A collaborative control method for joint modules based on hyperlocal model

Abstract

The present invention relates to a joint module collaborative control method based on a hyperlocal model. Compared with the prior art, it solves the problem that high-performance control of the joint module can only be completed by highly relying on many parameters of the joint module, and cannot effectively deal with the problem of decreased control performance caused by uncertain factors, and the defects of poor robustness of joint module control. The present invention comprises the following steps: acquisition of joint module operation data; establishment of the dynamic equation of the joint module; establishment of a hyperlocal model of the joint module; design of a collaborative controller; and implementation of joint module collaborative control. The present invention designs a collaborative controller based on a hyperlocal model of the joint module, has the characteristic of being independent of the system model, and can effectively deal with the problem of decreased control performance and poor robustness caused by uncertain factors in the joint module.

Description

Technical Field

[0001] The present invention relates to the technical field of robot arm joint module control, and in particular to a joint module collaborative control method based on a super local model. Background Art

[0002] With the rapid development of information technology, control technology and mechanical technology, robotics technology has emerged. As one of the hottest technologies in robotics, robotic arms have attracted more and more attention in recent years. With the widespread application of robotic arms in production and life, robotic arms are developing in the direction of modularization and human-machine collaboration. As the basic unit of modular robotic arms, the joint module is a typical motor-gear system, which is mainly composed of a servo system controller, a permanent magnet synchronous motor, a transmission device and a sensor. It has the advantages of light weight, a large load-to-weight ratio, low power and low power consumption. Therefore, the servo drive performance of the joint module largely determines the overall performance of the robotic arm.

[0003] However, the joint module is a complex, nonlinear system that is susceptible to uncertainty. There are various uncertainties in the joint module, including: uncertainty in system structure, uncertainty in modeling, such as uncertainty in moment of inertia, changes in system parameters such as viscous friction coefficient caused by temperature changes; non-structural uncertainties, such as load torque disturbance, electromagnetic interference, and changes in control targets, etc. These factors will greatly deteriorate the control performance of the joint module. In this case, the conventional control method cannot achieve satisfactory control results for the joint module. Therefore, how to achieve high-performance control of the joint module, a multivariable, strongly coupled, time-varying nonlinear system, is a challenging task.

[0004] In order to overcome the influence of many uncertain factors on the control performance of the robot joint module, some scholars began to introduce nonlinear control methods into the control system of the robot joint module. Reference (Liu Rongyao. Research on the design and drive control of collaborative robot joint module system. Hefei University of Technology, 2020) In order to solve the problem of many uncertain factors in the joint module causing the control performance to decline, an adaptive robust control method is adopted, but this method requires real-time parameter estimation and adjustment of the system, which requires a lot of computing and storage resources, making the controller more complex. Reference (Cui Yalei. Research on drive and control of collaborative robot joint module based on DSP. Hefei University of Technology, 2021) A model-based robust control algorithm is designed to solve the problem of control performance decline caused by uncertain factors in the joint module, but this method requires the construction of a system model. The construction of the system model requires many physical parameters of the system, and these parameters are often difficult to obtain accurately and are easily affected by some factors that are difficult to quantify, resulting in a decline in control performance and robustness. The literature (Xue Ye. Fuzzy backstepping control of joint robots driven by PMSM. Qingdao University, 2020) adopts fuzzy control. Although it does not require the establishment of an accurate mathematical model of the system and has strong anti-interference ability, its ability to eliminate steady-state errors is poor, making it difficult to achieve high-precision control of the joint module of the robot arm. The literature (Lu Zhiyuan. Research on anti-interference strategy of industrial robot joint servo load. Anhui University of Technology, 2022) adopts a nonlinear self-disturbance rejection controller to improve the anti-interference ability of the joint module servo control system, but the nonlinear self-disturbance rejection controller usually requires real-time parameter estimation and calculation of the system, which is higher in computational complexity than traditional controllers and has higher hardware requirements, requiring the controller to have stronger computing resources and real-time performance. The literature (Tang Bo. Research on high-response and high-precision position control of permanent magnet synchronous motors for integrated joints of collaborative robots. Zhejiang University of Technology, 2022) adopts sliding mode variable structure control to improve its response speed and anti-interference ability, but the sliding mode variable structure controller realizes control by introducing a sliding surface, and the control signal frequently switches on the sliding surface, which will cause the system to vibrate.

[0005] In summary, based on the shortcomings of the existing robotic arm joint module control method that is highly dependent on the system's precise mathematical model and has poor control performance, it has become an urgent problem to design a controller that can get rid of the dependence on the robotic arm joint module parameters, effectively deal with the uncertainty factors that lead to a decrease in control performance, and effectively improve its control performance. Summary of the invention

[0006] The purpose of the present invention is to solve the defects in the prior art that high-performance control of the joint module can only be achieved by highly relying on many parameters of the joint module, and cannot effectively deal with the problem of decreased control performance caused by uncertain factors, and the robustness of the joint module control is poor. A joint module collaborative control method based on a super local model is provided to solve the above problems.

[0007] In order to achieve the above object, the technical solution of the present invention is as follows:

[0008] A joint module collaborative control method based on a hyperlocal model comprises the following steps:

[0009] Acquisition of joint module operation data: The angular displacement of the joint module is measured by the absolute value encoder on the output shaft of the joint module, and the angular velocity of the joint module is obtained by differential processing of the angular displacement;

[0010] Establish the dynamic equations of the joint module;

[0011] Establishment of the hyperlocal model of the joint module: According to the dynamic equation of the joint module, establish the hyperlocal model of the joint module;

[0012] Design collaborative controller: Based on the hyperlocal model of joint modules, collaborative controller is designed according to collaborative control theory;

[0013] Implementation of collaborative control of joint modules: Based on the obtained angular displacement and angular velocity information of the joint module, the output electromagnetic torque of the permanent magnet synchronous motor in the joint module is obtained through the collaborative controller, thereby driving the joint module to reach the desired angular displacement.

[0014] The dynamic equation of establishing the joint module comprises the following steps:

[0015] Based on dynamic analysis, the joint module is equivalent to a permanent magnet synchronous motor and a harmonic reducer, and the mathematical model of the permanent magnet synchronous motor is set as:

[0016]

[0017] Among them, i d 、i q 、u d 、u q , L d , L q They represent the stator current, stator voltage and stator inductance of the d-axis and q-axis of the permanent magnet synchronous motor respectively, and n p represents the number of pole pairs, q, are the angular displacement, angular velocity and angular acceleration of the rotor respectively, R is the stator resistance, ψ f is the permanent magnet flux, J, B, τ and T lpThey represent the moment of inertia, viscous friction coefficient, electromagnetic torque and load torque of the permanent magnet synchronous motor respectively, t is the operating time of the joint module, is the derivative operation with respect to time t;

[0018] For the electromagnetic torque output by the permanent magnet synchronous motor, there is:

[0019]

[0020] Among them, i d 、i q 、u d 、u q , L d , L q They represent the stator current and stator inductance of the d-axis and q-axis of the permanent magnet synchronous motor, respectively. p represents the pole pair number, ψ f represents the permanent magnet flux, τ represents the electromagnetic torque of the permanent magnet synchronous motor;

[0021] According to the principle of magnetic field oriented control technology, for the surface mounted permanent magnet synchronous motor used in the joint module, the three-phase stator current synthesis vector is controlled on the q axis, so that i d is zero, that is, i d =0, achieving maximum torque control per ampere current, so that the torque control has better dynamic and steady-state performance;

[0022] For the surface-mounted permanent magnet synchronous motor used in the joint module, there is L d =L q =L S , therefore, the mathematical model of the surface-mounted permanent magnet synchronous motor is:

[0023]

[0024] Among them, i d 、i q 、u d 、u q , L d , L q They represent the stator current, stator voltage and stator inductance of the d-axis and q-axis of the permanent magnet synchronous motor respectively, and L S represents the stator inductance, n p represents the number of pole pairs, q, are the angular displacement, angular velocity and angular acceleration of the rotor respectively, R is the stator resistance, ψ f is the permanent magnet flux, J, B, τ and T lp They represent the moment of inertia, viscous friction coefficient, electromagnetic torque and load torque of the permanent magnet synchronous motor respectively, t is the operating time of the joint module, is the derivative operation with respect to time t;

[0025] According to the dynamic characteristics of the harmonic reducer, when the flexibility of the harmonic reducer is ignored, there is the following linear relationship between its input and output ends:

[0026]

[0027] Among them, η is the transmission efficiency of the harmonic gear reducer, λ is the transmission ratio, T l Indicates the load torque on the output shaft of the joint module, T lp represents the load torque at the permanent magnet synchronous motor end in the joint module, q is the angular displacement of the permanent magnet synchronous motor rotor, and x represents the angular displacement of the joint module;

[0028] Based on the above formula (3) and formula (4), the dynamic equation of the joint module is derived as follows:

[0029]

[0030] in, x、 and They represent the angular displacement, angular velocity and angular acceleration of the joint module, respectively; J, B and τ represent the moment of inertia, viscous friction coefficient and electromagnetic torque of the permanent magnet synchronous motor, respectively; T l Represents the load torque on the output shaft of the joint module, T f represents the friction force in the harmonic reducer, η is the transmission efficiency of the harmonic gear reducer, λ is the transmission ratio, and t is the operating time of the joint module.

[0031] The establishment of the joint module super-local model includes the following steps:

[0032] Define a hyperlocal model:

[0033] x (v) (t) = F + αu(t),

[0034] Where x(t) and u(t) represent the system output and system control input respectively, F is the sum of the nonlinearity and uncertainty of the system; α is the control channel gain, t is the running time of the system; v represents the highest order of the system, which is 1 or 2;

[0035] Here we take v = 2, and the hyperlocal model of the joint module is:

[0036]

[0037] in, represents the angular acceleration of the joint module, F is the sum of the nonlinearity and uncertainty of the joint module, τ represents the electromagnetic torque of the permanent magnet synchronous motor in the joint module, and α is the control channel gain;

[0038] The hyperlocal model of the above joint module is rewritten into the following form, that is,

[0039]

[0040] Among them, x1 represents the angular displacement of the joint module, x2 represents the angular velocity of the joint module, F is the sum of the nonlinearity and uncertainty of the joint module, τ represents the electromagnetic torque of the permanent magnet synchronous motor in the joint module, α is the control channel gain, and t is the running time of the joint module. is the derivative operation with respect to time t;

[0041] The estimated value of the sum of nonlinearity and uncertainty of the joint module F is obtained by algebraic estimation method, which is:

[0042]

[0043] Among them, T F Indicates the size of the sliding window, which is the sampling step n F times, n F It is set according to the system conditions; δ represents the sampling step, α is the control channel gain, is the time interval [0,T F ] within the integral operation.

[0044] The design of the collaborative controller comprises the following steps:

[0045] Define the angular displacement error of the joint module as e1(t)=x(t)-x d (t), angular velocity error of the joint module Angular acceleration error of joint module

[0046] Where e1(t) is the error between the expected angular displacement and the actual angular displacement, x(t) is the actual angular displacement of the joint module, and x d (t) is the expected angular displacement of the joint module, e2(t) is the error between the expected angular velocity and the actual angular velocity, is the actual angular velocity of the joint module, is the expected angular velocity of the joint module, e3(t) is the error between the expected angular acceleration and the actual angular acceleration, is the actual angular acceleration of the joint module, is the expected angular acceleration of the joint module;

[0047] Construct the macro variable ψ and design the macro variable in the cooperative control into the form of proportional differential:

[0048] ψ=λ1e1(t)+λ2e2(t) (9)

[0049] Among them, ψ is a macro variable, λ1, λ2 are two positive constants to be designed, e1(t) is the error between the expected angular displacement and the actual angular displacement, and e2(t) is the error between the expected angular velocity and the actual angular velocity;

[0050] In order to ensure that the joint module system converges to the control manifold under the action of cooperative control, the dynamic evolution equation for the convergence of macro variables is defined as follows:

[0051]

[0052] Among them, ψ is the macro variable constructed above, T is the designed time constant, which represents the time for the state variable to converge to the control manifold through the dynamic process. It has a great influence on the convergence time of the system state. In theory, the smaller the value of T is, the faster the dynamic response speed of the system is, but its value is constrained by the stability requirements of the system.

[0053] Substituting formula (9) into formula (10) yields:

[0054] T(λ1e2(t)+λ2e3(t))+(λ1e1(t)+λ2e2(t))=0 (11)

[0055] Among them, λ1, λ2 are two positive constants to be designed, T is the designed time constant, e1(t) is the error between the expected angular displacement and the actual angular displacement, e2(t) is the error between the expected angular velocity and the actual angular velocity, and e3(t) is the error between the expected angular acceleration and the actual angular acceleration;

[0056] Based on the hyperlocal model (7) and formula (11) of the joint module established above, the coordinated control law of the joint module is derived to generate the electromagnetic torque reference value of the permanent magnet synchronous motor:

[0057]

[0058] in, represents the estimation of the sum of system nonlinearity and uncertainty, λ1,λ2 are two positive constants to be designed, T is the designed time constant, e1(t) is the error between the expected angular displacement and the actual angular displacement, e2(t) is the error between the expected angular velocity and the actual angular velocity, is the desired angular acceleration of the joint module, α is the control channel gain, τ * is the generated permanent magnet synchronous motor electromagnetic torque reference value.

[0059] Beneficial Effects

[0060] Compared with the prior art, the joint module collaborative control method based on the hyperlocal model of the present invention designs the controller based on the hyperlocal model, has the characteristic of being independent of the system model, and can effectively deal with the problem of control performance degradation caused by uncertainty factors in the joint module. The present invention is based on the establishment of the hyperlocal model of the joint module, and then designs the collaborative controller, the control structure is simple, and the dynamic and steady-state control performance of the joint module is effectively improved, and at the same time, it has strong robustness against internal and external interference of the system. BRIEF DESCRIPTION OF THE DRAWINGS

[0061] Figure 1 is a method sequence diagram of the present invention;

[0062] Figure 2 is a block diagram of the control method of the present invention;

[0063] Figure 3 A comparison chart of the step response simulation effects of the joint module provided in the example of the present invention.

[0064] Figure 4 A comparison chart of the sinusoidal tracking simulation effects of the joint module provided in the example of the present invention. DETAILED DESCRIPTION

[0065] In order to have a further understanding and recognition of the structural features and the effects achieved by the present invention, a preferred embodiment and accompanying drawings are used for detailed description as follows:

[0066] like Figure 1 As shown, the joint module collaborative control method based on the hyperlocal model described in the present invention comprises the following steps:

[0067] The first step is to obtain the operation data of the joint module: the angular displacement of the joint module is measured by the absolute value encoder on the output shaft of the joint module, and the angular velocity of the joint module is obtained by differential processing of the angular displacement.

[0068] The second step is to establish the dynamic equation of the joint module.

[0069] The joint module can be equivalent to a harmonic reducer and a permanent magnet synchronous motor. The driving control performance of the permanent magnet synchronous motor will greatly affect the control performance of the joint module, so it is necessary to take the model of the permanent magnet synchronous motor into consideration. By linking the mathematical models of the permanent magnet synchronous motor and the harmonic reducer, a unified joint module dynamics equation is established.

[0070] The dynamic equation of establishing the joint module comprises the following steps:

[0071] (1) Based on dynamic analysis, the joint module is equivalent to a permanent magnet synchronous motor and a harmonic reducer, and the mathematical model of the permanent magnet synchronous motor is set as:

[0072]

[0073] Among them, i d 、i q 、u d 、u q , L d , L q They represent the stator current, stator voltage and stator inductance of the d-axis and q-axis of the permanent magnet synchronous motor respectively, and n p represents the number of pole pairs, q, are the angular displacement, angular velocity and angular acceleration of the rotor respectively, R is the stator resistance, ψ f is the permanent magnet flux, J, B, τ and T lp They represent the moment of inertia, viscous friction coefficient, electromagnetic torque and load torque of the permanent magnet synchronous motor respectively, t is the operating time of the joint module, is the derivative operation with respect to time t.

[0074] (2) For the electromagnetic torque output by the permanent magnet synchronous motor, we have:

[0075]

[0076] Among them, i d 、i q 、u d 、u q , L d , L q They represent the stator current and stator inductance of the d-axis and q-axis of the permanent magnet synchronous motor, respectively. p represents the pole pair number, ψ f represents the permanent magnet flux, and τ represents the electromagnetic torque of the permanent magnet synchronous motor.

[0077] (3) According to the principle of magnetic field oriented control technology, for the surface mounted permanent magnet synchronous motor used in the joint module, the three-phase stator current synthesis vector is controlled on the q axis so that i d is zero, that is, i d =0, achieving maximum torque control per ampere current, so that the torque control has better dynamic and steady-state performance;

[0078] For the surface-mounted permanent magnet synchronous motor used in the joint module, there is L d =L q =L S , therefore, the mathematical model of the surface-mounted permanent magnet synchronous motor is:

[0079]

[0080] Among them, i d 、i q 、u d、u q , L d , L q They represent the stator current, stator voltage and stator inductance of the d-axis and q-axis of the permanent magnet synchronous motor respectively, and L S represents the stator inductance, n p represents the number of pole pairs, q, are the angular displacement, angular velocity and angular acceleration of the rotor respectively, R is the stator resistance, ψ f is the permanent magnet flux, J, B, τ and T lp They represent the moment of inertia, viscous friction coefficient, electromagnetic torque and load torque of the permanent magnet synchronous motor respectively, t is the operating time of the joint module, is the derivative operation with respect to time t.

[0081] (4) According to the dynamic characteristics of the harmonic reducer, when the flexibility of the harmonic reducer is ignored, there is the following linear relationship between its input and output ends:

[0082]

[0083] Among them, η is the transmission efficiency of the harmonic gear reducer, λ is the transmission ratio, T l Indicates the load torque on the output shaft of the joint module, T lp represents the load torque at the permanent magnet synchronous motor end in the joint module, q is the angular displacement of the permanent magnet synchronous motor rotor, and x represents the angular displacement of the joint module.

[0084] (5) Based on the above formulas (3) and (4), the dynamic equation of the joint module is derived as follows:

[0085]

[0086] in, x、 and They represent the angular displacement, angular velocity and angular acceleration of the joint module, respectively; J, B and τ represent the moment of inertia, viscous friction coefficient and electromagnetic torque of the permanent magnet synchronous motor, respectively; T l Represents the load torque on the output shaft of the joint module, T f represents the friction force in the harmonic reducer, η is the transmission efficiency of the harmonic gear reducer, λ is the transmission ratio, and t is the operating time of the joint module.

[0087] The third step is to establish a hyperlocal model of the joint module: According to the dynamic equation of the joint module, establish a hyperlocal model of the joint module.

[0088] Based on the joint module dynamics equation in the second step, the controller is designed. It can be found that in order to achieve high-performance control of the joint module, many high-precision parameters of the joint module are required. Insufficient parameter accuracy will lead to deterioration of control performance and even system instability. At the same time, the controller design based on the joint module dynamics equation cannot effectively deal with the influence of parameter changes during the operation of the joint module, which leads to a decrease in control accuracy. Therefore, it is extremely important to establish a hyperlocal model of the joint module based on the joint module dynamics equation in the second step. Relying on the hyperlocal model of the joint module can get rid of the dependence on many parameters of the joint module, and can handle the parameter changes during the operation of the joint module well, which greatly improves the robustness of the joint module control.

[0089] The establishment of the joint module super-local model includes the following steps:

[0090] (1) Define the hyperlocal model:

[0091] x (v) (t) = F + αu(t),

[0092] Where x(t) and u(t) represent the system output and system control input respectively, F is the sum of the nonlinearity and uncertainty of the system; α is the control channel gain, t is the running time of the system; v represents the highest order of the system, which is 1 or 2;

[0093] Here we take v = 2, and the hyperlocal model of the joint module is:

[0094]

[0095] in, represents the angular acceleration of the joint module, F is the sum of the nonlinearity and uncertainty of the joint module, τ represents the electromagnetic torque of the permanent magnet synchronous motor in the joint module, and α is the control channel gain.

[0096] (2) The hyperlocal model of the joint module is rewritten as follows:

[0097]

[0098] Among them, x1 represents the angular displacement of the joint module, x2 represents the angular velocity of the joint module, F is the sum of the nonlinearity and uncertainty of the joint module, τ represents the electromagnetic torque of the permanent magnet synchronous motor in the joint module, α is the control channel gain, and t is the running time of the joint module. is the derivative operation with respect to time t;

[0099] The estimated value of the sum of nonlinearity and uncertainty of the joint module F is obtained by algebraic estimation method, which is:

[0100]

[0101] Among them, T F Indicates the size of the sliding window, which is the sampling step n F times, n F It is set according to the system conditions; δ represents the sampling step, α is the control channel gain, is the time interval [0,T F ] within the integral operation.

[0102] The fourth step is to design a collaborative controller: Based on the hyperlocal model of the joint module, the collaborative controller is designed according to the collaborative control theory.

[0103] The basic idea of ​​cooperative control is to utilize the self-organizing ability and nonlinear characteristics of the system and to achieve cooperative control of the system by designing a suitable control manifold. The core is to use the nonlinear characteristics of the system to achieve control. The cooperative controller has low design difficulty, can generate smooth control signals, has good rapid response performance, and can effectively enhance the robustness of joint module control.

[0104] The design of the collaborative controller comprises the following steps:

[0105] (1) Define the angular displacement error of the joint module as e1(t) = x(t) - x d (t), angular velocity error of the joint module Angular acceleration error of joint module

[0106] Where e1(t) is the error between the expected angular displacement and the actual angular displacement, x(t) is the actual angular displacement of the joint module, and x d (t) is the expected angular displacement of the joint module, e2(t) is the error between the expected angular velocity and the actual angular velocity, is the actual angular velocity of the joint module, is the expected angular velocity of the joint module, e3(t) is the error between the expected angular acceleration and the actual angular acceleration, is the actual angular acceleration of the joint module, is the expected angular acceleration of the joint module.

[0107] (2) Construct the macro variable ψ and design the macro variable in the cooperative control into the form of proportional differential:

[0108] ψ=λ1e1(t)+λ2e2(t) (21)

[0109] Among them, ψ is a macro variable, λ1, λ2 are two positive constants to be designed, e1(t) is the error between the expected angular displacement and the actual angular displacement, and e2(t) is the error between the expected angular velocity and the actual angular velocity;

[0110] (3) In order to ensure that the joint module system converges to the control manifold under the action of cooperative control, the dynamic evolution equation for the convergence of macro variables is defined as follows:

[0111]

[0112] Among them, ψ is the macro variable constructed above, T is the designed time constant, which represents the time for the state variable to converge to the control manifold through the dynamic process. It has a great influence on the convergence time of the system state. In theory, the smaller the value of T is, the faster the dynamic response speed of the system is, but its value is constrained by the stability requirements of the system.

[0113] Substituting formula (9) into formula (10) yields:

[0114] T(λ1e2(t)+λ2e3(t))+(λ1e1(t)+λ2e2(t))=0 (23)

[0115] Among them, λ1, λ2 are two positive constants to be designed, T is the designed time constant, e1(t) is the error between the expected angular displacement and the actual angular displacement, e2(t) is the error between the expected angular velocity and the actual angular velocity, and e3(t) is the error between the expected angular acceleration and the actual angular acceleration.

[0116] (4) Based on the hyperlocal model (7) and formula (11) of the joint module established above, the coordinated control law of the joint module is derived to generate the electromagnetic torque reference value of the permanent magnet synchronous motor:

[0117]

[0118] in, represents the estimation of the sum of system nonlinearity and uncertainty, λ1,λ2 are two positive constants to be designed, T is the designed time constant, e1(t) is the error between the expected angular displacement and the actual angular displacement, e2(t) is the error between the expected angular velocity and the actual angular velocity, is the desired angular acceleration of the joint module, α is the control channel gain, τ * is the generated permanent magnet synchronous motor electromagnetic torque reference value.

[0119] The fifth step is to realize the collaborative control of the joint module: based on the obtained angular displacement and angular velocity information of the joint module, the output electromagnetic torque of the permanent magnet synchronous motor in the joint module is obtained through the collaborative controller, thereby driving the joint module to reach the desired angular displacement.

[0120] In order to verify the effectiveness of the joint module collaborative control method based on the super local model described in the present invention, Matlab / Simulink simulation was carried out. The specific process of Matlab / Simulink simulation is as follows: Figure 2 The simulation model of the joint module based on the hyperlocal model collaborative control is shown in Table 1. The parameters of the joint module involved in the simulation are shown in Table 1.

[0121] Table 1 Joint module model parameters

[0122] Parameter name Symbolic representation Numeric unit Joint module displacement x - rad Joint module moment of inertia J <![CDATA[1.65×10 -3 ]]> <![CDATA[kg·m 2 ]]> PMSM viscous friction coefficient B <![CDATA[8×10 -3 ]]> Nm / rad / sec PMSM rotor flux <![CDATA[ψ f ]]> 0.025 volts / rad / sec PMSM pole pairs <![CDATA[n p ]]> 6 - Harmonic reducer reduction ratio λ 101 - Harmonic reducer transmission efficiency η 0.95 -

[0123] like Figure 3 As shown, in the simulation, the expectation is given as a step signal, and the control effects of the two different controllers on the joint module are compared between the traditional PID and the hyperlocal model collaborative control based on the present invention. It can be seen from the figure that the hyperlocal model collaborative control based joint module has a faster response speed to the step signal and no overshoot occurs, and the steady-state accuracy is also significantly improved compared with the PID control.

[0124] like Figure 4 As shown in the figure, the input reference signal is a sinusoidal signal. At the beginning of the simulation, the influence of the two controllers on the joint module is consistent with the step signal. When the system is stable, the cooperative control based on the super-local model has a smaller steady-state error than the PID control. The simulation results show that the designed controller has good dynamic performance, can achieve fast tracking, and greatly improves the steady-state accuracy.

[0125] The above shows and describes the basic principles, main features and advantages of the present invention. Those skilled in the art should understand that the present invention is not limited to the above embodiments. The above embodiments and descriptions only describe the principles of the present invention. The present invention may be subject to various changes and improvements without departing from the spirit and scope of the present invention. These changes and improvements fall within the scope of the present invention. The scope of protection claimed by the present invention is defined by the attached claims and their equivalents.

Claims

1. A joint module collaborative control method based on a hyperlocal model, characterized in that: The following steps are involved: 11) Acquisition of joint module operation data: The angular displacement of the joint module is measured by the absolute encoder on the output shaft of the joint module, and the angular velocity of the joint module is obtained by differential processing of the angular displacement; 12) Establish the dynamic equation of the joint module; The dynamic equation of establishing the joint module comprises the following steps: 121) Based on dynamic analysis, the joint module is equivalent to a permanent magnet synchronous motor and a harmonic reducer, and the mathematical model of the permanent magnet synchronous motor is: Among them, i d 、i q 、u d 、u q , L d , L q They represent the stator current, stator voltage and stator inductance of the d-axis and q-axis of the permanent magnet synchronous motor respectively, and n p represents the number of pole pairs, q, are the angular displacement, angular velocity and angular acceleration of the rotor respectively, R is the stator resistance, ψ f is the permanent magnet flux, J, B, τ and T lp They represent the moment of inertia, viscous friction coefficient, electromagnetic torque and load torque of the permanent magnet synchronous motor respectively, t is the operating time of the joint module, is the derivative operation with respect to time t; 122) For the electromagnetic torque of permanent magnet synchronous motor, we have: Among them, i d 、i q 、u d 、u q , L d , L q They represent the stator current and stator inductance of the d-axis and q-axis of the permanent magnet synchronous motor, respectively. p represents the pole pair number, ψ f represents the permanent magnet flux, τ represents the electromagnetic torque of the permanent magnet synchronous motor; 123) According to the principle of magnetic field oriented control technology, for the surface mounted permanent magnet synchronous motor used in the joint module, the three-phase stator current synthesis vector is controlled on the q axis to make i d is zero, that is, i d =0, achieving maximum torque control per ampere current, so that the torque control has better dynamic and steady-state performance; For the surface-mounted permanent magnet synchronous motor used in the joint module, there is L d =L q =L S , therefore, the mathematical model of the surface-mounted permanent magnet synchronous motor is: Among them, i d 、i q 、u d 、u q , L d , L q They represent the stator current, stator voltage and stator inductance of the d-axis and q-axis of the permanent magnet synchronous motor respectively, and L S represents the stator inductance, n p represents the number of pole pairs, q, are the angular displacement, angular velocity and angular acceleration of the rotor respectively, R is the stator resistance, ψ f is the permanent magnet flux, J, B, τ and T lp They represent the moment of inertia, viscous friction coefficient, electromagnetic torque and load torque of the permanent magnet synchronous motor respectively, t is the operating time of the joint module, is the derivative operation with respect to time t; 124) According to the dynamic characteristics of the harmonic reducer, when the flexibility of the harmonic reducer is ignored, there is the following linear relationship between its input and output ends: Among them, η is the transmission efficiency of the harmonic gear reducer, λ is the transmission ratio, T l Indicates the load torque on the output shaft of the joint module, T lp represents the load torque at the permanent magnet synchronous motor end in the joint module, q is the angular displacement of the permanent magnet synchronous motor rotor, and x represents the angular displacement of the joint module; 125) Based on the above formula (3) and formula (4), the dynamic equation of the joint module in step 12) is derived as follows: Where H(x,t)=λJ, x、 and They represent the angular displacement, angular velocity and angular acceleration of the joint module, respectively; J, B and τ represent the moment of inertia, viscous friction coefficient and electromagnetic torque of the permanent magnet synchronous motor, respectively; T l Represents the load torque on the output shaft of the joint module, T f represents the friction force in the harmonic reducer, η is the transmission efficiency of the harmonic gear reducer, λ is the transmission ratio, and t is the operating time of the joint module; 13) Establishment of the hyperlocal model of the joint module: According to the dynamic equation of the joint module, the hyperlocal model of the joint module is established; 14) Design of collaborative controller: Based on the hyperlocal model of joint modules, the collaborative controller is designed according to collaborative control theory; 15) Implementation of collaborative control of joint modules: Based on the obtained angular displacement and angular velocity information of the joint module, the electromagnetic torque of the permanent magnet synchronous motor in the joint module is obtained through the collaborative controller, thereby driving the joint module to reach the desired angular displacement.

2. The joint module collaborative control method based on the hyperlocal model according to claim 1 is characterized in that: The establishment of the joint module super-local model includes the following steps: 21) Define the hyperlocal model: x (v) (t)=F+αu(t), Where x(t) and u(t) represent the system output and system control input respectively, F is the sum of the nonlinearity and uncertainty of the system; α is the control channel gain, t is the running time of the system; v represents the highest order of the system, which is 1 or 2; Here we take v = 2, and the hyperlocal model of the joint module is: in, represents the angular acceleration of the joint module, F is the sum of the nonlinearity and uncertainty of the joint module, τ represents the electromagnetic torque of the permanent magnet synchronous motor in the joint module, and α is the control channel gain; 22) The hyperlocal model of the above joint module is rewritten into the following form, namely: Among them, x1 represents the angular displacement of the joint module, x2 represents the angular velocity of the joint module, F is the sum of the nonlinearity and uncertainty of the joint module, τ represents the electromagnetic torque of the permanent magnet synchronous motor in the joint module, α is the control channel gain, and t is the running time of the joint module. is the derivative operation with respect to time t; The estimated value of the sum of nonlinearity and uncertainty of the joint module F is obtained by algebraic estimation method, which is: Among them, T F Indicates the size of the sliding window, which is the sampling step n F times, n F It is set according to the system conditions; δ represents the sampling step, α is the control channel gain, is the time interval [0,T F ] within the integral operation.

3. The joint module collaborative control method based on the hyperlocal model according to claim 1 is characterized in that: The design of the collaborative controller comprises the following steps: 31) Define the angular displacement error of the joint module as e1(t)=x(t)-x d (t), angular velocity error of the joint module Angular acceleration error of joint module Where, e1(t) is the error between the expected angular displacement and the actual angular displacement, x(t) is the actual angular displacement of the joint module, and x d (t) is the expected angular displacement of the joint module, e2(t) is the error between the expected angular velocity and the actual angular velocity, is the actual angular velocity of the joint module, is the expected angular velocity of the joint module, e3(t) is the error between the expected angular acceleration and the actual angular acceleration, is the actual angular acceleration of the joint module, is the expected angular acceleration of the joint module; 32) Construct the macro variable ψ and design the macro variable in the cooperative control into the form of proportional differential: ψ=λ1e1(t)+λ2e2(t) (9) Among them, ψ is a macro variable, λ1, λ2 are two positive constants to be designed, e1(t) is the error between the expected angular displacement and the actual angular displacement, and e2(t) is the error between the expected angular velocity and the actual angular velocity; 33) In order to ensure that the joint module converges to the control manifold under the action of collaborative control, the dynamic evolution equation for the convergence of the macro variables is defined as: Among them, ψ is the macro variable constructed above, T is the designed time constant, which represents the time for the state variable to converge to the control manifold through the dynamic process. It has a great influence on the convergence time of the system state. In theory, the smaller the value of T is, the faster the dynamic response speed of the system is, but its value is constrained by the stability requirements of the system. Substituting formula (9) into formula (10) yields: T(λ1e2(t)+λ2e3(t))+(λ1e1(t)+λ2e2(t))=0 (11) Among them, λ1, λ2 are two positive constants to be designed, T is the designed time constant, e1(t) is the error between the expected angular displacement and the actual angular displacement, e2(t) is the error between the expected angular velocity and the actual angular velocity, and e3(t) is the error between the expected angular acceleration and the actual angular acceleration; 34) Based on the hyperlocal model (7) and formula (11) of the joint module established above, the coordinated control law of the joint module is derived to generate the electromagnetic torque reference value of the permanent magnet synchronous motor: in, represents the estimation of the sum of system nonlinearity and uncertainty, λ1,λ2 are two positive constants to be designed, T is the designed time constant, e1(t) is the error between the expected angular displacement and the actual angular displacement, e2(t) is the error between the expected angular velocity and the actual angular velocity, is the desired angular acceleration of the joint module, α is the control channel gain, τ * is the generated permanent magnet synchronous motor electromagnetic torque reference value.

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