CN114750152B - Volunteer compliance auxiliary control method for variable-rigidity exoskeleton - Google Patents
Volunteer compliance auxiliary control method for variable-rigidity exoskeleton Download PDFInfo
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Abstract
The invention discloses a volunteer compliance auxiliary control method for a variable-rigidity exoskeleton, which comprises the following steps of: 1) Firstly, substituting the preprocessed surface electromyographic signals into a musculoskeletal model to calculate to obtain estimated torque and rigidity of a human joint; 2) Setting auxiliary torque and rigidity of the exoskeleton according to the estimated human joint torque and rigidity; 3) And the torque and rigidity control of the exoskeleton joint is realized by utilizing the elastic characteristics of the variable-rigidity joint. The control method of the invention not only can effectively control the auxiliary torque of the exoskeleton according to the volunteer of the user, but also can adjust the rigidity in real time according to the exercise behavior of the user; the torque auxiliary method does not need to set a reference track or an additional torque sensor, and meets the auxiliary requirements of users in different movement modes; the stiffness-variable control can improve the adaptability of the exoskeleton to the environment and improve the interaction flexibility of the exoskeleton and a user.
Description
Technical Field
The invention relates to the field of robots, in particular to a volunteer compliant auxiliary control method for a variable-rigidity exoskeleton.
Background
China has entered an aging society, and the masses with lower limb movement dysfunction caused by age diseases are increasing. Lower limb motor dysfunction has severely impacted their daily lives and has placed a significant economic and mental burden on their families. Exoskeleton robots are an exciting potential solution that can help dyskinesia patients resume daily activities.
Traditional exoskeleton robots are usually driven by motors with high reduction ratios in combination with speed reducers, and accurate position control can be achieved. However, it is difficult for the user to back drive the exoskeleton robot because of the high back drive impedance that is typically caused by the high deceleration changes. Particularly in the case of sensor failure, it is difficult to ensure user safety. The rigidity-variable exoskeleton studied at present can adapt to complex tasks due to the rigidity-variable characteristic of the rigidity-variable exoskeleton, and has high interactive flexibility and safety, so that the rigidity-variable exoskeleton is favored.
At the same time, conventional exoskeleton control typically employs precise trajectory control, reference trajectory-based impedance control, and admittance control, which has proven to be effective in exoskeleton rehabilitation training. However, in the daily walking of the user, the movement track of the user is not fixed, and such a control strategy of the preset track is not suitable for assisting the daily life of the user. In addition, because the variable stiffness characteristic of the variable stiffness exoskeleton makes control more complex, how to effectively combine the variable stiffness characteristic of the exoskeleton to improve the performance of the exoskeleton is also a current research difficulty. Therefore, there is a need to further develop a voluntary compliant auxiliary control method for a variable stiffness exoskeleton to achieve daily life assistance for lower limb dyskinesia patients.
In the chinese patent application with application number 201910574269.3, an exoskeleton coordination gait control method based on human gait motion coordination characteristics is disclosed, which determines a gait phase of a user by detecting joint angles and angular velocities of a hip joint and a knee joint, constructs ideal knee joint and hip joint coordination trajectory curves in swing phases, and enables the exoskeleton to track ideal curve trajectories through a PD controller so as to coordinate the gait of the user. But the exoskeleton adopts a fixed preset track and is only suitable for a specific walking scene of a user.
In the Chinese patent application with the application number of 201510502174.2, a method for controlling adaptive robust cascade force of a reduced-order single-joint power-assisted exoskeleton is disclosed, wherein a cascade force control method is adopted, an upper controller generates a reference track of an exoskeleton joint by measuring an interaction force sensor, and a lower controller realizes tracking of the reference track. The reference track of the exoskeleton can be changed in real time according to the motion of the user, but the measured signal of the interaction force sensor is delayed from the motion intention of the user to some extent, and the exoskeleton has additional interaction force with the user.
Disclosure of Invention
Aiming at the defects of the background technology, the technical problem to be solved by the invention is to provide the volunteer compliant auxiliary control method for the variable-rigidity exoskeleton, which can actively provide torque assistance according to the volunteer of a user, adjust the joint rigidity in real time and realize the exercise assistance for the daily life of the user.
The invention adopts the following technical scheme for solving the technical problems:
a volunteer compliance auxiliary control method for a variable stiffness exoskeleton comprises the following steps:
step S1, acquiring and executing a preset control program;
step S2, surface electromyographic signals of the user' S medial femoral muscle, lateral femoral muscle, semi-membranous muscle and semi-tendinous muscle are obtained, filtering treatment is carried out, the treated electromyographic signals are substituted into a musculoskeletal model, and the torque and the rigidity of the user joint are obtained through calculation;
s3, generating auxiliary torque and rigidity of the exoskeleton of the joint according to the torque and rigidity of the joint of the user;
step S4, adjusting the reference rigidity of the exoskeleton of the joint by adopting the estimated active participation degree self-adaption of the user according to the set exoskeleton auxiliary torque of the joint;
s5, tracking and controlling auxiliary torque of the exoskeleton of the joint by adopting a torque controller without a torque sensor according to the set exoskeleton reference track of the joint; according to the set reference rigidity of the exoskeleton of the joint, tracking control of the exoskeleton rigidity of the joint is realized by adopting closed-loop PID control;
step S6, repeating the steps S2-S5 until the auxiliary task is completed, and adjusting the auxiliary torque of the exoskeleton in real time to enable the auxiliary torque of the exoskeleton to be consistent with the required torque direction of the joints of the user, so that the exercise assistance of the daily life of the user is realized; the rigidity of the exoskeleton of the joint is adjusted in real time to ensure the optimal rigidity of the exoskeleton of the joint, so that the adaptability of the exoskeleton to the environment is improved.
Preferably, in the step S2, the method for estimating the torque and the stiffness of the joint of the user according to the myoelectric signal of the surface of the user specifically includes:
building a musculoskeletal model of a human joint:
wherein ,Fi mt Muscle tendon force, eta is the angle between the muscle and the bone, F i a Is active muscle force, F i p Is a passive muscle force;
the active and passive muscle forces are:
wherein ,fa (l i) and fp (l i ) Is a function of the length of the muscle, l i Is normalized muscle length, v i Is normalized muscle speed, f v (v i ) Is a function related to normalized muscle speed, lambda i (t) is the surface electromyographic signal after treatment,is the maximum muscle force;
muscle to joint torque:
wherein ,is the torque of the ith muscle to the joint, < >>Is the muscle force of the ith muscle, r i Is the lever arm of the ith muscle;
joint torque synthesis:
wherein the subscript Extensor represents the torque of the Extensor, flexor represents the torque of the Flexor, σ 1 Representing the extensor scaling factor, sigma 2 Representing the proportionality coefficient of the flexor muscle;
joint stiffness calculation:
wherein k1 and k2 Is a constant;
preferably, the method for generating exoskeleton auxiliary torque and stiffness of the joint in step S3 is as follows:
assistance torque of joint exoskeleton:
T ref ＝ωτ joint (7)
wherein ω is an auxiliary scaling factor;
stiffness of joint exoskeleton:
wherein ,Kθ (K joint ) Is the setting rigidity of the knee joint exoskeleton, K θ，min Is the minimum stiffness, K, of the exoskeleton of the joint θ，max Is the maximum stiffness of the exoskeleton of the joint,is the maximum joint rigidity of human body in walking, K joint Is the real-time estimated human joint stiffness.
Preferably, in the step S4, the method for controlling torque and rigidity of the exoskeleton without torque sensor includes:
in the torque control method without torque sensor, the feedback torque is estimated by exoskeleton stiffness and elastic deflection angle:
T es ＝K θ θ (9)
wherein θ is the elastic deflection angle of the exoskeleton of the joint due to external load;
the torque control method of the torque-free sensor adopts closed-loop PID control, the motor works in a speed mode, and the control input is as follows:
wherein ,e1 (t) is the error of the reference torque and the estimated torque, K p1 ，K i1 and Kd1 Is a parameter of the PID controller.
Preferably, the exoskeleton stiffness control method adopts PID closed-loop control, the motor works in a speed mode, and the control input is as follows:
wherein ,e2 (t) is the error of the reference stiffness and the estimated stiffness, K p2 ，K i2 and Kd2 Is a parameter of the PID controller.
Compared with the prior art, the technical scheme has the following beneficial effects:
1. compared with the traditional identification algorithm based on the movement intention of the surface electromyographic signals, the volunteer compliance auxiliary control method for the rigidity-variable exoskeleton provided by the invention can accurately estimate the torque and rigidity of the joints of a human body by using the surface electromyographic signals of the muscles related to the joints, does not need to collect all the muscles, and is easier to realize.
2. The volunteer compliance auxiliary control method for the variable-rigidity exoskeleton can directly assist torque according to the movement intention of a user, does not need to set references and tracks, and can be used for movement assistance of a variable-movement scene.
3. The volunteer compliance auxiliary control method for the variable-rigidity exoskeleton provided by the invention directly estimates the auxiliary torque of the exoskeleton and realizes torque control without a torque sensor by using the elastic characteristics of the exoskeleton joints, so that the cost of the exoskeleton and the size of the exoskeleton can be reduced.
4. The volunteer compliance auxiliary control method for the variable-stiffness exoskeleton can directly control the stiffness of the exoskeleton in real time, can simulate the variable-stiffness behavior of a human joint when the human joint is used for adapting to environments and tasks, and improves the adaptability of the exoskeleton to the environments.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings that are needed in the description of the embodiments or the prior art will be briefly described, and it is obvious that the drawings in the description below are some embodiments of the present invention, and other drawings can be obtained according to the drawings without inventive effort for a person skilled in the art.
FIG. 1 is a schematic representation of a musculoskeletal model of the present invention based on surface electromyographic signal actuation;
FIG. 2 is a torque sensorless torque control block diagram of the present invention;
FIG. 3 is a block diagram of a voluntary compliant auxiliary control for a variable stiffness exoskeleton of the present invention;
FIG. 4 is a flow chart of a volunteer compliant auxiliary control method for a variable stiffness exoskeleton of the present invention;
FIG. 5 is a graph of torque estimation results based on a musculoskeletal model in an embodiment of the present invention;
FIG. 6 is a graph of the results of torque control without torque sensor in an embodiment of the invention.
Detailed Description
The following description of the embodiments of the present invention will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present invention, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
The following describes the method steps in detail with reference to the flowchart, as shown in fig. 4, a volunteer compliant auxiliary control method for a variable stiffness exoskeleton, taking knee joint as an example, comprising the steps of:
step S1, acquiring and executing a preset control program;
s2, obtaining surface electromyographic signals of the user 'S medial femoral muscle, lateral femoral muscle, semi-membranous muscle and semi-tendinous muscle, filtering, substituting the processed electromyographic signals into a musculoskeletal model, and calculating to obtain the torque and rigidity of the user' S knee joint;
s3, generating auxiliary torque and rigidity of the exoskeleton knee joint according to the torque and rigidity of the knee joint of the user;
step S4, according to the set auxiliary torque of the exoskeleton knee joint, the estimated active participation degree of the user is adopted to adaptively adjust the reference rigidity of the exoskeleton knee joint;
s5, tracking and controlling auxiliary torque of the exoskeleton knee joint by adopting a torque controller without a torque sensor according to the set exoskeleton knee joint reference track; according to the set reference rigidity of the exoskeleton knee joint, tracking control of the rigidity of the exoskeleton knee joint is realized by adopting closed-loop PID control;
step S6, repeating the steps S2-S5 until the auxiliary task is completed, and adjusting the auxiliary torque of the exoskeleton in real time to enable the auxiliary torque of the exoskeleton to be consistent with the required torque direction of the knee joint of the user, so that the exercise assistance of the daily life of the user is realized; the rigidity of the exoskeleton knee joint is adjusted in real time to ensure the optimal rigidity of the exoskeleton knee joint, so that the adaptability of the exoskeleton to the environment is improved;
the invention relates to a volunteer compliance control method for a variable-rigidity exoskeleton, which mainly comprises a human joint torque and rigidity estimation algorithm driven by a surface electromyographic signal and a musculoskeletal model, an exoskeleton joint auxiliary torque and rigidity generation strategy, a sensorless torque control algorithm and exoskeleton joint rigidity closed-loop control, and is characterized by comprising the following steps:
the human joint torque and rigidity estimation algorithm based on surface electromyographic signals and musculoskeletal model driving is shown in fig. 1, taking knee joint assistance for a user as an example:
firstly, collecting surface electromyographic signals of user's vastus outside, vastus inside, semimembranous and semitendinous muscles, and filtering the collected surface electromyographic signals. The filtering sequence is as follows: the original surface electromyographic signals are filtered by a band-pass filter of 10Hz-500Hz, then filtered by a high-pass filter of 410Hz, then subjected to full-wave finishing, filtered by a 50 notch filter, finally filtered by a low-pass filter of 1Hz to obtain filtered surface electromyographic signals,
the filtered surface electromyographic signals are subjected to nonlinear mapping to obtain muscle activation:
λ i (t)＝(e ξEi(t) -1)/(e ξ -1) (a) wherein E i (t) represents the filtered surface electromyographic signal, ζ is a nonlinear mapping factor, λ i (t) is the activation of a muscle;
substituting the activation of the muscle into a musculoskeletal model to calculate the torque and stiffness of the human joint, the musculoskeletal model:
wherein ,Fi mt Muscle tendon force, eta is the angle between the muscle and the bone, F i a Is active muscle force, F i p Is a passive muscle force;
the active and passive muscle forces are:
wherein ,fa (l i) and fp (l i ) Is a function of the length of the muscle, l i Is normalized muscle length, v i Is normalized muscle speed, f v (v i ) Is a function related to normalized muscle speed, lambda i (t) is the processed surface electromyographic signal, F i max Is the maximum muscle force;
muscle length and joint angle of human bodyCan be expressed by a cubic polynomial:
wherein Is the length of the muscle, c 0i 、c 1i 、c 2i 、c 3i Coefficients that are polynomials;
normalized muscle length and angle η between muscle and bone can be expressed as:
η＝arcsin(sin(η 0 )/l i ) (d)
wherein isOptimal muscle length, eta 0 Is the optimal musculoskeletal angle;
function f related to muscle length a (l i) and fp (l i ) Can be expressed as:
wherein A, B, C, alpha 1 、α 2 、β 1 、β 2 Is a constant;
the torque of the muscle to the joint is expressed as:
wherein ,is the torque of the ith muscle to the joint, F i mt Is the muscle force of the ith muscle, r i Is the lever arm of the ith muscle;
the lever arm can be calculated as:
joint torque synthesis:
wherein the subscript Extensor represents the torque of the Extensor, flexor represents the torque of the Flexor, σ 1 Representing the extensor scaling factor, sigma 1 Representing the proportionality coefficient of the flexor muscle;
joint stiffness calculation:
wherein k1 and k2 Is a constant;
the exoskeleton joint auxiliary torque and rigidity generation strategy comprises the following specific steps:
auxiliary torque of exoskeleton knee joint:
T ref ＝ωτ joint (7)
wherein ω is an auxiliary scaling factor;
stiffness of exoskeleton knee joint:
wherein ,Kθ (K joint ) Is the setting rigidity, K, of the exoskeleton knee joint θ，min Is the minimum stiffness, K, of the exoskeleton joint θ，max Is the maximum stiffness of the exoskeleton joint,is the maximum human knee joint rigidity in walking, K joint Is the real-time estimated human knee joint rigidity.
The sensorless torque control algorithm, as shown in fig. 2, specifically comprises the following steps:
according to the elastic deflection angle theta and the rigidity K of the exoskeleton joint θ Estimating actual assist torque T of an exoskeleton joint es ：
T es ＝K θ θ (9)
Taking the estimated exoskeleton joint torque as the feedback torque of the torque controller, performing closed-loop control on the exoskeleton joint torque through the PID controller, and enabling the driving motor to work in a speed mode, wherein a speed control signal can be expressed as:
wherein ,e1 (t) is the error of the reference torque and the estimated torque, K p1 ，K i1 and Kd1 Is a parameter of the PID controller;
the exoskeleton joint stiffness closed-loop control, as shown in the stiffness control part of fig. 3, specifically comprises the following steps:
according to the characteristics of the torque T and the elastic deflection angle theta of the exoskeleton joint, the rigidity of the exoskeleton joint is estimated, and the specific method comprises the following steps:
taking the estimated exoskeleton joint stiffness as the feedback stiffness of the torque controller, performing closed-loop control on the exoskeleton joint stiffness through a PID controller, and enabling a motor to work in a speed mode, wherein the control input is as follows:
wherein ,e2 (t) is the error of the reference stiffness and the estimated stiffness, K p2 ，K i2 and Kd2 Is a parameter of the PID controller.
Finally, it should be noted that: the above embodiments are only for illustrating the technical solution of the present invention, and not for limiting the same; although the invention has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical scheme described in the foregoing embodiments can be modified or some or all of the technical features thereof can be replaced by equivalents; such modifications and substitutions do not depart from the spirit of the invention.
Claims (4)
1. A volunteer compliance auxiliary control method for a variable-stiffness exoskeleton is characterized by comprising the following steps of:
step S1, acquiring and executing a preset control program;
step S2, surface electromyographic signals of the user' S medial femoral muscle, lateral femoral muscle, semi-membranous muscle and semi-tendinous muscle are obtained, filtering treatment is carried out, the treated electromyographic signals are substituted into a musculoskeletal model, and the torque and the rigidity of the user joint are obtained through calculation;
s3, generating auxiliary torque and rigidity of the exoskeleton of the joint according to the torque and rigidity of the joint of the user;
step S4, adjusting the reference rigidity of the exoskeleton of the joint by adopting the estimated active participation degree self-adaption of the user according to the set exoskeleton auxiliary torque of the joint;
s5, tracking and controlling auxiliary torque of the exoskeleton of the joint by adopting a torque controller without a torque sensor according to the set exoskeleton reference track of the joint; according to the set reference rigidity of the exoskeleton of the joint, tracking control of the exoskeleton rigidity of the joint is realized by adopting closed-loop PID control;
step S6, repeating the steps S2-S5 until the auxiliary task is completed, and adjusting the auxiliary torque of the exoskeleton in real time to enable the auxiliary torque of the exoskeleton to be consistent with the required torque direction of the joints of the user, so that the exercise assistance of the daily life of the user is realized; adjusting the rigidity of the exoskeleton of the joint in real time to ensure the optimal rigidity of the exoskeleton of the joint, thereby improving the adaptability of the exoskeleton to the environment;
in the step S2, the processed electromyographic signals are substituted into a musculoskeletal model, and the torque and rigidity of the joints of the user are calculated as follows:
building a musculoskeletal model of a human joint:
，
wherein ,is the force of the muscle tendon and the muscle,ηis the angle between the muscle and the bone, < > and>is active muscle force, < >>Is a passive muscle force;
the active and passive muscle forces are:
，
wherein , and />Is a function of the length of the muscle, +.>Is normalized muscle length, ++>Is normalized muscle speed, ++>Is a function related to normalized muscle speed, < >>Is the processed surface electromyographic signal, +.>Is the maximum muscle force;
muscle to joint torque:
，
wherein ,is the firstiTorque of block muscle to joint, +.>Is the firstiMuscle force of block muscle,/->Is the firstiLever arm of block muscle;
joint torque synthesis:
，
wherein the subscript Extensor represents the torque of the Extensor, flexor represents the torque of the Flexor,scale factor representing extensor>Representing the proportionality coefficient of the flexor muscle;
joint stiffness calculation:
，
wherein and />Is a constant.
2. A method for voluntary compliant assistance control for a variable stiffness exoskeleton according to claim 1 wherein the assistance torque and stiffness method for generating the exoskeleton of the joint in step S3 is:
assistance torque of joint exoskeleton:
，
wherein ωIs an auxiliary proportion systemA number;
stiffness of joint exoskeleton:
，
wherein ,is the setting rigidity of the joint exoskeleton knee, +.>Is the minimum stiffness of the exoskeleton of the joint, < ->Is the maximum stiffness of the exoskeleton of the joint, +.>Is the maximum joint stiffness of the human body in walking,is the real-time estimated human joint stiffness.
3. The method according to claim 1, wherein in step S5, the auxiliary torque of the exoskeleton of the joint is tracked and controlled by the torque-sensor-free torque controller according to the set exoskeleton reference trajectory of the joint, wherein the auxiliary torque is:
feedback torque is estimated by exoskeleton stiffness and elastic deflection:
，
wherein θAn elastic deflection angle of the exoskeleton of the joint due to external load;
the control method adopts closed-loop PID control, the motor works in a speed mode, and the control input is as follows:
，
wherein ,error for reference torque and estimated torque, +.>，/> and />Is a parameter of the PID controller.
4. A voluntary compliance aid control method for a variable stiffness exoskeleton according to claim 3 in which the motor is operated in speed mode with control inputs of:
，
wherein ,e 2 (t) For the reference stiffness and the error in estimating the stiffness,K p2 ，K i2 andK d2 is a parameter of the PID controller.
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