CN104698848B - A kind of control method of lower limb exoskeleton rehabilitation robot rehabilitation training - Google Patents

Abstract

The invention discloses a kind of control method of lower limb exoskeleton rehabilitation robot rehabilitation training, by being modeled to lower limb exoskeleton rehabilitation robot, obtain model equation, adaptive controller and control rate calculation formula are built again, for wherein undetermined control gain parameter, obtained by training in advance, then the angle of rotation and velocity of rotation of actually measured lower limb exoskeleton rehabilitation robot knee joint and hip joint, actual parameter is finally substituted into Self Adaptive Control rate calculation formula, so as to obtain moment t adaptive controller, drive device applies active force according to Self Adaptive Control rate to lower limb exoskeleton rehabilitation robot.

Description

A kind of control method of lower limb exoskeleton rehabilitation robot rehabilitation training

Technical field

The invention belongs to technique of medical rehabilitation field, more specifically, it is related to a kind of lower limb exoskeleton rehabilitation robot The control method of rehabilitation training.

Background technology

With the aggravation of China's aging, the health care of elderly population causes the concern of society.Hemiplegia is old Common a kind of disease in crowd, gently can then cause inconvenient walking, gait deformation, heavy then be unable to leave the bed, completely lose life energy Power.If effective rehabilitation can not be obtained, their lower extremity motor function can not may recover forever, had a strong impact on to Their normal life.Healing robot is the new opplication that robot and rehabilitation medical are combined, and healing robot combines different Robot control method, rehabilitation training actively and passively can be provided for lower limb paralysis patient.In China human mortality aging Under increasing background, the application of healing robot can not only alleviate the heavy of rehabilitation physical therapy teacher in Traditional Rehabilitation treatment Work, it is often more important that healing robot can provide rehabilitation whenever and wherever possible according to the wish of patient, therapeutic process can be with It is monitored in real-time and records, and then analyze and can update rehabilitation after these data, so healing robot can be with Scientificlly and effectively rehabilitation is provided.

It is passively adaptive that Chinese invention patent 201110404114.9 discloses a kind of master of upper and lower limbs rehabilitation training robot Control method is answered, but passively control is simply simply its so-called master to judge patient according to the deviation of motor power voltage value It is no have actively be intended to, but do not provide this processing procedure basis and this method whether have reliability.Institute The Self Adaptive Control of meaning is also a simple judgement, is taken the initiative or passive controlling party in some scope according to voltage error value Method.This Self Adaptive Control can not overcome the influence of robot Parameters variation or disturbance to robot control system.

Chinese invention patent 201010561379.5 discloses a kind of motion control method of lower limb rehabilitative robot, the invention In planned two kinds of training modes for two stages in the rehabilitation course of patient, i.e. actively and passively training mode.According to people Machine interactive forces judge the motion intention of patient, then pass through adaptive controller and produce gait track, carry out active instruction Practice.The invention gives robot system two close cycles prosecutor method, and the design of specific algorithm is not related to, and the control method does not have Consider the influence of robot system external disturbance and Parameters variation to the control of robot.

The existing invention of analysis is it can be found that the control method in existing invention focuses mostly in robot system upper strata The design of control method, such as, actively and passively train, and is but seldom related to the bottom control method realized and actively and passively trained Design, such as, it is considered to which, when realizing main passive control, how control machine person joint accurately realizes movement locus.

The content of the invention

It is an object of the invention to overcome the deficiencies of the prior art and provide a kind of lower limb exoskeleton rehabilitation robot rehabilitation instruction Experienced control method, by way of bottom control, control lower limb rehabilitation robot does accurate motion in accordance with the instructions.

For achieving the above object, the control method of a kind of lower limb exoskeleton rehabilitation robot rehabilitation training of the invention, It is characterised in that it includes following steps：

(1), lower limb exoskeleton rehabilitation robot is modeled, the governing equation of lower limb exoskeleton rehabilitation robot is obtained For：

Wherein, q (t) represents the angle of rotation of knee joint and hip joint；Represent knee joint and hip joint Velocity of rotation；Represent the rotation acceleration of knee joint and hip joint；τ (t) is adaptive controller；M (q (t)) represents the inertial matrix of lower limb exoskeleton rehabilitation robot model；G (q (t)) represents lower limb exoskeleton rehabilitation robot The gravity of model；Represent centrifugation and the coriolis force matrix of lower limb exoskeleton robot model；

Formula (1) is linearized, obtained：

Wherein,The matrix constituted for the function of time, and angle of rotation q (t) with knee joint and hip joint, Velocity of rotationIt is related；Represent the unknown parameter in robot model；

(2) adaptive controller τ (t), and Self Adaptive Control rate, are built

Wherein,Respectively：Estimate, centrifugation and the coriolis force of inertial matrix Estimate, the estimate of gravity of item matrix；

ForEstimation, over time, constantly level off to true valueForFirst derivative；

E (t)=q_d(t)-q (t), represents tracking error vector, Wherein, q_d(t) it is that knee joint and hip joint anticipate the angle of rotation reached；

K_vAnd K_pIt is control gain parameter, is obtained by training in advance, training method is：It is imitative beforehand through MATLAB softwares A true lower limb exoskeleton rehabilitation robot system, sets other parameters in boarder controller τ (t), is controlled further according to border Governing equation in device τ (t) processed and step (1) carries out simulation training, and its training objective is to make lower limb exoskeleton rehabilitation robot The tracking error e (t) in each joint≤M in system, 0≤M ＜ 100；

(3), in moment t, the angle of rotation q (t) and velocity of rotation of knee joint and hip joint are gathered using photoelectric encoder

(4), the actual parameter for obtaining step (3) substitutes into step (2) and obtains Self Adaptive Control rateSo as to when obtaining T adaptive controller τ (t) is carved, drive device is acted on further according to adaptive controller τ (t) to lower limb rehabilitation robot application Power, driving articulation to q_d(t)。

What the goal of the invention of the present invention was realized in：

The control method of invention lower limb exoskeleton rehabilitation robot rehabilitation training, by lower limb exoskeleton health Multiple robot is modeled, and obtains model equation, then builds adaptive controller and control rate calculation formula, for wherein not true Fixed control gain parameter, is obtained by training in advance, then actually measured lower limb exoskeleton rehabilitation robot knee joint and hip The angle of rotation and velocity of rotation in joint, finally substitute into Self Adaptive Control rate calculation formula, so as to obtain moment t's by actual parameter Adaptive controller, drive device applies active force according to Self Adaptive Control rate to lower limb exoskeleton rehabilitation robot.

Meanwhile, a kind of control method of lower limb exoskeleton rehabilitation robot rehabilitation training of the invention also has following beneficial effect Really：

(1) it is lower limb applied to lower limb exoskeleton rehabilitation robot system, present invention employs adaptive control algorithm Paralysed patient provides rehabilitation training, even in occurring under disturbance and inherent parameters change, can equally solve robot model's parameter Change the not enough problem of the control accuracy brought；

(2), the present invention is compared to Traditional Rehabilitation training method, and advantage is that patient is not constrained by time, place, and Training process is recordable, assess；

(3), the present invention adds trace vector, i.e., when lower limb exoskeleton rehabilitation machine when designing adaptive controller When people is moved by driving instruction, it can judge whether to control lower limb exoskeleton rehabilitation robot by way of tracking by driving Instruction carries out rehabilitation exercise.

Brief description of the drawings

Fig. 1 Fig. 1 is the mechanical structure schematic diagram of lower limb exoskeleton rehabilitation robot；

Fig. 2 is the control method flow chart of lower limb exoskeleton rehabilitation robot rehabilitation training of the present invention；

Fig. 3 is the control method theory diagram of lower limb exoskeleton rehabilitation robot rehabilitation training of the present invention；

Fig. 4 is kneed rotational angle tracking schematic diagram；

Fig. 5 is the rotational angle tracking schematic diagram of hip joint；

Fig. 6 is the rotational angle tracking error schematic diagram of knee joint and hip joint.

Embodiment

The embodiment to the present invention is described below in conjunction with the accompanying drawings, so as to those skilled in the art preferably Understand the present invention.Requiring particular attention is that, in the following description, when known function and design detailed description perhaps When can desalinate the main contents of the present invention, these descriptions will be ignored herein.

Embodiment

Fig. 1 is the mechanical structure schematic diagram of lower limb exoskeleton rehabilitation robot.

In the present embodiment, as shown in figure 1, every leg of lower limb exoskeleton rehabilitation robot is respectively provided with 2 frees degree, i.e., Hip joint and knee joint respectively have one degree of freedom.In following adaptive controller design process, be all based on the 2 of single leg from Designed by degree model.

Fig. 2 is the control method flow chart of lower limb exoskeleton rehabilitation robot rehabilitation training of the present invention.

As shown in Fig. 2 in the present embodiment, a kind of control method of lower limb exoskeleton rehabilitation robot rehabilitation training, bag Include following steps：

S201, lower limb exoskeleton rehabilitation robot is modeled, obtains the model side of lower limb exoskeleton rehabilitation robot Cheng Wei：

Wherein, q (t)=[q₁(t),q₂(t)]^T, represent knee joint q₁(t) with hip joint q₂(t) angle of rotation；Represent the velocity of rotation of knee joint and hip joint；Represent knee joint and hip joint Rotation acceleration；τ (t) is adaptive controller；M (q (t)) represents the moment of inertia of lower limb exoskeleton rehabilitation robot model Battle array；G (q (t)) represents the gravity of lower limb exoskeleton rehabilitation robot model；Represent lower limb exoskeleton robot The centrifugation of model and coriolis force matrix；

Wherein,

Wherein：m₁,m₂The quality of knee joint and hip joint is represented respectively；a₁,a₂The length of knee joint and hip joint is represented respectively Degree, g is gravity constant；

Order：Then Obtain：

Formula (1) is linearized, obtained：

Wherein,The matrix constituted for the function of time, and angle of rotation q (t) with knee joint and hip joint, Velocity of rotationIt is related；Represent the unknown parameter in robot model；

After the model equation of lower limb exoskeleton rehabilitation robot is set up, it is thus necessary to determine that the relevant parameter in equation, and combine In the motion of state modulator lower limb exoskeleton rehabilitation robot, step below, to being but described in detail for relevant parameter, such as Under：

S202, structure adaptive controller τ (t), and Self Adaptive Control rate

Wherein,Respectively：Estimate, centrifugation and the coriolis force of inertial matrix Estimate, the estimate of gravity of item matrix；

ForEstimation, over time, constantly level off to true valueForFirst derivative；

E (t)=q_d(t)-q (t), represents tracking error vector, Wherein, q_d(t) it is that knee joint and hip joint anticipate the angle of rotation reached；

K_vAnd K_pIt is control gain parameter, is obtained by training in advance, training method is：It is imitative beforehand through MATLAB softwares A true lower limb exoskeleton rehabilitation robot system, sets other parameters in boarder controller τ (t), is controlled further according to border Governing equation in device τ (t) processed and step S201 carries out simulation training, and its training objective is to make lower limb exoskeleton rehabilitation robot The tracking error e (t) in each joint≤M in system, 0≤M ＜ 100；In the present embodiment as M=5, training objective is met K_vAnd K_p, it is the required control gain parameter of the present invention；

S203, in moment t, the angle of rotation q (t) and velocity of rotation of knee joint and hip joint are gathered using photoelectric encoder

S204, the actual parameter for obtaining step S203 substitute into step S202 and obtain Self Adaptive Control rateSo as to To moment t adaptive controller τ (t), drive device applies further according to adaptive controller τ (t) to lower limb rehabilitation robot Active force, driving articulation to q_d(t)。

Practicality to illustrate the invention, carries out stability checking to lower limb rehabilitation robot system below.

Defining tracking error is：E (t)=q_d(t)-q(t)；

By t unknown parameterEstimateFormula (2) is updated to, can be obtained：

It can be obtained according to formula (1), (2)：

It can be obtained further according to formula (3) and (6)：

Define unknown parameterError be：Therefore, it can be obtained according to error definition：

Formula (8) is rewritten into following form：

Single order and second dervative are asked to tracking error e (t), obtained：

OrderO_nFor the vector of 2 × 1 rank 0, I_nFor 2 × 1 ranks Unit vector；

Then formula (10) can be write as vector form：

Choosing Liapunov function is：

Wherein, P is 4 × 4 symmetric positive definite scalar matrixes；Γ is 5 × 5 diagonal positive definite scalar matrixes.

First derivative is asked to formula (13), obtained：

According toSymmetry, and by (12) substitution (14) can obtain：

Wherein, Q is positive definite symmetric matrices, and meets Li Yapuduofu equations

A^TP+PA=-Q (16)

Adaptive rate in formula (4) is equivalent to

It is unit diagonal matrix to take Γ, P, and (17) substitution (15) is obtained：

Understand that liapunov function V (t) lower bounds are zero according to formula (18)；Understood according to formula (13), E (t),All bounded；It can be seen from the definition of tracking error,It is bounded, meanwhile,It is also bounded.Further according to Formula (12) is understoodIt is bounded；Therefore, Rayleigh-inner hereby theorem is passed throughIt can obtain, lower limb exoskeleton rehabilitation Robot system is asymptotically stability.

Fig. 3 is the control method theory diagram of lower limb exoskeleton rehabilitation robot rehabilitation training of the present invention.

In the present embodiment, as shown in figure 3, adaptive controller is according to the actual rail expected rehabilitation track and fed back Mark data calculate control torque, then export corresponding torque by motor, and then control machine people moves, and then are apoplexy Patient provides lower limb rehabilitation training.

Fig. 4 is kneed rotational angle tracking schematic diagram.

Fig. 5 is the rotational angle tracking schematic diagram of hip joint.

In the presence of adaptive controller τ (t), as shown in figure 4, the knee joint of lower limb exoskeleton rehabilitation robot is actual Rotational angle q₁(t) it is achieved that in 1s for expected angle q_1d(t) high-precision position tracking, and tracked after t=1s Error is less than 1；As shown in figure 5, the hip joint actual rotation angle q of lower limb exoskeleton rehabilitation robot₂(t) it is just real in 1.1s Show for expected angle q_1d(t) high-precision position tracking, tracking error is similarly less than 1 after t=1.1s.

Fig. 6 is the rotational angle tracking error schematic diagram of knee joint and hip joint.

In the presence of adaptive controller, after t=1s, the tracking error e of knee joint and hip joint₁(t)、e₂(t) it is small In 1, setting index is met, the control targe of position tracking is completed, it was demonstrated that the validity of controller.And e₁(t)、e₂(t) exist Tend to 0 after 2s, this illustrates that the controller of design has good control performance, can satisfactorily reach effect needed for us Really.So as to realize the accuracy that fast driving system reaches precalculated position control machine people motion.

Although illustrative embodiment of the invention is described above, in order to the technology of the art Personnel understand the present invention, it should be apparent that the invention is not restricted to the scope of embodiment, to the common skill of the art For art personnel, as long as various change is in the spirit and scope of the present invention that appended claim is limited and is determined, these Change is it will be apparent that all utilize the innovation and creation of present inventive concept in the row of protection.

Claims (1)

1. a kind of control method of lower limb exoskeleton rehabilitation robot rehabilitation training, it is characterised in that comprise the following steps：

(1), lower limb exoskeleton rehabilitation robot is modeled, the governing equation for obtaining lower limb exoskeleton rehabilitation robot is：

$M\left(q\right(t\left)\right)\stackrel{\·\·}{q}\left(t\right)+V\left(q\right(t),\stackrel{\·}{q}(t\left)\right)+G\left(q\right(t\left)\right)=\mathrm{\τ}\left(t\right)---\left(1\right)$

Wherein, q (t) represents the angle of rotation of knee joint and hip joint；Represent turn of knee joint and hip joint Dynamic speed；Represent the rotation acceleration of knee joint and hip joint；τ (t) is adaptive controller；M(q (t) inertial matrix of lower limb exoskeleton rehabilitation robot model) is represented；G (q (t)) represents lower limb exoskeleton rehabilitation robot mould The gravity of type；Represent centrifugation and the coriolis force matrix of lower limb exoskeleton robot model；

Wherein,

$M\left(q\right(t\left)\right)=\left[\begin{array}{cc}(\frac{1}{4}{m}_1+m_2)a_1^2+\frac{1}{4}{m}_2{a}_2^2+m_2{a}_1{a}_{2}cos\left(q_2\right(t\left)\right)& \frac{1}{4}{m}_2{a}_2^2+m_2{a}_1{a}_{2}cos\left(q_2\right(t\left)\right)\\ \frac{1}{4}{m}_2{a}_2^2+m_2{a}_1{a}_2\cos \left(q_2\right(t\left)\right)& \frac{1}{4}{m}_2{a}_2^2\end{array}\right]$

$V\left(q\right(t),\stackrel{\·}{q}(t\left)\right)=\frac{1}{2}{m}_2{a}_1{a}_{2}sin\left(q_2\right(t\left)\right)\left[\begin{array}{cc}-2{\stackrel{\·}{q}}_2\left(t\right)& -{\stackrel{\·}{q}}_2\left(t\right)\\ {\stackrel{\·}{q}}_1\left(t\right)& 0\end{array}\right]$

$G\left(q\right(t\left)\right)=\left[\begin{array}{c}(\frac{1}{2}{m}_1+m_2)g{a}_{1}cos\left(q_1\left(t\right)\right)+\frac{1}{2}{m}_{2}g{a}_{2}cos(q_1\left(t\right)+q_2\left(t\right))\\ \frac{1}{2}{m}_{2}g{a}_2\cos (q_1\left(t\right)+q_2\left(t\right))\end{array}\right]$

Wherein：m₁,m₂The quality of knee joint and hip joint is represented respectively；a₁,a₂The length of knee joint and hip joint, g are represented respectively For gravity constant；

Order： Then obtain：

Formula (1) is linearized, obtained：

Wherein,The matrix constituted for the function of time, and angle of rotation q (t) with knee joint and hip joint, rotate SpeedIt is related；Represent the unknown parameter in robot model；

(2) adaptive controller τ (t), and Self Adaptive Control rate, are built

Wherein,Respectively：Estimate, centrifugation and coriolis force a matrix for inertial matrix Estimate, the estimate of gravity；

ForEstimation, over time, constantly level off to true valueForFirst derivative；

E (t)=q_d(t)-q (t), represents tracking error vector,Wherein, q_d(t) it is that knee joint and hip joint anticipate the angle of rotation reached；

$\mathrm{\Ω}\left(t\right)={\[0,0,\stackrel{\·}{e}{\left(t\right)}^T\]}^T;$

K_vAnd K_pIt is control gain parameter, is obtained by training in advance, training method is：Beforehand through MATLAB software emulations one Individual lower limb exoskeleton rehabilitation robot system, sets other parameters in adaptive controller τ (t), further according to boundary Control Governing equation in device τ (t) and step (1) carries out simulation training, and its training objective is to make lower limb exoskeleton rehabilitation robot system The tracking error e (t) in each joint≤M% in system, 0≤M ＜ 100；

(3), in moment t, the angle of rotation q (t) and velocity of rotation of knee joint and hip joint are gathered using photoelectric encoder

(4), the actual parameter for obtaining step (3) substitutes into step (2) and obtains Self Adaptive Control rateSo as to obtain moment t Adaptive controller τ (t), drive device further according to adaptive controller τ (t) to lower limb rehabilitation robot apply active force, Articulation is driven to q_d(t)。