Multi-joint robot control method and system based on intelligent large health

Abstract

The invention relates to the technical field of exoskeleton robots, and provides a multi-joint robot control method and system based on intelligent mass health, and the method comprises the steps: S1, obtaining a behavior instruction which comprises a leg motion behavior of a user, and converting the behavior instruction into a first target motion and a second target motion; s2, acquiring a first behavior parameter required for executing the first target action and a second behavior parameter required for executing the second target action; s3, adjusting the target rotating speed of a first motor according to the first behavior parameter to drive a first joint to control a first leg actuator to execute a first target action, and synchronously adjusting the target rotating speed of a second motor according to the second behavior parameter to drive a second joint to control a second leg actuator to execute a second target action, the behavior parameters can be adjusted according to the behavior instruction, and the multi-joint robot is optimized while the motor is controlled according to the behavior parameters.

Description

Technical Field

[0001] The present invention relates to the technical field of exoskeleton robots, and in particular to a multi-joint robot control method and system based on intelligent health. Background Art

[0002] With the rapid development of society, the intelligent health industry has gradually emerged. The intelligent health industry mainly includes medical device manufacturing, health device manufacturing, health care and rehabilitation products, health management and other sub-industries. Among them, the medical device manufacturing industry and the health device manufacturing industry have made major breakthroughs, especially in the field of multi-joint robot technology and wearable devices. Multi-joint rehabilitation robots have gradually become a hot spot for research and application. Multi-joint rehabilitation robots, especially exoskeleton robots for lower limbs, are designed to improve the daily quality and work efficiency of users by enhancing human strength, improving athletic ability or assisting those with limited mobility.

[0003] Traditional lower limb assistive devices, such as crutches and wheelchairs, provide help to a certain extent, but they have many limitations, such as strong dependence and lack of flexibility. In contrast, multi-joint leg exoskeleton robots can more closely fit human movements through precise mechanical structures, advanced sensor technology and intelligent control algorithms, achieving a more natural and efficient assistive effect.

[0004] However, there are still some challenges in the control methods of existing multi-joint leg rehabilitation robots. On the one hand, how to accurately understand and execute the user's intentions, such as moving forward, backward, and turning, is the key to achieving good human-computer interaction. On the other hand, how to dynamically adjust the robot's behavioral parameters based on the user's real-time feedback to ensure comfort and safety is also an urgent problem to be solved.

[0005] In terms of control algorithms, although traditional PID control methods are simple and effective, they often fail to achieve ideal control effects when faced with complex and changing motion requirements. Especially when robots need to perform extreme tasks such as high speed and heavy load, how to ensure the stable operation and high-efficiency output of the motor has become an important research topic.

[0006] In summary, the aim is to develop a scheme that can adjust the behavior parameters according to the behavior instructions and optimize the multi-joint robot while controlling the motors according to the behavior parameters. Summary of the invention

[0007] In view of the above-mentioned defects, the purpose of the present invention is to propose a multi-joint robot control method and system based on intelligent health, aiming to develop a control scheme that can adjust behavior parameters according to behavior instructions and optimize the multi-joint robot while controlling the motor according to the behavior parameters.

[0008] To achieve this object, the present invention adopts the following technical solutions:

[0009] A multi-joint robot control method based on intelligent big health is applied to the multi-joint robot, the multi-joint robot comprising a first joint, a second joint, a first motor, a second motor, a first leg actuator and a second leg actuator;

[0010] The method comprises: step S1: obtaining a behavior instruction, the behavior instruction comprising a user's leg movement behavior, and converting the behavior instruction into a first target movement and a second target movement;

[0011] Step S2: Acquire a first behavior parameter required to perform a first target action and a second behavior parameter required to perform a second target action;

[0012] Step S3: Adjust the target speed of the first motor according to the first behavior parameter to drive the first joint to control the first leg actuator to perform the first target action, and synchronously adjust the target speed of the second motor according to the second behavior parameter to drive the second joint to control the second leg actuator to perform the second target action.

[0013] Preferably, the leg movements of the user include: fast walking, slow walking, jogging and squatting.

[0014] Furthermore, converting the behavior instruction into the first target action and the second target action includes:

[0015] When the leg motion of the user is fast walking, slow walking or jogging, if the current leg is not the supporting leg, the first target motion includes the first leg actuator swinging forward with the first joint as the origin, and the second target motion includes the second leg actuator swinging upward with the second joint as the origin; if the current leg is the supporting leg, the first target motion includes the first leg actuator swinging backward with the first joint as the origin, and the second target motion includes the second leg actuator swinging downward with the second joint as the origin;

[0016] When the user's leg movement is squatting, when squatting, the first target movement includes the first leg actuator swinging forward with the first joint as the origin, and the second target movement includes the second leg actuator swinging downward with the second joint as the origin; when standing up, the first target movement includes the first leg actuator swinging backward with the first joint as the origin, and the second target movement includes the second leg actuator swinging upward with the second joint as the origin.

[0017] Further, the first behavior parameter includes a swing angle of the first leg actuator relative to the first joint, and the second behavior parameter includes a swing angle of the second leg actuator relative to the second joint;

[0018] When the user's leg motion is fast walking, slow walking or jogging, the relationship is satisfied:

[0019] S=L1(sinθ 11 +sinθ 21 )+L2(sinθ 12 +sinθ 22 );

[0020] Where S represents the distance between the first leg actuators at the current moment, L1 represents the length of the first leg actuator, L2 represents the length of the second leg actuator, θ 11 represents the swing angle of the first leg actuator corresponding to the non-supporting leg with the first joint as the origin, θ 12 represents the swing angle of the second leg actuator corresponding to the non-supporting leg with the second joint as the origin, θ 21 represents the swing angle of the first leg actuator corresponding to the supporting leg with the first joint as the origin, θ 22 represents the swing angle of the second leg actuator corresponding to the supporting leg with the second joint as the origin;

[0021] When the user's leg movement is squatting, the relationship is satisfied:

[0022] H=L1cosθ 31 +L2cosθ 32 ;

[0023] Where L1 represents the length of the first leg actuator, L2 represents the length of the second leg actuator, H is the current squat distance, θ 31 represents the swing angle of the first leg actuator with the first joint as the origin, θ 32 Indicates the swing angle of the second leg actuator with the second joint as the origin.

[0024] Further, the first behavior parameter and the second behavior parameter further include frequencies at which the first leg actuator and the second leg actuator respectively perform the first target action and the second target action;

[0025] The target speed of the first motor and the target speed of the second motor required for the first leg actuator to perform the first target action and the second leg actuator to perform the second target action respectively satisfy the relationship:

[0026]

[0027] Among them, f represents the frequency of the leg actuator performing the target action, N represents the number of revolutions that the motor output end needs to rotate when the leg actuator completes one action, Δθ represents the angle change of the leg actuator to complete one action, and 60 is a constant used for unit conversion.

[0028] Further, in step S3, when the target speed of the first motor is adjusted according to the first behavior parameter and the target speed of the second motor is adjusted according to the second behavior parameter, it includes:

[0029] Determine whether the target speed of the first motor or the second motor is lower than the preset motor turning speed, and if so, use the MTPA current control method to generate corresponding d-axis and q-axis currents;

[0030] The d-axis current and the q-axis current are input into the controller to obtain the d-axis and q-axis voltages, and the first motor or the second motor is driven to operate according to the d-axis and q-axis voltages.

[0031] Further, in step S3, when the target speed of the first motor is adjusted according to the first behavior parameter and the target speed of the second motor is adjusted according to the second behavior parameter, it includes:

[0032] Determine whether the target speed of the first motor or the second motor is higher than the preset motor turning speed. If so, obtain the d-axis current according to the motor's operating parameters, design parameters and target speed, and obtain the q-axis current limit value according to the maximum current and the d-axis current;

[0033] The d-axis current and the q-axis current are input into the controller to obtain the d-axis and q-axis voltages, and the first motor or the second motor is driven to operate according to the d-axis and q-axis voltages.

[0034] Furthermore, the operating parameters include: a given current of the q-axis, a feedback current of the q-axis;

[0035] The design parameters include: rated current of the motor, rated speed of the motor;

[0036] The steps of obtaining the current of the d-axis are as follows:

[0037] Get the given current I of the q axis in real time qRef , the given current I qRef Input to the low-pass filter to get the first parameter I q ′ Ref ;

[0038] Get the feedback current I of the q axis in real time q , the given current I q Input to the low-pass filter to obtain the second parameter I q ′ ;

[0039] Get the first parameter I q ′ Ref With the second parameter I q ′ The difference E is used as the input of the PI controller to obtain the current feedback given term D1;

[0040] According to the rated current I n and rated speed ω n Calculate the amplification factor Kc of the current feedforward given term;

[0041] Obtain the current speed increment, adjust the speed increment by the amplification factor Kc, and obtain the current feedback given item D2;

[0042] The d-axis current I is obtained by adding the feedback given term D1 and the feedforward given term D2. d .

[0043] A multi-joint robot control system based on intelligent health, applied to the control method according to any one of claims 1 to 8, comprising a first joint, a second joint, a first motor, a second motor, a first leg actuator and a second leg actuator, the system comprising:

[0044] An instruction conversion module is used to obtain a behavior instruction, the behavior instruction includes a leg movement behavior of the user, and convert the behavior instruction into a first target action and a second target action;

[0045] A behavior parameter acquisition module, used to acquire a first behavior parameter required to perform a first target action and a second behavior parameter required to perform a second target action;

[0046] An action execution module is used to adjust the target speed of the first motor according to the first behavior parameter to drive the first joint to control the first leg actuator to perform the first target action, and synchronously adjust the target speed of the second motor according to the second behavior parameter to drive the second joint to control the second leg actuator to perform the second target action.

[0047] One of the above technical solutions has the following advantages or beneficial effects:

[0048] This solution can convert the user's leg movement behavior into the corresponding target action, so that the exoskeleton robot can more naturally imitate and support the user's natural movement, and can handle complex movement patterns and changes, such as gait transitions and squatting movements, so that the robot can effectively support the user's movement needs in various activity scenarios. By adjusting the motor speed by frequency and angle changes, and adjusting the motor control strategy accordingly according to the motor speed, more precise action execution can be achieved. For high frequency or large stride, the current of the d-axis and q-axis is adjusted to ensure the stable operation of the motor under high load and high speed, thereby ensuring the movement efficiency and safety of the exoskeleton robot; in the case of low frequency and stride, the MTPA method can more effectively utilize the motor's power output, thereby reducing energy consumption and extending the life of the motor. BRIEF DESCRIPTION OF THE DRAWINGS

[0049] Figure 1 is a flow chart of a multi-joint robot control method based on intelligent health provided by an embodiment of the present invention;

[0050] Figure 2 It is a structural schematic diagram of a multi-joint robot control system based on intelligent health provided by an embodiment of the present invention;

[0051] Figure 3 It is a walking schematic diagram of a multi-joint robot control method based on intelligent health at a certain moment provided by an embodiment of the present invention;

[0052] Figure 4 It is a schematic diagram of squatting at a certain moment of the multi-joint robot control method based on intelligent health provided by an embodiment of the present invention;

[0053] Figure 5 It is a schematic diagram of a single leg structure of a multi-joint robot applied in the multi-joint robot control method based on intelligent health provided in an embodiment of the present invention. DETAILED DESCRIPTION

[0054] Embodiments of the present invention are described in detail below, examples of which 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 only used to explain the present invention, and cannot be understood as limiting the present invention.

[0055] In the description of the present invention, it is to be understood that the terms “center”, “longitudinal”, “lateral”, “length”, “width”, “thickness”, “up”, “down”, “left”, “right”, “vertical”, “horizontal”, “top”, “bottom”, “inside”, “outside”, “axial”, “radial”, “circumferential”, etc., indicating orientations or positional relationships based on the orientations or positional relationships shown in the accompanying drawings, are only for the convenience of describing the present invention and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore should not be understood as a limitation on the present invention.

[0056] In addition, the terms "first" and "second" are used for descriptive purposes only and should not be understood as indicating or implying relative importance or implicitly indicating the number of the indicated technical features. Thus, a feature defined as "first" or "second" may explicitly or implicitly include one or more of the features. In the description of the present invention, unless otherwise specified, "plurality" means two or more.

[0057] In the description of the present invention, it should be noted that, unless otherwise clearly specified and limited, the terms "installed", "connected", and "connected" should be understood in a broad sense, for example, it can be a fixed connection, a detachable connection, or an integral connection; it can be a direct connection, or an indirect connection through an intermediate medium, or it can be the internal communication of two components. For ordinary technicians in this field, the specific meanings of the above terms in the present invention can be understood according to specific circumstances.

[0058] like Figure 1 As shown, a preferred embodiment of the present application is a multi-joint robot control method based on intelligent big health, which is applied to the multi-joint robot, and the multi-joint robot includes a first joint, a second joint, a first motor, a second motor, a first leg actuator and a second leg actuator;

[0059] The method comprises:

[0060] Step S1: Obtaining a behavior instruction, the behavior instruction includes the user's leg movement behavior, and converting the behavior instruction into a first target action and a second target action;

[0061] Step S2: Acquire a first behavior parameter required to perform a first target action and a second behavior parameter required to perform a second target action;

[0062] Step S3: Adjust the target speed of the first motor according to the first behavior parameter to drive the first joint to control the first leg actuator to perform the first target action, and synchronously adjust the target speed of the second motor according to the second behavior parameter to drive the second joint to control the second leg actuator to perform the second target action.

[0063] Specifically, in this embodiment, the first joint and the second joint are arranged at the knee joint (such as Figure 3 X1 and X2), X1 and X2 are the knee joint of the non-supporting foot and the knee joint of the supporting foot, respectively. In this embodiment, Figure 5 As shown, A1 is the first motor, A2 is the second motor, L1 is the first leg actuator, L2 is the second leg actuator, B1 is the first joint, B2 is the second joint, and the multi-joint robot can be understood as the following existing structure, specifically including: taking a single leg as an example, the first leg actuator is installed on the calf, the second leg actuator is installed on the thigh, the first joint is set on one side of the knee joint, the first joint is connected to the first leg actuator, and the first motor outputs power to drive the output end of the first joint to rotate, thereby driving the first leg actuator to swing back and forth with the knee joint as the center point, and perform To drive the calf to swing back and forth, similarly, the second joint is arranged on the other side of the knee joint, opposite to the first joint, and the second joint is connected to the second leg actuator, and the output power is driven by the second motor to drive the output end of the second joint to rotate, thereby driving the second leg actuator to swing back and forth with the knee joint as the center, and then driving the thigh to swing back and forth; the two motors independently control the two joints to respectively drive the combined coordinated movement of the first leg actuator and the second leg actuator, and use the above-mentioned existing structure to lend force to the entire leg, thereby assisting in driving the entire leg to perform actions such as walking or running.

[0064] In step S1, the behavior instruction can be input by the user, which can be understood here as the user inputting the corresponding behavior instruction through the client. In this technical solution, the behavior instruction input by the user is converted into the output of the motor by the following method, so as to control the multiple components of the above-mentioned existing robot to assist the user in walking. Specifically, the behavior instruction can be the user's leg action behavior, such as fast walking, slow walking, trotting, running and squatting, etc., and such actions are converted into actions to be performed by the first leg actuator and the second leg actuator respectively. The first target action and the second target action are specific conversions of the user's leg actions. In one embodiment, the walking instruction is slow walking, and the slow walking action is decomposed into the action of taking a step forward, that is, lifting and landing of a single leg. The lifting action is further decomposed into the action that the calf and thigh need to perform, that is, the calf and thigh are lifted up and forward. At this time, the first leg actuator needs to swing forward and lift up, so the forward swing and lift up are the first target action, and the second leg actuator needs to swing forward, and the forward swing is the second target action.

[0065] In step S2, after determining the action to be performed by the leg actuator in step S1, it is necessary to determine the specific values ​​or methods required to perform the target, that is, behavioral parameters, such as angle, speed, torque, frequency and stride, etc. These parameters help determine how the motor, joint and actuator work to achieve the desired action effect, wherein the first target action corresponds to the first behavioral parameter, and the second target action corresponds to the second behavioral parameter;

[0066] In one of the embodiments mentioned above, when the behavior instruction is to walk slowly, the second target action is to lift forward, then the behavior parameters of the second target action are the direction and angle of the swing of the second leg actuator with the knee joint as the center, the torque required for the second joint to rotate, the speed of the motor, etc.

[0067] In step S3, the target speed is the speed that the motor should reach when performing the target action. Adjusting the speed of the motor can accurately control the movement of the joint. The speed of the motor is adjusted so that the first joint and the second joint operate within the required angle and range of motion, thereby controlling the corresponding leg actuator. In addition, during the driving process, the target speeds of the two motors are adjusted at the same time to reduce delays and asynchronism problems and improve the coordination and smoothness of the robot's execution of actions.

[0068] This solution can convert the user's leg movement behavior into the corresponding target action, so that the exoskeleton robot can more naturally imitate and support the user's natural movement, thereby assisting and supporting the user's leg rehabilitation. It can handle complex movement patterns and changes, such as gait transitions and squatting movements, so that the robot can effectively support the user's movement needs in various activity scenarios. By adjusting the motor speed with behavioral parameters, more precise action execution can be achieved.

[0069] Preferably, the leg movements of the user include: fast walking, slow walking, jogging and squatting.

[0070] Among them, brisk walking is a fast gait with fast steps but not running, and usually requires moderate leg swing; slow walking is a slow gait with slow steps and relatively small leg swing; trotting is a gait slightly faster than brisk walking, involving a higher step frequency and a larger leg swing; squatting is the action of squatting down and then standing up from a standing position, which requires a larger leg range of motion and torque.

[0071] Furthermore, converting the behavior instruction into the first target action and the second target action includes:

[0072] When the leg motion of the user is fast walking, slow walking or jogging, if the current leg is not the supporting leg, the first target motion includes the first leg actuator swinging forward with the first joint as the origin, and the second target motion includes the second leg actuator swinging upward with the second joint as the origin; if the current leg is the supporting leg, the first target motion includes the first leg actuator swinging backward with the first joint as the origin, and the second target motion includes the second leg actuator swinging downward with the second joint as the origin;

[0073] When the user's leg movement is squatting, when squatting, the first target movement includes the first leg actuator swinging forward with the first joint as the origin, and the second target movement includes the second leg actuator swinging downward with the second joint as the origin; when standing up, the first target movement includes the first leg actuator swinging backward with the first joint as the origin, and the second target movement includes the second leg actuator swinging upward with the second joint as the origin.

[0074] Specifically, the walking patterns of fast walking, slow walking and jogging are similar, so the leg actuators operate in the same way. When the leg is not the supporting leg, the second leg actuator needs to swing upward to simulate the real way of walking, that is, to simulate the natural lift of the thigh when walking, and the first leg actuator swings forward to simulate the forward swing action in the human gait, providing forward horizontal displacement. By simulating the natural forward swing action and lift, the gait is made more natural, imitating the real walking behavior and improving the naturalness of the gait.

[0075] When the leg is the supporting leg, when the current leg is in the supporting state (that is, the leg with the sole of the foot on the ground), the first leg actuator swings backward. This action simulates the backward swinging action of the leg when walking, providing forward power and support. At the same time, the knee also needs to be adjusted to provide stable support. The second leg actuator swings downward to simulate the natural bending action of the knee in the supporting state, enhance the stability of the gait, and enable the supporting leg to provide sufficient backward thrust when supporting the body to avoid falling or instability.

[0076] During the squatting process, the first leg actuator swings forward, which helps simulate the forward leaning of the legs when squatting. At the same time, the second leg actuator swings downward to simulate the natural bending of the thigh when squatting, supporting the naturalness and smoothness of the squatting action, making the overall squatting action conform to the biomechanical characteristics and assisting users in rehabilitation training.

[0077] During the standing process, the first leg actuator swings backwards, simulating the backward swing of the calf when people return to standing from a squatting state. At the same time, the second leg actuator swings upwards, simulating the natural extension of the thigh when standing up, making the transition from squatting to standing smooth and giving the user a better rehabilitation experience.

[0078] Further, the first behavior parameter includes a swing angle of the first leg actuator relative to the first joint, and the second behavior parameter includes a swing angle of the second leg actuator relative to the second joint;

[0079] When the user's leg motion is fast walking, slow walking or jogging, the relationship is satisfied:

[0080] S=L1(sinθ 11 +sinθ 21 )+L2(sinθ 12 +sinθ 22 );

[0081] Where S represents the distance between the first leg actuators at the current moment, L1 represents the length of the first leg actuator, L2 represents the length of the second leg actuator, θ 11 represents the swing angle of the first leg actuator corresponding to the non-supporting leg with the first joint as the origin, θ 12 represents the swing angle of the second leg actuator corresponding to the non-supporting leg with the second joint as the origin, θ 21 represents the swing angle of the first leg actuator corresponding to the supporting leg with the first joint as the origin, θ 22 represents the swing angle of the second leg actuator corresponding to the supporting leg with the second joint as the origin;

[0082] When the user's leg movement is squatting, the relationship is satisfied:

[0083] H=L1cosθ 31 +L2cosθ 32 ;

[0084] Where L1 represents the length of the first leg actuator, L2 represents the length of the second leg actuator, H is the current squat distance, θ 31 represents the swing angle of the first leg actuator with the first joint as the origin, θ 32 Indicates the swing angle of the second leg actuator with the second joint as the origin.

[0085] Specifically, the first joint controls the first leg actuator, so the leg actuator uses the corresponding joint as a reference during calculation, and the swing angle of the leg actuator reflects the stride of the user's leg movement, such as Figure 3 As shown, Figure 3The state shown is the moment when the swing angle of the leg actuator in this embodiment is the largest. The swing angle of the leg actuator changes all the time during the movement, so S changes all the time. X1 and X2 both contain the first joint and the second joint. The leg where X1 is located is the non-support leg, and the leg where X2 is located is the support leg. When S reaches the maximum, it is the stride of the leg controller to perform the target action. The first joint and the second joint are both in the vertical direction, for example, L1 = 0.5m, L2 = 0.6m, θ 11 =17°,θ 12 =42°,θ 21 =32°,θ 22 =18°, S is 1m.

[0086] like Figure 4 As shown, Figure 4 This is a schematic diagram of the leg structure at a certain moment of squatting in this embodiment, that is, H = L1cosθ 31 +L2cosθ 32 , the rightmost dashed line (not marked) is the height when standing, θ 32 =29°,θ 31 =36°, at this time H is 0.93m.

[0087] Further, the first behavior parameter and the second behavior parameter further include frequencies at which the first leg actuator and the second leg actuator respectively perform the first target action and the second target action;

[0088] The target speed of the first motor and the target speed of the second motor required for the first leg actuator to perform the first target action and the second leg actuator to perform the second target action respectively satisfy the relationship:

[0089]

[0090] Among them, f represents the frequency of the leg actuator performing the target action, N represents the number of revolutions that the motor needs to rotate when the leg actuator completes one action, Δθ represents the angle change of the leg actuator to complete one action, and 60 is a constant used for unit conversion.

[0091] Specifically, Figure 3 As shown, in this embodiment, the Δθ when the swing angle of the first leg actuator is the largest is θ 11 +θ 21 =49°, the target speed of the first motor is Where f is the preset leg frequency and 60 is the factor used to convert the frequency f from Hertz (Hz) to revolutions per minute (RPM).

[0092] Furthermore, in step S3, because the target speed of the motor needs to be continuously adjusted according to the behavior parameter, there may be a situation where the target speed of the motor that needs to be adjusted next time is significantly increased compared to the current target speed of the motor. When the target speed of the motor exceeds the turning speed of the motor, in order to meet the significant speed increase and stability during the increase, it is necessary to enter the weak magnetic control stage;

[0093] Therefore, if the target speed of the first motor or the second motor is lower than the preset motor turning speed, the MTPA current control method is used to generate the corresponding d-axis and q-axis currents;

[0094] The d-axis current and the q-axis current are input into the controller to obtain the d-axis and q-axis voltages, and the first motor or the second motor is driven to operate according to the d-axis and q-axis voltages.

[0095] Specifically, in order to use the minimum current to generate the maximum motor speed, the MTPA current control method is adopted, in which the output current I is divided into the current I output to the d-axis d And the current I output to the q axis q , where the current I q The main control is the current in the torque direction, where the current I d The main control is the current in the direction of the magnetic field. This embodiment is mainly to weaken the motor magnetic field and reduce the back electromotive force when the power input voltage is limited, so as to achieve the purpose of increasing the motor speed. For this reason, in the present invention, it is first determined whether the current speed is lower than the turning speed. Because when the current speed is lower than the turning speed, it means that the motor is still running in the constant torque area, and there is no need to reduce the motor back electromotive force or increase the speed by weakening the magnetic flux. At this time, the MTPA method is used to reduce the current I d Set it to 0 and then calculate the minimum current I q To generate as much torque as possible, so that the motor can quickly increase the speed, so that the current speed rises rapidly, because in I d = 0, the motor's d-axis current is always zero, reducing the electromagnetic interference and vibration caused by the change of d-axis current, which helps to maintain the stable operation of the motor. q ,I d Inverse PARK transformation is performed to generate Ua and Ub control signals, which are then sent to the SVPWM module to generate drive signals to control the motor.

[0096] Further, in step S3, if the target speed of the first motor or the second motor is higher than the preset motor turning speed, the d-axis current is obtained according to the motor operation parameters, design parameters and the target speed, and the q-axis current limit value is obtained according to the maximum current and the d-axis current;

[0097] The d-axis current and the q-axis current are input into the controller to obtain the d-axis and q-axis voltages, and the first motor or the second motor is driven to operate according to the d-axis and q-axis voltages.

[0098] Specifically, when the target speed of the first motor or the second motor is higher than the preset motor turning speed, the output of the motor will increase, resulting in an increase in the magnetic flux level inside the motor, and the motor will consume more energy to maintain the magnetic field. Therefore, in order to reduce the magnetic flux, when the target speed of the first motor or the second motor is higher than the preset motor turning speed, it enters the weak magnetic control stage, and the d-axis current is controlled and the q-axis current is limited based on the operating parameters and design parameters, which can speed up the achievement of the target stride and step frequency requirements, and at the same time limit the q-axis current. If the q-axis current I d If the current command is too high, the motor may generate large torque fluctuations during dynamic response, affecting the stable operation of the motor. By limiting the q-axis current command, the torque fluctuation can be reduced and the stability of the motor can be enhanced. q ,I d Inverse PARK transformation is performed to generate Ua and Ub control signals, which are then sent to the SVPWM module to generate drive signals to control the motor.

[0099] Furthermore, the operating parameters include: a given current of the q-axis, a feedback current of the q-axis;

[0100] The design parameters include: rated current of the motor and rated speed of the motor.

[0101] The steps of obtaining the current of the d-axis are as follows:

[0102] Get the given current I of the q axis in real time qRef , the given current I qRef Input to the low-pass filter to get the first parameter I q ′ Ref ;

[0103] Get the feedback current I of the q axis in real time q , the given current I q Input to the low-pass filter to obtain the second parameter I q ′ ;

[0104] Get the first parameter I q ′ Ref With the second parameter I q ′ The difference E is used as the input of the PI controller to obtain the current feedback given term D1;

[0105] According to the rated current I nand rated speed ω n Calculate the amplification factor Kc of the feedforward given term of the weak magnetic current;

[0106] Obtain the current speed increment, adjust the speed increment by the amplification factor Kc, and obtain the current feedback given item D2;

[0107] The d-axis current I is obtained by adding the feedback given term D1 and the feedforward given term D2. d .

[0108] Specifically, when the motor drives the leg actuator to work, by obtaining the given current and feedback current of the q-axis in real time and applying a low-pass filter for processing, a more stable and accurate current parameter can be obtained. This method helps to accurately control the operation of the motor and improve stability and reliability. By calculating the difference E between the given current and the feedback current and using it as the input of the PI controller, a feedback given item D1 for adjusting the current can be obtained. The PI controller can effectively reduce errors and improve the accuracy of current control. The determination of the calculated amplification factor Kc is based on the rated current and rated speed of the motor. The speed increment is adjusted by the amplification factor Kc, which can ensure that the motor runs in an efficient and stable state. In the present invention, feedback control and feedforward control are combined, and the current of the d-axis is obtained by a simple addition operation. The d-axis current can also be accurately obtained without relying on a complex algorithm, and the current feedforward given item D1 can improve the speed response of the motor speed during rapid switching, and the current feedback given item ensures the speed stability of the motor under heavy load conditions. The method has a small amount of calculation, a simple structure, and high operating stability.

[0109] like Figure 2 As shown, a multi-joint robot control system based on intelligent health is applied to the control method according to any one of claims 1 to 8, comprising a first joint, a second joint, a first motor, a second motor, a first leg actuator and a second leg actuator, characterized in that the system comprises:

[0110] The instruction conversion module 1 is used to obtain a behavior instruction, the behavior instruction includes the user's leg movement behavior, and convert the behavior instruction into a first target action and a second target action;

[0111] A behavior parameter acquisition module 2, used to acquire a first behavior parameter required to perform a first target action and a second behavior parameter required to perform a second target action;

[0112] The action execution module 3 is used to adjust the target speed of the first motor according to the first behavior parameter to drive the first joint to control the first leg actuator to perform the first target action, and synchronously adjust the target speed of the second motor according to the second behavior parameter to drive the second joint to control the second leg actuator to perform the second target action.

[0113] This embodiment realizes the control method and implementation process of a multi-joint robot based on intelligent health. Please refer to the above embodiments and will not go into details here.

[0114] In the description of this specification, the description with reference to the terms "one embodiment", "some embodiments", "illustrative embodiments", "examples", "specific examples", or "some examples" means that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present invention. In this specification, the schematic representation of the above terms does not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described may be combined in any one or more embodiments or examples in a suitable manner.

[0115] Although the embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions and variations may be made to the embodiments without departing from the principles and spirit of the present invention, and that the scope of the present invention is defined by the claims and their equivalents.

Claims

1. A multi-joint robot control method based on intelligent health, It is characterized in that Applied to a multi-joint robot, the multi-joint robot comprises a first joint, a second joint, a first motor, a second motor, a first leg actuator and a second leg actuator; The method comprises: Step S1: Obtaining a behavior instruction, the behavior instruction includes the user's leg movement behavior, and converting the behavior instruction into a first target action and a second target action; Step S2: Acquire a first behavior parameter required to perform a first target action and a second behavior parameter required to perform a second target action; Step S3: Adjust the target speed of the first motor according to the first behavior parameter to drive the first joint to control the first leg actuator to perform the first target action, and synchronously adjust the target speed of the second motor according to the second behavior parameter to drive the second joint to control the second leg actuator to perform the second target action.

2. The control method according to claim 1, It is characterized in that The leg movements of the user include: fast walking, slow walking, jogging and squatting.

3. The control method according to claim 2, It is characterized in that The converting the behavior instruction into the first target action and the second target action comprises: When the leg motion of the user is fast walking, slow walking or jogging, if the current leg is not the supporting leg, the first target motion includes the first leg actuator swinging forward with the first joint as the origin, and the second target motion includes the second leg actuator swinging upward with the second joint as the origin; if the current leg is the supporting leg, the first target motion includes the first leg actuator swinging backward with the first joint as the origin, and the second target motion includes the second leg actuator swinging downward with the second joint as the origin; When the user's leg movement is squatting, when squatting, the first target movement includes the first leg actuator swinging forward with the first joint as the origin, and the second target movement includes the second leg actuator swinging downward with the second joint as the origin; when standing up, the first target movement includes the first leg actuator swinging backward with the first joint as the origin, and the second target movement includes the second leg actuator swinging upward with the second joint as the origin.

4. The control method according to claim 3, It is characterized in that The first behavior parameter includes a swing angle of the first leg actuator relative to the first joint, and the second behavior parameter includes a swing angle of the second leg actuator relative to the second joint; When the user's leg motion is fast walking, slow walking or jogging, the relationship is satisfied: S=L 1 (sinθ 11 +sinθ 21 )+L 2 (sinθ 12 +sinθ 22 ); Where S represents the distance between the first leg actuators at the current moment, L 1 represents the length of the first leg actuator, L 2 represents the length of the second leg actuator, θ 11 represents the swing angle of the first leg actuator corresponding to the non-supporting leg with the first joint as the origin, θ 12 represents the swing angle of the second leg actuator corresponding to the non-supporting leg with the second joint as the origin, θ 21 represents the swing angle of the first leg actuator corresponding to the supporting leg with the first joint as the origin, θ 22 represents the swing angle of the second leg actuator corresponding to the supporting leg with the second joint as the origin; When the user's leg movement is squatting, the relationship is satisfied: H=L 1 cosθ 31 +L 2 cosθ 32 ; Among them, L 1 represents the length of the first leg actuator, L 2 represents the length of the second leg actuator, H is the current squat distance, θ 31 represents the swing angle of the first leg actuator with the first joint as the origin, θ 32 Indicates the swing angle of the second leg actuator with the second joint as the origin.

5. The control method according to claim 4, It is characterized in that The first behavior parameter and the second behavior parameter further include frequencies at which the first leg actuator and the second leg actuator respectively perform the first target action and the second target action; The target speed of the first motor and the target speed of the second motor required for the first leg actuator to perform the first target action and the second leg actuator to perform the second target action respectively satisfy the relationship: Among them, f represents the frequency of the leg actuator performing the target action, N represents the number of revolutions that the motor output end needs to rotate when the leg actuator completes one action, Δθ represents the angle change of the leg actuator to complete one action, and 60 is a constant used for unit conversion.

6. The control method according to claim 5, It is characterized in that In step S3, when the target speed of the first motor is adjusted according to the first behavior parameter and the target speed of the second motor is adjusted according to the second behavior parameter, it includes: Determine whether the target speed of the first motor or the second motor is lower than the preset motor turning speed, and if so, use the MTPA current control method to generate corresponding d-axis and q-axis currents; The d-axis current and the q-axis current are input into the controller to obtain the d-axis and q-axis voltages, and the first motor or the second motor is driven to operate according to the d-axis and q-axis voltages.

7. The control method according to claim 5, It is characterized in that In step S3, when the target speed of the first motor is adjusted according to the first behavior parameter and the target speed of the second motor is adjusted according to the second behavior parameter, it includes: Determine whether the target speed of the first motor or the second motor is higher than the preset motor turning speed. If so, obtain the d-axis current according to the motor's operating parameters, design parameters and target speed, and obtain the q-axis current limit value according to the maximum current and the d-axis current; The d-axis current and the q-axis current are input into the controller to obtain the d-axis and q-axis voltages, and the first motor or the second motor is driven to operate according to the d-axis and q-axis voltages.

8. The control method according to claim 7, It is characterized in that The operating parameters include: given current of q axis, feedback current of q axis; The design parameters include: rated current of the motor, rated speed of the motor; The steps of obtaining the current of the d-axis are as follows: Get the given current I of the q axis in real time qRef , the given current I qRef Input to the low-pass filter to get the first parameter I' qRef ; Get the feedback current I of the q axis in real time q , the given current I q Input to the low-pass filter to obtain the second parameter I' q ; Get the first parameter I' qRef and the second parameter I′ q The difference E is used as the input of the PI controller to obtain the current feedback given term D1; According to the rated current E n and rated speed ω n Calculate the amplification factor Kc of the current feedforward given term; Obtain the current speed increment, adjust the speed increment by the amplification factor Kc, and obtain the current feedback given item D2; The d-axis current I is obtained by adding the feedback given term D1 and the feedforward given term D2. d .

9. A multi-joint robot control system based on intelligent health, applied to the control method according to any one of claims 1 to 8, comprising a first joint, a second joint, a first motor, a second motor, a first leg actuator and a second leg actuator, It is characterized in that The system comprises: An instruction conversion module is used to obtain a behavior instruction, the behavior instruction includes a leg movement behavior of the user, and convert the behavior instruction into a first target action and a second target action; A behavior parameter acquisition module, used to acquire a first behavior parameter required to perform a first target action and a second behavior parameter required to perform a second target action; An action execution module is used to adjust the target speed of the first motor according to the first behavior parameter to drive the first joint to control the first leg actuator to perform the first target action, and synchronously adjust the target speed of the second motor according to the second behavior parameter to drive the second joint to control the second leg actuator to perform the second target action.

Images