CN113855477A - Layered control method for lower limb exoskeleton robot - Google Patents

Layered control method for lower limb exoskeleton robot Download PDF

Info

Publication number
CN113855477A
CN113855477A CN202111044404.7A CN202111044404A CN113855477A CN 113855477 A CN113855477 A CN 113855477A CN 202111044404 A CN202111044404 A CN 202111044404A CN 113855477 A CN113855477 A CN 113855477A
Authority
CN
China
Prior art keywords
joint
exoskeleton robot
exoskeleton
instantaneous
track
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Granted
Application number
CN202111044404.7A
Other languages
Chinese (zh)
Other versions
CN113855477B (en
Inventor
秦利
王珂
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Yanshan University
Original Assignee
Yanshan University
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Yanshan University filed Critical Yanshan University
Priority to CN202111044404.7A priority Critical patent/CN113855477B/en
Publication of CN113855477A publication Critical patent/CN113855477A/en
Application granted granted Critical
Publication of CN113855477B publication Critical patent/CN113855477B/en
Active legal-status Critical Current
Anticipated expiration legal-status Critical

Links

Images

Classifications

    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61H—PHYSICAL THERAPY APPARATUS, e.g. DEVICES FOR LOCATING OR STIMULATING REFLEX POINTS IN THE BODY; ARTIFICIAL RESPIRATION; MASSAGE; BATHING DEVICES FOR SPECIAL THERAPEUTIC OR HYGIENIC PURPOSES OR SPECIFIC PARTS OF THE BODY
    • A61H1/00—Apparatus for passive exercising; Vibrating apparatus; Chiropractic devices, e.g. body impacting devices, external devices for briefly extending or aligning unbroken bones
    • A61H1/02—Stretching or bending or torsioning apparatus for exercising
    • A61H1/0237—Stretching or bending or torsioning apparatus for exercising for the lower limbs
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61H—PHYSICAL THERAPY APPARATUS, e.g. DEVICES FOR LOCATING OR STIMULATING REFLEX POINTS IN THE BODY; ARTIFICIAL RESPIRATION; MASSAGE; BATHING DEVICES FOR SPECIAL THERAPEUTIC OR HYGIENIC PURPOSES OR SPECIFIC PARTS OF THE BODY
    • A61H2201/00—Characteristics of apparatus not provided for in the preceding codes
    • A61H2201/16—Physical interface with patient
    • A61H2201/1602—Physical interface with patient kind of interface, e.g. head rest, knee support or lumbar support
    • A61H2201/164—Feet or leg, e.g. pedal
    • A61H2201/1642—Holding means therefor
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61H—PHYSICAL THERAPY APPARATUS, e.g. DEVICES FOR LOCATING OR STIMULATING REFLEX POINTS IN THE BODY; ARTIFICIAL RESPIRATION; MASSAGE; BATHING DEVICES FOR SPECIAL THERAPEUTIC OR HYGIENIC PURPOSES OR SPECIFIC PARTS OF THE BODY
    • A61H2201/00—Characteristics of apparatus not provided for in the preceding codes
    • A61H2201/16—Physical interface with patient
    • A61H2201/1602—Physical interface with patient kind of interface, e.g. head rest, knee support or lumbar support
    • A61H2201/165—Wearable interfaces
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61H—PHYSICAL THERAPY APPARATUS, e.g. DEVICES FOR LOCATING OR STIMULATING REFLEX POINTS IN THE BODY; ARTIFICIAL RESPIRATION; MASSAGE; BATHING DEVICES FOR SPECIAL THERAPEUTIC OR HYGIENIC PURPOSES OR SPECIFIC PARTS OF THE BODY
    • A61H2201/00—Characteristics of apparatus not provided for in the preceding codes
    • A61H2201/50—Control means thereof
    • A61H2201/5007—Control means thereof computer controlled
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61H—PHYSICAL THERAPY APPARATUS, e.g. DEVICES FOR LOCATING OR STIMULATING REFLEX POINTS IN THE BODY; ARTIFICIAL RESPIRATION; MASSAGE; BATHING DEVICES FOR SPECIAL THERAPEUTIC OR HYGIENIC PURPOSES OR SPECIFIC PARTS OF THE BODY
    • A61H2201/00—Characteristics of apparatus not provided for in the preceding codes
    • A61H2201/50—Control means thereof
    • A61H2201/5058—Sensors or detectors
    • A61H2201/5061—Force sensors
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61H—PHYSICAL THERAPY APPARATUS, e.g. DEVICES FOR LOCATING OR STIMULATING REFLEX POINTS IN THE BODY; ARTIFICIAL RESPIRATION; MASSAGE; BATHING DEVICES FOR SPECIAL THERAPEUTIC OR HYGIENIC PURPOSES OR SPECIFIC PARTS OF THE BODY
    • A61H2201/00—Characteristics of apparatus not provided for in the preceding codes
    • A61H2201/50—Control means thereof
    • A61H2201/5058—Sensors or detectors
    • A61H2201/5069—Angle sensors
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61H—PHYSICAL THERAPY APPARATUS, e.g. DEVICES FOR LOCATING OR STIMULATING REFLEX POINTS IN THE BODY; ARTIFICIAL RESPIRATION; MASSAGE; BATHING DEVICES FOR SPECIAL THERAPEUTIC OR HYGIENIC PURPOSES OR SPECIFIC PARTS OF THE BODY
    • A61H2201/00—Characteristics of apparatus not provided for in the preceding codes
    • A61H2201/50—Control means thereof
    • A61H2201/5058—Sensors or detectors
    • A61H2201/5084—Acceleration sensors

Landscapes

  • Health & Medical Sciences (AREA)
  • Epidemiology (AREA)
  • Pain & Pain Management (AREA)
  • Physical Education & Sports Medicine (AREA)
  • Rehabilitation Therapy (AREA)
  • Life Sciences & Earth Sciences (AREA)
  • Animal Behavior & Ethology (AREA)
  • General Health & Medical Sciences (AREA)
  • Public Health (AREA)
  • Veterinary Medicine (AREA)
  • Manipulator (AREA)

Abstract

The invention provides a layered control method for a lower limb exoskeleton robot, which comprises the following specific implementation processes: s1, analyzing the characteristic information of the sample, and constructing an outer-layer control structure: setting an initial reference gait track of the exoskeleton robot, and acquiring interaction torque of the exoskeleton robot and a sample; correcting the initial reference gait track and outputting a phase space reference gait track; the initial reference gait trajectory is reset and the output of the outer control structure is periodically updated. S2, constructing an inner layer control structure based on the reference gait track of S1: collecting numerical values of joint angles, speeds and accelerations of the exoskeleton robot in real time; and outputting the reference quantity of the exoskeleton robot joint speed based on the joint angle and the reference gait track. And S3, controlling the speed of the joint motor of the exoskeleton robot based on the joint speed reference of S2. The invention can adjust the output torque of the joint motor in real time according to the training condition, and improve the flexibility and the training effect of the exoskeleton robot.

Description

Layered control method for lower limb exoskeleton robot
Technical Field
The invention relates to the field of exoskeleton robots, in particular to a layered control method for a lower limb exoskeleton robot.
Background
With the development of robotics, exoskeleton robots in particular have shown great practicability and development potential in various fields including medical treatment, military industry and the like.
However, the traditional exoskeleton robot is only limited to specific work content, the motion trajectory of the traditional exoskeleton robot is planned in advance before use, although the requirement can be met when a task in a fixed scene is processed, the traditional exoskeleton robot lacks flexibility, a user can only passively move or train, active participation is lacked, once a task target is changed or the motion state of the exoskeleton user is changed, a preset task or a training target cannot be completed, the flexibility between the exoskeleton robot and the user is poor, and even unnecessary damage can be caused in severe cases.
Disclosure of Invention
Aiming at the problems in the prior art, the invention provides a layered control method for a lower limb exoskeleton robot, which utilizes an inner-layer and outer-layer control structure, collects the characteristics of samples through an outer-layer control structure, provides reasonable initial gait references for different samples or different training targets of the same sample, and adjusts the initial gait references by measuring active interaction torque information between the samples and an exoskeleton; the joint angle and the speed information of the sample are collected through the inner layer, the controlled variable is converted into the joint speed value through vector synthesis in a phase space, the training effect is further enhanced on the basis of the outer layer, the target adjustability is realized, and meanwhile, the overall smoothness and the flexibility of the system are improved by adopting speed control.
The invention provides a layered control method for a lower limb exoskeleton robot, which comprises the following specific implementation steps:
s1, analyzing the characteristic information of the sample, constructing an outer layer control structure, and outputting the exoskeleton robot reference gait track in the joint phase space, specifically comprising the following substeps:
s11, setting an initial reference gait track of the exoskeleton robot, and collecting the interaction torque of the exoskeleton robot and the sample, wherein the method comprises the following substeps:
s111, analyzing objective physiological characteristics of the sample and combining with a training target, setting an initial reference gait track of the exoskeleton robot, and selecting a track parameter ai、ci、diRobot for exoskeletonsParameterizing an initial reference gait track, wherein a specific expression is as follows:
Figure BDA0003250695980000021
wherein,
Figure BDA0003250695980000022
in order to meet the initial reference gait track of the exoskeleton robot with objective physiological characteristics of a target, the parameter a represents the change of the angle of each joint along with time in a complete motion cycleiRepresenting the amplitude of the scaled track, parameter ciCapable of varying and influencing the period of movement of the object, parameter diChanging the flexion and extension amount of each joint of the exoskeleton robot, wherein i-1 represents a first joint of the exoskeleton robot, and i-2 represents a second joint of the exoskeleton robot;
s112, in a complete movement period, collecting and storing the interaction torque of the exoskeleton robot and the sample;
s12, based on the exoskeleton robot initial reference gait track obtained in the step S11, correcting the exoskeleton robot initial reference gait track, and outputting the exoskeleton robot reference gait track of the joint phase space, wherein the method comprises the following substeps:
s121, deducing a dynamic model of the exoskeleton robot by using a Lagrange method according to the structure of the exoskeleton robot;
s122, according to impedance parameter K of interaction between exoskeleton robot and samplePAnd KDAnd calculating the correction quantity delta q of the instantaneous reference joint angle of the exoskeleton robot at each sampling moment and the corrected instantaneous reference joint angle q in a complete movement cycle by combining the interactive torque obtained in the step S112REF,NEW；
S123, obtaining the instantaneous reference joint angle q based on the step S122REF,NEWConstructing a cost function, and fitting the corrected exoskeleton robot reference gait track by minimizing the cost function through a steepest descent method
Figure BDA0003250695980000023
Wherein t is time, and i is the ith joint of the exoskeleton robot;
s124, the reference gait track obtained in the step S123
Figure BDA0003250695980000024
Exoskeleton robot reference gait track for joint phase space output through combined processing
Figure BDA0003250695980000025
Wherein hip represents a first joint angle of the exoskeleton robot, and knee represents a second joint angle of the exoskeleton robot;
s13, resetting the initial reference gait track of the exoskeleton robot and periodically updating the output of the outer layer control structure;
s2, constructing an inner layer control structure based on the joint phase space exoskeleton robot reference gait track obtained in the step S1, and outputting the exoskeleton robot joint speed reference, wherein the method comprises the following substeps:
s21, collecting values of joint angles, joint speeds and joint accelerations of the exoskeleton robot in real time through absolute value encoders at joints;
s22, the exoskeleton robot reference gait track under the joint phase space acquired based on the joint angle acquired in the step S21 and the joint phase space acquired in the step S125
Figure BDA0003250695980000031
Determining an inner layer control structure, comprising the following sub-steps:
s221, mapping the sample joint angle at any moment into an instantaneous actual vector point in a joint phase space, and finding out an instantaneous target vector point closest to the instantaneous actual vector point through geometric analysis;
s222, taking the normal direction of the instantaneous target vector point as an adjusting direction
Figure BDA0003250695980000032
Taking the tangential direction of the instantaneous target vector point as the tracking direction
Figure BDA0003250695980000033
Then selecting control parameters lambda and k according to the training target, and calculating to obtain a velocity synthetic vector
Figure BDA0003250695980000034
The specific expression is as follows:
Figure BDA0003250695980000035
wherein, λ and k are inner layer control structure parameters which are respectively used for adjusting the size and the direction of the reference quantity of the joint velocity,
Figure BDA0003250695980000036
and
Figure BDA0003250695980000037
respectively a tracking direction and an adjustment direction,
Figure BDA0003250695980000038
is the distance norm between the instantaneous reference vector point and the instantaneous target vector point;
and S3, controlling the speed of the joint motor of the exoskeleton robot based on the reference joint speed obtained by the inner-layer control structure in the step S2.
Preferably, in step S111, different exoskeleton joint initial reference gait trajectory curves can be generated by changing the parameter sets a to d.
Preferably, the specific expression of the kinetic model in step S121 is as follows:
Figure BDA0003250695980000039
wherein M (q) is a 2 x 2 symmetric positive definite inertia matrix,
Figure BDA00032506959800000310
a matrix of coriolis forces and centrifugal forces, a g (q) gravity matrix,
Figure BDA00032506959800000311
is a joint clearance friction force matrix, T ═ T1,T2]T，T1Driving torque for the first joint of the exoskeleton, T2Driving torque for the second joint of the exoskeleton, Th＝[Th1,Th2]TFor man-machine interaction torque, T, measured by force sensorsh1Moment of man-machine interaction for first joint of exoskeleton, Th2For the exoskeleton second joint human-computer interaction moment, q ═ q1,q2]T，q1For the first joint angle of the exoskeleton, q2For the second joint angle of the exoskeleton,
Figure BDA0003250695980000041
Figure BDA0003250695980000042
for the first joint angular velocity of the exoskeleton,
Figure BDA0003250695980000043
for the second joint angular velocity of the exoskeleton,
Figure BDA0003250695980000044
Figure BDA0003250695980000045
for the first joint angular acceleration of the exoskeleton,
Figure BDA0003250695980000046
a second joint angular acceleration for the exoskeleton.
Preferably, in step S122, a specific expression of the correction amount Δ q of the instantaneous reference joint angle of the exoskeleton robot at each sampling time is as follows:
Figure BDA0003250695980000047
wherein, KP、KDAs an impedance parameter, ThThe interaction torque of the exoskeleton robot and the sample is obtained;
instantaneous reference joint angle q of exoskeleton robot after correction at each sampling momentREF,NEWThe specific expression of (a) is as follows:
qREF,NEW＝qREF,OLD-ω·Δq
wherein Δ q is a correction amount of an instantaneous reference joint angle, qREF,NEWFor the corrected instantaneous reference joint angle, qREF,OLDIs the instantaneous reference joint angle before correction, where ω is the scaling factor.
Preferably, in step S123, the specific expression of the cost function is as follows:
Figure BDA0003250695980000048
wherein k represents the kth sampling time, i-1 represents the first joint of the exoskeleton robot, i-2 represents the second joint of the exoskeleton robot, and q represents the second joint of the exoskeleton robotREF,NEWi(k)Is the instant desired joint angle after the modification at the kth sampling instant,
Figure BDA0003250695980000049
is the reference gait track to be corrected at the kth sampling moment.
Preferably, the step S13 specifically includes the following steps:
s131, the corrected exoskeleton robot obtained in the step S124 is used for consulting gait tracks
Figure BDA00032506959800000410
Updating the step S111 as the initial reference gait track of the next complete movement cycle;
and S132, repeating the step S1 based on the initial reference gait track updated in the step S131, and periodically updating the output of the outer layer control structure.
Preferably, the step S221 specifically includes the following steps:
s2211, mapping the first joint angle and the second joint angle of the sample to be a vector point in a joint phase space at any sampling time
Figure BDA00032506959800000411
The specific expression is as follows:
Figure BDA00032506959800000412
wherein q is1Is a sample first joint angle, q2A sample second joint angle;
s2212, finding out a point on the exoskeleton robot reference gait track in the joint facies space through geometric analysis
Figure BDA0003250695980000051
Recording as instantaneous reference vector point and making instantaneous reference vector point
Figure BDA0003250695980000052
To the instantaneous actual vector point
Figure BDA0003250695980000053
Distance between two adjacent plates
Figure BDA0003250695980000054
The norm of (2) is minimum, namely the norm is an instantaneous target vector point, and the specific expression is as follows:
Figure BDA0003250695980000055
wherein,
Figure BDA0003250695980000056
for the instant reference vector point(s) it is,
Figure BDA0003250695980000057
the instantaneous actual vector points.
Preferably, in step S222, the adjusting direction
Figure BDA0003250695980000058
The specific expression of (a) is as follows:
Figure BDA0003250695980000059
wherein,
Figure BDA00032506959800000510
for instantaneous reference vector points
Figure BDA00032506959800000511
To the instantaneous actual vector point
Figure BDA00032506959800000512
Is determined by the distance vector of (a),
Figure BDA00032506959800000513
for instantaneous reference vector points
Figure BDA00032506959800000514
To the instantaneous actual vector point
Figure BDA00032506959800000515
Distance vector norm of (2).
Compared with the prior art, the invention has the beneficial effects that:
1. the invention realizes a layered control structure, the outer layer control structure can provide reasonable gait reference for different samples or different rehabilitation stages of different training targets of the same sample, the inner layer is on the basis of the outer layer, the training effect is better, simultaneously the aim is adjustable, the real-time control is realized, and the flexibility is improved by using a speed control mode.
2. The traditional lower limb exoskeleton control method requires that a training track is preset, a sample can only passively follow the track to move, and the training effect is poor; the method can adjust the target reference in time according to the intention of the sample.
3. The invention is different from the traditional position tracking, adopts layered speed control and improves the flexibility of the exoskeleton robot.
4. The invention has strong parameter flexibility, can realize personalized rehabilitation therapy through parameter adjustment, provides personalized gait for different samples, and can adjust parameters in real time according to training purposes.
Drawings
FIG. 1 is a flow chart of a hierarchical control method for a lower extremity exoskeleton robot in accordance with the present invention;
FIG. 2 is a schematic block diagram of a layered control method for a lower extremity exoskeleton robot in accordance with the present invention;
FIG. 3 is a schematic diagram of the parameterization of the hip joint gait trajectory in the hierarchical control method for the lower extremity exoskeleton robot according to the present invention;
FIG. 4 is a schematic diagram of a trajectory phase diagram of the hip joint and the knee joint in the hierarchical control method for the lower extremity exoskeleton robot according to the present invention;
FIG. 5 is a parameter diagram of an inner layer control structure of the hierarchical control method for the lower extremity exoskeleton robot according to the present invention;
FIG. 6 is a schematic output diagram of an inner ring control structure for a hierarchical control method for a lower extremity exoskeleton robot in accordance with the present invention;
fig. 7 is a schematic diagram showing comparison between a phase space actual gait trajectory and a reference gait trajectory in the hierarchical control method for the lower extremity exoskeleton robot according to the present invention.
Detailed Description
The technical contents, structural features, attained objects and effects of the present invention are explained in detail below with reference to the accompanying drawings.
The overall control block diagram of the invention is shown in fig. 2, wherein the outer ring is responsible for collecting and analyzing user characteristic information, outputting a reference gait track conforming to the user characteristic and the expectation according to the interaction torque between the user and the exoskeleton robot, and representing the reference gait track in a phase space; the inner ring outputs a joint speed reference quantity as a final control quantity by processing the relation between the instantaneous joint angle, the speed information and the reference phase space reference gait track based on the phase space reference gait track output by the outer layer, and controls the exoskeleton robot joint motor in a speed control mode to drive the exoskeleton robot to move, so that the aim of adjusting the training target and the strength in real time is fulfilled, meanwhile, the flexibility of the control method is improved, and the training effect is enhanced. The specific implementation steps are as follows:
and S1, analyzing the characteristic information of the sample, constructing an outer layer control structure, outputting the reference gait track of the exoskeleton robot in the joint phase space, and periodically updating.
S2, constructing an inner layer control structure based on the joint phase space exoskeleton robot reference gait track obtained in the step S1, outputting the exoskeleton robot joint speed reference quantity, adjusting a training target and strength in real time, improving the training effect, and improving the flexibility of the control method by adopting a speed control mode.
And S3, controlling the speed of the joint motor of the exoskeleton robot based on the reference joint speed obtained by the inner-layer control structure in the step S2.
In a preferred embodiment of the present invention, the hierarchical control method for the lower extremity exoskeleton robot according to the present invention, as shown in fig. 1, includes the following steps:
and S11, setting an initial reference gait track of the exoskeleton robot, and collecting the interaction torque of the exoskeleton robot and the sample.
And S12, correcting the initial reference gait track of the exoskeleton robot based on the initial reference gait track of the exoskeleton robot obtained in the S11 to obtain a corrected reference gait track of the exoskeleton robot, expressing the corrected reference gait track of the exoskeleton robot in a joint phase space, and outputting the reference gait track of the exoskeleton robot in the joint phase space.
And S13, resetting the initial reference gait track of the exoskeleton robot and periodically updating the output of the outer layer control structure.
S131, the corrected exoskeleton robot obtained in the step S124 is used for consulting gait tracks
Figure BDA0003250695980000071
Step S111 is updated as the initial reference gait trajectory for the next complete movement cycle.
And S132, repeating the step S1 based on the initial reference gait track updated in the step S131, and periodically updating the output of the outer layer control structure.
And S21, acquiring values of joint angles, joint speeds and joint accelerations of the exoskeleton robot in real time through absolute value encoders at joints.
S22, the exoskeleton robot reference gait track under the joint phase space acquired based on the joint angle acquired in the step S21 and the joint phase space acquired in the step S125
Figure BDA0003250695980000072
And an inner layer control structure is designed, so that the flexibility of the system is improved.
And S3, controlling the speed of the joint motor of the exoskeleton robot based on the reference quantity of the joint speed obtained by the inner-layer control structure in the step S2, and driving the exoskeleton robot to move.
Further, the method for setting the initial reference gait track of the exoskeleton robot and acquiring the interaction torque of the exoskeleton robot with the sample in step S11 comprises,
s111, analyzing objective physiological characteristics of the sample and combining with a training target, setting an initial reference gait track of the exoskeleton robot, and selecting a track parameter ai、ci、diParameterizing an initial reference gait track of the exoskeleton robot, wherein the specific expression is as follows:
Figure BDA0003250695980000073
wherein,
Figure BDA0003250695980000074
representing the angle of each joint in a complete motion cycle for the exoskeleton robot to meet the initial reference gait track of the target objective physiological characteristicsVariation with time, parameter aiRepresenting the amplitude of the scaled track, parameter ciThe period of the movement of the object, parameter d, can be varied and influencediThe flexion and extension amounts of all joints of the exoskeleton robot are changed, i is 1 to represent a first joint of the exoskeleton robot, i is 2 to represent a second joint of the exoskeleton robot, and different initial reference gait track curves of the exoskeleton joints can be generated by changing parameter sets a-d.
And S112, in a complete movement period, collecting and storing the interaction torque of the exoskeleton robot and the sample, wherein the numerical value of the interaction torque is used for representing the deviation degree of the current reference gait track of the exoskeleton robot and the expected reference gait track of the exoskeleton robot.
Further, the method for obtaining the reference gait trajectory of the exoskeleton robot outputting the joint phase space by using the obtained initial reference gait trajectory of the exoskeleton robot in step S12 includes:
s121, deducing a dynamic model of the exoskeleton robot by using a Lagrange method according to the structure of the exoskeleton robot, wherein the specific expression is as follows:
Figure BDA0003250695980000081
wherein M (q) is a 2 x 2 symmetric positive definite inertia matrix,
Figure BDA0003250695980000082
a matrix of coriolis forces and centrifugal forces, a g (q) gravity matrix,
Figure BDA0003250695980000083
is a joint clearance friction force matrix, T ═ T1,T2]T，T1Driving torque for the first joint of the exoskeleton, T2Driving torque for the second joint of the exoskeleton, Th＝[Th1,Th2]TFor man-machine interaction torque, T, measured by force sensorsh1Moment of man-machine interaction for first joint of exoskeleton, Th2For the exoskeletonsTwo-joint man-machine interaction moment, q ═ q1,q2]T，q1For the first joint angle of the exoskeleton, q2For the second joint angle of the exoskeleton,
Figure BDA0003250695980000084
Figure BDA0003250695980000085
for the first joint angular velocity of the exoskeleton,
Figure BDA0003250695980000086
for the second joint angular velocity of the exoskeleton,
Figure BDA0003250695980000087
Figure BDA0003250695980000088
for the first joint angular acceleration of the exoskeleton,
Figure BDA0003250695980000089
a second joint angular acceleration for the exoskeleton.
S122, according to impedance parameter K of interaction between exoskeleton robot and samplePAnd KDAnd calculating a specific expression of the correction quantity Δ q of the instantaneous reference joint angle of the exoskeleton robot at each sampling moment in a complete motion cycle by combining the interactive torque obtained in step S112 as follows:
Figure BDA00032506959800000810
wherein, KP、KDAs an impedance parameter, ThThe interaction torque of the exoskeleton robot and the sample is obtained;
instantaneous reference joint angle q of exoskeleton robot after correction at each sampling momentREF,NEWThe specific expression of (a) is as follows:
qREF,NEW＝qREF,OLD-ω·Δq
wherein Δ q is a correction amount of an instantaneous reference joint angle, qREF,NEWFor the corrected instantaneous reference joint angle, qREF,OLDIs the instantaneous reference joint angle before correction, where ω is the scaling factor.
S123, obtaining the instantaneous reference joint angle q based on the step S122REF,NEWConstructing a cost function, and minimizing the cost function by a steepest descent method to obtain a track parameter piFitting the corrected exoskeleton robot reference gait track by using the obtained track parameters
Figure BDA0003250695980000091
Wherein t is time, and i is the ith joint of the exoskeleton robot, so that the corrected reference gait track can be closest to the corrected instantaneous reference joint angle q at each sampling momentREF,NEWThe specific expression of the constructed cost function is as follows:
Figure BDA0003250695980000092
wherein k represents the kth sampling time, i-1 represents the first joint of the exoskeleton robot, i-2 represents the second joint of the exoskeleton robot, and q represents the second joint of the exoskeleton robotREF,NEWi(k)Is the instant desired joint angle after the modification at the kth sampling instant,
Figure BDA0003250695980000093
is the reference gait track to be corrected at the kth sampling moment.
S124, the corrected reference gait track obtained in the step S123
Figure BDA0003250695980000094
Carrying out combined processing, eliminating the time parameter t, establishing a joint phase space, and outputting the exoskeleton robot reference gait track of the joint phase space
Figure BDA0003250695980000095
Wherein hip represents a first joint angle of the exoskeleton robot, and knee represents the first joint angle of the exoskeleton robotA second joint angle.
Further, the method for designing the inner-layer control structure in step S22 includes:
s221, mapping the sample joint angle at any moment into an instantaneous actual vector point in the joint phase space, and finding out an instantaneous target vector point closest to the instantaneous actual vector point through geometric analysis.
S2211, mapping the first joint angle and the second joint angle of the sample to be a vector point in a joint phase space at any sampling time
Figure BDA0003250695980000096
The specific expression is as follows:
Figure BDA0003250695980000097
wherein q is1Is a sample first joint angle, q2Sample second joint angle.
S2212, finding out a point on the exoskeleton robot reference gait track in the joint facies space through geometric analysis
Figure BDA0003250695980000098
Recording as instantaneous reference vector point and making instantaneous reference vector point
Figure BDA0003250695980000099
To the instantaneous actual vector point
Figure BDA00032506959800000910
Distance between two adjacent plates
Figure BDA00032506959800000911
The norm of (2) is minimum, namely the norm is an instantaneous target vector point, and the specific expression is as follows:
Figure BDA00032506959800000912
wherein,
Figure BDA00032506959800000913
for the instant reference vector point(s) it is,
Figure BDA00032506959800000914
the instantaneous actual vector points.
S222, taking the normal direction of the instantaneous target vector point as an adjusting direction
Figure BDA00032506959800000915
The specific expression is as follows:
Figure BDA00032506959800000916
wherein,
Figure BDA0003250695980000101
for instantaneous reference vector points
Figure BDA0003250695980000102
To the instantaneous actual vector point
Figure BDA0003250695980000103
Is determined by the distance vector of (a),
Figure BDA0003250695980000104
for instantaneous reference vector points
Figure BDA0003250695980000105
To the instantaneous actual vector point
Figure BDA0003250695980000106
The distance vector norm of (d);
taking the tangential direction of the instantaneous target vector point as the tracking direction
Figure BDA0003250695980000107
Then selecting control parameters lambda and k according to the training target, and calculating to obtain a velocity synthetic vector
Figure BDA0003250695980000108
The specific expression is as follows:
Figure BDA0003250695980000109
wherein, λ and k are inner layer control structure parameters which are respectively used for adjusting the size and the direction of the reference quantity of the joint velocity,
Figure BDA00032506959800001010
and
Figure BDA00032506959800001011
respectively a tracking direction and an adjustment direction,
Figure BDA00032506959800001012
is the distance norm between the instantaneous reference vector point and the instantaneous target vector point.
The invention further describes a layered control method for a lower limb exoskeleton robot in combination with the following embodiments:
the invention is realized by the following steps:
s1, analyzing the characteristic information of the user, constructing an outer layer control structure, and outputting the exoskeleton robot reference gait track under the joint phase space, wherein the specific operation steps are as follows:
and S11, setting an initial reference gait track of the exoskeleton robot, and collecting the interaction torque of the exoskeleton robot and a user.
S111, analyzing objective physiological characteristics of a user, setting an initial reference gait track of the exoskeleton robot by combining a training target and traditional database data
Figure BDA00032506959800001013
Wherein, i-1 represents the initial reference gait track of the hip joint, and i-2 represents the initial reference gait track of the knee joint. Based on the initial reference gait track, selecting proper track parameter ai、ci、diParameterizing the reference gait track of the exoskeleton robot, specifically referring to fig. 3, on the basis of giving the initial gait reference track, adjusting the amplitude, the period and the extension of the initial reference track by changing three parameters, namely a, c and d, so as to generate different hip and knee joint reference gait tracks, namely a track parameterization process:
Figure BDA00032506959800001014
wherein,
Figure BDA00032506959800001015
in order to meet the initial reference gait track of the exoskeleton robot with objective physiological characteristics of a target, the parameter a represents the change of the angle of each joint along with time in a complete motion cycleiRepresenting the amplitude of the scaled track, parameter ciThe period of the movement of the object, parameter d, can be varied and influencediAnd (3) changing the flexion and extension amount of each joint of the exoskeleton robot, wherein i-1 represents a hip joint of the exoskeleton robot, and i-2 represents a knee joint of the exoskeleton robot.
And S112, in a complete movement period, collecting and storing the interaction torque of the exoskeleton robot and a user, wherein the numerical value of the interaction torque is used for representing the deviation degree of the current reference gait track of the exoskeleton robot and the expected reference gait track of the exoskeleton robot.
S12, correcting the initial reference gait track of the exoskeleton robot based on the initial reference gait track of the exoskeleton robot obtained in S11, and outputting the reference gait track of the exoskeleton robot in the joint phase space:
s121, deducing a dynamic model of the exoskeleton robot by using a Lagrange method according to the structure of the exoskeleton robot, and describing a dynamic equation of the exoskeleton robot into the following form for convenient expression;
Figure BDA0003250695980000111
wherein M (q) is a 2 x 2 symmetric positive definite inertia matrix,
Figure BDA0003250695980000112
a matrix of coriolis forces and centrifugal forces, a g (q) gravity matrix,
Figure BDA0003250695980000113
is a joint clearance friction force matrix, T ═ T1,T2]T，T1Driving moment for exoskeleton hip joint, T2Driving moment for exoskeleton knee joint, Th＝[Th1,Th2]TFor man-machine interaction torque, T, measured by force sensorsh1For exoskeleton hip joint man-machine interaction torque, Th2Is the man-machine interaction moment of the exoskeleton knee joint, q ═ q1,q2]T，q1For exoskeleton hip joint angle, q2The angle of the exoskeleton knee joint is the angle,
Figure BDA0003250695980000114
Figure BDA0003250695980000115
in order to provide the angular velocity of the exoskeleton hip joint,
Figure BDA0003250695980000116
in order to determine the angular velocity of the exoskeleton knee joint,
Figure BDA0003250695980000117
Figure BDA0003250695980000118
in order to realize the angular acceleration of the exoskeleton hip joint,
Figure BDA0003250695980000119
is the exoskeleton knee angular acceleration.
S122, according to impedance parameter K of interaction between the exoskeleton robot and the userPAnd KDAnd combined with the interactive torque obtained in step S112, calculatingWithin a complete movement period, the correction quantity delta q of the instantaneous reference joint angle of the exoskeleton robot at each sampling moment and the corrected instantaneous reference joint angle qREF,NEWThe method comprises the following specific steps:
recording the instantaneous interaction torque of the exoskeleton robot and the user as ThWhen T ishWhen the reference gait track is not 0, the current reference gait track is not in accordance with the expectation of the user, the correction is needed in time, the variation of the reference gait track expected by the user is recorded as delta q, and a proper impedance parameter K is selected according to the impedance relation between the exoskeleton robot and the userPAnd KDThen the moment T is instantaneously interacted between the exoskeleton robot and the userhThe impedance relationship with the reference gait trajectory variation Δ q desired by the user can be obtained:
Figure BDA00032506959800001110
wherein, KP、KDIs an impedance parameter.
The corrected instantaneous reference joint angle qREF,NEWComprises the following steps:
qREF,NEW＝qREF,OLD-ω×Δq
wherein Δ q is a correction amount of an instantaneous reference joint angle, qREF,NEWFor the corrected instantaneous reference joint angle, qREF,OLDIs the instantaneous reference joint angle before correction, where ω is the scaling factor.
S123, the corrected instantaneous reference joint angle q obtained based on the step S122REF,NEWConstructing a cost function, and minimizing the cost function by a steepest descent method to obtain a track parameter piFitting the corrected exoskeleton robot reference gait track by using the obtained track parameters
Figure BDA0003250695980000121
Wherein t is time, i is the ith joint of the exoskeleton robot, so that the corrected reference gait track can be closest to the corrected instantaneous reference joint angle q at each sampling momentREF,NEW. The constructed cost function is as follows:
Figure BDA0003250695980000122
where k denotes a kth sampling time, i-1 denotes a hip joint of the exoskeleton robot, i-2 denotes a knee joint of the exoskeleton robot, and q denotes a knee joint of the exoskeleton robotREF,NEWi(k)Is the instant desired joint angle after the modification at the kth sampling instant,
Figure BDA0003250695980000123
is a reference gait track to be corrected at the kth sampling moment;
s124, the reference gait track obtained in the step S123
Figure BDA0003250695980000124
Exoskeleton robot reference gait track for joint phase space output through combined processing
Figure BDA0003250695980000125
Wherein hip represents the hip joint angle of the exoskeleton robot, knee represents the knee joint angle of the exoskeleton robot, and the specific steps are as follows:
first, as shown in fig. 4, the exoskeleton robot joint phase space is established with the exoskeleton robot hip joint angle as the horizontal axis and the exoskeleton robot knee joint angle as the vertical axis.
For the two reference gait tracks obtained in step S123
Figure BDA0003250695980000126
Reference gait trajectories for hip joints respectively
Figure BDA0003250695980000127
And knee joint reference gait track
Figure BDA0003250695980000128
Carrying out combined processing, eliminating the time parameter t in the formula, and finally obtaining the exoskeleton machine in the joint phase spaceHuman reference gait trajectory
Figure BDA0003250695980000129
Wherein hip represents the hip joint angle of the exoskeleton robot, and knee represents the knee joint angle of the exoskeleton robot.
S13, resetting the initial reference gait track of the exoskeleton robot and periodically updating the output of the outer layer control structure, wherein the specific operation steps are as follows:
s131, the corrected exoskeleton robot obtained in the step S124 is used for consulting gait tracks
Figure BDA00032506959800001210
And updating the step S111 as the initial reference gait track of the next complete movement cycle to obtain the initial reference gait track of the next movement cycle.
S132 and based on the initial reference gait track updated in step S131, repeating step S1 to periodically update the output of the outer control structure, i.e. periodically update the reference gait track of the exoskeleton robot in the joint phase space
Figure BDA0003250695980000131
S2, constructing an inner layer control structure based on the joint phase space exoskeleton robot reference gait track obtained in the step S1, and outputting the reference quantity of the exoskeleton robot joint speed;
s21, collecting values of joint angles, joint speeds and joint accelerations of the exoskeleton robot in real time through absolute value encoders at joints;
s22, the joint angle of the exoskeleton robot collected in the step S21 and the joint phase space obtained in the step S125 are used as the basis of the reference gait track of the exoskeleton robot
Figure BDA0003250695980000132
Designing an inner layer control structure, and specifically comprising the following operation steps:
s221, with reference to the parameter schematic diagram of the inner layer control structure of the layered compliance control method for the lower extremity exoskeleton robot shown in fig. 5, maps the hip and knee joint angles of the user to an instantaneous actual vector point in the joint phase space, and finds out the instantaneous target vector point closest to the instantaneous actual vector point through geometric analysis.
S2211, mapping the hip and knee joint angles of the user at any moment to be a vector point in the joint phase space
Figure BDA0003250695980000133
The specific expression is as follows:
Figure BDA0003250695980000134
wherein q is1For the instantaneous hip angle of the user, q2The user's instantaneous knee joint angle.
S2212, finding out a point on the exoskeleton robot reference gait track in the joint facies space through geometric analysis
Figure BDA0003250695980000135
Is recorded as an instantaneous reference vector point, so that the instantaneous reference vector point
Figure BDA0003250695980000136
To the instantaneous actual vector point
Figure BDA0003250695980000137
Distance between two adjacent plates
Figure BDA0003250695980000138
The norm of (a) is minimum, namely:
Figure BDA0003250695980000139
wherein,
Figure BDA00032506959800001310
for the instant reference vector point(s) it is,
Figure BDA00032506959800001311
the instantaneous actual vector points.
S222, as shown in FIG. 5, selecting instantaneous reference vector points
Figure BDA00032506959800001312
To the instantaneous actual vector point
Figure BDA00032506959800001313
Distance vector
Figure BDA00032506959800001314
The direction vector of (1) is the adjustment direction, and is recorded as
Figure BDA00032506959800001315
The concrete expression is as follows:
Figure BDA00032506959800001316
wherein
Figure BDA00032506959800001317
For instantaneous reference vector points
Figure BDA00032506959800001318
To the instantaneous actual vector point
Figure BDA00032506959800001319
Is determined by the distance vector of (a),
Figure BDA00032506959800001320
for instantaneous reference vector points
Figure BDA00032506959800001321
To the instantaneous actual vector point
Figure BDA00032506959800001322
Distance vector norm of (2).
Simultaneously selecting adjustment directions
Figure BDA00032506959800001323
Is the tracking direction and is recorded as
Figure BDA00032506959800001324
Then according to the control parameters lambda and k selected by the training target, calculating to obtain a velocity synthetic vector
Figure BDA0003250695980000141
The specific expression is as follows:
Figure BDA0003250695980000142
wherein, λ and k are inner layer control structure parameters which are respectively used for adjusting the size and the direction of the reference quantity of the joint velocity,
Figure BDA0003250695980000143
and
Figure BDA0003250695980000144
respectively a tracking direction and an adjustment direction,
Figure BDA0003250695980000145
is the distance norm between the instantaneous reference vector point and the instantaneous target vector point. As shown in fig. 6, the reference joint speed output by the inner ring control structure is adjusted based on the initial reference joint speed, in the figure, the dotted line represents an initial reference hip joint speed curve, the solid line represents a reference hip joint speed curve output by the inner ring control structure, and it can be seen that the reference hip joint speed curve output by the inner ring control structure is adjusted in real time. When in use
Figure BDA0003250695980000146
When the gait vector is larger, the velocity vector of the adjusting direction is larger, so that the synthesized velocity reference quantity can guide the user to approach the reference track, and abnormal gait is prevented; when in use
Figure BDA0003250695980000147
When the gait track is small, the velocity vector of the tracking direction is large, which indicates that the current actual gait track is close to the reference gait track, encourages the user to keep the current state to advance and provides certain auxiliary force.
And S3, based on the reference quantity of the joint speed obtained by the inner-layer control structure in the step S2, carrying out speed control on a joint motor of the exoskeleton robot, and driving the exoskeleton robot to move, wherein in a joint phase space, the actual gait track of the exoskeleton robot is compared with the reference gait track output by the outer-layer control structure within 2 seconds as shown in figure 7. Therefore, the exoskeleton robot can be adjusted in real time on the basis of the reference gait track, passive track tracking cannot be performed singly, and accordingly can move more actively on the basis of meeting the requirement of the reference gait track, and flexibility is improved.
According to the invention, through the layered control structure, the outer layer control structure can provide reasonable gait track reference for different users or different motion stages of the same user, the inner layer control structure enables the training effect to be better on the basis of the outer layer control structure, and simultaneously, the purposes of adjusting and controlling in real time are realized, and the flexibility is improved by using a speed control mode. The method provided by the invention has good real-time performance, flexibility and flexibility, and can greatly improve the training effect of the exoskeleton robot.
The above-mentioned embodiments are merely illustrative of the preferred embodiments of the present invention, and do not limit the scope of the present invention, and various modifications and improvements made to the technical solution of the present invention by those skilled in the art without departing from the spirit of the present invention shall fall within the protection scope defined by the claims of the present invention.

Claims (8)

1. A layered control method for a lower limb exoskeleton robot is characterized by comprising the following steps:
s1, extracting sample information from the database, analyzing the characteristic information of the sample, constructing an outer layer control structure, and outputting the reference gait track of the exoskeleton robot in the joint phase space, which specifically comprises the following substeps:
s11, setting an initial reference gait track of the exoskeleton robot, and collecting the interaction torque of the exoskeleton robot and the sample, wherein the method comprises the following substeps:
s111, analyzing objective physiological characteristics of the sample and combining with a training target, setting an initial reference gait track of the exoskeleton robot, and selecting a track parameter ai、ci、diParameterizing an initial reference gait track of the exoskeleton robot, wherein the specific expression is as follows:
Figure FDA0003250695970000011
wherein,
Figure FDA0003250695970000012
in order to meet the initial reference gait track of the exoskeleton robot with objective physiological characteristics of a target, the parameter a represents the change of the angle of each joint along with time in a complete motion cycleiRepresenting the amplitude of the scaled track, parameter ciCapable of varying and influencing the period of movement of the object, parameter diChanging the flexion and extension amount of each joint of the exoskeleton robot, wherein i is 1 to represent a first joint of the exoskeleton robot, i is 2 to represent a second joint of the exoskeleton robot, and t is time;
s112, in a complete movement period, collecting and storing the interaction torque of the exoskeleton robot and the sample;
s12, based on the exoskeleton robot initial reference gait track obtained in the step S11, correcting the exoskeleton robot initial reference gait track, and outputting the exoskeleton robot reference gait track of the joint phase space, wherein the method comprises the following substeps:
s121, deducing a dynamic model of the exoskeleton robot by using a Lagrange method according to the structure of the exoskeleton robot;
s122, according to impedance parameter K of interaction between exoskeleton robot and samplePAnd KDAnd calculating the correction quantity delta q of the instantaneous reference joint angle of the exoskeleton robot at each sampling moment and the corrected instantaneous reference joint angle q in a complete movement cycle by combining the interactive torque obtained in the step S112REF,NEW；
S123, obtaining the instantaneous reference joint angle q based on the step S122REF,NEWConstructing a cost function, and fitting the corrected exoskeleton robot reference gait track by minimizing the cost function through a steepest descent method
Figure FDA0003250695970000021
Wherein t is time, and i is the ith joint of the exoskeleton robot;
s124, the reference gait track obtained in the step S123
Figure FDA0003250695970000022
Exoskeleton robot reference gait track for joint phase space output through combined processing
Figure FDA0003250695970000023
Wherein hip represents a first joint angle of the exoskeleton robot, and knee represents a second joint angle of the exoskeleton robot;
s13, resetting the initial reference gait track of the exoskeleton robot and periodically updating the output of the outer layer control structure;
s2, constructing an inner layer control structure based on the joint phase space exoskeleton robot reference gait track obtained in the step S1, and outputting the exoskeleton robot joint speed reference, wherein the method specifically comprises the following substeps:
s21, collecting values of joint angles, joint speeds and joint accelerations of the exoskeleton robot in real time through absolute value encoders at joints;
s22, the exoskeleton robot reference gait track under the joint phase space acquired based on the joint angle acquired in the step S21 and the joint phase space acquired in the step S125
Figure FDA0003250695970000024
Determining an inner layer control structure, comprising the following sub-steps:
s221, mapping the sample joint angle at any moment into an instantaneous actual vector point in a joint phase space, and finding out an instantaneous target vector point closest to the instantaneous actual vector point through geometric analysis;
s222, taking the normal direction of the instantaneous target vector point as an adjusting direction
Figure FDA0003250695970000025
Taking the tangential direction of the instantaneous target vector point as the tracking direction
Figure FDA0003250695970000026
Then selecting control parameters lambda and k according to the training target, and calculating to obtain a velocity synthetic vector
Figure FDA0003250695970000027
The specific expression is as follows:
Figure FDA0003250695970000028
wherein, λ and k are inner layer control structure parameters which are respectively used for adjusting the size and the direction of the reference quantity of the joint velocity,
Figure FDA0003250695970000029
and
Figure FDA00032506959700000210
respectively a tracking direction and an adjustment direction,
Figure FDA00032506959700000211
is the distance norm between the instantaneous reference vector point and the instantaneous target vector point;
and S3, controlling the speed of the joint motor of the exoskeleton robot based on the reference joint speed obtained by the inner-layer control structure in the step S2.
2. The hierarchical control method for a lower extremity exoskeleton robot of claim 1, wherein in step S111, different initial reference gait trajectory curves for the exoskeleton joints can be generated by changing the parameter sets a-d.
3. The hierarchical control method for the lower extremity exoskeleton robot of claim 1, wherein the specific expression of the dynamical model in step S121 is as follows:
Figure FDA0003250695970000031
wherein M (q) is a 2 x 2 symmetric positive definite inertia matrix,
Figure FDA00032506959700000311
a matrix of coriolis forces and centrifugal forces, a g (q) gravity matrix,
Figure FDA0003250695970000032
is a joint clearance friction force matrix, T ═ T1,T2]T，T1Driving torque for the first joint of the exoskeleton, T2Driving torque for the second joint of the exoskeleton, Th＝[Th1,Th2]TFor man-machine interaction torque, T, measured by force sensorsh1Moment of man-machine interaction for first joint of exoskeleton, Th2For the exoskeleton second joint human-computer interaction moment, q ═ q1,q2]T，q1For the first joint angle of the exoskeleton, q2For the second joint angle of the exoskeleton,
Figure FDA0003250695970000033
Figure FDA0003250695970000034
for the first joint angular velocity of the exoskeleton,
Figure FDA0003250695970000035
for the second joint angular velocity of the exoskeleton,
Figure FDA0003250695970000036
Figure FDA0003250695970000037
for the first joint angular acceleration of the exoskeleton,
Figure FDA0003250695970000038
a second joint angular acceleration for the exoskeleton.
4. The hierarchical control method for the lower extremity exoskeleton robot of claim 1, wherein in step S122, the concrete expression of the correction amount Δ q of the instantaneous reference joint angle of the exoskeleton robot at each sampling time is as follows:
Figure FDA0003250695970000039
wherein, KP、KDAs an impedance parameter, ThThe interaction torque of the exoskeleton robot and the sample is obtained;
instantaneous reference joint angle q of exoskeleton robot after correction at each sampling momentREF,NEWThe specific expression of (a) is as follows:
qREF,NEW＝qREF,OLD-ω·Δq
wherein Δ q is a correction amount of an instantaneous reference joint angle, qREF,NEWFor the corrected instantaneous reference joint angle, qREF,OLDIs the instantaneous reference joint angle before correction, where ω is the scaling factor.
5. The hierarchical control method for a lower extremity exoskeleton robot as claimed in claim 1, wherein in step S123, the specific expression of the cost function is as follows:
Figure FDA00032506959700000310
wherein k represents the kth sampling time, i-1 represents the first joint of the exoskeleton robot, i-2 represents the second joint of the exoskeleton robot, and q represents the second joint of the exoskeleton robotREF,NEWi(k)Is the instant desired joint angle after the modification at the kth sampling instant,
Figure FDA0003250695970000041
is the reference gait track to be corrected at the kth sampling moment.
6. The hierarchical control method for a lower extremity exoskeleton robot of claim 1, wherein said step S13 specifically comprises the steps of:
s131, the corrected exoskeleton robot obtained in the step S124 is used for consulting gait tracks
Figure FDA0003250695970000042
Updating the step S111 as the initial reference gait track of the next complete movement cycle;
and S132, repeating the step S1 based on the initial reference gait track updated in the step S131, and periodically updating the output of the outer layer control structure.
7. The hierarchical control method for a lower extremity exoskeleton robot as claimed in claim 1, wherein said step S221 specifically comprises the steps of:
s2211, mapping the first joint angle and the second joint angle of the sample to be a vector point in a joint phase space at any sampling time
Figure FDA00032506959700000415
The specific expression is as follows:
Figure FDA0003250695970000043
wherein q is1Is a sample first joint angle, q2A sample second joint angle;
s2212, finding out a point on the exoskeleton robot reference gait track in the joint facies space through geometric analysis
Figure FDA00032506959700000416
Recording as instantaneous reference vector point and making instantaneous reference vector point
Figure FDA00032506959700000418
To the instantaneous actual vector point
Figure FDA00032506959700000419
Distance between two adjacent plates
Figure FDA00032506959700000417
The norm of (2) is minimum, namely the norm is an instantaneous target vector point, and the specific expression is as follows:
Figure FDA0003250695970000044
wherein,
Figure FDA0003250695970000045
for the instant reference vector point(s) it is,
Figure FDA0003250695970000046
the instantaneous actual vector points.
8. The hierarchical control method for a lower extremity exoskeleton robot of claim 1, wherein in step S222, the adjustment direction is adjusted
Figure FDA0003250695970000047
The specific expression of (a) is as follows:
Figure FDA0003250695970000048
wherein,
Figure FDA0003250695970000049
for instantaneous reference vector points
Figure FDA00032506959700000410
To the instantaneous actual vector point
Figure FDA00032506959700000411
Is determined by the distance vector of (a),
Figure FDA00032506959700000412
for instantaneous reference vector points
Figure FDA00032506959700000413
To the instantaneous actual vector point
Figure FDA00032506959700000414
Distance vector norm of (2).
CN202111044404.7A 2021-09-07 2021-09-07 Layered control method for lower limb exoskeleton robot Active CN113855477B (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
CN202111044404.7A CN113855477B (en) 2021-09-07 2021-09-07 Layered control method for lower limb exoskeleton robot

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
CN202111044404.7A CN113855477B (en) 2021-09-07 2021-09-07 Layered control method for lower limb exoskeleton robot

Publications (2)

Publication Number Publication Date
CN113855477A true CN113855477A (en) 2021-12-31
CN113855477B CN113855477B (en) 2022-07-19

Family

ID=78994628

Family Applications (1)

Application Number Title Priority Date Filing Date
CN202111044404.7A Active CN113855477B (en) 2021-09-07 2021-09-07 Layered control method for lower limb exoskeleton robot

Country Status (1)

Country Link
CN (1) CN113855477B (en)

Cited By (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN115416003A (en) * 2022-10-10 2022-12-02 电子科技大学 On-demand auxiliary control method for lower limb exoskeleton of old people
CN115416003B (en) * 2022-10-10 2024-07-30 电子科技大学 Auxiliary control method for lower limb exoskeleton as required for old people

Citations (8)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN102058464A (en) * 2010-11-27 2011-05-18 上海大学 Motion control method of lower limb rehabilitative robot
EP2384863A2 (en) * 2010-01-21 2011-11-09 Institutul de Mecanica Solidelor al Academiei Romane Method and device for dynamic control of a walking robot
EP2497610A1 (en) * 2011-03-09 2012-09-12 Syco Di Hedvig Haberl & C. S.A.S. System for controlling a robotic device during walking, in particular for rehabilitation purposes, and corresponding robotic device
CN108888473A (en) * 2018-05-22 2018-11-27 哈尔滨工业大学 Joint of lower extremity based on wearable walk-aiding exoskeleton moves reproducing method
CN110215648A (en) * 2019-06-28 2019-09-10 华中科技大学 Ectoskeleton based on body gait motor coordination characteristic coordinates gait control method
CN110703604A (en) * 2019-10-29 2020-01-17 电子科技大学 Exoskeleton dynamic model parameter identification method and exoskeleton device
CN111281743A (en) * 2020-02-29 2020-06-16 西北工业大学 Self-adaptive flexible control method for exoskeleton robot for upper limb rehabilitation
CN113001540A (en) * 2021-02-19 2021-06-22 华南理工大学 Man-machine interaction intelligent control method of load-mobile exoskeleton and exoskeleton system

Patent Citations (8)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
EP2384863A2 (en) * 2010-01-21 2011-11-09 Institutul de Mecanica Solidelor al Academiei Romane Method and device for dynamic control of a walking robot
CN102058464A (en) * 2010-11-27 2011-05-18 上海大学 Motion control method of lower limb rehabilitative robot
EP2497610A1 (en) * 2011-03-09 2012-09-12 Syco Di Hedvig Haberl & C. S.A.S. System for controlling a robotic device during walking, in particular for rehabilitation purposes, and corresponding robotic device
CN108888473A (en) * 2018-05-22 2018-11-27 哈尔滨工业大学 Joint of lower extremity based on wearable walk-aiding exoskeleton moves reproducing method
CN110215648A (en) * 2019-06-28 2019-09-10 华中科技大学 Ectoskeleton based on body gait motor coordination characteristic coordinates gait control method
CN110703604A (en) * 2019-10-29 2020-01-17 电子科技大学 Exoskeleton dynamic model parameter identification method and exoskeleton device
CN111281743A (en) * 2020-02-29 2020-06-16 西北工业大学 Self-adaptive flexible control method for exoskeleton robot for upper limb rehabilitation
CN113001540A (en) * 2021-02-19 2021-06-22 华南理工大学 Man-machine interaction intelligent control method of load-mobile exoskeleton and exoskeleton system

Non-Patent Citations (1)

* Cited by examiner, † Cited by third party
Title
LINGLING CHEN等: "Dynamic trajectory adjustment oflower limb exoskeleton in swing phase based on impedance control strategy", 《PROC IMECHE PART I-J SYSTEMS AND CONTROL ENGINEERING》 *

Cited By (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN115416003A (en) * 2022-10-10 2022-12-02 电子科技大学 On-demand auxiliary control method for lower limb exoskeleton of old people
CN115416003B (en) * 2022-10-10 2024-07-30 电子科技大学 Auxiliary control method for lower limb exoskeleton as required for old people

Also Published As

Publication number Publication date
CN113855477B (en) 2022-07-19

Similar Documents

Publication Publication Date Title
CN111281743B (en) Self-adaptive flexible control method for exoskeleton robot for upper limb rehabilitation
CN111546315B (en) Robot flexible teaching and reproducing method based on human-computer cooperation
EP2814643B1 (en) Control systems and methods for gait devices
CN111290272B (en) Attitude stationarity adjusting method based on multi-legged robot
CN113001540B (en) Man-machine interaction intelligent control method of load-mobile exoskeleton and exoskeleton system
CN110244714B (en) Sliding mode control-based robot single-leg swinging phase double-closed-loop control method
CN112975987B (en) Orthopedic surgery robot control method based on dynamic model
Wu et al. Fuzzy dynamic gait pattern generation for real-time push recovery control of a teen-sized humanoid robot
CN113771040A (en) Control system and method for lower limb exoskeleton robot
CN113855477B (en) Layered control method for lower limb exoskeleton robot
Lopez Infante et al. Usability of force-based controllers in physical human-robot interaction
CN111965979B (en) Limited time control method based on exoskeleton robot actuator
CN112171670A (en) Rehabilitation robot equal-tension motion control method and system
CN113867157B (en) Optimal trajectory planning method and device for control compensation and storage device
CN114795604B (en) Method and system for controlling lower limb prosthesis in coordination based on non-zero and game
CN113715024B (en) Position tracking control method of multi-degree-of-freedom upper limb rehabilitation robot
CN116533227A (en) Polishing method of robot polishing system based on teaching track optimization and correction
CN111158238B (en) Force feedback equipment dynamics parameter estimation algorithm based on particle swarm optimization
CN107485540A (en) A kind of intelligence that is used for assists the energy injection system for walking walking stick
Duan et al. Design of Robot Control System for Knee Joint Replacement Surgery Based on STM32
CN113987961A (en) Robot jump landing detection method
Ankarali et al. ANFIS Inverse kinematics and hybrid control of a human leg gait model
Zha et al. Exoskeleton Follow‐Up Control Based on Parameter Optimization of Predictive Algorithm
Zhang et al. Design on subsection based mix position controller for lower limb rehabilitation robot
CN114115310B (en) Motion control method and system for four-foot robot

Legal Events

Date Code Title Description
PB01 Publication
PB01 Publication
SE01 Entry into force of request for substantive examination
SE01 Entry into force of request for substantive examination
GR01 Patent grant
GR01 Patent grant