A method and device for identifying model parameters of a hydraulic system of construction machinery and an excavator

Abstract

The present application discloses a method and apparatus for identifying model parameters of a hydraulic system and an excavator. Among them, the method for identifying model parameters of a construction machinery hydraulic system includes: constructing a model structure of the hydraulic system according to historical data of the construction machinery and hydraulic structure characteristics; wherein, the model structure represents the corresponding relationship between the pilot pressure of the hydraulic system and the angular velocity of the working device of the construction machinery; and performing parameter identification according to the historical data and the model structure. The present application can solve the problem of low accuracy of the existing hydraulic system model.

Description

Technical Field

[0001] The present application relates to the technical field of construction machinery, and particularly to a method and device for identifying model parameters of a hydraulic system of construction machinery and an excavator. Background Art

[0002] The global construction machinery industry is facing digital transformation, and the demands for unmanned and intelligent operation are becoming increasingly urgent. Model predictive control technology designs future control variables based on the current state of the system and is applicable to intelligent control scenarios, and its implementation requires a mathematical model of the system. However, the hydraulic systems of some construction machinery are complex nonlinear systems with multiple couplings, which makes it difficult to establish their mechanism models. Therefore, the existing mathematical models are difficult to establish and have low accuracy, which is not conducive to the control machine design of some construction machinery, resulting in difficulty in realizing intelligent control for some construction machinery. Summary of the Invention

[0003] To solve the above technical problems, the present application is proposed. Embodiments of the present application provide a method and device for identifying model parameters of a hydraulic system of construction machinery and an excavator, which can solve the problem of low accuracy of the existing hydraulic system model.

[0004] According to one aspect of the present application, there is provided a method for identifying model parameters of a hydraulic system of construction machinery, including: constructing a model structure of the hydraulic system according to historical data of the construction machinery and hydraulic structure characteristics; wherein, the model structure characterizes the corresponding relationship between the pilot pressure of the hydraulic system and the angular velocity of the working device of the construction machinery; and performing parameter identification according to the historical data and the model structure.

[0005] In one embodiment, constructing a model structure of the hydraulic system according to historical data of the construction machinery and hydraulic structure characteristics includes: constructing a Hammerstein model of the hydraulic system according to historical data of the construction machinery and hydraulic structure characteristics; wherein, the Hammerstein model includes a static nonlinear module and a dynamic linear module.

[0006] In one embodiment, the static nonlinear module includes a piecewise linear function, and the hydraulic structure characteristics include the spool opening characteristics of the construction machinery; wherein, constructing a Hammerstein model of the hydraulic system according to historical data of the construction machinery and hydraulic structure characteristics includes: determining the segmentation points of the piecewise linear function according to the spool opening characteristics.

[0007] In one embodiment, constructing the Hammerstein model of the hydraulic system further includes: adding equality constraints to the piecewise linear function to obtain a continuous piecewise linear function.

[0008] In one embodiment, the dynamic linear module includes a transfer function, and the historical data includes historical pilot pressure and corresponding historical angular velocity. Wherein, constructing a Hammerstein model of the hydraulic system according to the historical data of the construction machinery and the hydraulic structure characteristics includes: using the historical pilot pressure as input information and the historical angular velocity as output information to determine the structural parameters of the transfer function.

[0009] In one embodiment, constructing the Hammerstein model of the hydraulic system further includes: adding inequality constraints and nonlinear constraints to the transfer function to constrain the poles of the transfer function within a preset range.

[0010] In one embodiment, the static nonlinear module includes a piecewise linear function, the dynamic linear module includes a transfer function, the historical data includes historical pilot pressure and corresponding historical angular velocity, and performing parameter identification according to the historical data and the model structure includes: inputting the historical pilot pressure into the piecewise linear function to solve for an intermediate quantity; inputting the intermediate quantity and the historical angular velocity into the transfer function to obtain an output result; the output result includes parameters to be identified.

[0011] In one embodiment, performing parameter identification according to the historical data and the model structure further includes: solving the parameters to be identified using the least squares method to obtain target model parameters.

[0012] In one embodiment, the static nonlinear module includes a dead zone nonlinear function; wherein, constructing a Hammerstein model of the hydraulic system according to the historical data of the construction machinery and the hydraulic structure characteristics includes: calculating the break points and slopes at both ends of the dead zone nonlinear function to obtain the dead zone nonlinear function; wherein the slope of the middle section of the dead zone nonlinear function is 0.

[0013] In one embodiment, constructing the model structure of the hydraulic system according to the historical data of the construction machinery and the hydraulic structure characteristics includes: constructing a Hammerstein-Wiener model or a Wiener model of the hydraulic system according to the historical data of the construction machinery and the hydraulic structure characteristics; wherein the Hammerstein-Wiener model includes an input nonlinear module, a linear module, and an output nonlinear module, and the Wiener model includes a dynamic linear module and a static nonlinear module.

[0014] According to another aspect of the present application, there is provided a device for identifying model parameters of a construction machinery hydraulic system, including: a construction module, which constructs a model structure of the hydraulic system according to the historical data of the construction machinery and the hydraulic structure characteristics; wherein the model structure characterizes the corresponding relationship between the pilot pressure of the hydraulic system and the angular velocity of the working device of the construction machinery; an identification module, which is used to perform parameter identification according to the historical data and the model structure.

[0015] According to another aspect of the present application, an excavator is provided, including: a hydraulic system, the hydraulic system including a spool valve; wherein, the hydraulic system receives a pilot pressure to regulate the opening area of the spool valve; a working device, the working device being connected to the hydraulic system; a controller, the controller being connected to the hydraulic system and the working device, the controller being configured to execute the hydraulic system model parameter identification method according to any one of the above embodiments.

[0016] The method, device and excavator for identifying model parameters of a construction machinery hydraulic system provided by the present application collect historical pilot pressure and historical angular velocity of the hydraulic system of the construction machinery, construct a mathematical model based on the Hammerstein model framework, identify model parameters according to the measured data of the hydraulic system, and after obtaining the model parameters, optimize to make the model accuracy meet the requirements, which can be used for controller design. The construction machinery hydraulic system model provided by the present application not only directly obtains the mathematical model of the corresponding relationship between the pilot pressure and the angular velocity without secondary solution, but also adds constraints during the solution to ensure that the model parameters are within a reasonable range, making the model parameters controllable. It can not only improve the accuracy of the model, but also predict future control quantities, playing a role in intelligent control. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] By describing the embodiments of the present application in more detail in conjunction with the drawings, the above and other objects, features and advantages of the present application will become more obvious. The drawings are used to provide a further understanding of the embodiments of the present application, and constitute a part of the specification. Together with the embodiments of the present application, they are used to explain the present application and do not constitute a limitation to the present application. In the drawings, the same reference numerals generally represent the same components or steps.

[0018] Figure 1 is a schematic flow chart of a method for identifying model parameters of a construction machinery hydraulic system provided by an exemplary embodiment of the present application.

[0019] Figure 2 is a schematic diagram of the working principle of a Hammerstein model provided by an exemplary embodiment of the present application.

[0020] Figure 3 is a schematic diagram of the principle of a method for identifying model parameters of a construction machinery hydraulic system provided by an exemplary embodiment of the present application.

[0021] Figure 4 is a schematic diagram of the working principle of a Wiener model provided by an exemplary embodiment of the present application.

[0022] Figure 5 is a schematic diagram of the working principle of a Hammerstein-Wiener model provided by an exemplary embodiment of the present application.

[0023] Figure 6 It is a schematic structural diagram of a method for identifying model parameters of a construction machinery hydraulic system provided by an exemplary embodiment of the present application.

[0024] Figure 7 It is a schematic structural diagram of a device for identifying model parameters of a construction machinery hydraulic system provided by an exemplary embodiment of the present application.

[0025] Figure 8 It is a structural diagram of an electronic device provided by an exemplary embodiment of the present application. Detailed implementation manners

[0026] Next, exemplary embodiments according to the present application will be described in detail with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of the present application, rather than all the embodiments of the present application. It should be understood that the present application is not limited by the exemplary embodiments described herein.

[0027] Overview of the application

[0028] Traditional excavator control mainly relies on PID, and there are two main problems with PID control technology. On the one hand, to achieve the desired control effect, a suitable set of PID parameters is required, and the parameter adjustment process is time-consuming and laborious and depends on the technician's own experience. On the other hand, PID control only relies on the historical information of the system and cannot predict future control quantities, and its control accuracy can no longer meet the requirements of excavator intelligent control. Model predictive control technology designs future control quantities based on the current state of the system and is suitable for intelligent control scenarios. Its implementation requires a mathematical model of the system, and the hydraulic system of an excavator is a multi-coupled complex nonlinear system, which makes it difficult to establish its mechanism model.

[0029] Therefore, the present application proposes a method for identifying model parameters of a construction machinery hydraulic system, which can adopt a data-driven method to construct a mathematical model of the excavator hydraulic system based on the Hammerstein model framework. For example, a suitable function is adopted according to the device characteristics of the excavator, and the function is used to form the framework of the mathematical model to obtain the parameters to be identified. The historical data of the excavator (such as the pilot pressure output by the controller model in the excavator system and the historical angular velocity signal obtained by the sensor) is collected, and the parameters to be identified can be solved according to the least square cost function, so as to construct a complete mathematical model.

[0030] After the mathematical model of the hydraulic system is constructed, the pilot pressure output by the controller model in the excavator system can be received, and a new angular velocity value can be predicted and then sent to the kinematic model as input. In model predictive control, after determining the working trajectory of the excavator, the input value can be deduced inversely according to the output values of each model, and then the excavator can be controlled to perform operations according to the specified actions.

[0031] Exemplary excavator

[0032] This application provides an excavator, including: a hydraulic system, the hydraulic system includes a spool valve; wherein, the hydraulic system receives a pilot pressure to regulate the opening area of the spool valve; a working device, the working device is connected to the hydraulic system; a controller, the controller is connected to the hydraulic system and the working device, and the controller is used for the hydraulic system model parameter identification method provided by this application.

[0033] In the hydraulic system of the excavator, the pilot pressure pushes the spool valve to generate displacement and controls the opening area of the spool valve, and there is a piecewise linear relationship between the pilot pressure and the opening area of the spool valve. Therefore, according to the piecewise characteristics of the pilot pressure and the opening characteristics of the spool valve, the piecewise linear relationship between the pilot pressure and the opening area can be used to construct the function combination in the Hammerstein model, and the function combination can describe the relationship between the pilot pressure and the angular velocity of the working device.

[0034] The Hammerstein model is composed of a static nonlinear module and a dynamic linear module connected in series, which can handle nonlinear problems well and is suitable for modeling the hydraulic system. The model parameters in the Hammerstein model are identified by the least squares method. First, the input and output quantities and model parameters are sorted according to the model structure to obtain the least squares solution equation. By adding constraints to the solution equation, the continuity of the piecewise function at the break point, the convergence of the transfer function, and the controllability of the model parameters are ensured. Finally, the model parameters are identified by the least squares method to improve the model. The model is put into use in the hydraulic system. For example, by inputting the pilot pressure, the predicted angular velocity value can be obtained to indicate the excavator to work.

[0035] For the excavator provided by this application, by collecting the historical pilot pressure and historical angular velocity of the hydraulic system of the excavator, a mathematical model is constructed based on the Hammerstein model framework, the model parameters are identified according to the historical pilot pressure and historical angular velocity of the hydraulic system, and after obtaining the model parameters, the model accuracy is optimized to meet the requirements, and then it can be used for controller design. The excavator provided by this application not only directly obtains the mathematical model of the corresponding relationship between the pilot pressure and the angular velocity without secondary solution, but also adds constraints during the solution to ensure that the model parameters are within a reasonable range and the model parameters are controllable. This can not only improve the accuracy of the model, but also predict the future control quantity and play a role in intelligent control.

[0036] Exemplary method

[0037] Figure 1 It is a schematic flow chart of a method for identifying model parameters of a construction machinery hydraulic system provided by an exemplary embodiment of this application. As Figure 1 shown, the method for identifying model parameters of the construction machinery hydraulic system includes:

[0038] Step 100: Construct the model structure of the hydraulic system based on the historical data and hydraulic structure characteristics of the construction machinery.

[0039] Among them, the model structure characterizes the corresponding relationship between the pilot pressure of the hydraulic system and the angular velocity of the working device of the construction machinery.

[0040] Step 200: Perform parameter identification according to the historical data and the model structure.

[0041] This application can construct a model in a data-driven manner. For example, collect the input and output data of the construction machinery, identify the model parameters according to the measured data of the construction machinery, and optimize the model through an optimization algorithm to improve the model accuracy. That is to say, first determine the basic model as the Hammerstein model, and then determine the function modules used in the Hammerstein model according to the historical data and hydraulic structure characteristics. The function modules constitute the framework of the model, and the model parameters in this framework are unknown, that is, the parameters to be identified. After collecting the historical data, these unknown parameters can be solved according to the least squares cost function. After identifying the parameters, the construction machinery hydraulic system model is completed.

[0042] For example, in the hydraulic system of an excavator, the construction machinery hydraulic system model provided by this application receives the pilot pressure signal output by the controller model and the historical angular velocity signal obtained by the sensor, predicts a new angular velocity value, and then sends it to the kinematic model as an input. In model predictive control, after determining the operation trajectory of the excavator, the input value can be deduced inversely according to the output values of each model, and then the excavator can be controlled to operate according to the specified actions.

[0043] Therefore, the method for identifying the parameters of the construction machinery hydraulic system model provided by this application, by collecting the historical pilot pressure and historical angular velocity of the hydraulic system of the construction machinery, constructs a mathematical model based on the Hammerstein model framework, identifies the model parameters according to the measured data of the hydraulic system, and after obtaining the model parameters, makes the model accuracy meet the requirements through optimization, and can be used for controller design. The construction machinery hydraulic system model provided by this application not only directly obtains the mathematical model of the corresponding relationship between the pilot pressure and the angular velocity without secondary solution, but also adds constraints during the solution to ensure that the model parameters are within a reasonable range, making the model parameters controllable. It can not only improve the accuracy of the model, but also predict future control quantities, playing the role of intelligent control.

[0044] In one embodiment, the above step 100 may include: constructing a Hammerstein model of the hydraulic system according to the historical data and hydraulic structure characteristics of the construction machinery; among them, the Hammerstein model includes a static nonlinear module and a dynamic linear module.

[0045] This application can model a hydraulic system based on the Hammerstein model. The Hammerstein model consists of a static nonlinear module and a dynamic linear module connected in series, and can handle nonlinear problems well. The hydraulic system of construction machinery is usually a multi-coupled complex nonlinear system. Therefore, the Hammerstein model can well describe the relationship between the pilot pressure and the angular velocity of the working device. The mathematical model constructed based on the Hammerstein model can directly take the pilot pressure as the input and the angular velocity as the output, and obtain the input and output of the system at one time without secondary solution. And the data used therein are all measured data of the hydraulic system. Parameter identification is carried out according to the measured data of the hydraulic system, without manual parameter adjustment based on personal experience, reducing the dependence on the personal experience of technicians.

[0046] In one embodiment, the static nonlinear module includes a piecewise linear function, and the hydraulic structure characteristics include the spool opening characteristics of construction machinery; wherein, the above step 100 may include: determining the break points of the piecewise linear function according to the spool opening characteristics.

[0047] For example, in the hydraulic system of an excavator, the pilot pressure pushes the spool to generate displacement, thereby controlling its opening, and there is a piecewise linear relationship between the pilot pressure and the spool opening area. Therefore, the static nonlinear module of the Hammerstein model can select a piecewise linear function. The break points of the piecewise linear function can be determined according to the spool opening characteristic curve. The piecewise characteristics of the pilot pressure are described by the piecewise linear function, and the break points of the piecewise linear function are determined according to the spool opening characteristics of the excavator.

[0048] In one embodiment, the above step 100 may further include: adding an equality constraint to the piecewise linear function to obtain a continuous piecewise linear function.

[0049] An equality constraint can be added to the piecewise linear function to ensure its continuity at the break points, which is convenient for controller design. Therefore, adding an equality constraint can ensure the continuity of the piecewise linear function. For example, for the model parameters θ = [θ1, θ2,..., θ g , the form of adding an equality constraint can be: A eq1 θ1 + A eq2 θ2 +... + A eqg θ g = b eq , where A eqi and b eq are constraint parameters. For multiple equality constraint conditions, let A eq = [A eq1 , A eq2 ,..., A eqg , and the matrix form A eq θ = b eq can be constructed.

[0050] In one embodiment, the dynamic linear module includes a transfer function, and the historical data includes historical pilot pressure and corresponding historical angular velocity. Wherein, step 100 may include: determining the structural parameters of the transfer function with the historical pilot pressure as the input information and the historical angular velocity as the output information.

[0051] For example, there are complex coupling relationships among the pilot pressures corresponding to the working devices of an excavator. Incorporating historical data into the model can improve the model accuracy. Therefore, the dynamic linear module selects a transfer function model that includes both input and output information. Wherein, the historical data includes historical pilot pressure and corresponding historical angular velocity. The transfer function integrates the historical information of the pilot pressure and the angular velocity, thereby constructing the equation of the transfer function, and the structural parameters of the transfer function can be obtained therefrom. The structural parameters of the transfer function are parameters to be identified. After obtaining the parameters to be identified, parameter identification can be performed through optimization algorithms and cost functions, etc.

[0052] In one embodiment, step 100 may further include: adding inequality constraints and nonlinear constraints to the transfer function, and constraining the poles of the transfer function within a preset range.

[0053] To ensure the stability of the controller, the transfer function needs to converge. Therefore, it is necessary to constrain the poles of the transfer function. Corresponding nonlinear constraint conditions can be designed for the transfer functions in different stages so that the poles of the transfer function are all within the preset range. Wherein, the preset range can be the unit circle. The order of the transfer function is determined by optimizing the search algorithm. At the same time, inequality constraints and nonlinear constraints are used to constrain the poles of the transfer function within the unit circle to ensure the convergence of the construction machinery hydraulic system model and make the parameters of the construction machinery hydraulic system controllable.

[0054] The form of adding inequality constraints to the model parameters is: A1θ1 + A2θ2 +... + A g θ g ≤b, where A i and b are constraint parameters. Similarly, for multiple inequality constraint conditions, let A = [A1, A2,..., A g , and its matrix form is Aθ ≤ b. Adding nonlinear constraints to the model parameters θ requires constructing a function c of θ, and the constraint equation form is c(θ) < 0.

[0055] For example, for a second-order transfer function, to ensure its convergence, it is necessary to constrain the poles within the unit circle. The characteristic equation of the denominator term of the transfer function is:

[0056] D(z) = a0 + a1z + a2z 2 = 0, where a are the equation coefficients and z is the variable;

[0057] Its poles are:

[0058] The constraint equations are as follows:

[0059] To determine the convergence of the high-order transfer function, the Jury criterion is needed. The Jury criterion can be converted into a non-linear constraint equation to constrain θ. The characteristic equation of the denominator term of the high-order transfer function is:

[0060] D(z) = a0 + a1z +... + a N z N = 0

[0061] The criterion coefficients can be calculated from the coefficients of the characteristic equation:

[0062] where b k , c k , d k represent the criterion coefficients;

[0063] The constraint equations obtained from the Jury criterion are:

[0064] D(1) > 0

[0065] (-1) N D(-1) > 0

[0066] |a0| < |a N |

[0067] |b0| > |b N-1 |

[0068] |c0| > |c N-2 |

[0069] |d0| > |d N-3 |

[0070] In one embodiment, the static non-linear module includes a piecewise linear function, the dynamic linear module includes a transfer function, and the historical data includes historical pilot pressure and corresponding historical angular velocity. The above step 200 may include: inputting the historical pilot pressure into the piecewise linear function to obtain an intermediate quantity; inputting the intermediate quantity and the historical angular velocity into the transfer function to obtain an output result; the output result includes the parameter to be identified.

[0071] The Hammerstein model is composed of a static non-linear module and a dynamic linear module in series. Therefore, Figure 2 is a schematic diagram of the working principle of the Hammerstein model provided by an exemplary embodiment of the present application. The working structure of the Hammerstein model is as Figure 2As shown: The input quantity u is input to the static non - linear module 4, the intermediate quantity w is obtained through the conversion of the static non - linear module 4, then the intermediate quantity w is input to the dynamic linear module 5, and finally the output quantity y is obtained. When performing parameter identification, the input quantity u can be multiple historical pilot pressures, and the output quantity y can be multiple historical angular velocities corresponding to the historical pilot pressures.

[0072] Figure 3 It is a schematic diagram of the principle of the method for identifying the parameters of the construction machinery hydraulic system model provided by an exemplary embodiment of the present application. When the Hammerstein model is constructed and applied to the parameter identification of the hydraulic system model, its specific working process is as Figure 3 shown: The historical pilot pressure is used as the input quantity and input to the piece - wise linear function for solution. Among them, the break points of the piece - wise linear function are determined according to the spool opening characteristics, so as to add equality constraints to ensure the continuity of the piece - wise linear function. The intermediate quantity is obtained through the piece - wise function, and then the intermediate quantity and the historical angular velocity are input to the transfer function. The order of the transfer function is determined by optimizing according to the search algorithm, and the structure of the transfer function is constructed. The transfer function integrates the intermediate quantity and the historical angular velocity, and adds non - linear constraints and inequality constraints to constrain the poles of the transfer function within the preset range. Finally, the output result, that is, the parameter equation, is obtained, and the parameter equation contains the parameters to be identified.

[0073] For example, the input of the piece - wise function is the pilot pressure u, and the output is the intermediate quantity w, and its form is:

[0074]

[0075] Among them, where k i , c i , i = 1, 2, … p + 1 are the parameters of the piece - wise equation, and D = [d1, d2, …, d p are the break points.

[0076] The transfer function integrates the historical information of the pilot pressure and the angular velocity, and is expressed as:

[0077]

[0078] Among them, W represents the Laplace transform of the intermediate quantity w, and Y represents the Laplace transform of the output quantity (angular velocity) y.

[0079] Therefore, combining the piece - wise function and the transfer function, the parameter to be identified θ is:

[0080] θ = [k1, c1, …, k p+1 , c p+1 , b0, …, b m , a0, …, a n

[0081] ​The parameter θ to be identified becomes the model parameter after identification and is applied in the model.

[0082] In one embodiment, step 200 above may further include: solving the parameter to be identified by the least square method to obtain the target model parameter.

[0083] Through the above steps, after obtaining the parameter to be identified by combining the piecewise function and the transfer function, the parameter to be identified is identified by the least square method. First, the historical data (such as the historical input pilot pressure and the historical output angular velocity) and the parameter to be identified are sorted according to the model structure. For example, the collected historical pilot pressure and other data are a time series with a total of 1000 values, and these 1000 values will be used for the least square solution at the same time. The least square solution equation is obtained by combining the cost function.

[0084] The cost function is used to measure the difference between the predicted value of the model and the true value y. The smaller the cost function, the higher the accuracy of the model. The predicted value represents the predicted value output by the model according to the input quantity. The true value y represents the data obtained by actually detecting the construction machinery. One input quantity can correspond to a predicted value and a true value at the same time. By comparing the difference between the predicted value and the true value, the accuracy of the model can be determined. The common form of the cost function is the mean square error:

[0085]

[0086] When solving the parameter to be identified by the least square method, first construct the matrix expression of the predicted value where X is the input matrix, θ is the parameter to be identified, is the predicted value matrix, then the cost function can be expressed as:

[0087]

[0088] where Y represents the true value matrix and T represents the transpose.

[0089] Let θ be the one that makes the cost function minimum during the solution. Let the derivative of J(θ) with respect to θ be 0, that is The least square solution equation can be obtained as:

[0090] θ * =(X T X) -1 X T Y

[0091] where θ * represents the θ that makes the cost function minimum, that is, the target model parameter.

[0092] In one embodiment, the static non-linear module includes a dead zone non-linear function; wherein, step 100 may include: calculating the break points and the slopes at both ends of the dead zone non-linear function to obtain the dead zone non-linear function; wherein, the slope of the middle section of the dead zone non-linear function is 0.

[0093] The piecewise linear function in the Hammerstein model can be replaced by a dead zone non-linear function. The slope of the middle section of the dead zone function is 0. The break points and the slopes at both ends of the dead zone non-linear function can be obtained through presetting or parameter identification calculation.

[0094] In one embodiment, step 100 may include: constructing a Hammerstein-Wiener model or a Wiener model of the hydraulic system according to the historical data of the construction machinery and the hydraulic structure characteristics; wherein, the Hammerstein-Wiener model includes an input non-linear module, a linear module, and an output non-linear module, and the Wiener model includes a dynamic linear module and a static non-linear module.

[0095] The Hammerstein model can be replaced by a Wiener model or a Hammerstein-Wiener model. Figure 4 FIG. is a schematic diagram of the working principle of the Wiener model provided by an exemplary embodiment of the present application. As Figure 4 shown, the Wiener model is formed by connecting a dynamic linear module 61 and a static non-linear module 62 in series. The input quantity u is input into the Wiener model. The input quantity u is converted into an intermediate quantity w through the dynamic linear module 61, and then the intermediate quantity w is input into the static non-linear module 62, and finally the model outputs the output quantity y. Among them, the input quantity u can be replaced by the pilot pressure, and the output quantity y can be replaced by the angular velocity.

[0096] Figure 5 FIG. is a schematic diagram of the working principle of the Hammerstein-Wiener model provided by an exemplary embodiment of the present application. As Figure 5 shown, the Hammerstein-Wiener model includes a non-linear module 71, a linear module 72, and an output non-linear module 73. The input quantity u is input into the input non-linear module 71 and converted into an intermediate quantity w through the input non-linear module 71. The intermediate quantity w is then input into the linear module 72 to obtain an intermediate quantity x. The intermediate quantity x is input into the output non-linear module 73, and finally the model outputs the output quantity y. Among them, the input quantity u can be replaced by the pilot pressure, and the output quantity y can be replaced by the angular velocity.

[0097] In one embodiment, a method of combining mechanism modeling and data-driven modeling can also be used to construct a model of the hydraulic system.

[0098] The above embodiments of the present application all propose data-driven modeling methods, but a combination of mechanism modeling and data-driven modeling can also be adopted. For example, the spool opening characteristics can be tested and calculated through experiments. There is an approximate linear relationship between the pressure in the hydraulic cylinder and the cylinder speed. Therefore, a mechanism model can be constructed for the relationships between the pilot pressure and the spool opening area, and between the cylinder pressure and the speed. For the hydraulic process with complex coupling relationships and difficult-to-measure intermediate quantities, a data-driven approach is used for modeling.

[0099] Figure 6 FIG. is a schematic structural diagram of a method for identifying model parameters of a construction machinery hydraulic system provided by an exemplary embodiment of the present application. The technical framework for identifying model parameters of the construction machinery hydraulic system proposed in the above embodiment is as Figure 6 shown. Among them, the input pilot pressure and historical angular velocity are input into a piecewise linear function. The piecewise linear function is used to describe the piecewise characteristics of the pilot pressure, and the break points of the piecewise linear function are determined according to the spool opening characteristics of the construction machinery. Equality constraints can be added to the piecewise linear function to ensure its continuity at the break points, which is convenient for controller design. An intermediate quantity is output from the piecewise linear function, and the intermediate quantity and the historical angular velocity are input into a transfer function. The transfer function integrates the historical information of the pilot pressure and the angular velocity, thereby constructing the equation of the transfer function, and the structural parameters of the transfer function can be obtained therefrom. Therefore, the transfer function outputs a parameter equation, and the parameter equation is optimized and solved by a cost function and the least squares method to obtain the target model parameters. The target model parameters and the model framework are combined to build a complete Hammerstein model. After the Hammerstein model is built, the input pilot pressure can be used to predict the angular velocity.

[0100] Exemplary device

[0101] Figure 7 FIG. is a schematic structural diagram of a device for identifying model parameters of a construction machinery hydraulic system provided by an exemplary embodiment of the present application. As Figure 7 shown, the device 8 for identifying model parameters of the construction machinery hydraulic system includes: a construction module 81, which constructs a model structure of the hydraulic system according to the historical data and hydraulic structure characteristics of the construction machinery; wherein, the model structure represents the corresponding relationship between the pilot pressure of the hydraulic system and the angular velocity of the working device of the construction machinery; an identification module 82, which is used to perform parameter identification according to the historical data and the model structure.

[0102] The device for identifying model parameters of a construction machinery hydraulic system provided by this application collects the historical pilot pressure and historical angular velocity of the hydraulic system of the construction machinery, constructs a mathematical model based on the Hammerstein model framework, identifies the model parameters according to the measured data of the hydraulic system, and after obtaining the model parameters, optimizes them to meet the requirements, and then it can be used for controller design. The construction machinery hydraulic system model provided by this application not only directly obtains the mathematical model of the corresponding relationship between the pilot pressure and the angular velocity without secondary solution, but also adds constraints during the solution process to ensure that the model parameters are within a reasonable range, making the model parameters controllable. It can not only improve the accuracy of the model, but also predict future control quantities, playing a role in intelligent control.

[0103] In one embodiment, the above-mentioned construction module 81 can be configured to: construct a Hammerstein model of the hydraulic system according to the historical data and hydraulic structure characteristics of the construction machinery; wherein, the Hammerstein model includes a static nonlinear module and a dynamic linear module.

[0104] In one embodiment, the above-mentioned construction module 81 can be configured to: determine the segmentation points of the piecewise linear function according to the spool opening characteristics.

[0105] In one embodiment, the above-mentioned construction module 81 can be configured to: add equality constraints to the piecewise linear function to obtain a continuous piecewise linear function.

[0106] In one embodiment, the above-mentioned construction module 81 can be configured to: use the historical pilot pressure as input information and the historical angular velocity as output information to determine the structural parameters of the transfer function.

[0107] In one embodiment, the above-mentioned construction module 81 can be configured to: add inequality constraints and nonlinear constraints to the transfer function to constrain the poles of the transfer function within a preset range.

[0108] In one embodiment, the above-mentioned identification module 82 can be configured to: input the historical pilot pressure into the piecewise linear function, solve to obtain an intermediate quantity; input the intermediate quantity and the historical angular velocity into the transfer function to obtain an output result; the output result includes the parameters to be identified.

[0109] In one embodiment, the above-mentioned identification module 82 can be configured to: solve the parameters to be identified by using the least squares method to obtain the target model parameters.

[0110] In one embodiment, the above-mentioned construction module 81 can be configured to: calculate the segmentation points and the slopes at both ends of the dead zone nonlinear function to obtain the dead zone nonlinear function; wherein, the slope of the middle section of the dead zone nonlinear function is 0.

[0111] In one embodiment, the above-mentioned building block 81 may be configured to: construct a Hammerstein-Wiener model or a Wiener model of the hydraulic system according to the historical data of the construction machinery and the hydraulic structure characteristics; wherein, the Hammerstein-Wiener model includes an input nonlinear module, a linear module, and an output nonlinear module, and the Wiener model includes a dynamic linear module and a static nonlinear module.

[0112] Exemplary electronic device

[0113] Next, refer to Figure 8 to describe the electronic device according to an embodiment of the present application. The electronic device may be any one or both of the first device and the second device, or a stand-alone device independent of them, and the stand-alone device may communicate with the first device and the second device to receive the input signals collected by them.

[0114] Figure 8 The block diagram of the electronic device according to an embodiment of the present application is illustrated.

[0115] As Figure 8 shown, the electronic device 10 includes one or more processors 11 and a memory 12.

[0116] The processor 11 may be a central processing unit (CPU) or other forms of processing units with data processing capabilities and / or instruction execution capabilities, and may control other components in the electronic device 10 to perform desired functions.

[0117] The memory 12 may include one or more computer program products, and the computer program products may include various forms of computer-readable storage media, such as volatile memory and / or non-volatile memory. The volatile memory may include, for example, random access memory (RAM) and / or cache memory, etc. The non-volatile memory may include, for example, read-only memory (ROM), hard disk, flash memory, etc. One or more computer program instructions may be stored on the computer-readable storage medium, and the processor 11 may run the program instructions to implement the method for identifying the parameters of the construction machinery hydraulic system model in various embodiments of the present application described above and / or other desired functions. Various contents such as input signals, signal components, and noise components may also be stored in the computer-readable storage medium.

[0118] In one example, the electronic device 10 may further include: an input device 13 and an output device 14, and these components are interconnected through a bus system and / or other forms of connection mechanisms (not shown).

[0119] When the electronic device is a stand-alone device, the input device 13 may be a communication network connector for receiving the input signals collected from the first device and the second device.

[0120] In addition, the input device 13 may further include, for example, a keyboard, a mouse, and the like.

[0121] The output device 14 can output various information to the outside, including the determined distance information, direction information, etc. The output device 14 may include, for example, a display, a speaker, a printer, and a communication network and its connected remote output devices, and the like.

[0122] Of course, for the sake of simplicity, Figure 8 only some of the components related to the present application in the electronic device 10 are shown, and components such as a bus, an input / output interface, and the like are omitted. In addition, according to specific application scenarios, the electronic device 10 may further include any other appropriate components.

[0123] The computer program product may be written in any combination of one or more programming languages for programming code to perform the operations of the embodiments of the present application. The programming languages include object-oriented programming languages such as Java, C++, etc., and also include conventional procedural programming languages such as the "C" language or similar programming languages. The programming code may be executed entirely on the user computing device, partially on the user device, executed as an independent software package, partially on the user computing device and partially on a remote computing device, or entirely on a remote computing device or server.

[0124] The computer-readable storage medium may employ any combination of one or more readable media. The readable media may be a readable signal medium or a readable storage medium. The readable storage medium may, for example, include but is not limited to an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination of the above. More specific examples (non-exhaustive list) of the readable storage medium include: an electrical connection having one or more wires, a portable disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above.

[0125] The above description has been given for purposes of illustration and description. In addition, this description is not intended to limit the embodiments of the present application to the forms disclosed herein. Although multiple example aspects and embodiments have been discussed above, those skilled in the art will recognize certain variations, modifications, changes, additions, and sub-combinations thereof.

Claims

1. A method for identifying model parameters of a hydraulic system of construction machinery, characterized in that, Including: Construct a model structure of the hydraulic system based on the historical data and hydraulic structure characteristics of the construction machinery; wherein, the model structure represents the corresponding relationship between the pilot pressure of the hydraulic system and the angular velocity of the working device of the construction machinery. Constructing a model structure of the hydraulic system based on the historical data and hydraulic structure characteristics of the construction machinery includes: Construct a Hammerstein model of the hydraulic system based on the historical data and hydraulic structure characteristics of the construction machinery; wherein, the Hammerstein model includes a static nonlinear module and a dynamic linear module. The dynamic linear module includes a transfer function, and the historical data includes historical pilot pressure and corresponding historical angular velocity. Wherein, constructing a Hammerstein model of the hydraulic system based on the historical data and hydraulic structure characteristics of the construction machinery includes: Taking the historical pilot pressure as input information and the historical angular velocity as output information to determine the structural parameters of the transfer function. Perform parameter identification according to the historical data and the model structure. The static nonlinear module includes a piecewise linear function. Performing parameter identification according to the historical data and the model structure includes: Input the historical pilot pressure into the piecewise linear function to solve and obtain an intermediate quantity. Input the intermediate quantity and the historical angular velocity into the transfer function to obtain an output result; the output result includes parameters to be identified.

2. The hydraulic system model parameter identification method according to claim 1, characterized in that The static nonlinear module includes a piecewise linear function, and the hydraulic structure characteristics include the spool opening characteristics of the construction machinery; wherein, constructing a Hammerstein model of the hydraulic system based on the historical data and hydraulic structure characteristics of the construction machinery includes: Determine the break points of the piecewise linear function according to the spool opening characteristics.

3. The hydraulic system model parameter identification method according to claim 2, characterized in that, Constructing the Hammerstein model of the hydraulic system further includes: Adding equality constraints to the piecewise linear function to obtain the continuous piecewise linear function.

4. The hydraulic system model parameter identification method according to claim 1, characterized in that, Constructing the Hammerstein model of the hydraulic system further includes: Adding inequality constraints and nonlinear constraints to the transfer function to constrain the poles of the transfer function within a preset range.

5. The hydraulic system model parameter identification method according to claim 1, characterized in that, Performing parameter identification according to the historical data and the model structure further includes: Solving the parameters to be identified by the least squares method to obtain the target model parameters.

6. The hydraulic system model parameter identification method according to claim 1, characterized in that The static nonlinear module includes a dead zone nonlinear function; wherein, constructing a Hammerstein model of the hydraulic system based on the historical data and hydraulic structure characteristics of the construction machinery includes: Calculate the break points and the slopes at both ends of the dead zone nonlinear function to obtain the dead zone nonlinear function; wherein, the slope of the middle section of the dead zone nonlinear function is 0.

7. The method for identifying the parameters of the hydraulic system model according to claim 1, characterized in that Constructing a model structure of the hydraulic system based on the historical data and hydraulic structure characteristics of the construction machinery includes: Construct a Hammerstein-Wiener model or a Wiener model of the hydraulic system based on the historical data and hydraulic structure characteristics of the construction machinery; wherein, the Hammerstein-Wiener model includes an input nonlinear module, a linear module, and an output nonlinear module, and the Wiener model includes a dynamic linear module and a static nonlinear module.

8. An apparatus for identifying model parameters of a hydraulic system of construction machinery, characterized in that, Including: A construction module, which constructs a model structure of the hydraulic system according to the historical data and hydraulic structure characteristics of the construction machinery; wherein, the model structure represents the corresponding relationship between the pilot pressure of the hydraulic system and the angular velocity of the working device of the construction machinery. The building module is configured to: construct a Hammerstein model of the hydraulic system according to the historical data and the hydraulic structure characteristics of the construction machinery; wherein, the Hammerstein model includes a static nonlinear module and a dynamic linear module; The dynamic linear module includes a transfer function, and the historical data includes historical pilot pressure and corresponding historical angular velocity; The building module is configured to: determine the structural parameters of the transfer function with the historical pilot pressure as the input information and the historical angular velocity as the output information; An identification module, configured to perform parameter identification according to the historical data and the model structure; The static nonlinear module includes a piecewise linear function; The identification module is configured to: input the historical pilot pressure into the piecewise linear function to solve for an intermediate quantity; input the intermediate quantity and the historical angular velocity into the transfer function to obtain an output result; the output result includes parameters to be identified.

9. An excavator, characterized in that, Comprising: A hydraulic system, the hydraulic system includes a spool valve; wherein, the hydraulic system receives pilot pressure to regulate the opening area of the spool valve; A working device, the working device is connected to the hydraulic system; A controller, the controller is connected to the hydraulic system and the working device, and the controller is configured to execute the hydraulic system model parameter identification method according to any one of claims 1-7 above.

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