Stiffness control method and external force estimation method of lever-type variable stiffness joint

Abstract

The present invention provides a stiffness control method for a lever-type variable stiffness joint. A stiffness variable region controller is designed based on a maximum external torque constraint and an estimated external force value at the previous moment, enabling dynamic updating of the stiffness value. By dynamically adjusting the stiffness variable to maintain the stiffness within a constant stiffness region, the joint is ensured to have appropriate stiffness, thereby improving safety in interacting with the external environment while avoiding output of saturated torque. The present invention also proposes a method for estimating external force for a lever-type variable stiffness joint. The method utilizes the acquired stiffness value to calculate an adaptive fusion coefficient. External force estimation I is obtained based on current information of the variable stiffness joint. External force estimation II is obtained based on elastic deformation information and stiffness values of the variable stiffness joint. Based on the adaptive fusion coefficient, external force estimation I, and external force estimation II, an external force estimation value based on the fusion of current and elastic deformation information is obtained, thereby improving the external force estimation effect under dynamic and quasi-static stiffness conditions.

Description

Technical Field

[0001] The present invention belongs to the technical field of variable stiffness joints of robots, and in particular relates to a stiffness control method and an external force estimation method of a lever-type variable stiffness joint. Background Art

[0002] This application is a divisional application of a patent with an application date of January 18, 2023, application number 2023100885343, and invention name “A method and device for estimating external force of a variable stiffness joint”.

[0003] Stiffness is a crucial factor in variable-stiffness joints, directly impacting joint performance metrics such as force estimation resolution, safety of interactions with the outside world, and dynamic adaptability during tasks. Low stiffness improves the safety of interactions between the robot and the outside world (robot-human, robot-environment), resulting in higher resolution and accuracy of force estimation based on elastic deformation. High stiffness, on the other hand, increases the torque tolerance of variable-stiffness joints, making them suitable for larger torques. (If a low-stiffness joint is subjected to a large torque, exceeding the permitted range, the torque output during force estimation will be saturated, failing to accurately reflect the current torque.) For applications requiring high stability, higher stiffness also increases stability. In certain applications, multiple mutually constrained stiffness-related performance metrics may be required, each with varying weights. In these cases, stiffness control is necessary to achieve a comprehensive performance that meets the required requirements.

[0004] Therefore, how to adjust the joint stiffness characteristics to meet the performance index requirements in different application scenarios is an important problem that needs to be solved urgently during the interactive contact and operation control process of physical interactive robots with the external environment.

[0005] In addition, in complex interactive tasks, high-precision external force self-sensing is an important future development direction. Currently, robots' external force self-sensing relies more on current information. For example, the external force estimation methods published in Chinese patents 201410112717.5, 202210279718.3, and 202210207511.5 all require the establishment of a dynamic model that can reflect the mapping relationship between current and external force. However, this method is greatly affected by the accuracy of the dynamic model. In addition, for variable stiffness joints, which use a dual-drive configuration of position motors and stiffness adjustment motors, the complexity of the dynamic model and the residual part of the dynamic unmodeled part restrict the external force estimation effect.

[0006] Since variable stiffness joints have internal compliance, external forces can also be estimated by detecting the elastic deformation inside the joints. However, this method has a good external force estimation effect under quasi-static stiffness, but its external force estimation effect is often poor under dynamic stiffness.

[0007] Therefore, how to achieve high-precision external force estimation of variable stiffness joints is an urgent problem to be solved. Summary of the Invention

[0008] In view of the need to accurately control the joint stiffness of variable stiffness joints in real applications to meet certain characteristics and the lack of existing related technologies, the present invention provides a stiffness control method for a lever-type variable stiffness joint, which can obtain stiffness values in a lever-type variable stiffness joint system to accurately quantify the joint deformation status of the variable stiffness joint during motion control, and control the joint stiffness in real time to meet the performance index requirements under different tasks.

[0009] In response to the problem in the prior art that high-precision external force estimation of lever-type variable stiffness joints is needed, the present invention provides a lever-type variable stiffness joint external force estimation method, which improves the external force estimation resolution under dynamic stiffness and can accurately achieve high-precision external force estimation of variable stiffness joints.

[0010] Specifically, the present invention achieves the above technical objectives through the following technical means.

[0011] A first aspect of the present invention provides a method for controlling the stiffness of a lever-type variable stiffness joint, comprising the following steps:

[0012] Design a stiffness region controller to calculate the expected value of the stiffness variable based on the estimated external force at the previous moment and the maximum external torque constraint;

[0013] Applying the expected value of the stiffness variable to the motion control of the stiffness regulating motor to obtain the actual value of the stiffness variable;

[0014] Substitute the actual value of the stiffness variable into the stiffness model to obtain an updated stiffness value, wherein the stiffness model is a function of the stiffness variable.

[0015] In one embodiment of the first aspect, designing a stiffness region controller to calculate an expected value of a stiffness variable based on an estimated external force value at a previous moment and a maximum external torque constraint includes:

[0016] Based on the Lyapunov barrier function, a stiffness zone controller is designed;

[0017] For the lever-type variable stiffness joint, the Lyapunov barrier function used for the stiffness region controller is expressed as:

[0018]

[0019] Among them, η represents the function variable, η=|τ q | / τ em -η0; η0, η1, η2 are all positive numbers and satisfy η0=η2=0.5, η1<0.5; τ q represents the estimated external torque; τ em represents the maximum allowable external moment of the joint under a specific stiffness variable γ, which is related to the stiffness variable γ; |τ q | / τ em The value range of is [0, 1];

[0020] Based on the Lyapunov barrier function, the stiffness regulation is divided into three regions, namely the stiffness increase region, the stiffness decrease region and the constant stiffness region;

[0021] According to the area involved in the Lyapunov barrier function, its derivative is expressed as:

[0022]

[0023] Design the right Satisfy To ensure that η is in the constant stiffness region, The expression is:

[0024]

[0025] Among them, k η is a constant that indicates how fast the stiffness of the lever-type variable stiffness joint changes from the stiffness increasing region or the stiffness decreasing region to the constant stiffness region, and k η greater than 0;

[0026] According to the definition of η, the derivative of η is expressed as:

[0027]

[0028] in, represents the derivative of the lever-type variable stiffness joint stiffness variable γ;

[0029] After further sorting, we get The expression:

[0030]

[0031] In one embodiment, when dividing the stiffness adjustment into three regions based on the Lyapunov barrier function, the parameter η of the Lyapunov barrier function is used;

[0032] When η>η1, it is the area where stiffness increases;

[0033] When η<-η1, it is the stiffness reduction area;

[0034] When -η1<η<η1, it is a constant stiffness region.

[0035] A second aspect of the present invention further provides a method for obtaining an adaptive fusion coefficient, comprising:

[0036] The aforementioned lever-type variable stiffness joint stiffness control method is used to obtain stiffness values in real time;

[0037] Substitute the obtained stiffness value into the adaptive fusion coefficient model for solution to obtain the adaptive fusion coefficient; the adaptive fusion coefficient model is:

[0038]

[0039] in, represents the absolute value of the derivative of joint stiffness K, R w1 and R w2 are all positive numbers, satisfying R w2 >R w1 .

[0040] A third aspect of the present invention provides a method for estimating external forces of a variable stiffness joint, comprising the following steps:

[0041] Adopting the adaptive fusion coefficient acquisition method to acquire the adaptive fusion coefficient in real time;

[0042] Obtain external force estimation I based on current information of variable stiffness joints;

[0043] The external force estimation II is obtained based on the elastic deformation information and stiffness value of the variable stiffness joint. The expression of the external force estimation II is:

[0044]

[0045] Where K(γ) represents the stiffness value, Indicates the elastic deformation inside the joint;

[0046] Based on the adaptive fusion coefficient, external force estimation I and external force estimation II, the external force estimation value based on the fusion of current and elastic deformation information is obtained:

[0047] τ q =K τ τ ei +(1-K τ )τ ec

[0048] Among them, τ ei Estimate the external force I, τ ec Estimation of external force II, K τ is the adaptive fusion coefficient.

[0049] In a specific implementation, the method of obtaining the external force estimation I based on the current information of the variable stiffness joint includes:

[0050] Establish the dynamic model of the position drive module and stiffness adjustment module:

[0051]

[0052] in, and Respectively represent the moment of inertia of the position drive module and the stiffness adjustment module; and Represent the friction forces of the position driving module and the stiffness adjustment module respectively; and Represent the output torques of the position drive module and stiffness adjustment module respectively; and Represent the input torque of the position drive module and the stiffness adjustment module respectively; θ1 and θ2 represent the output angular displacement of the position drive module and the stiffness adjustment module respectively;

[0053] Obtaining the moment of inertia in the dynamic model through dynamic parameter identification method and friction The exact value of

[0054] Measure the current information I of the position motor and stiffness adjustment motor p and I s , calculate the input torque of the position drive module and stiffness adjustment module according to the following formula:

[0055]

[0056] Among them, K pi and K si Represent the total torque constants of the position drive module and stiffness adjustment module respectively;

[0057] Substituting the calculated input torques of the position driving module and the stiffness adjustment module into the dynamic models of the position driving module and the stiffness adjustment module for solving the problems, thereby obtaining the output torques of the position driving module and the stiffness adjustment module;

[0058] Calculate the sum of the output torques of the position drive module and the stiffness adjustment module as the external force estimate I:

[0059]

[0060] Compared with the prior art, the present invention has outstanding substantive features and significant progress, specifically:

[0061] The present invention takes into account the different maximum allowable external torques of joints under different stiffnesses, and designs a stiffness region variable controller based on the maximum external torque constraint and the external force estimation value at the previous moment, thereby realizing the dynamic update of the stiffness value, and the stiffness value is closer to the actual stiffness value; by dynamically adjusting the stiffness variable so that the stiffness is in the constant stiffness region, it is ensured that the joint has a smaller stiffness and at the same time avoids the output saturation torque.

[0062] The present invention designs an adaptive fusion coefficient model based on the stiffness variable. The adaptive fusion coefficient changes autonomously with the stiffness value, which can achieve a smooth transition of the external force estimation value and avoid the jump of the external force estimation value.

[0063] The present invention obtains the stiffness value and the measured internal elastic deformation of the joint in real time, obtains the external force estimation II based on the elastic deformation information, and improves the resolution of the external force estimation under dynamic stiffness.

[0064] The external force estimation method proposed in the present invention realizes the fusion of external force estimation based on current and external force estimation based on elastic deformation information, makes up for the defects of a single external force estimation method, improves the external force estimation effect under dynamic and quasi-static stiffness, and is suitable for variable stiffness joint systems that require high-precision external force estimation in force interaction scenarios. BRIEF DESCRIPTION OF THE DRAWINGS

[0065] Figure 1 Flowchart of the variable stiffness joint external force estimation method of Example 1;

[0066] Figure 2 The corresponding relationship between the maximum external torque allowed by the lever-type variable stiffness joint and the stiffness variable;

[0067] Figure 3 This is a simplified diagram of stiffness area control;

[0068] Figure 4 It is a schematic diagram of adaptive fusion coefficient;

[0069] Figure 5 Comparison of the results of three different external force estimation methods. DETAILED DESCRIPTION

[0070] The following describes embodiments of the present invention in detail. Examples of the illustrated embodiments are shown in the accompanying drawings, wherein the same or similar reference numerals throughout represent the same or similar elements or elements having the same or similar functions. The embodiments described below with reference to the accompanying drawings are exemplary and are intended to be used to explain the present invention, and are not to be construed as limiting the present invention.

[0071] In response to the defect of joint stiffness control in the existing technology that it cannot simultaneously meet the requirements of multiple indicators, the present invention provides a stiffness control method for a lever-type variable stiffness joint, which can simultaneously meet the requirements of multiple indicators such as interactive safety and external force estimation resolution, and at the same time, obtain stiffness values in the variable stiffness joint system to accurately quantify the joint deformation condition of the variable stiffness joint during the motion control process.

[0072] In response to the problem in the existing technology that high-precision external force estimation of variable stiffness joints is needed, the present invention provides a variable stiffness joint external force estimation method, which can accurately achieve high-precision external force estimation of variable stiffness joints and is suitable for variable stiffness joint systems that require high-precision external force estimation in force interaction scenarios.

[0073] Hereinafter, exemplary embodiments of the present invention will be discussed in detail with reference to the accompanying drawings.

[0074] Example 1

[0075] like Figure 1 As shown, this embodiment provides a method for controlling the stiffness of a lever-type variable stiffness joint, comprising the following steps:

[0076] Design a stiffness region controller based on the estimated external force value τ at the previous moment q and the maximum external moment constraint τ em , calculate the expected value of the stiffness variable γ d .

[0077] The specific steps are as follows:

[0078] Step 1: Design a stiffness region controller based on the Lyapunov barrier function.

[0079] For the lever-type variable stiffness joint, the Lyapunov barrier function used for the stiffness region controller is expressed as:

[0080]

[0081] Among them, η represents the function variable, η=|τ q | / τ em -η0; η0, η1, η2 are all positive numbers and satisfy η0=η2=0.5, η1<0.5; τ q represents the estimated external torque; τ em represents the maximum allowable external moment of the joint under a specific stiffness variable γ, which is related to the stiffness variable γ; |τ q | / τ em The value range is [0, 1].

[0082] like Figure 2 As shown, the maximum external torque τ allowed by the joint emConstrained by the maximum compression of the elastic element and the rated moment, it is not a constant value, but is related to the stiffness variable γ: between [0, γ1], τ em As γ increases, the process is mainly constrained by the maximum compression of the elastic element; in the interval [γ1, γ2], τ em It is a constant value and is subject to the rated torque.

[0083] It is understandable that due to |τ q | / τ em The value range of is [0, 1], so by introducing η0 and defining η0=η2=0.5, η can be made between [-0.5, 0.5].

[0084] Step 2: Based on the Lyapunov barrier function, the stiffness adjustment is divided into three regions, namely the stiffness increase region, the stiffness decrease region and the constant stiffness region; Figure 3 As shown in Figure 1, the basis for regional division is the parameter η.

[0085] Specifically, when η>η1, |τ q | / τ em The ratio is close to or greater than 1, and the external torque τ on the joint q Close to or greater than the maximum tolerable moment τ under this stiffness em , control the stiffness K to increase the maximum allowable moment τ em It also increases to ensure that the external force on the joint is within the tolerable range, so it is called the "stiffness increase area";

[0086] When η<-η1, |τ q | / τ em The ratio is close to 0, and the external torque τ on the joint q Much smaller than the maximum allowable moment τ under this stiffness em , the control stiffness K is reduced and the resolution of external force estimation is improved, so it is called the “stiffness reduction region”;

[0087] When -η1<η<η1, |τ q | / τ em In a reasonable range, the joint has a suitable external force estimation resolution, and the torque it bears is less than the maximum allowable torque τ em , at this time, the joint is in the "constant stiffness zone" and no stiffness adjustment is made.

[0088] It can be understood that the constant stiffness region is a desired region, and the purpose of stiffness adjustment is to keep the stiffness in the constant stiffness region.

[0089] Step 3: Based on the area involved in the Lyapunov barrier function, its derivative is expressed as:

[0090]

[0091] Step 4: Design a suitable Satisfy To ensure that η is in the constant stiffness region, The expression is:

[0092]

[0093] Among them, k η is a constant that indicates how fast the stiffness of a variable stiffness joint changes from a stiffness increase region or a stiffness decrease region to a constant stiffness region, and k η Greater than 0, its value can be selected according to actual needs.

[0094] The constant stiffness area can ensure the external torque τ q Not exceeding the maximum allowable moment τ under a certain stiffness em , while also ensuring that the joint is in a smaller stiffness and higher external force resolution; therefore, it is necessary to try to ensure that η is in the constant stiffness area, so as to avoid the stiffness being in the process of adjustment all the time and save energy.

[0095] Furthermore, when the direction of the external torque changes, |τ q | / τ em The ratio fluctuates around 0. Setting the minimum stiffness value can avoid stiffness fluctuations.

[0096] Step 5, according to the definition of η η=|τ q | / τ em -η;0 expresses the derivative of η as:

[0097]

[0098] in, It represents the derivative of the variable stiffness joint stiffness variable γ, reflects the magnitude of the stiffness adjustment rate, and affects the speed of stiffness adjustment.

[0099] Step 6: After further sorting, we get The expression:

[0100]

[0101] It can be seen that in this embodiment, a stiffness region controller is designed taking into account the different maximum allowable external torques of the joints under different stiffnesses. By adjusting the stiffness variable, it is ensured that η is in the constant stiffness region, ensuring that the joint has a good external force estimation resolution and avoiding the detection torque saturation output.

[0102] After calculating the expected value of the stiffness variable γ dAfter that, considering the expected value of the stiffness variable γ calculated by the stiffness region controller d It is just a theoretical value, so the expected value of the stiffness variable γ d Acting on the motion control of the stiffness adjustment motor, the actual value of the stiffness variable γ is obtained r , to achieve real-time update of stiffness variables.

[0103] Furthermore, when applied to discrete-time control systems, the stiffness variable γ is expressed as:

[0104]

[0105] Among them, t i represents the i-th sampling moment; Δt is the sampling period of the system, t i+1 =t i +Δt.

[0106] The actual value of the stiffness variable γ r Substitute into the stiffness model K(γ) to obtain the updated stiffness value K(γ r ).

[0107] The present invention takes into account the different maximum allowable external torques of joints under different stiffnesses, designs a stiffness region variable controller based on the maximum external torque constraint and the external force estimation value at the previous moment, and realizes the stiffness variable expected value γ d Dynamic update, after calculating the expected value of the stiffness variable γ d Finally, considering the expected value of the stiffness variable γ calculated by the stiffness region variable controller d It is just a theoretical value, so the expected value of the stiffness variable γ d Acting on the motion control of the stiffness adjustment motor, the actual value of the stiffness variable γ is obtained r , using the actual value of the stiffness variable γ r The calculated stiffness value is closer to the actual stiffness value. Based on the dynamic actual stiffness value, the joint deformation condition of the variable stiffness joint during motion control can be accurately quantified.

[0108] It can be seen that the stiffness region variable controller is dynamically adjusted according to the stiffness range. By dynamically adjusting the stiffness variable, the stiffness is placed in the constant stiffness region, thereby ensuring that the joint has a smaller stiffness and improving the accuracy of external force estimation, thereby achieving the requirements of interactive safety and external force estimation resolution performance indicators at the same time.

[0109] Example 2

[0110] A second aspect of this embodiment provides a method for obtaining an adaptive fusion coefficient, characterized by comprising:

[0111] Design an adaptive fusion coefficient model:

[0112]

[0113] Where K represents the joint stiffness, represents the absolute value of the derivative of joint stiffness K, R w1 and R w2 are all positive numbers, satisfying R w2 >R w1 ;

[0114] The stiffness value K(γ r ); Set the stiffness value K(γ r ) is substituted into the adaptive fusion coefficient model to obtain the adaptive fusion coefficient K τ .

[0115] like Figure 4 As shown, the adaptive fusion coefficient K calculated in step S2 τ Schematic diagram. It can be seen that the adaptive fusion coefficient K τ According to Self-regulation, when When K τ When the value is 1, the external force estimation value based on current information plays a dominant role; when When K τ When the value is 0, the external force estimation value based on elastic deformation information plays a dominant role; When , the external force estimation value is calculated by combining the current and elastic deformation.

[0116] By setting the adaptive fusion coefficient K τ The expression designed in the form of a sine curve can achieve a smooth transition between the external force estimation value based on the current and the external force estimation value based on the elastic deformation, thereby avoiding the jump of the external force estimation value.

[0117] The present invention designs an adaptive fusion coefficient model based on the stiffness variable. The adaptive fusion coefficient changes autonomously with the stiffness value, which can achieve a smooth transition between the external force estimation value based on current and the external force estimation value based on elastic deformation, avoiding the jump of the external force estimation value.

[0118] Example 3

[0119] This embodiment provides a lever-type variable stiffness joint external force estimation method, such as Figure 1 As shown, the following steps are included:

[0120] The adaptive fusion coefficient is obtained in real time using the adaptive fusion coefficient acquisition method described in Example 2;

[0121] Obtain external force estimation I based on current information of variable stiffness joints;

[0122] The external force estimation II is obtained based on the elastic deformation information and stiffness value of the variable stiffness joint. The expression of the external force estimation II is:

[0123]

[0124] Where K(γ) represents the stiffness value, Indicates the elastic deformation inside the joint;

[0125] Based on the adaptive fusion coefficient, external force estimation I and external force estimation II, the external force estimation value based on the fusion of current and elastic deformation information is obtained:

[0126] τ q =K τ τ ei +(1-K τ )τ ec

[0127] Among them, τ ei Estimate the external force I, τ ec Estimation of external force II, K τ is the adaptive fusion coefficient.

[0128] The present invention obtains external force estimation II based on elastic deformation information based on the updated stiffness variable and the measured internal elastic deformation of the joint, thereby improving the external force estimation effect under dynamic stiffness.

[0129] The external force estimation method proposed in the present invention realizes the fusion of external force estimation based on current and external force estimation based on elastic deformation information through the fusion coefficient, which makes up for the defects of the single external force estimation method, improves the external force estimation effect under dynamic and quasi-static stiffness, and is suitable for variable stiffness joint systems that require high-precision external force estimation in force interaction scenarios.

[0130] Example 4

[0131] The difference between this embodiment and embodiment 3 is that: an embodiment of obtaining external force estimation I based on current information of variable stiffness joint is provided, such as Figure 1 shown.

[0132] The specific steps are as follows:

[0133] Establish the dynamic models of the position driving module and the stiffness adjustment module.

[0134] The kinetic model is expressed as:

[0135]

[0136] in, and Represent the moment of inertia of the position drive module and the stiffness adjustment module respectively, which are unknown parameters; and Represent the friction forces of the position driving module and the stiffness adjustment module respectively, which are unknown parameters; and Represent the output torques of the position drive module and stiffness adjustment module respectively; and They represent the input torques of the position driving module and the stiffness adjustment module respectively; θ1 and θ2 represent the output angular displacements of the position driving module and the stiffness adjustment module respectively.

[0137] Obtaining the moment of inertia in the dynamic model through dynamic parameter identification method and friction The exact value of .

[0138] The dynamic model includes both motion parameters θ1 and θ2 and unknown dynamic parameters and The motion parameters θ1 and θ2 can be obtained by measurement, while the dynamic parameters that cannot be measured are and It is necessary to obtain the accurate values of the parameters through the dynamic parameter identification method.

[0139] Dynamic parameter identification involves using mathematical methods to determine the unknown parameters of the joint dynamics model based on the dynamic parameter model and the angular position errors at the joint output. Numerous algorithms can be used for dynamic parameter identification, including maximum likelihood estimation, least squares method, particle swarm optimization, Kalman filtering, neural networks, and genetic algorithms.

[0140] It should be noted that in the variable stiffness joint, the motion parameters include not only the position drive module angle θ1 and the stiffness adjustment module angle θ2, but also the internal elastic deformation And the joint output angle displacement q, while satisfying the following constraints: These motion parameters can be acquired through additional sensors.

[0141] Measure the motor current values of the position drive module and stiffness adjustment module, and calculate the input torque of the position drive module and stiffness adjustment module according to the following formula:

[0142]

[0143] Among them, K pi and K si Respectively represent the total torque constants of the position drive module and the stiffness adjustment module, reflecting parameters such as the motor torque constant and reduction ratio; I p and i sRespectively represent the motor current values of the position drive module and the stiffness adjustment module;

[0144] The calculated input torque of the position drive module and the stiffness adjustment module is substituted into the dynamic model of the position drive module and the stiffness adjustment module for solution to obtain the output torque of the position drive module and the stiffness adjustment module. and

[0145] The output torque of the position drive module and the stiffness adjustment module and The external force estimation I based on the current information is obtained by performing the following operations:

[0146] It can be seen that in this embodiment, when estimating external force based on current information, the output torque of the stiffness adjustment module is introduced on the basis of comprehensively considering the dynamic information of the position drive module and the stiffness adjustment module. By obtaining the output torque of the position drive module and the stiffness adjustment module respectively, and taking the sum of the two as the overall output torque of the joint, the overall output torque of the joint is made closer to the actual output torque, thereby improving the accuracy of external force estimation based on current information; the dynamic model of each sub-drive includes unknown parameters that can be obtained through dynamic parameter identification and measurable angular displacement, which further reduces the influence of model error on external force estimation.

[0147] Example 5

[0148] In this embodiment, the variable stiffness joint is set to be a lever-type variable stiffness joint system. Figure 1 As shown, a specific implementation method of external force estimation is given.

[0149] The specific steps are as follows:

[0150] Step A, obtaining stiffness values in real time;

[0151] Step A1, design the stiffness region controller based on the estimated external force value τ at the previous moment q and the maximum external moment constraint τ em , calculate the expected value of the stiffness variable γ d .

[0152] The specific steps are as follows:

[0153] Step 1: Design a stiffness region controller based on the Lyapunov barrier function.

[0154] For the lever-type variable stiffness joint, the Lyapunov barrier function used for the stiffness region controller is expressed as:

[0155]

[0156] Among them, η represents the function variable, η=|τ q | / τ em -η0; η0, η1, η2 are all positive numbers and satisfy η0=η2=0.5, η1<0.5; τ q represents the estimated external torque; τ em represents the maximum allowable external moment of the joint under a specific stiffness variable γ, which is related to the stiffness variable γ; |τ q | / τ em The value range is [0, 1].

[0157] like Figure 2 As shown, the maximum external torque τ allowed by the joint em Constrained by the maximum compression of the elastic element and the rated moment, it is not a constant value, but is related to the stiffness variable γ: between [0, γ1], τ em As γ increases, the process is mainly constrained by the maximum compression of the elastic element; in the interval [γ1, γ2], τ em It is a constant value and is subject to the rated torque.

[0158] It is understandable that due to |τ q | / τ em The value range of is [0, 1], so by introducing η0 and defining η0=η2=0.5, η can be made between [-0.5, 0.5].

[0159] Step 2: Based on the Lyapunov barrier function, the stiffness adjustment is divided into three regions, namely the stiffness increase region, the stiffness decrease region and the constant stiffness region; Figure 3 As shown in Figure 1, the basis for regional division is the parameter η.

[0160] Specifically, when η>η1, |τ q | / τ em The ratio is close to or greater than 1, and the external torque τ on the joint q Close to or greater than the maximum tolerable moment τ under this stiffness em , control the stiffness K to increase the maximum allowable moment τ em It also increases to ensure that the external force on the joint is within the tolerable range, so it is called the "stiffness increase area";

[0161] When η<-η1, |τ q | / τ em The ratio is close to 0, and the external torque τ on the joint q Much smaller than the maximum allowable moment τ under this stiffness em , the control stiffness K is reduced and the resolution of external force estimation is improved, so it is called the “stiffness reduction region”;

[0162] When -η1<η<η1, |τ q | / τ em In a reasonable range, the joint has a suitable external force estimation resolution, and the torque it bears is less than the maximum allowable torque τ em , at this time, the joint is in the "constant stiffness zone" and no stiffness adjustment is made.

[0163] It can be understood that the constant stiffness region is a desired region, and the purpose of stiffness adjustment is to keep the stiffness in the constant stiffness region.

[0164] Step 3: Based on the area involved in the Lyapunov barrier function, its derivative is expressed as:

[0165]

[0166] Step 4: Design a suitable Satisfy To ensure that η is in the constant stiffness region, The expression is:

[0167]

[0168] Among them, k η is a constant that indicates how fast the stiffness of a variable stiffness joint changes from a stiffness increase region or a stiffness decrease region to a constant stiffness region, and k η Greater than 0, its value can be selected according to actual needs.

[0169] The constant stiffness area can ensure the external torque τ q Not exceeding the maximum allowable moment τ under a certain stiffness em , while also ensuring that the joint is in a smaller stiffness and higher external force resolution; therefore, it is necessary to try to ensure that η is in the constant stiffness area, so as to avoid the stiffness being in the process of adjustment all the time and save energy.

[0170] Furthermore, when the direction of the external torque changes, |τ q | / τ em The ratio fluctuates around 0. Setting the minimum stiffness value can avoid stiffness fluctuations.

[0171] Step 5, according to the definition of η η=|τ q | / τ em -η0 expresses the derivative of η as:

[0172]

[0173] in, It represents the derivative of the variable stiffness joint stiffness variable γ, reflects the magnitude of the stiffness adjustment rate, and affects the speed of stiffness adjustment.

[0174] Step 6: After further sorting, we get The expression:

[0175]

[0176] It can be seen that in this embodiment, a stiffness region controller is designed taking into account the different maximum allowable external torques of the joints under different stiffnesses. By adjusting the stiffness variable, it is ensured that η is in the constant stiffness region, ensuring that the joint has a good external force estimation resolution and avoiding the detection torque saturation output.

[0177] Step A2, after calculating the expected value of the stiffness variable γ d After that, considering the expected value of the stiffness variable γ calculated by the stiffness region controller d It is just a theoretical value, so the expected value of the stiffness variable γ d Acting on the motion control of the stiffness adjustment motor, the actual value of the stiffness variable γ is obtained r , to achieve real-time update of stiffness variables.

[0178] Furthermore, when applied to discrete-time control systems, the stiffness variable γ is expressed as:

[0179]

[0180] Among them, t i represents the i-th sampling moment; Δt is the sampling period of the system, t i+1 =t i +Δt.

[0181] Step A3: Set the actual value of the stiffness variable γ r Substitute into the stiffness model K(γ) to obtain the updated stiffness value K(γ r ).

[0182] Step B: Obtain the adaptive fusion coefficient.

[0183] Step B1, design an adaptive fusion coefficient model:

[0184]

[0185] Where K represents the joint stiffness, represents the absolute value of the derivative of joint stiffness K, R w1 and R w2 are all positive numbers, satisfying R w2 >R w1 ;

[0186] Step B2: Update the stiffness value K(γ r ) is substituted into the adaptive fusion coefficient model to obtain the adaptive fusion coefficient Kτ .

[0187] Step C, obtaining external force estimation I based on the current information of the variable stiffness joint:

[0188] The specific implementation includes the following steps:

[0189] Step C1: establishing the dynamic models of the position driving module and the stiffness adjustment module.

[0190] The kinetic model is expressed as:

[0191]

[0192] in, and Represent the moment of inertia of the position drive module and the stiffness adjustment module respectively, which are unknown parameters; and Represent the friction forces of the position driving module and the stiffness adjustment module respectively, which are unknown parameters; and Represent the output torques of the position drive module and stiffness adjustment module respectively; and They represent the input torques of the position driving module and the stiffness adjustment module respectively; θ1 and θ2 represent the output angular displacements of the position driving module and the stiffness adjustment module respectively.

[0193] Step C2: Obtain the moment of inertia in the dynamic model through the dynamic parameter identification method and friction The exact value of

[0194] Step C3: Measure the motor current values of the position drive module and the stiffness adjustment module, and calculate the input torque of the position drive module and the stiffness adjustment module according to the following formula:

[0195]

[0196] Among them, K pi and K si Respectively represent the total torque constants of the position drive module and the stiffness adjustment module, reflecting parameters such as the motor torque constant and reduction ratio; I p and I s Respectively represent the motor current values of the position drive module and the stiffness adjustment module;

[0197] Step C4: Substitute the calculated input torque of the position drive module and the stiffness adjustment module into the dynamic model of the position drive module and the stiffness adjustment module to solve and obtain the output torque of the position drive module and the stiffness adjustment module. and

[0198] Step C5: The output torque of the position drive module and the stiffness adjustment module and The external force estimation I based on the current information is obtained by performing the following operations:

[0199] It can be seen that in this embodiment, the dynamic model is decoupled and split into the dynamic model of the position drive module and the dynamic model of the stiffness adjustment module, thereby reducing the high-order dynamic model to the control of each sub-drive, simplifying the model and reducing the control difficulty; the dynamic model of each sub-drive includes unknown parameters that can be obtained through dynamic parameter identification and measurable angular displacement, further reducing the impact of model errors on external force estimation.

[0200] Step D, based on the elastic deformation information of the variable stiffness joint and the updated stiffness value K(γ r ) Obtain external force estimate II:

[0201]

[0202] Step E, based on the adaptive fusion coefficient K τ , external force estimation Iτ ei and external force estimation IIτ ec , obtain the external force estimate based on the fusion of current and elastic deformation information:

[0203] τ q =K τ τ ei +(1-K τ )τ ec .

[0204] like Figure 5 The following figure shows an experimental comparison of three different external force estimation methods in a lever-type variable stiffness joint scenario. The average absolute value of the error of the three different external force estimation results is shown below:

[0205]

[0206] It can be seen that the external force estimation based on elastic deformation has a better external force estimation effect under quasi-static stiffness, but the external force estimation effect under dynamic stiffness is poor;

[0207] The external force estimation effect based on current information is stable under both dynamic and quasi-static stiffness. However, its external force estimation effect under quasi-static stiffness is inferior to that based on elastic deformation.

[0208] The external force estimation method based on the fusion of current and elastic deformation information proposed in the present invention combines the advantages of the two types of information, improves the external force estimation effect under dynamic and quasi-static stiffness, and has the smallest average value of the overall absolute value of the error in terms of external force estimation error.

[0209] Although the present invention is disclosed above with reference to preferred embodiments, this is not intended to limit the scope of the present invention. Any person skilled in the art may make slight modifications without departing from the scope of the present invention. In other words, any equivalent modifications made in accordance with the present invention should be included within the scope of the present invention.

Claims

1. A lever-type variable stiffness joint external force estimation method, characterized in that: The following steps are involved: Design a stiffness region controller to calculate the expected value of the stiffness variable based on the estimated external force at the previous moment and the maximum external torque constraint; Applying the expected value of the stiffness variable to the motion control of the stiffness regulating motor to obtain the actual value of the stiffness variable; Substituting the actual value of the stiffness variable into the stiffness model to obtain an updated stiffness value, wherein the stiffness model is a function of the stiffness variable; Substitute the obtained stiffness value into the adaptive fusion coefficient model for solution to obtain the adaptive fusion coefficient; the adaptive fusion coefficient model is: in, represents the absolute value of the derivative of joint stiffness K, R w1 and R w2 are all positive numbers, satisfying R w2 >R w1 ; Obtain external force estimation I based on current information of variable stiffness joints; The external force estimation II is obtained based on the elastic deformation information and stiffness value of the variable stiffness joint. The expression of the external force estimation II is: Where K(γ) represents the stiffness value, Indicates the elastic deformation inside the joint; Based on the adaptive fusion coefficient, external force estimation I and external force estimation II, the external force estimation value based on the fusion of current and elastic deformation information is obtained: t q =K τ t ei +(1-K τ )t ec Among them, τ ei Estimate the external force I, τ ec Estimation of external force II, K τ is the adaptive fusion coefficient.

2. A lever-type variable stiffness joint external force estimation method according to claim 1, characterized in that: Design a stiffness region controller to calculate the expected value of the stiffness variable based on the estimated external force at the previous moment and the maximum external torque constraint, including: Based on the Lyapunov barrier function, a stiffness zone controller is designed; For the lever-type variable stiffness joint, the Lyapunov barrier function used for the stiffness region controller is expressed as: Among them, η represents the function variable, η=|τ q | / τ em -η0; η0, η1, η2 are all positive numbers and satisfy η0=η2=0.5, η1<0.5; τ q represents the estimated external torque; τ em represents the maximum allowable external moment of the joint under a specific stiffness variable γ, which is related to the stiffness variable γ; |τ q | / τ em The value range of is [0,1]; Based on the Lyapunov barrier function, the stiffness regulation is divided into three regions, namely the stiffness increase region, the stiffness decrease region and the constant stiffness region; According to the area involved in the Lyapunov barrier function, its derivative is expressed as: Design the right Satisfy To ensure that η is in the constant stiffness region, The expression is: Among them, k η is a constant that indicates how fast the stiffness of the lever-type variable stiffness joint changes from the stiffness increasing region or the stiffness decreasing region to the constant stiffness region, and k η greater than 0; According to the definition of η, the derivative of η is expressed as: in, represents the derivative of the lever-type variable stiffness joint stiffness variable β; After further sorting, we get The expression:

3. The lever-type variable stiffness joint external force estimation method according to claim 2, characterized in that: Based on the Lyapunov barrier function, the stiffness regulation is divided into three regions according to the parameter η of the Lyapunov barrier function; When η>η1, it is the area where stiffness increases; When η<-η1, it is the stiffness reduction area; When -η1<η<η1, it is a constant stiffness region.

4. A lever-type variable stiffness joint external force estimation method according to claim 1, 2 or 3, characterized in that: The obtaining of external force estimation I based on current information of the variable stiffness joint includes: Establish the dynamic model of the position drive module and stiffness adjustment module: in, and Respectively represent the moment of inertia of the position drive module and the stiffness adjustment module; and Represent the friction forces of the position driving module and the stiffness adjustment module respectively; and Represent the output torques of the position drive module and stiffness adjustment module respectively; and Represent the input torque of the position drive module and the stiffness adjustment module respectively; θ1 and θ2 represent the output angular displacement of the position drive module and the stiffness adjustment module respectively; Obtaining the moment of inertia in the dynamic model through dynamic parameter identification method and friction The exact value of Measure the current information I of the position motor and stiffness adjustment motor p and I s , calculate the input torque of the position drive module and stiffness adjustment module according to the following formula: Among them, K pi and K si Represent the total torque constants of the position drive module and stiffness adjustment module respectively; Substituting the calculated input torques of the position driving module and the stiffness adjustment module into the dynamic models of the position driving module and the stiffness adjustment module for solving the problems, thereby obtaining the output torques of the position driving module and the stiffness adjustment module; Calculate the sum of the output torques of the position drive module and the stiffness adjustment module as the external force estimate I:

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