Harmonic reducer vibration suppression method, device, equipment, storage medium and product

Abstract

This invention discloses a method, apparatus, device, storage medium, and product for suppressing vibration in a harmonic reducer. The method involves extracting the vibration signal from the previous sampling period of a target joint based on its position error. This position error is determined based on the actual position value and the corresponding desired position value of the previous sampling period. The target joint is driven by a harmonic reducer. Based on the vibration signal and desired position value from the previous sampling period, the current parameter values ​​of the parameters to be identified in a preset vibration model are identified, resulting in an identified preset vibration model. The preset vibration model is a sinusoidal function relating the vibration signal to the desired position, including the parameters to be identified for vibration amplitude and phase, and the number of wave generator cams. Based on the identified preset vibration model and the current desired position value, the current desired vibration signal is calculated. Based on the current desired position value, the current desired vibration signal, and a preset compensation coefficient, the current servo control command is determined. This method effectively suppresses the vibration of the harmonic reducer and improves its response.

Description

Technical Field

[0001] The embodiments of the present invention relate to the field of robotics technology, and in particular to a method, apparatus, device, storage medium and product for suppressing vibration of a harmonic reducer. Background Technology

[0002] Robots typically employ a semi-closed control method, where control is achieved by directly detecting the motor status (position or speed) on each axis using sensors on the motor shafts. Therefore, each axis can be viewed as a dual-inertia system consisting of a motor, a harmonic reducer, and a robotic arm. Due to structural errors and the presence of nonlinear structures like flexsplines in the harmonic reducer, the robot's control performance is rarely ideal. Periodic angular transmission errors caused by structural errors synchronize with gear rotation. Therefore, resonance occurs when the rotational frequency corresponds to the mechanical resonant frequency of the axis. Control stability is typically ensured by designing a controller to correct the vibration modes.

[0003] Currently, robot vibration suppression methods can be broadly categorized into passive resonance suppression methods and active resonance suppression methods. Active resonance suppression technology faces three main technical bottlenecks in practical applications: firstly, it is limited by the dynamic response characteristics of the hardware system; secondly, it suffers from the complexity of the control architecture; and thirdly, it faces the challenge of excessively high real-time computing resource consumption. In contrast, passive resonance suppression introduces frequency domain compensation strategies, with typical schemes including low-pass filters, notch filters, and lead-lag correction stages. Its core mechanism lies in selectively attenuating the resonant frequency characteristic components in the signal while improving control stability. However, it should be particularly noted that the performance of notch filters is significantly sensitive to the accuracy of center frequency matching: when there is a deviation between the actual resonant frequency and the notch filter's center frequency, it not only leads to a decrease in the expected attenuation effect but also introduces additional phase lag in the target frequency band. This unexpected phase characteristic may deteriorate the system's damping performance and may even induce more severe vibrations.

[0004] It is evident that existing methods for suppressing the vibration of robot harmonic reducers suffer from poor suppression effects and slow response due to the coupling of periodic angular transmission errors and mechanical resonant frequencies. These methods are unable to adapt to dynamic changes in a timely manner. Summary of the Invention

[0005] This invention provides a method, apparatus, equipment, storage medium, and product for suppressing vibrations in harmonic reducers, in order to solve the problems of poor suppression effect and untimely response in existing methods for suppressing vibrations in harmonic reducers.

[0006] According to one aspect of the present invention, a method for suppressing vibration of a harmonic reducer is provided, comprising:

[0007] Based on the actual position value and the corresponding expected position value of the target joint in the previous sampling period, the position error of the target joint in the previous sampling period is determined, wherein the target joint is driven by a harmonic reducer;

[0008] The vibration signal of the previous sampling period is extracted from the position error of the previous sampling period;

[0009] Based on the vibration signal of the previous sampling period and the expected position value of the previous sampling period, the current parameter value of the parameter to be identified in the preset vibration model is identified using a parameter identification algorithm, thereby obtaining the identified preset vibration model. The preset vibration model is a sinusoidal function relationship between the vibration signal and the expected position. The sinusoidal function relationship includes the preset number of wave generator cams and the parameter to be identified. The parameter to be identified includes the vibration amplitude and the vibration phase.

[0010] Based on the identified preset vibration model and the current desired position value, the current desired vibration signal is calculated;

[0011] Based on the current desired position value, the current desired vibration signal, and the preset compensation coefficient, the current servo control command is determined to control the movement of the target joint in the current sampling period.

[0012] According to another aspect of the present invention, a harmonic reducer vibration suppression device is provided, comprising:

[0013] An error determination module is used to determine the position error of the target joint in the previous sampling period based on the actual position value and the corresponding expected position value of the target joint in the previous sampling period, wherein the target joint is driven by a harmonic reducer;

[0014] The previous signal extraction module is used to extract the vibration signal of the previous sampling period from the position error of the previous sampling period;

[0015] The model identification module is used to identify the current parameter values ​​of the parameters to be identified in the preset vibration model based on the vibration signal and the expected position value of the previous sampling period using a parameter identification algorithm, so as to obtain the identified preset vibration model. The preset vibration model is a sinusoidal function relationship between the vibration signal and the expected position. The sinusoidal function relationship includes the preset number of wave generator cams and the parameters to be identified. The parameters to be identified include the vibration amplitude and the vibration phase.

[0016] The current signal calculation module is used to calculate the current desired vibration signal based on the identified preset vibration model and the current desired position value;

[0017] The instruction determination module is used to determine the current servo control instruction based on the current desired position value, the current desired vibration signal, and the preset compensation coefficient, so as to control the movement of the target joint in the current sampling period.

[0018] According to another aspect of the present invention, an electronic device is provided, the electronic device comprising:

[0019] At least one processor; and

[0020] A memory communicatively connected to the at least one processor; wherein,

[0021] The memory stores a computer program that can be executed by the at least one processor, which enables the at least one processor to perform the harmonic reducer vibration suppression method according to any embodiment of the present invention.

[0022] According to another aspect of the present invention, a computer-readable storage medium is provided, the computer-readable storage medium storing computer instructions for causing a processor to execute and implement the harmonic reducer vibration suppression method according to any embodiment of the present invention.

[0023] According to another aspect of the present invention, a computer program product is provided, the computer program product comprising a computer program that, when executed by a processor, implements the harmonic reducer vibration suppression method according to any embodiment of the present invention.

[0024] The technical solution provided by this invention determines the position error of the target joint in the previous sampling period based on the actual position value and the corresponding expected position value of the target joint in the previous sampling period, wherein the target joint is driven by a harmonic reducer; the vibration signal of the previous sampling period is extracted from the position error of the previous sampling period; based on the vibration signal and the expected position value of the previous sampling period, a parameter identification algorithm is used to identify the current parameter value of the parameter to be identified in the preset vibration model, thereby obtaining the identified preset vibration model, wherein the preset vibration model is a sine function relationship between the vibration signal and the expected position, the sine function relationship includes a preset number of wave generator cams and the parameter to be identified, the parameter to be identified including vibration amplitude and vibration phase; based on the identified preset vibration model and the current expected position value, the current expected vibration signal is calculated; based on the current expected position value, the current expected vibration signal, and a preset compensation coefficient, the current servo control command is determined to control the movement of the target joint in the current sampling period. By extracting vibration signals based on the position error of the previous sampling period, the vibration characteristics caused by the harmonic reducer can be identified in real time and accurately. Then, a parameter identification algorithm is used to dynamically update the parameters to be identified in the preset vibration model, ensuring that the preset vibration model accurately reflects the current vibration situation. Based on the identified preset vibration model and the current desired position value, the current desired vibration signal is calculated, and combined with preset compensation coefficients, the current servo control command is generated, achieving fast and accurate vibration compensation. This effectively solves the problems of poor suppression effect and untimely response in existing harmonic reducer vibration suppression methods.

[0025] It should be understood that the description in this section is not intended to identify key or essential features of the embodiments of the present invention, nor is it intended to limit the scope of the invention. Other features of the invention will become readily apparent from the following description. Attached Figure Description

[0026] To more clearly illustrate the technical solutions in the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0027] Figure 1 This is a flowchart of a method for suppressing vibration of a harmonic reducer provided in Embodiment 1 of the present invention;

[0028] Figure 2 This is a schematic diagram of the structure of a harmonic reducer vibration suppression device provided in Embodiment 2 of the present invention;

[0029] Figure 3This is a schematic diagram of the structure of an electronic device provided in Embodiment 3 of the present invention. Detailed Implementation

[0030] To enable those skilled in the art to better understand the present invention, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort should fall within the scope of protection of the present invention.

[0031] It should be noted that the terms "first," "second," etc., in the specification, claims, and accompanying drawings of this invention are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of the invention described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover a non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0032] Example 1

[0033] Figure 1 This is a flowchart of a harmonic reducer vibration suppression method provided in Embodiment 1 of the present invention. This embodiment is applicable to the suppression of vibrations caused by harmonic reducers. The method can be executed by a harmonic reducer vibration suppression device, which can be implemented in hardware and / or software and can be configured in an electronic device. Figure 1 As shown, the method includes:

[0034] S110. Determine the position error of the target joint in the previous sampling period based on the actual position value and the corresponding expected position value of the target joint in the previous sampling period, wherein the target joint is driven by a harmonic reducer.

[0035] In this embodiment, the target joint can be understood as a robot joint driven by a harmonic reducer and requiring suppression of the reducer's vibration, such as the shoulder, elbow, or wrist joints in a robot arm. The sampling period represents the time interval for data acquisition. The previous sampling period can be understood as a complete sampling time period immediately preceding the current sampling moment. The actual position value can be understood as the true position of the target joint corresponding to the expected position value in the previous sampling period, typically measured by a data acquisition device (such as an angle sensor). The expected position value can be understood as the preset, desired ideal position of the target joint within the previous sampling period. The position error can be understood as the difference between the actual position value and the expected position value. A harmonic reducer is a high-precision, high-reduction-ratio gear transmission device, mainly composed of a flexible gear, a rigid gear, and a wave generator.

[0036] Specifically, the desired position value and actual position value of the target joint in the previous sampling period are obtained. Then, based on the actual position value and desired position value in the previous sampling period, the position error of the target joint in the previous sampling period is determined using a preset difference algorithm (such as a simple difference algorithm or a weighted difference algorithm).

[0037] S120. Extract the vibration signal of the previous sampling period from the position error of the previous sampling period.

[0038] In this embodiment, the vibration signal can be understood as a periodic deviation component caused by the inherent vibration characteristics of the harmonic reducer.

[0039] Specifically, the transmission principle of a harmonic reducer is based on the rotation of a wave generator forcing the flexspline to undergo elastic deformation. During its translational motion around a fixed point, the flexspline teeth mesh with the rigid wheel teeth. A certain difference in the number of teeth between the rigid and flexsplines achieves speed change. The rotation of the wave generator forces the flexspline to undergo periodic elliptical deformation, with the deformation frequency equal to the input shaft speed multiplied by the number of cams in the wave generator. This deformation causes the meshing position and contact force amplitude between the flexspline and rigid wheel teeth to change periodically over time, forming a dynamic excitation source. When the deformation frequency (excitation frequency) approaches the natural frequency of the flexspline, structural resonance is triggered. These vibrations manifest as positional errors, forming specific vibration signals.

[0040] Therefore, the periodic component caused by the resonance of the harmonic reducer, i.e. the vibration signal of the previous sampling period, can be extracted by filtering or spectral analysis of the position error of the previous sampling period, so as to further suppress and control vibration.

[0041] S130. Based on the vibration signal of the previous sampling period and the expected position value of the previous sampling period, the current parameter value of the parameter to be identified in the preset vibration model is identified using a parameter identification algorithm to obtain the identified preset vibration model. The preset vibration model is a sinusoidal function relationship between the vibration signal and the expected position. The sinusoidal function relationship includes the preset number of wave generator cams and the parameter to be identified. The parameter to be identified includes the vibration amplitude and the vibration phase.

[0042] In this embodiment, the preset vibration model can be understood as a pre-set sine function relationship between the vibration signal and the desired position.

[0043] The process of establishing a preset vibration model is as follows:

[0044] The transmission principle of a harmonic reducer: The rotation of the wave generator forces the flexspline to undergo elastic deformation. During its translational motion around a fixed point, the flexspline teeth mesh with the rigid gear teeth. A certain difference in the number of teeth exists between the rigid and flexsplines, thus achieving speed transmission. Specifically, the rotation of the wave generator forces the flexspline to undergo periodic elliptical deformation. The deformation frequency is equal to the input shaft speed multiplied by the number of cams in the wave generator, expressed by the following formula:

[0045]

[0046] in, Indicates the deformation frequency; This indicates the number of cams in the wave generator, which can be set according to the actual situation, such as 2. This indicates the rotational speed of the input shaft.

[0047] This periodic elliptical deformation causes the meshing position and contact force amplitude between the flexible and rigid gear teeth to change periodically over time, creating a dynamic excitation source. When the deformation frequency (excitation frequency) approaches the natural frequency of the flexible gear, structural resonance occurs. At this point, the excitation frequency of the vibration... It can be represented as:

[0048]

[0049] To describe these vibrations, an initial vibration model is established:

[0050]

[0051] in, This represents the periodic deviation component caused by the inherent vibration characteristics of the harmonic reducer, i.e., the vibration signal. This indicates the vibration amplitude. Indicates the vibration phase. Indicates time.

[0052] Due to the desired position value of the target joint The following relationship exists between the input shaft speed and the input shaft speed:

[0053]

[0054] Therefore, by combining the initial vibration model formula, the preset vibration model can be obtained:

[0055]

[0056] Among them, vibration amplitude and vibration phase These are the parameters to be identified in the preset vibration model.

[0057] In this embodiment, the parameter identification algorithm can be understood as a pre-set algorithm used to identify the parameters to be identified in a preset vibration model.

[0058] Specifically, based on the vibration signal and the expected position value from the previous sampling period, a parameter identification algorithm is used to identify the current parameter value of the parameter to be identified in the preset vibration model. Then, by substituting the current parameter value into the preset vibration model, the identified preset vibration model can be obtained. It is worth noting that this embodiment does not limit the specific parameter identification algorithm; for example, the algorithm can be recursive least squares, gradient descent, or a Kalman filter, etc.

[0059] S140. Based on the identified preset vibration model and the current desired position value, calculate the current desired vibration signal.

[0060] In this embodiment, the current expected position value can be understood as the expected position value in the current sampling period. The current expected vibration signal can be understood as the vibration signal predicted within the current sampling period.

[0061] Specifically, by inputting the current desired position value into the identified preset vibration model, the current desired vibration signal can be calculated.

[0062] S150. Based on the current desired position value, the current desired vibration signal, and the preset compensation coefficient, determine the current servo control command to control the movement of the target joint in the current sampling period.

[0063] In this embodiment, the preset compensation coefficient can be understood as a coefficient pre-set according to the actual situation, used to adjust the vibration compensation force. The servo control command can be understood as the command used to control the movement of the target joint within the current sampling period.

[0064] Specifically, the current vibration compensation value is calculated based on the current desired vibration signal and the preset compensation coefficient. The current desired position value is then corrected using the vibration compensation value to obtain the current servo control command. Subsequently, the current servo control command is sent to the target joint to control the movement of the target joint in the current sampling period, thereby achieving effective suppression of vibration and precise control of joint movement.

[0065] The technical solution provided in Embodiment 1 of the present invention determines the position error of the target joint in the previous sampling period based on the actual position value and the corresponding expected position value of the target joint in the previous sampling period, wherein the target joint is driven by a harmonic reducer; the vibration signal of the previous sampling period is extracted from the position error of the previous sampling period; based on the vibration signal and the expected position value of the previous sampling period, a parameter identification algorithm is used to identify the current parameter value of the parameter to be identified in the preset vibration model, thereby obtaining the identified preset vibration model, wherein the preset vibration model is a sine function relationship between the vibration signal and the expected position, the sine function relationship includes a preset number of wave generator cams and the parameter to be identified, the parameter to be identified including vibration amplitude and vibration phase; based on the identified preset vibration model and the current expected position value, the current expected vibration signal is calculated; based on the current expected position value, the current expected vibration signal, and a preset compensation coefficient, the current servo control command is determined to control the movement of the target joint in the current sampling period. By extracting vibration signals based on the position error of the previous sampling period, the vibration characteristics caused by the harmonic reducer can be identified in real time and accurately. Then, a parameter identification algorithm is used to dynamically update the parameters to be identified in the preset vibration model, ensuring that the preset vibration model accurately reflects the current vibration situation. Based on the identified preset vibration model and the current desired position value, the current desired vibration signal is calculated, and combined with preset compensation coefficients, the current servo control command is generated, achieving fast and accurate vibration compensation. This effectively solves the problems of poor suppression effect and untimely response in existing harmonic reducer vibration suppression methods.

[0066] In some embodiments, extracting the vibration signal of the previous sampling period from the position error of the previous sampling period includes: determining the non-vibration error based on the position error of historical sampling periods using a preset filtering algorithm; and determining the vibration signal of the previous sampling period based on the difference between the position error of the previous sampling period and the non-vibration error.

[0067] In this embodiment, non-vibration error can be understood as the position error component caused by factors other than harmonic reducer resonance. The preset filtering algorithm can be understood as a pre-set algorithm used to determine the non-vibration error. This preset filtering algorithm may include a peak filter or an adaptive filter, etc.

[0068] Specifically, based on the positional error of historical sampling periods, a preset filtering algorithm is used to determine non-vibration errors. Then, based on the following algorithm, the vibration signal of the previous sampling period is confirmed:

[0069]

[0070] in, This represents the vibration signal from the previous sampling period; This represents the non-vibration error of the previous sampling period; This indicates the position error of the previous sampling period.

[0071] The above technical solutions can effectively separate vibration signals from non-vibration errors, improve the accuracy of vibration signal extraction, and thus provide more accurate data support for subsequent vibration suppression and control, thereby enhancing the control performance and stability of the system.

[0072] In some embodiments, the preset filtering algorithm includes: determining non-vibration error based on the position error of historical sampling periods, the filter value of historical sampling periods, and preset filtering coefficients, wherein the preset filtering coefficients include a quality factor, a gain coefficient, and a discretization parameter, and the discretization parameter is determined based on the number of cams in the wave generator and the expected position value of the historical sampling periods.

[0073] In this embodiment, the preset filtering algorithm uses a peak filter. A peak filter is a special filter that can selectively enhance or attenuate signals within a specific frequency range. Its core function is to extract or suppress specific frequency components related to the vibration characteristics of the harmonic reducer through precisely designed frequency response characteristics, thus providing a clean data foundation for subsequent vibration signal extraction.

[0074] The principle of peak filters in digital signal processing:

[0075] The transfer function of a peak filter can typically be expressed as:

[0076]

[0077] in, Represents a complex frequency variable; , Indicates the center frequency of the filter; The quality factor determines the bandwidth and selectivity of the filter. This represents the gain coefficient, which is typically used to adjust the damping characteristics of a filter.

[0078] To implement a peak filter in digital signal processing, it needs to be discretized. The discretized filter can be represented as:

[0079]

[0080] in, This represents the output after the nth filtering. This represents the input signal sampled for the nth time. , and The coefficients represent the input signal; and The feedback coefficients represent the output signal; the specific expressions for each coefficient are as follows:

[0081]

[0082]

[0083]

[0084]

[0085]

[0086] in, , This indicates the sampling rate.

[0087] Extracting non-vibration errors using a peak filter:

[0088]

[0089] in, This represents the non-vibration error in the nth sampling period; Indicates the first Position error per sampling period; Indicates the first Position error per sampling period; Indicates the first Position error per sampling period; Indicates the first Non-vibration error per sampling period; Indicates the first Non-vibration error per sampling period; Indicates the quality factor; This represents the gain coefficient. , , , and The specific expression is the same as above, and will not be repeated here.

[0090] It is worth noting that, , .

[0091] in, Indicates the number of cams in the wave generator; This represents the expected position value in the nth sampling period; Indicates the first The expected location value for each sampling period.

[0092] By using a peak filter, specific frequency components related to the vibration of the harmonic reducer can be accurately separated, effectively extracting the vibration signal and providing accurate data for subsequent vibration suppression. At the same time, the discretization of the peak filter ensures real-time performance and optimizes the dynamic response.

[0093] In some embodiments, the parameter identification algorithm is the recursive least squares method.

[0094] In this embodiment, the parameter identification algorithm employs the recursive least squares method. The recursive least squares method is an online parameter estimation algorithm used for real-time parameter estimation of dynamic systems. It continuously updates parameter estimates using new observation data, eliminating the need to store all historical data, thus improving computational efficiency and real-time performance.

[0095] First, the preset vibration model is linearized: the preset vibration model can be represented as the inner product of a first vector and a second vector. The first vector consists of parameters to be identified, including vibration amplitude and vibration phase; the second vector consists of the number of wave generator cams and the current desired position value, as shown below:

[0096]

[0097] in, Indicates the desired position. Denotes the first vector. , Represents the second vector. .

[0098] Therefore, the update process using the recursive least squares method is as follows:

[0099] 1. Calculate the gain matrix :

[0100]

[0101] in, express The covariance matrix corresponding to the sampling period; This represents the forgetting factor (0 < λ <= 1), used to adjust the weights of historical data. Indicates the first The input variable for each sampling period, in this embodiment, is specifically in the form of: . Indicates the first The input variable for each sampling period, in this embodiment, is specifically in the form of: .

[0102] 2. Update parameter estimates :

[0103]

[0104] in, This represents the estimated parameter vector. In this embodiment, the specific form of the parameter vector is: ; Indicates the vibration signal at the 1st The sampled values ​​for each sampling period.

[0105] 3. Update the covariance matrix :

[0106]

[0107] in, Indicates the first The covariance matrix corresponding to each sampling period; I represents the identity matrix.

[0108] The recursive least squares method can update parameter estimates in real time, adapt to dynamically changing systems, and effectively improve computational efficiency.

[0109] In some embodiments, determining the current servo control command based on the current desired position value, the current desired vibration signal, and a preset compensation coefficient includes: determining the current vibration compensation value based on the product of the current desired vibration signal and the preset compensation coefficient; and determining the current servo control command based on the difference between the current desired position value and the current vibration compensation value.

[0110] Specifically, the product of the current desired vibration signal and the preset compensation coefficient is determined as the current vibration compensation value. Then, the difference between the current desired position value and the current vibration compensation value is determined as the current servo control command. This method allows for real-time adjustment of the servo control command, effectively suppressing vibration and improving the accuracy and stability of joint movements.

[0111] In some embodiments, determining the position error of the target joint in the previous sampling period based on the actual position value and the corresponding expected position value of the target joint in the previous sampling period includes: determining the position error of the target joint in the previous sampling period based on the difference between the actual position value and the expected position value of the target joint in the previous sampling period.

[0112] Specifically, the difference between the actual position value and the expected position value of the target joint in the previous sampling period is determined as the position error of the target joint in the previous sampling period. This method effectively improves the efficiency of position error determination.

[0113] Example 2

[0114] Figure 2 This is a schematic diagram of the structure of a harmonic reducer vibration suppression device provided in Embodiment 2 of the present invention. Figure 2 As shown, the device includes:

[0115] Error determination module 21 is used to determine the position error of the target joint in the previous sampling period based on the actual position value and the corresponding expected position value of the target joint in the previous sampling period, wherein the target joint is driven by a harmonic reducer;

[0116] The previous signal extraction module 22 is used to extract the vibration signal of the previous sampling period from the position error of the previous sampling period;

[0117] The model identification module 23 is used to identify the current parameter value of the parameter to be identified in the preset vibration model based on the vibration signal of the previous sampling period and the expected position value of the previous sampling period, using a parameter identification algorithm, so as to obtain the identified preset vibration model. The preset vibration model is a sinusoidal function relationship between the vibration signal and the expected position. The sinusoidal function relationship includes the preset number of wave generator cams and the parameter to be identified. The parameter to be identified includes the vibration amplitude and the vibration phase.

[0118] The current signal calculation module 24 is used to calculate the current desired vibration signal based on the identified preset vibration model and the current desired position value;

[0119] The instruction determination module 25 is used to determine the current servo control instruction based on the current desired position value, the current desired vibration signal and the preset compensation coefficient, so as to control the movement of the target joint in the current sampling period.

[0120] The technical solution provided in Embodiment 2 of this invention extracts vibration signals based on the position error of the previous sampling period, enabling real-time and accurate identification of vibration characteristics caused by the harmonic reducer. Furthermore, a parameter identification algorithm is used to dynamically update the parameters to be identified in the preset vibration model, ensuring the model accurately reflects the current vibration situation. Based on the identified preset vibration model and the current desired position value, the desired vibration signal is calculated, and combined with preset compensation coefficients to generate the current servo control command, achieving rapid and accurate vibration compensation. This effectively solves the problems of poor suppression effect and untimely response in existing harmonic reducer vibration suppression methods.

[0121] Optionally, the previous signal extraction module 22 includes:

[0122] The error determination unit is used to determine the non-vibration error based on the position error of the historical sampling period and using a preset filtering algorithm.

[0123] The previous signal determination unit is used to determine the vibration signal of the previous sampling period based on the difference between the position error of the previous sampling period and the non-vibration error.

[0124] Optionally, the preset filtering algorithm includes:

[0125] The non-vibration error is determined based on the position error of the historical sampling period, the filter value of the historical sampling period, and the preset filter coefficient. The preset filter coefficient includes a quality factor, a gain coefficient, and a discretization parameter. The discretization parameter is determined based on the number of cams in the wave generator and the expected position value of the historical sampling period.

[0126] Optionally, the parameter identification algorithm is the recursive least squares method.

[0127] Optionally, the instruction determination module 25 includes:

[0128] The compensation value determination unit is used to determine the current vibration compensation value based on the product of the current expected vibration signal and the preset compensation coefficient.

[0129] The instruction determination unit is used to determine the current servo control instruction based on the difference between the current desired position value and the current vibration compensation value.

[0130] Optionally, the error determination module 21 is specifically used to determine the position error of the target joint in the previous sampling period based on the difference between the actual position value and the expected position value of the target joint in the previous sampling period.

[0131] The harmonic reducer vibration suppression device provided in the embodiments of the present invention can execute the harmonic reducer vibration suppression method provided in any embodiment of the present invention, and has the corresponding functional modules and beneficial effects of the method.

[0132] Example 3

[0133] Figure 3This is a schematic diagram of an electronic device according to Embodiment 3 of the present invention. This electronic device is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device can also represent various forms of mobile devices, such as personal digital processors, cellular phones, smartphones, wearable devices (such as helmets, glasses, watches, etc.), and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely illustrative and are not intended to limit the implementation of the invention described and / or claimed herein.

[0134] like Figure 3 As shown, the electronic device 10 includes at least one processor 11 and a memory, such as a read-only memory (ROM) 12 or a random access memory (RAM) 13, communicatively connected to the at least one processor 11. The memory stores computer programs executable by the at least one processor. The processor 11 can perform various appropriate actions and processes based on the computer program stored in the ROM 12 or loaded into the RAM 13 from storage unit 18. The RAM 13 can also store various programs and data required for the operation of the electronic device 10. The processor 11, ROM 12, and RAM 13 are interconnected via a bus 14. An input / output (I / O) interface 15 is also connected to the bus 14.

[0135] Multiple components in electronic device 10 are connected to I / O interface 15, including: input unit 16, such as keyboard, mouse, etc.; output unit 17, such as various types of displays, speakers, etc.; storage unit 18, such as disk, optical disk, etc.; and communication unit 19, such as network card, modem, wireless transceiver, etc. Communication unit 19 allows electronic device 10 to exchange information / data with other devices through computer networks such as the Internet and / or various telecommunications networks.

[0136] Processor 11 can be a variety of general-purpose and / or special-purpose processing components with processing and computing capabilities. Some examples of processor 11 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various special-purpose artificial intelligence (AI) computing chips, various processors running machine learning model algorithms, a digital signal processor (DSP), and any suitable processor, controller, microcontroller, etc. Processor 11 performs the various methods and processes described above, such as the harmonic reducer vibration suppression method.

[0137] In some embodiments, the harmonic reducer vibration suppression method may be implemented as a computer program tangibly contained in a computer-readable storage medium, such as storage unit 18. In some embodiments, part or all of the computer program may be loaded and / or installed on electronic device 10 via ROM 12 and / or communication unit 19. When the computer program is loaded into RAM 13 and executed by processor 11, one or more steps of the harmonic reducer vibration suppression method described above may be performed. Alternatively, in other embodiments, processor 11 may be configured to perform the harmonic reducer vibration suppression method by any other suitable means (e.g., by means of firmware).

[0138] Various embodiments of the systems and techniques described above herein can be implemented in digital electronic circuit systems, integrated circuit systems, field-programmable gate arrays (FPGAs), application-specific integrated circuits (ASICs), application-specific standard products (ASSPs), systems-on-a-chip (SoCs), payload-programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various embodiments may include implementations in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which may be a dedicated or general-purpose programmable processor, capable of receiving data and instructions from a storage system, at least one input device, and at least one output device, and transmitting data and instructions to the storage system, the at least one input device, and the at least one output device.

[0139] Computer programs used to implement the methods of the present invention may be written in any combination of one or more programming languages. These computer programs may be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing device, such that when executed by the processor, the computer programs cause the functions / operations specified in the flowcharts and / or block diagrams to be performed. The computer programs may be executed entirely on a machine, partially on a machine, or as a standalone software package, partially on a machine and partially on a remote machine, or entirely on a remote machine or server.

[0140] In the context of this invention, a computer-readable storage medium can be a tangible medium that may contain or store a computer program for use by or in conjunction with an instruction execution system, apparatus, or device. A computer-readable storage medium may include, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, apparatus, or devices, or any suitable combination thereof. Alternatively, a computer-readable storage medium may be a machine-readable signal medium. More specific examples of machine-readable storage media include electrical connections based on one or more wires, portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fibers, portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination thereof.

[0141] To provide interaction with a user, the systems and techniques described herein can be implemented on an electronic device having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user; and a keyboard and pointing device (e.g., a mouse or trackball) through which the user provides input to the electronic device. Other types of devices can also be used to provide interaction with the user; 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 sound input, voice input, or tactile input).

[0142] The systems and technologies described herein can be implemented in computing systems that include backend components (e.g., as data servers), or middleware components (e.g., application servers), or frontend components (e.g., user computers with graphical user interfaces or web browsers through which users can interact with implementations of the systems and technologies described herein), or any combination of such backend, middleware, or frontend components. The components of the system can be interconnected via digital data communication of any form or medium (e.g., communication networks). Examples of communication networks include local area networks (LANs), wide area networks (WANs), blockchain networks, and the Internet.

[0143] A computing system can include clients and servers. Clients and servers are generally located far apart and typically interact through communication networks. The client-server relationship is created by computer programs running on the respective computers and having a client-server relationship with each other. The server can be a cloud server, also known as a cloud computing server or cloud host, which is a hosting product within the cloud computing service system to address the shortcomings of traditional physical hosts and VPS services, such as high management difficulty and weak business scalability.

[0144] It should be understood that the various forms of processes shown above can be used, with steps reordered, added, or deleted. For example, the steps described in this invention can be executed in parallel, sequentially, or in different orders, as long as the desired result of the technical solution of this invention can be achieved, and this is not limited herein.

[0145] The specific embodiments described above do not constitute a limitation on the scope of protection of this invention. Those skilled in the art should understand that various modifications, combinations, sub-combinations, and substitutions can be made according to design requirements and other factors. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of this invention should be included within the scope of protection of this invention.

[0146] This invention also provides a computer program product, including a computer program and / or instructions, which, when executed by a processor, implements the harmonic reducer vibration suppression method provided in any embodiment of this application.

[0147] In implementing the computer program product, computer program code for performing the operations of this invention can be written in one or more programming languages ​​or a combination thereof. Programming languages ​​include object-oriented programming languages ​​such as Java, Smalltalk, and C++, as well as conventional procedural programming languages ​​such as C or similar languages. The program code can be executed entirely on the user's computer, partially on the user's computer, as a standalone software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In cases involving remote computers, the remote computer can be connected to the user's computer via any type of network—including a local area network (LAN) or a wide area network (WAN)—or can be connected to an external computer (e.g., via the Internet using an Internet service provider).

[0148] Note that the above description is merely a preferred embodiment of the present invention and the technical principles employed. Those skilled in the art will understand that the present invention is not limited to the specific embodiments described herein, and various obvious changes, readjustments, and substitutions can be made without departing from the scope of protection of the present invention. Therefore, although the present invention has been described in detail through the above embodiments, the present invention is not limited to the above embodiments, and may include many other equivalent embodiments without departing from the concept of the present invention, the scope of which is determined by the scope of the appended claims.

Claims

1. A harmonic reducer vibration suppression method characterized by comprising: include: Based on the actual position value and the corresponding expected position value of the target joint in the previous sampling period, the position error of the target joint in the previous sampling period is determined, wherein the target joint is driven by a harmonic reducer; The vibration signal of the previous sampling period is extracted from the position error of the previous sampling period; Based on the vibration signal of the previous sampling period and the expected position value of the previous sampling period, the current parameter value of the parameter to be identified in the preset vibration model is identified using a parameter identification algorithm, thereby obtaining the identified preset vibration model. The preset vibration model is a sinusoidal function relationship between the vibration signal and the expected position. The sinusoidal function relationship includes the preset number of wave generator cams and the parameter to be identified. The parameter to be identified includes the vibration amplitude and the vibration phase. Based on the identified preset vibration model and the current desired position value, the current desired vibration signal is calculated; Based on the current desired position value, the current desired vibration signal, and the preset compensation coefficient, the current servo control command is determined to control the movement of the target joint in the current sampling period; The step of extracting the vibration signal of the previous sampling period from the position error of the previous sampling period includes: Based on the position error of historical sampling periods, a preset filtering algorithm is used to determine the non-vibration error; Based on the difference between the position error of the previous sampling period and the non-vibration error, the vibration signal of the previous sampling period is determined. The preset filtering algorithm includes: The non-vibration error is determined based on the position error of the historical sampling period, the filter value of the historical sampling period, and the preset filter coefficient. The preset filter coefficient includes a quality factor, a gain coefficient, and a discretization parameter. The discretization parameter is determined based on the number of cams in the wave generator and the expected position value of the historical sampling period.

2. The method of claim 1, wherein, The parameter identification algorithm is the recursive least squares method.

3. The method according to claim 1, characterized in that, The determination of the current servo control command based on the current desired position value, the current desired vibration signal, and the preset compensation coefficient includes: The current vibration compensation value is determined based on the product of the current expected vibration signal and the preset compensation coefficient. The current servo control command is determined based on the difference between the current desired position value and the current vibration compensation value.

4. The method according to claim 1, characterized in that, The step of determining the position error of the target joint in the previous sampling period based on the actual position value and the corresponding expected position value of the target joint in the previous sampling period includes: The position error of the target joint in the previous sampling period is determined based on the difference between the actual position value and the expected position value of the target joint in the previous sampling period.

5. A vibration suppression device for a harmonic reducer, characterized in that, include: An error determination module is used to determine the position error of the target joint in the previous sampling period based on the actual position value and the corresponding expected position value of the target joint in the previous sampling period, wherein the target joint is driven by a harmonic reducer; The previous signal extraction module is used to extract the vibration signal of the previous sampling period from the position error of the previous sampling period; The model identification module is used to identify the current parameter values ​​of the parameters to be identified in the preset vibration model based on the vibration signal and the expected position value of the previous sampling period using a parameter identification algorithm, so as to obtain the identified preset vibration model. The preset vibration model is a sinusoidal function relationship between the vibration signal and the expected position. The sinusoidal function relationship includes the preset number of wave generator cams and the parameters to be identified. The parameters to be identified include the vibration amplitude and the vibration phase. The current signal calculation module is used to calculate the current desired vibration signal based on the identified preset vibration model and the current desired position value; The instruction determination module is used to determine the current servo control instruction based on the current desired position value, the current desired vibration signal, and the preset compensation coefficient, so as to control the movement of the target joint in the current sampling period; The aforementioned signal extraction module includes: The error determination unit is used to determine the non-vibration error based on the position error of the historical sampling period and using a preset filtering algorithm. The previous signal determination unit is used to determine the vibration signal of the previous sampling period based on the difference between the position error of the previous sampling period and the non-vibration error. The preset filtering algorithm includes: The non-vibration error is determined based on the position error of the historical sampling period, the filter value of the historical sampling period, and the preset filter coefficient. The preset filter coefficient includes a quality factor, a gain coefficient, and a discretization parameter. The discretization parameter is determined based on the number of cams in the wave generator and the expected position value of the historical sampling period.

6. An electronic device, characterized in that, The electronic device includes: At least one processor; and A memory communicatively connected to the at least one processor; wherein, The memory stores a computer program that can be executed by the at least one processor, the computer program being executed by the at least one processor to enable the at least one processor to perform the harmonic reducer vibration suppression method as described in any one of claims 1-4.

7. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer instructions that cause a processor to execute and implement the harmonic reducer vibration suppression method as described in any one of claims 1-4.

8. A computer program product, characterized in that, The computer program product includes a computer program that, when executed by a processor, implements the harmonic reducer vibration suppression method as described in any one of claims 1-4.

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