Hybrid active-disturbance-rejection admittance control system of cervical vertebra rehabilitation robot

Abstract

The invention provides a hybrid active-disturbance-rejection admittance control system of a cervical vertebra rehabilitation robot, and relates to the technical field of admittance control, the cervical vertebra rehabilitation robot adopts a pneumatic artificial muscle system as a driving element, and the control system comprises an outer ring admittance controller, an inner ring active-disturbance-rejection controller and a self-adaptive combination valve; the outer ring admittance controller is used for adjusting an expected track according to the error between the actual feedback force and the expected tracking force; the inner-loop active-disturbance-rejection controller comprises a tracking differentiator, an extended observer and a nonlinear feedback controller and is used for suppressing nonlinearity and external disturbance of the pneumatic artificial muscle system; the self-adaptive combination valve is used for controlling the inflation and deflation flow of the pneumatic artificial muscle system; wherein the output of the outer ring admittance controller is used as the input of the inner ring active-disturbance-rejection controller, and the output of the inner ring active-disturbance-rejection controller is used for controlling the adaptive combination valve. According to the invention, effective suppression of nonlinearity and external interference is realized, and the accuracy of position control and the flexibility of force output are considered at the same time.

Description

Technical Field

[0001] The invention relates to the technical field of admittance control, and in particular to a hybrid auto-disturbance rejection admittance control system of a cervical vertebra rehabilitation robot. Background Art

[0002] As a device for assisting rehabilitation, cervical rehabilitation robots play an important role in improving cervical function. Traditional cervical rehabilitation robots are mainly driven by motors and achieve traction movements through mechanical structures. This method can achieve the purpose of cervical rehabilitation to a certain extent, but it still has some limitations.

[0003] With the continuous development of automation technology, the continuous integration of control force, mechanical technology and medical technology, researchers have developed a variety of cervical rehabilitation robots. For example, some researchers have designed an automatic robot that can perform cervical traction in a single extension spring and cadaver model. The device can accurately apply traction and maintain a corresponding linear increase in steady-state force and actuator displacement during operation. Other researchers have invented a horizontal cervical rehabilitation robot that can accurately adjust the angle, direction, and traction of cervical traction. In order to achieve multi-degree-of-freedom rehabilitation, some researchers have designed a six-degree-of-freedom cable-driven robot platform that can achieve natural head and neck movement.

[0004] However, existing cervical rehabilitation robots still face some challenges. First, most devices use motor-driven end effectors. Although they have high control accuracy, they have strong rigidity and small allowable misalignment. If the maximum tensile displacement and angle of the rehabilitation patient are exceeded during traction, it is easy to cause cervical spine injury. Secondly, the existing control methods mainly include PID control, fuzzy control, adaptive control, etc. These methods have improved the control performance of the system to a certain extent, but it is still difficult to effectively solve the problems of nonlinearity and external interference.

[0005] Therefore, developing a new cervical rehabilitation robot control system is of great significance to improving the performance and safety of the cervical rehabilitation robot. Summary of the invention

[0006] In view of this, the present invention proposes a hybrid self-disturbance rejection admittance control system for a cervical rehabilitation robot, aiming to solve the shortcomings of existing cervical rehabilitation robots in terms of control accuracy and safety. The system uses pneumatic artificial muscles as driving elements, combined with an outer loop admittance controller and an inner loop self-disturbance rejection controller, as well as an adaptive combination valve, to achieve effective suppression of nonlinearity and external interference, while taking into account the accuracy of position control and the flexibility of force output. The system can improve the control performance of the cervical rehabilitation robot, ensure safety and comfort during traction, and thus provide more accurate, safe and effective technical support for cervical rehabilitation.

[0007] The technical solution of the present invention is implemented as follows: The present invention provides a hybrid auto-disturbance rejection admittance control system of a cervical vertebra rehabilitation robot, the cervical vertebra rehabilitation robot adopts a pneumatic artificial muscle system as a driving element, and the control system includes:

[0008] Outer loop admittance controller, inner loop anti-disturbance controller and adaptive combination valve;

[0009] The outer loop admittance controller uses a mass-spring-damper virtual dynamic model to adjust the desired trajectory according to the error between the actual feedback force and the desired tracking force;

[0010] The inner loop anti-disturbance controller includes a tracking differentiator, an extended observer and a nonlinear feedback controller, which is used to suppress the nonlinearity and external disturbance of the pneumatic artificial muscle system and realize position control.

[0011] The adaptive combination valve is used to control the charging and discharging flow of the pneumatic artificial muscle system;

[0012] The output of the outer loop admittance controller is used as the input of the inner loop anti-disturbance rejection controller, and the output of the inner loop anti-disturbance rejection controller is used to control the adaptive combination valve to achieve position control of the cervical rehabilitation robot during traction.

[0013] Based on the above solution, preferably, the force equation of the mass-spring-damper virtual dynamic model is:

[0014]

[0015] In the formula, m r is the expected inertia matrix, b r is the desired damping matrix, k r is the expected stiffness matrix; e w =v d -v0,v d is the reference trajectory, v0 is the desired trajectory after the outer loop admittance controller; Δf = f e -f r >0,f r is the expected tracking force, f e is the actual feedback force.

[0016] Based on the above scheme, preferably, the tracking differentiator is designed as follows:

[0017]

[0018]

[0019] Where r0 is the tracking differentiator speed factor; h0 is the tracking differentiator filter factor; v1 is the tracking signal of the input signal v0 obtained by the tracking differentiator; and v2 is the differential signal of v1.

[0020] Based on the above scheme, preferably, the expression of the extended observer is as follows:

[0021]

[0022] In the formula, x p1 , x p2 and x p3 is the state of the pneumatic artificial muscle system; w is x p3 The differentials of; z1, z2 and z3 are x p1 , x p2 and x p3 The estimated observation value of the angle observation z1 and the output angle x p1 The error of 01 , β 02 and β 03 is the gain coefficient of the extended observer; u0 is the output duty cycle; b0 is the polynomial coefficient;

[0023] fal(e1,a i ,δ) function expression is as follows:

[0024]

[0025] In the formula, δ i is the length of the linear interval; a i is the feedback power.

[0026] Based on the above solution, preferably, the expression of the nonlinear feedback controller is as follows:

[0027]

[0028] In the formula, ε i , i = 1, 2 is the v after the tracking differentiator i and the estimated observation z i Error, β1 and β2 are proportional differential coefficients.

[0029] Based on the above solution, preferably, the adaptive combination valve includes two electrical proportional valves, a control unit and a pressure sensor;

[0030] The air inlet of the first electrical proportional valve is connected to the air compressor, and the air outlet is connected to the pneumatic artificial muscle; the air inlet of the second electrical proportional valve is connected to the pneumatic artificial muscle, and the air outlet is connected to the atmosphere;

[0031] The control unit is used for adjusting the opening of two electric proportional valves according to the output of the inner loop anti-disturbance controller;

[0032] Pressure sensors are used to detect the internal pressure of pneumatic artificial muscle systems.

[0033] On the basis of the above scheme, preferably, the cervical rehabilitation robot includes a seat, a displacement sensor, a tension sensor, a steel cable, a neck brace and a pneumatic artificial muscle system;

[0034] Among them, the pneumatic artificial muscle system is placed side by side with the displacement sensor, the lower end is fixed, and the upper end is connected to the tension sensor, and the tension sensor is connected to the neck support through a cable.

[0035] Based on the above solution, preferably, the traction mode of the cervical rehabilitation robot includes continuous traction and intermittent traction;

[0036] Among them, continuous traction is achieved by fixed-point position control, and intermittent traction is achieved by intermittent cervical stretching optimal control curve.

[0037] On the basis of the above scheme, preferably, the intermittent cervical stretching optimal control curve is generated based on the minimum jerk model, and its expression is:

[0038]

[0039] Among them, v t is the optimal control curve of intermittent cervical traction, T is the period of the optimal control curve of intermittent cervical traction, n is the number of repetitions of the optimal control curve of intermittent cervical traction, t is the time value, d is the interval time, t0 is the start time of joint movement, t f is the moment when the joint movement stops, v s0 is the initial position of the joint movement, v s1 This is the stop position of the joint movement.

[0040] On the basis of the above scheme, preferably, the operation process of the control system is:

[0041] The S1 outer loop admittance controller receives the actual feedback force and the desired tracking force, calculates the error and adjusts the desired trajectory;

[0042] The desired trajectory adjusted by S2 is input into the inner loop ADRC;

[0043] The S3 tracking differentiator generates a smooth trajectory and a differential signal;

[0044] S4 extended observer estimates system state and total disturbance;

[0045] The S5 nonlinear feedback controller calculates the control quantity based on the output of the extended observer;

[0046] The S6 control quantity is transmitted to the adaptive combination valve to adjust the filling and discharging flow of the pneumatic artificial muscle system;

[0047] The S7 pneumatic artificial muscle system drives the cervical rehabilitation robot to perform traction movements;

[0048] The S8 displacement sensor and tension sensor provide real-time feedback of displacement and force information to form a closed-loop control.

[0049] Compared with the prior art, the present invention has the following beneficial effects:

[0050] (1) The control system proposed in the present invention, by combining an outer loop admittance controller and an inner loop anti-disturbance control controller, effectively suppresses the nonlinearity and external interference of the pneumatic artificial muscle system, while taking into account the accuracy of position control and the compliance of force output. The system can adaptively adjust the desired trajectory according to the error between the actual feedback force and the desired tracking force, thereby ensuring the position control accuracy of the cervical rehabilitation robot during traction, while effectively avoiding potential damage to the cervical spine caused by excessive tension;

[0051] (2) The present invention uses a pneumatic artificial muscle system as a driving element, which has better flexibility and continuous deformation ability than traditional motor drive. This driving method can provide buffering and protection for the cervical spine during traction, thereby improving the comfort and safety of the rehabilitation process;

[0052] (3) The inner loop anti-disturbance control of the present invention introduces a tracking differentiator, which can quickly track the input signal and generate a smooth trajectory and differential signal, effectively improving the signal-to-noise ratio and control quality of the system;

[0053] (4) The extended observer of the present invention can accurately estimate the system state and total disturbance. Combined with the nonlinear feedback controller, it effectively overcomes the inherent nonlinearity, time-varying and susceptibility to external interference of the pneumatic artificial muscle system, thereby improving the accuracy of position control.

[0054] (5) The present invention adopts an adaptive combination valve to control the charging and discharging flow of the pneumatic artificial muscle system. Through the coordinated work of two electrical proportional valves, a more precise and flexible control of the pneumatic artificial muscle system is achieved, further improving the response speed and control accuracy of the system.

[0055] (6) The present invention provides two traction modes: continuous traction and intermittent traction. The intermittent traction adopts an optimal control curve generated based on a minimum jerk model, which can minimize the discomfort during the traction process while ensuring the rehabilitation effect, thereby improving comfort and safety. BRIEF DESCRIPTION OF THE DRAWINGS

[0056] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0057] Figure 1 It is a control system framework diagram of the present invention;

[0058] Figure 2 A schematic diagram of the pneumatic artificial muscle of the present invention;

[0059] Figure 3 A schematic diagram of a three-element model of a pneumatic artificial muscle system of the present invention;

[0060] Figure 4 is a control block diagram of the inner loop ADRC controller of the present invention;

[0061] Figure 5 This is a comparison chart of the fixed-point position control results of the inner-loop anti-disturbance controller and the PID controller of the present invention;

[0062] Figure 6 It is a result comparison diagram of the intermittent cervical vertebra stretching optimal control curve of the inner loop anti-disturbance controller and the PID controller of the present invention;

[0063] Figure 7 This is a diagram of trajectory tracking control experimental results of Example 1 of the present invention;

[0064] Figure 8 Schematic diagram of the relationship between the desired force and the pulling force of Example 1 of the present invention;

[0065] Fig. 9 This is a graph showing the trajectory tracking control experimental results of Example 2 of the present invention;

[0066] Fig.10 Schematic diagram of the relationship between the desired force and the pulling force of Example 2 of the present invention. DETAILED DESCRIPTION

[0067] The following will be combined with the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0068] like Figure 1As shown, the present invention provides a hybrid auto-disturbance rejection admittance control system of a cervical vertebra rehabilitation robot, the cervical vertebra rehabilitation robot adopts a pneumatic artificial muscle system as a driving element, and the control system includes:

[0069] Outer loop admittance controller, inner loop anti-disturbance controller and adaptive combination valve;

[0070] The outer loop admittance controller uses a mass-spring-damper virtual dynamic model to adjust the desired trajectory according to the error between the actual feedback force and the desired tracking force;

[0071] The inner loop anti-disturbance controller includes a tracking differentiator, an extended observer and a nonlinear feedback controller, which is used to suppress the nonlinearity and external disturbance of the pneumatic artificial muscle system and realize position control.

[0072] The adaptive combination valve is used to control the charging and discharging flow of the pneumatic artificial muscle system;

[0073] The output of the outer loop admittance controller is used as the input of the inner loop anti-disturbance rejection controller, and the output of the inner loop anti-disturbance rejection controller is used to control the adaptive combination valve to achieve position control of the cervical rehabilitation robot during traction.

[0074] Specifically, the cervical rehabilitation robot of the present invention adopts a pneumatic artificial muscle system (PAM) as a driving element, and its main body is mainly a seat, a displacement sensor, a tension sensor, a steel cable and a neck brace, etc. The PAM and the displacement sensor are placed side by side, the lower end is fixed, and the upper end is connected to the tension sensor, and the tension sensor is connected to the neck brace through a cable. In order to avoid damage to the cervical spine during the debugging process during the test, a group of springs are used to simulate the neck structure, the lower end of the spring is fixed, and the upper end of the spring is connected to the tension sensor through a cable. Inflating and deflating the PAM can drive the spring to stretch up and down, imitating the process of cervical traction, and the displacement sensor and the tension sensor can respectively monitor and detect the displacement and tension in real time.

[0075] The control system of the present invention adopts an outer loop admittance controller, an inner loop anti-disturbance control controller and an adaptive combination valve to control the charging and discharging flow of PAM. The adaptive combination valve includes two electrical proportional valves, a control unit and a pressure sensor; wherein the air inlet of the first electrical proportional valve is connected to the air compressor, and the air outlet is connected to the pneumatic artificial muscle; the air inlet of the second electrical proportional valve is connected to the pneumatic artificial muscle, and the air outlet is connected to the atmosphere; the control unit is used to adjust the opening of the two electrical proportional valves according to the output of the inner loop anti-disturbance control controller; the pressure sensor is used to detect the internal pressure of the pneumatic artificial muscle system, predict the definition data, and transmit the pressure data to the host computer through the control unit.

[0076] During the PAM inflation and deflation process, a low-noise air compressor is used to inflate the PAM, a displacement sensor is used to detect the displacement of the PAM inflation and deflation (corresponding to the displacement of the cervical traction), and a tension sensor is used to detect the tension generated by the PAM (corresponding to the tension of the cervical traction). The air inlet and outlet of the electrical proportional valve 1 are connected to the air compressor and the PAM respectively. When valve 1 is opened, the air compressor sends gas into the PAM, the volume of the PAM increases, and the radial shortening generates a downward pulling force. The air inlet of the electrical proportional valve 2 is connected to the PAM. When valve 2 is opened, the PAM discharges the internal gas, the volume of the PAM decreases, and the radial lengthens to generate a contraction force. By adjusting the duty cycle of the PWM wave input to valves 1 and 2, the acceleration when the displacement changes can be controlled.

[0077] See also Figure 2 The PAM used in the present invention is a flexible controller composed of an inner rubber tube and an outer fiber layer. When inflated, it will expand radially and contract axially, and the opposite will happen when deflated. Figure 2 Where L is the length and D is the width. Let the volume of PAM be V q for:

[0078]

[0079] The present invention has two electric proportional valves EPV. When modeling them, the Sanville flow formula is used to calculate the mass flow rate q of the ideal gas. m :

[0080]

[0081] In the formula, C q A is the high-speed switch valve flow coefficient; v is the effective valve port area; K = 1.4 is the air specific heat ratio, R = 287 N·m / kg·k is the ideal gas constant, T is the absolute temperature of the gas source, p a 、p b is the valve inlet and outlet pressure.

[0082] When the temperature inside the electric proportional valve remains unchanged, the flow rate is related to the valve opening area, and the PWM wave duty cycle determines the valve opening area and thus affects the outlet pressure p b Therefore, q m Equivalently viewed as:

[0083] q m =K a u0+K b p b (3)

[0084] Where K a , K b is the unknown coefficient, and u0 is the output duty cycle.

[0085] In the present invention, the adiabatic filling / deflating process of the pneumatic artificial muscle chamber with limited internal volume still complies with the thermodynamic energy conservation equation. Therefore, the energy conservation equation of the pneumatic artificial muscle is:

[0086]

[0087] Where P q is the internal driving pressure of the pneumatic artificial muscle, V q is the volume of the pneumatic artificial muscle chamber, q m1 is the net mass flow rate entering the pneumatic artificial muscle chamber, q m1 =q m2 -q m3 . Where q m2 is the mass flow rate of gas filling the pneumatic artificial muscle chamber, q m3 Mass flow rate for deflation of the pneumatic artificial muscle chamber.

[0088] Schematic diagram of the pneumatic artificial muscle system Figure 3 As shown in the figure, in the three-element model of pneumatic artificial muscle, it is equivalent to a structure composed of a damping element, a spring element and a contraction element in parallel. Based on this, the dynamic model of the pneumatic artificial muscle system is established:

[0089]

[0090] Among them, F t F is the tension of the spring on the pneumatic artificial muscle, and x is the displacement of the pneumatic artificial muscle. c (P q ), F s (x,P q ) represent the contraction force, damping force and spring force of the pneumatic artificial muscle, respectively, which can be expressed as:

[0091]

[0092] In the formula, C(P q ), K1(P q ), K2(P q ) represent the damping coefficient, first-order spring coefficient and second-order spring coefficient, respectively, f1, f2, c1, c2, k 11 , k 12 , k 21 , k 22 are all unknown polynomial coefficients. Substituting equation (6) into equation (5), we can get:

[0093]

[0094] Substituting equation (1), equation (3) and equation (4) into equation (7), we can get:

[0095]

[0096] f s Considered as the total disturbance of the system, its expression is:

[0097]

[0098] Pick Write the system (8) as a state space expression:

[0099]

[0100] Specifically, the inner loop anti-disturbance controller of the present invention is to ensure the control accuracy of the system when facing variable load, unknown disturbance and nonlinear terms. Its control block diagram is as follows Figure 4 The inner loop ADRC includes a tracking differentiator, an extended observer and a nonlinear feedback controller.

[0101] The tracking differentiator can quickly track the input signal without overshoot or chatter, and can improve the signal-to-noise ratio of the signal and output a high-quality differential signal. The tracking differentiator of the present invention is a second-order tracking differentiator, and its design is as follows:

[0102]

[0103] Where r0 is the tracking differentiator speed factor; h0 is the tracking differentiator filter factor; v1 is the tracking signal of the input signal v0 obtained by the tracking differentiator; and v2 is the differential signal of v1.

[0104] f han The specific expression of (v1-v0,v2,r0,h0) is designed as follows:

[0105]

[0106] Where:

[0107]

[0108] The extended observer ESO of the present invention is used to estimate the state variables and the total disturbance of the system f s . The total disturbance f in equation (9) is s Expanding into a new state The new system state space expression is obtained as follows:

[0109]

[0110] In the formula, x p1 , and is the state of the pneumatic artificial muscle system; is continuously differentiable, w is The differential of . The expression of the designed third-order ESO is as follows:

[0111]

[0112] Where z1, z2 and z3 are x p1 , and The estimated observation value of the angle observation z1 and the output angle x p1 The error of 01 , β 02 and β 03 is the gain coefficient of the extended observer; u0 is the output duty cycle; b0 is the polynomial coefficient. fal(e1,a i ,δ) function expression is as follows:

[0113]

[0114] In the formula, δ i is the length of the linear interval; a i is the feedback power.

[0115] In the present invention, in order to speed up the response speed, the nonlinear feedback controller adopts a non-smooth feedback method to make the steady-state error decrease exponentially. The specific expression is as follows:

[0116]

[0117] In the formula, ε i , i = 1, 2 is the v after the tracking differentiator i and the estimated observation z i Error, β1 and β2 are proportional differential coefficients.

[0118] Finally, the ESO estimated total disturbance z3 is compensated into the control quantity to improve the control performance. The specific expression is as follows:

[0119]

[0120] The compensated u0 is used as input, and the dead zone nonlinearity of the input is eliminated by the dead zone nonlinear system as the high-speed switch valve charging and discharging control duty cycle instruction, denoted as u. When u0 is positive and non-zero, the control rate u=u a , as the duty cycle of the inflation valve, controls the inflation volume of the PAM; when u0 is less than 0, the control rate u=-u b , as the inflation valve duty cycle, controls the PAM deflation flow.

[0121] Specifically, the output of the outer loop admittance controller of the present invention is used as the input of the inner loop anti-disturbance controller, and the output of the inner loop anti-disturbance controller is used to control the adaptive combination valve to achieve the position control of the cervical rehabilitation robot during the traction process. That is, the control system of the present invention is essentially a two-level control system for cervical trajectory tracking control with flexibility adaptation. The outer loop admittance controller is used at the high level to adjust the desired trajectory v according to the error between the actual feedback force and the desired tracking force. d , and sends the position command v0 to the underlying inner-loop anti-disturbance controller to achieve feedback force-position tracking control.

[0122] The admittance controller of the present invention converts the physical system into a mass-spring-damper virtual dynamic model, and the force equation is:

[0123]

[0124] In the formula, m r is the expected inertia matrix, b r is the desired damping matrix, k r is the expected stiffness matrix; e w =v d -v0,v d is the reference trajectory, v0 is the desired trajectory after the outer loop admittance controller; Δf = f e -f r >0,f r is the expected tracking force, f e is the actual feedback force.

[0125] In the present invention, the traction mode of the cervical vertebra rehabilitation robot includes continuous traction and intermittent traction; wherein, the continuous traction is realized by fixed-point position control, and the intermittent traction is realized by an intermittent cervical vertebra stretching optimal control curve.

[0126] The optimal control curve for intermittent cervical stretching is generated based on the minimum jerk model. The expression of the minimum jerk model is as follows:

[0127]

[0128]

[0129] Where t0 is the start time of joint movement, is the initial position of the joint movement, t1 is the moment when the joint movement stops, The stop position of the joint movement. is the linear acceleration, which is the third-order derivative of the motion displacement with respect to time.

[0130] Based on the minimum jerk model, the optimal cervical spine stretching motion curve v is obtained through variational transformation. t :

[0131]

[0132] In order to achieve intermittent cervical spine stretching, a delay of 1 / 4T is maintained when the movement reaches the lowest position and the highest position, so that traction treatment can be maintained for a certain period of time when the movement reaches the highest position, and the patient's cervical spine can be rested and relaxed when the movement reaches the lowest position to prepare for the next stretching. After adding the delay, the optimal curve law of intermittent cervical spine stretching is finally obtained in formula (19):

[0133]

[0134] Among them, v t is the optimal control curve of intermittent cervical traction, T is the period of the optimal control curve of intermittent cervical traction, n is the number of repetitions of the optimal control curve of intermittent cervical traction, t is the time value, d is the interval time, t0 is the start time of joint movement, t f is the moment when the joint movement stops, v s0 is the initial position of the joint movement, v s1 This is the stop position of the joint movement.

[0135] Specifically, in one embodiment of the present invention, the operation process of the control system is:

[0136] The S1 outer loop admittance controller receives the actual feedback force and the desired tracking force, calculates the error and adjusts the desired trajectory.

[0137] Specifically, the actual feedback force is the actual force acting on the neck measured by the tension sensor; the expected tracking force is the preset ideal traction force. The actual feedback force is compared with the expected tracking force to obtain an error value. According to the error value, the mass-spring-damper virtual dynamics model is used to adjust the expected trajectory.

[0138] The desired trajectory adjusted by S2 is input into the inner loop ADRC.

[0139] Specifically, the adjusted desired trajectory output by the outer loop admittance controller is passed to the inner loop ADRC.

[0140] The S3 tracking differentiator generates a smooth trajectory and a differentiated signal.

[0141] Specifically, the tracking differentiator receives the adjusted desired trajectory. Generate smooth trajectory: Smooth the input signal using a specific algorithm. Generate derivative signal: Calculate the rate of change of the smoothed signal.

[0142] The S4 extended observer estimates the system state and the total disturbance.

[0143] Specifically, the extended observer estimates the system state, including the position and velocity of the pneumatic artificial muscle system, and estimates the total disturbance, including system nonlinearity, external disturbance, etc.

[0144] The S5 nonlinear feedback controller calculates the control variable according to the output of the extended observer.

[0145] Specifically, the nonlinear feedback controller receives the output of the extended observer. Calculate the control quantity: Calculate the required control signal based on the estimated value of the system state and the total disturbance.

[0146] The S6 control quantity is transmitted to the adaptive combination valve to adjust the charging and discharging flow of the pneumatic artificial muscle system.

[0147] Specifically, the adaptive combination valve receives the control amount of the nonlinear feedback controller. Adjust the charging and discharging flow of the pneumatic artificial muscle system: control the opening of the two electrical proportional valves to achieve precise airflow control.

[0148] The S7 pneumatic artificial muscle system drives the cervical rehabilitation robot to perform traction movements.

[0149] Specifically, the pneumatic artificial muscle system performs actions, and the pneumatic artificial muscle contracts or relaxes according to the changes in the inflation and deflation flow. The cervical vertebra rehabilitation robot is driven to perform traction actions: the force is transmitted through the steel cable and the neck support to achieve traction of the cervical vertebra.

[0150] The S8 displacement sensor and tension sensor provide real-time feedback of displacement and force information to form a closed-loop control.

[0151] Specifically, during the control process, the displacement sensor measures the traction distance in real time. The tension sensor measures the applied force in real time. The displacement and force information are fed back to the control system, especially the outer loop admittance controller, to form a closed-loop control: through continuous feedback and adjustment, it is ensured that the system can accurately perform the traction action according to the expected trajectory and force.

[0152] In one embodiment of the present invention, two groups of experiments are conducted on the inner loop active disturbance rejection controller (ADRC) proposed by the present invention and the traditional PID controller to compare the performances of ADRC and PID.

[0153] The first set of experiments is a comparative experiment of trajectory tracking. In this experiment, a step signal with a traction displacement of 30 mm is given. The ADRC and PID controller parameters are set as follows:

[0154] ADRC: h0=0.01, r0=300, b0=1000, β 01 =20,β 02 =1200,β 03 =8000, β1=1, β2=2,

[0155] δ1=0.03, δ2=0.3.

[0156] PID: k p =0.05, k i =0.08, k d =0.001.

[0157] The results of the first set of experiments are as follows Figure 5 shown. Figure 5 (a) is the ADRC control experiment result. Figure 5 (b) is the response curve of the PID controller. Figure 5 It can be seen that the output v1 of the tracking differentiator of ADRC quickly and stably tracks the given signal v0. The actual output x p1 Both can quickly and accurately reach the required input v0. The observed value z1 is almost consistent with x1. According to the results of the comparative test, the root mean square error of the system after reaching a stable state under ADRC control is 0.112mm, and the mean absolute error is 0.084. On the other hand, the two index values ​​of the PID controller are much larger than those of the ADRC controller. The transition process time for ADRC to reach a stable state is 1.02s, while the PID process takes 8.41s. Table 1 compares the response time t, root mean square error and mean absolute error of the two controllers. It can be seen that the control effect of ADRC is better than that of PID in terms of response time, stability and accuracy.

[0158] Table 1 Response time, root mean square error (RSME) and mean absolute error (MAE) of ADRC and PID

[0159] Controller Response time(s) RSME(°) MAE(°) ADRC 1.02s 0.112 0.084 PID 8.41s 1.004 1.004

[0160] The second group of experiments was to conduct an intermittent cervical spine stretching optimal control curve trajectory tracking control experiment with ADRC and PID at a frequency of 0.01Hz and an amplitude of 30mm. Compared with the first group of experiments, the ADRC parameters of this group of experiments were adjusted to β1=1, β2=2, and the other parameters were consistent with the first group of experiments; the PID parameters were adjusted to k p =0.2, k i =0.5, k d =0.001. In this group of experiments, the root mean square error and mean absolute error of the optimal control curve trajectory tracking control of ADRC and PID intermittent cervical traction are shown in Table 2.

[0161] Table 2 Root mean square error (RSME) and mean absolute error (MAE) of optimal control curve trajectory tracking control of ADRC and PID intermittent cervical traction

[0162]

[0163]

[0164] The results of the second group of experiments are as follows Figure 6 As shown, Figure 6 (a) and (c) are the output control curves of ADRC and PID respectively. Figure 6 (b) in the figure is the error curve of the two controller outputs. Figure 6 It can be seen that since the control curve is an intermittently changing curve, the tension of the external load spring on the pneumatic muscle also changes intermittently, and PID cannot adapt well to the influence of this changing force on the system. If the PID parameters are adjusted down, the upward and downward moving curves cannot be tracked quickly and accurately. This group of experiments increased the PID parameters. Although the effect of tracking the changing curve is better, the control accuracy is poor at the trough and is prone to fluctuations. The ADRC controller of the present invention adds an observer ESO, which can well estimate the influence of the changing spring force on the system, and compensate for the influence of the intermittent spring force on the system in the non-linear controller. In the entire trajectory tracking process, whether it is a peak or a trough, it can track the given curve well, so the entire tracking error is smaller than the tracking error of the PID controller.

[0165] The present invention verifies through two sets of experiments that ADRC can overcome the nonlinearity of pneumatic muscles, the interference of external forces on the system, etc., and achieve high-precision position control. The following will provide two examples to verify the compliant control effect of the control system of the present invention during cervical traction. In Example 1 and Example 2, the parameters of the outer loop admittance controller are set as: m r =1, b r =0.03, k r =8, the expected tracking force is set to f r 20N.

[0166] Example 1

[0167] The traction mode of this embodiment is continuous traction, which is achieved by fixed-point position control. The control test results of this embodiment are as follows: Figure 7 shown. Figure 7 (a) is the trajectory replanning result. Figure 7 (b) is the trajectory tracking control result of the desired position. The relationship between the desired tracking force and the feedback pulling force of this embodiment is as follows: Figure 8 As shown. Figure 7 and Figure 8 It can be analyzed that when the feedback tension f e When the displacement is less than or equal to 20N, the outer loop admittance controller does not work. As the displacement increases, the feedback tension increases. When the displacement is greater than the critical value of 20N, the outer loop admittance controller is activated. The difference between the feedback force and the expected force will produce a certain displacement difference e.w , which will make the reference trajectory v d changes, and obtains the desired trajectory v0 (see Figure 7 Then ADRC trajectory tracking control is performed, from Figure 7 In (b), we can see the feedback trajectory x q1 It can track the expected trajectory v0 very well. After passing through the outer loop admittance controller, it can be seen that the feedback tension f e At a tension greater than the expected f r After that, it will change with the change of feedback position, gradually become smaller, and finally tend to the given tension f r (See Figure 8 ), thereby achieving a flexible traction effect.

[0168] Example 2

[0169] The traction method of this embodiment is intermittent traction, which is achieved by using the intermittent cervical vertebra stretching optimal control curve. Fig. 9 shown. Fig. 9 (a) is the replanning result of the trajectory after the outer loop admittance controller. Fig. 9 (b) is the trajectory tracking curve after passing through the outer loop admittance controller. The relationship between the expected tracking force and the feedback tension based on the intermittent cervical traction optimal control curve admittance control of this embodiment is as follows: Fig.10 As shown. Fig. 9 and Fig.10 From the analysis, we can see that, firstly, as the displacement increases, the feedback tension increases continuously; then, when the feedback tension is greater than the expected tension, it enters the outer loop admittance controller, thereby changing the expected trajectory; finally, it enters ADRC to achieve the expected trajectory tracking control. Similarly, when the feedback tension is too large, the feedback tension is adjusted to make it tend to the expected tension, so that the traction force of the cervical traction rehabilitation robot in rehabilitation operations can be adjusted to avoid damage to the cervical spine caused by excessive tension.

[0170] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the protection scope of the present invention.

Claims

1. A hybrid auto-disturbance rejection admittance control system for a cervical rehabilitation robot, characterized in that: The cervical rehabilitation robot uses a pneumatic artificial muscle system as a driving element, and the control system includes: Outer loop admittance controller, inner loop anti-disturbance controller and adaptive combination valve; The outer loop admittance controller uses a mass-spring-damper virtual dynamic model to adjust the desired trajectory according to the error between the actual feedback force and the desired tracking force; The inner loop anti-disturbance controller includes a tracking differentiator, an extended observer and a nonlinear feedback controller, which is used to suppress the nonlinearity and external disturbance of the pneumatic artificial muscle system and realize position control. The adaptive combination valve is used to control the charging and discharging flow of the pneumatic artificial muscle system; The output of the outer loop admittance controller is used as the input of the inner loop anti-disturbance rejection controller, and the output of the inner loop anti-disturbance rejection controller is used to control the adaptive combination valve to achieve position control of the cervical rehabilitation robot during traction.

2. A hybrid auto-disturbance rejection admittance control system for a cervical vertebra rehabilitation robot as claimed in claim 1, characterized in that: The force equation of the mass-spring-damper virtual dynamic model is: In the formula, m r is the expected inertia matrix, b r is the desired damping matrix, k r is the expected stiffness matrix; e w =v d -v0,v d is the reference trajectory, v0 is the desired trajectory after the outer loop admittance controller; Δf = f e -f r >0,f r is the expected tracking force, f e is the actual feedback force.

3. The hybrid auto-disturbance rejection admittance control system of a cervical vertebra rehabilitation robot according to claim 1, characterized in that: The tracking differentiator is designed as follows: Where r0 is the tracking differentiator speed factor; h0 is the tracking differentiator filter factor; v1 is the tracking signal of the input signal v0 obtained by the tracking differentiator; and v2 is the differential signal of v1.

4. A hybrid auto-disturbance rejection admittance control system for a cervical vertebra rehabilitation robot as claimed in claim 3, characterized in that: The expression of the extended observer is as follows: In the formula, x p1 , and is the state of the pneumatic artificial muscle system; w is The differentials of; z1, z2 and z3 are x p1 , and The estimated observation value of the angle observation z1 and the output angle x p1 The error of 01 , β 02 and β 03 is the gain coefficient of the extended observer; u0 is the output duty cycle; b0 is the polynomial coefficient; fal(e1,a i ,δ) function expression is as follows: In the formula, δ i is the length of the linear interval; a i is the feedback power.

5. A hybrid auto-disturbance rejection admittance control system for a cervical vertebra rehabilitation robot as claimed in claim 4, characterized in that: The expression of the nonlinear feedback controller is as follows: In the formula, ε i , i = 1, 2 is the v after the tracking differentiator i and the estimated observation z i Error, β1 and β2 are proportional differential coefficients.

6. The hybrid auto-disturbance rejection admittance control system of a cervical vertebra rehabilitation robot according to claim 1, characterized in that: The adaptive combination valve includes two electrical proportional valves, a control unit and a pressure sensor; The air inlet of the first electrical proportional valve is connected to the air compressor, and the air outlet is connected to the pneumatic artificial muscle; the air inlet of the second electrical proportional valve is connected to the pneumatic artificial muscle, and the air outlet is connected to the atmosphere; The control unit is used for adjusting the opening of two electric proportional valves according to the output of the inner loop anti-disturbance controller; Pressure sensors are used to detect the internal pressure of pneumatic artificial muscle systems.

7. The hybrid auto-disturbance rejection admittance control system of a cervical vertebra rehabilitation robot according to claim 1, characterized in that: The cervical rehabilitation robot includes a seat, a displacement sensor, a tension sensor, a steel cable, a neck brace and a pneumatic artificial muscle system; Among them, the pneumatic artificial muscle system is placed side by side with the displacement sensor, the lower end is fixed, and the upper end is connected to the tension sensor, and the tension sensor is connected to the neck support through a cable.

8. The hybrid auto-disturbance rejection admittance control system of a cervical vertebra rehabilitation robot according to claim 1, characterized in that: The traction modes of the cervical rehabilitation robot include continuous traction and intermittent traction; Among them, continuous traction is achieved by fixed-point position control, and intermittent traction is achieved by intermittent cervical stretching optimal control curve.

9. A hybrid auto-disturbance rejection admittance control system for a cervical vertebra rehabilitation robot as claimed in claim 8, characterized in that: The optimal control curve of intermittent cervical stretching is generated based on the minimum jerk model, and its expression is: Among them, v t is the optimal control curve of intermittent cervical traction, T is the period of the optimal control curve of intermittent cervical traction, n is the number of repetitions of the optimal control curve of intermittent cervical traction, t is the time value, d is the interval time, t0 is the start time of joint movement, t f is the moment when the joint movement stops, v s0 is the initial position of the joint movement, v s1 This is the stop position of the joint movement.

10. The hybrid active disturbance rejection admittance control system of a cervical vertebra rehabilitation robot according to claim 1, characterized in that: The operation process of the control system is as follows: The S1 outer loop admittance controller receives the actual feedback force and the desired tracking force, calculates the error and adjusts the desired trajectory; The desired trajectory adjusted by S2 is input into the inner loop ADRC; The S3 tracking differentiator generates a smooth trajectory and a differential signal; S4 extended observer estimates system state and total disturbance; The S5 nonlinear feedback controller calculates the control quantity based on the output of the extended observer; The S6 control quantity is transmitted to the adaptive combination valve to adjust the filling and discharging flow of the pneumatic artificial muscle system; The S7 pneumatic artificial muscle system drives the cervical rehabilitation robot to perform traction movements; The S8 displacement sensor and tension sensor provide real-time feedback of displacement and force information to form a closed-loop control.

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