in an embodiment of the present invention. Detailed Implementation

[0025] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are some embodiments of the present invention, but not all embodiments. All other embodiments obtained by those skilled in the art based on the embodiments of the present invention without creative effort are within the scope of protection of the present invention.

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

[0027] Based on this, the concept of the present invention is to suppress thrust noise by combining hysteresis model and active disturbance rejection control, thereby meeting the application requirements 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 The present invention provides a method for suppressing spacecraft propulsion thrust noise, the method comprising:

[0030] Step 100: Based on the hysteresis model used to characterize the nonlinear relationship between the input voltage and output displacement of the piezoelectric ceramic, establish the valve needle coupling dynamic equation that includes the fluid reaction force.

[0031] Step 102: Calculate the input voltage of the desired displacement of the valve needle according to the valve needle coupling dynamic equation, and apply the calculation result 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 quantity of the valve needle is output.

[0032] Step 104: Perform parameter identification and gain update processing on the valve needle coupled dynamic equation and the active disturbance rejection control model, respectively, and update the displacement compensation control quantity 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 this embodiment of the invention, a hysteresis model is used to accurately describe the nonlinear relationship between the input voltage and output displacement of the piezoelectric ceramic, and a valve needle dynamic equation incorporating fluid reaction force is constructed. Then, a pre-defined active disturbance rejection controller is used to generate a smooth command signal via a tracking differentiator, and an extended state observer is used to estimate the total system disturbance in real time. Compensation control quantities are generated through nonlinear state error feedback. Finally, the recursive least squares method is used to identify the hysteresis model parameters online, and the controller gain and observer bandwidth are dynamically adjusted to achieve adaptive optimization of the compensation control quantities. 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, significantly improves the attitude control accuracy of spacecraft, and features modular integration, low cost, strong robustness, and wide applicability.

[0034] The following description Figure 1 The execution method for each step is shown.

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

[0036] Considering that traditional linear models cannot accurately characterize the hysteresis effect of piezoelectric ceramics, leading to deviations in controller design from actual dynamics, this embodiment of the invention uses the Bouc-Wen hysteresis model 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] Where d is the linear proportional coefficient; du(t) is the linear displacement output; h(t) is the hysteresis displacement output; α, These are the hysteresis loop shape control coefficients for the hysteresis model. A comparison of the hysteresis model and the measured hysteresis curves is shown in the figure below. Figure 2 As shown.

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

[0041]

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

[0043] Based on the hysteresis model and the fluid reaction force, the valve needle coupling dynamic model is established as follows:

[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 This represents the equivalent stiffness of the piezoelectric ceramic stack.

[0046] Then, for step 102, 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 the preset active disturbance rejection control model, and the displacement compensation control quantity of the valve needle is output.

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

[0048] Specifically, the tracking micro-molecule model is used to generate an overshoot-free target displacement signal v1(t) and the differential ν2(t) of the target displacement signal according to the target displacement command:

[0049]

[0050] In the formula, R is the tracking speed factor;

[0051] The extended state observation sub-model is used to estimate the system states z1, z2 and total disturbance z3 of the spacecraft propulsion system based on the output displacement:

[0052]

[0053] In the formula, β 01 β 02 and β 03 All are observation gains; b0 is the control input coefficient;

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

[0055] The nonlinear state error feedback sub-model is used to calculate the state error based on the target displacement signal and the system state, and to determine the displacement compensation control quantity based on 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] In the formula, e1 and e2 are both state errors; λ1, λ2 and τ are all nonlinear filtering parameters; u is the displacement compensation control quantity; f al (·) is a nonlinear function with filtering capabilities:

[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 parameters of its nonlinear filter function are set to λ1 = 0.5, λ2 = 0.25, and τ = 0.01 to balance response speed and anti-chattering capability.

[0065] For step 104, parameter identification and gain update processing are performed on the valve needle coupled dynamic equation and the active disturbance rejection control model, respectively. The displacement compensation control quantity 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 this embodiment of the invention, the recursive least squares method is used to identify the Bouc-Wen hysteresis model parameters α and β online. It also dynamically updates the ESO bandwidth and NLSEF gain of ADRC to achieve collaborative optimization between the model and the controller. The specific process is as follows: Figure 4 As shown.

[0067] In this embodiment of the invention, the parameter identification process for the hysteresis model includes the following steps: establishing a dataset with an increasing triangular wave excitation voltage 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 the initial parameters of the valve needle coupling dynamic equation; substituting the dataset 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 where the change in parameters between adjacent iterations is lower than a preset threshold.

[0068] Specifically, firstly, a dataset is constructed by simultaneously collecting displacement response data while exciting a piezoelectric ceramic with an increasing triangular wave voltage. Then, an offline global parameter identification algorithm (PSO) is used, setting the population size and number of iterations, with a model error less than 3% as the convergence condition. Subsequently, the algorithm switches to recursive least squares for online identification, inputting displacement-voltage data streams in real time. The parameters are continuously corrected by dynamically calculating prediction errors and updating the gain and covariance matrices until the parameter changes in adjacent iterations are below a threshold. The combination of PSO and recursive least squares ensures both the physical rationality of the initial parameter values ​​and the ability to track the time-varying characteristics of the parameters.

[0069] In this embodiment of the invention, updating the gain of the active disturbance rejection control model includes the following steps: adjusting the broadband of the extended state observation sub-model based on the online global parameter identification results to improve the disturbance estimation accuracy; updating the control gain of the nonlinear state error feedback sub-model based on the online global parameter identification results to obtain the real-time control gain coefficient.

[0070] Specifically, the nonlinear parameters (α, β, γ) of the Bouc-Wen model are identified online in real time using the recursive least squares method. The system utilizes dynamically updated error covariance and gain matrices to achieve parameter tracking. Simultaneously, the identification results are fed back to the ADRC controller, dynamically adjusting the bandwidth of the ESO (Extended State Observer) to optimize the perturbation estimation accuracy, and adaptively adjusting the gain coefficient of the NLSEF (Nonlinear State Error Feedback). This ultimately forms a closed loop of "parameter identification - controller parameter tuning," improving the system's ability to suppress hysteresis nonlinearity and its dynamic response performance.

[0071] Compared with existing technologies, the above thrust noise suppression method has the following effects: (1) High-precision noise suppression: within the 0.001-1Hz frequency band, the thrust noise spectral density is reduced by 85% to below 0.2μN / √Hz, which is micro-Newton level thrust accuracy; (2) Strong robustness: ESO real-time compensation model uncertainty, 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 into existing FPGA controllers without 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 setup: Commercial piezoelectric ceramic stacks were used, with a displacement resolution of 0.1 nm; the cross-sectional area of ​​the micro-thruster flow channel was A = 0.1 mm². 2 The propellant is xenon gas (density ρ = 5.89 kg / m³). 3 The data acquisition system has a sampling frequency of 10kHz.

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

[0076] Active disturbance rejection control model parameter settings: the velocity factor R of the tracking molecular model is 500, the observer bandwidth w0 of the extended state observation sub-model is 150Hz, and the corresponding gain β... 01 =450, β 02 =67500, β 03 =3375000; Nonlinear state error feedback gain β1=100, β2=50, λ1=0.5, λ2=0.25, τ=0.01.

[0077] Implementation Case 2: Verification of Noise Suppression Effect

[0078] Open-loop test: With ADRC disabled, the noise spectral density in the 1Hz band was tested. The noise spectral density in the 1Hz band was 1.5μN / √Hz.

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

[0080] Robustness verification: With an artificial perturbation of ±20% of the model parameters, the system can still operate stably, and the noise suppression effect fluctuates by less than 5%.

[0081] Please refer to Figure 5 This invention provides a spacecraft propulsion thrust noise suppression device, which includes:

[0082] Modeling module 500 is used to establish valve needle coupling dynamic equations that include fluid reaction forces based on the hysteresis model used to characterize the nonlinear relationship between input voltage and output displacement of piezoelectric ceramics.

[0083] The calculation module 502 is used to calculate the input voltage of the desired displacement of the valve needle according to the valve needle coupling dynamic equation, and apply the calculation result 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 quantity of the valve needle is output.

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

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

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

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

[0088]

[0089] Where d is the linear proportional coefficient; du(t) is the linear displacement output; h(t) is the hysteresis displacement output; α, These are the hysteresis shape control coefficients for the hysteresis model;

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

[0091]

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

[0093] Based on the hysteresis model and the fluid reaction force, the valve needle coupling dynamic model is established as follows:

[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 This represents the equivalent stiffness of the piezoelectric ceramic stack.

[0096] In this embodiment of the 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 an overshoot-free target displacement signal v1(t) and the derivative v2(t) of the target displacement signal according to the target displacement command:

[0098]

[0099] In the formula, R is the tracking speed factor;

[0100] The extended state observation sub-model is used to estimate the system states z1, z2 and total disturbance z3 of the spacecraft propulsion system based on the output displacement:

[0101]

[0102] In the formula, β 01 β 02 and β 03 All are observation gains; b0 is the control input coefficient;

[0103] The nonlinear state error feedback sub-model is used to calculate the state error based on the target displacement signal and the system state, and to determine the displacement compensation control quantity based on the calculation result.

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

[0105] u=u0-z3 / b

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

[0107] In this embodiment of the invention, the observation gain is set sequentially as follows:

[0108] β 01 =3ω o

[0109]

[0110] In the formula, w0 is the observation bandwidth;

[0111] The nonlinear filtering parameters are set sequentially as follows: λ1 = 0.5, λ2 = 0.25, τ = 0.01.

[0112] In this embodiment of the invention, when the processing module 504 performs parameter identification on the valve needle coupling dynamic equation, it specifically performs the following operations: establishing a dataset with an increasing triangular wave excitation voltage 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 the initial parameters of the valve needle coupling dynamic equation; substituting the dataset 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 where the change in parameters between adjacent iterations is lower than a preset threshold.

[0113] In this embodiment of the invention, when the processing module 504 performs gain updates on the active disturbance rejection control model, it specifically performs the following operations: wideband adjustment of the extended state observation sub-model based on the online global parameter identification results to improve the disturbance estimation accuracy; and updating the control gain of the nonlinear state error feedback sub-model based on the online global parameter identification results to obtain the real-time control gain coefficient.

[0114] It should be noted that the spacecraft propulsion thrust noise suppression device provided in the above embodiments is only an example of the division of the above functional modules. In practical applications, the above 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. In addition, the spacecraft propulsion thrust noise suppression device provided in the above embodiments and the spacecraft propulsion thrust noise suppression method embodiments belong to the same concept, and the specific implementation process is detailed in the method embodiments, which will not be repeated here.

[0115] Embodiments of this application also provide a computer device, please refer to... Figure 6 The computer device includes a processor and a memory, the memory storing at least one instruction, at least one program, code set or instruction set, the at least one instruction, at least one program, code set or instruction set being loaded and executed by the processor to implement the spacecraft propulsion thrust noise suppression method provided in the above-described method embodiments.

[0116] The embodiments of this application also provide a computer-readable storage medium storing at least one instruction, at least one program, code set, or instruction set, wherein 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 in the above-described method embodiments.

[0117] Embodiments of this application also provide 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 executes the computer program, causing the computer device to perform any of the spacecraft propulsion thrust noise suppression methods described in the above embodiments.

[0118] For ease of description, the above systems or devices are described separately as various modules or units based on their functions. Of course, in implementing this application, the functions of each unit can be implemented in one or more software and / or hardware components.

[0119] As can be seen from the above description of the embodiments, those skilled in the art can clearly understand that this application can be implemented by means of software plus necessary general-purpose hardware platforms. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product can be stored in a storage medium, such as ROM / RAM, magnetic disk, optical disk, etc., and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute the methods described in various embodiments or some parts of the embodiments of this application.

[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, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitations, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes said element.

[0121] The above description is only a preferred embodiment of this application. It should be noted that for those skilled in the art, several improvements and modifications can be made without departing from the principle of this application, and these improvements and modifications should also be considered within the scope of protection of this application.

Claims

1. A method for suppressing spacecraft propulsion thrust noise, characterized in that, The method includes: Based on the hysteresis model used to characterize the nonlinear relationship between the input voltage and output displacement of piezoelectric ceramics, a valve needle coupling dynamic equation incorporating fluid reaction force is established, including: Based on the hysteresis characteristics of piezoelectric ceramics, a method for characterizing input voltage is established. u ( t and output displacement x ( t Hysteresis model of nonlinear relationship: in, d It is a linear proportionality coefficient; Linear displacement output; h ( t This is a hysteresis displacement output; , φ 1. φ 2 represents the hysteresis shape control coefficient of the hysteresis model; Calculate the fluid reaction force based on the pressure gradient in the flow field caused by the valve needle motion. : in, Where A is the propellant density; A is the cross-sectional area of ​​the flow channel; v is the flow velocity; Based on the hysteresis model and the fluid reaction force, the valve needle coupling dynamic equation is established as follows: in, , and The equivalent mass, equivalent damping coefficient, and equivalent stiffness of the piezoelectric valve needle system are, in order. This represents the equivalent stiffness of the piezoelectric ceramic stack. The input voltage for the desired displacement of the valve needle is calculated based on 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 quantity of the valve needle is output. The valve needle coupled dynamic equation and the active disturbance rejection control model are respectively subjected to parameter identification and gain update processing, and the displacement compensation control quantity 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 as described in claim 1, characterized in that, 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 an overshoot-free target displacement signal based on the target displacement command. and the differential of the target displacement signal : In the formula, For tracking velocity factor; The extended state observation sub-model is used to estimate the system state of the spacecraft propulsion system based on the output displacement. , and total disturbance : In the formula, , and All are observation gains; To control the input coefficients; The nonlinear state error feedback sub-model is used to calculate the state error based on the target displacement signal and the system state, and to determine the displacement compensation control quantity based on the calculation result. In the formula, and All of these are the aforementioned state errors; ( ) is a nonlinear function; λ 1 , λ 2 and τ All are nonlinear filtering parameters; For output control quantity; This is the displacement compensation control quantity; b To control the gain.

3. The method as described in claim 2, characterized in that, The observation gains are set sequentially as follows: In the formula, w 0 represents the observation bandwidth; The nonlinear filtering parameters are set sequentially as follows: λ 1 = 0.5 λ 2 = 0.25 τ =0.

01.

4. The method as described in claim 1, characterized in that, Parameter identification of the valve needle coupling dynamic equation includes: A dataset is established with a triangular wave excitation voltage of increasing amplitude as input and voltage response displacement data as output; The initial parameters of the valve needle coupling dynamic equation are obtained by using the particle swarm optimization algorithm to perform offline global parameter initial identification based on the preset convergence conditions and iteratively updating. The dataset is substituted into the valve needle coupling dynamic equation composed of initial parameters, and the least squares method is used for online global parameter identification to obtain the optimal parameters where the parameter change in adjacent iterations is lower than a preset threshold.

5. The method as described in claim 4, characterized in that, The gain update of the active disturbance rejection control model includes: Broadband adjustments are made to the extended state observation sub-model based on the online global parameter identification results to improve the accuracy of perturbation estimation; The control gain of the nonlinear state error feedback sub-model is updated based on the online global parameter identification results to obtain the real-time control gain coefficient.

6. A spacecraft propulsion thrust noise suppression device, characterized in that, The apparatus, used in the method of any one of claims 1-5, comprises: The modeling module is used to establish the valve needle coupling dynamic equation, which includes fluid reaction force, based on the hysteresis model used to characterize the nonlinear relationship between the input voltage and output displacement of piezoelectric ceramics. The calculation module is used to calculate the input voltage of the desired displacement of the valve needle according to the valve needle coupling dynamic equation, and apply the calculation result 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 quantity of the valve needle is output. The processing module is used to perform parameter identification and gain update processing on the valve needle coupled dynamic equation and the active disturbance rejection control model, respectively, and update the displacement compensation control quantity according to the processing results and the real-time input voltage of the spacecraft, so as to suppress the thrust noise of the spacecraft in real time.

7. A computer device, characterized in that, The computer device includes a memory and a processor. The memory is used to store computer programs, and the processor is used to execute the computer programs stored in the memory to implement the steps of the method according to any one of claims 1-5.

8. 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 described in any one of claims 1-5.

9. A computer program product, characterized in that, Includes a computer program, which, when executed by a processor, implements the steps of the method according to any one of claims 1-5.

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