Soft continuum robot finite time robust trajectory tracking control method

Abstract

The invention relates to the field of soft continuum robot control, in particular to a soft continuum robot finite time robust trajectory tracking control method, which comprises the following steps: step 1, based on a segmented constant curvature hypothesis of a soft continuum robot, considering system uncertainty including unmodeled dynamics and exogenous disturbance; establishing a soft continuum robot dynamic model and converting the soft continuum robot dynamic model into a state space model; 2, based on nonlinearity of the state space model of the soft continuum robot, designing a finite time stability criterion for a nonlinear system; 3, designing a disturbance observer of a finite time stability criterion, and ensuring finite time convergence of an estimation error; 4, designing a nonsingular terminal sliding mode controller based on a result of the estimation error; 5, applying a trajectory tracking control strategy to the soft continuum robot; accurate trajectory tracking control of the soft continuum robot in finite time can be realized.

Description

Technical Field

[0001] The present invention relates to the field of soft continuum robot control, and more specifically to a finite-time robust trajectory tracking control method for soft continuum robots. Background Art

[0002] Soft continuum robots have attracted much attention in recent years due to their unique structures and flexible materials. It is hoped that they can perform tasks that rigid robots cannot, such as human-robot interaction in dangerous and harsh environments and safe operation in uncertain environments. They are capable of performing tasks that traditional rigid robots cannot achieve.

[0003] However, compared with the finite degrees of freedom and rigid materials of rigid robots, soft continuum robots often have infinite degrees of freedom and non-linear flexible time-varying characteristics in theory. Therefore, the kinematics and dynamics of soft continuum robots usually have complex non-linearity, making it difficult to establish accurate and efficient models, which will lead to unmodeled dynamics in the modeling process of soft continuum robots. In addition, in practical engineering applications, there are often exogenous disturbances, such as noise, etc., which will further cause uncertainty deviations between the dynamic models of soft robots and the actual models.

[0004] On the other hand, compared with other methods, the sliding mode control method has strong robustness and can cope with model uncertainties, parameter variations, and exogenous disturbances. The goal of sliding mode control is to force the trajectory of the soft robot into a carefully designed subspace, in which the required tracking performance can be guaranteed according to parameter selection. It should be noted that most sliding mode control methods only asymptotically stabilize the tracking error and do not limit the convergence within a finite time. With the development of industrial production, traditional asymptotic convergence can no longer meet people's needs.

[0005] In this context, based on the above two-point analysis, it is very necessary to study soft continuum robots with uncertainties and achieve accurate and efficient finite-time trajectory tracking control. Summary of the Invention

[0006] The purpose of the present invention is to provide a finite-time robust trajectory tracking control method for soft continuum robots, which can solve the problem that it is difficult to achieve accurate trajectory tracking control of soft continuum robots within a finite time due to the system uncertainties caused by the unmodeled dynamics in the dynamic modeling process and the exogenous disturbances in actual operations.

[0007] The purpose of the present invention is achieved through the following technical solutions:

[0008] A finite-time robust trajectory tracking control method for soft continuum robots, the method comprising the following steps:

[0009] Step 1: Based on the piecewise constant curvature assumption of the soft continuum robot, considering the system uncertainties including unmodeled dynamics and exogenous disturbances, establish the dynamic model of the soft continuum robot and transform it into a state-space model;

[0010] Step 2: Based on the nonlinearity of the state-space model of the soft continuum robot, design a finite-time stability criterion for the nonlinear system;

[0011] Step 3: Design a disturbance observer for the finite-time stability criterion to ensure the finite-time convergence of the estimation error;

[0012] Step 4: Design a nonsingular terminal sliding mode controller based on the result of the estimation error, and based on the nonsingular terminal sliding mode controller, achieve the convergence of the trajectory tracking error to the sliding mode surface in finite time;

[0013] Step 5: Apply it to the trajectory tracking control strategy of the soft continuum robot;

[0014] The piecewise constant curvature assumption of the soft continuum robot is as follows: Under the assumption of piecewise constant curvature, the soft continuum robot is divided into multiple models with constant curvature. The curvature of each segment is variable in time but invariant in space, and each segment is connected end to end and smooth;

[0015] In the above Step 1, the dynamic model of the soft continuum robot with n segments, including unmodeled dynamics and exogenous disturbances, is:

[0016]

[0017] where, represents the spatial pose angle of the soft continuum robot, represents the real number field, and represent the first-order and second-order time derivatives of the pose angle respectively, M 0 (q) represents the inertia matrix, aggregates the Coriolis force and centrifugal force G 0 (q) simulates the gravity effect, K 0 (q) and D 0 (q) are the stiffness matrix and damping matrix respectively, A q (q) maps the input τ ∈ R2n containing forces and torques to the configuration space to fully actuated the continuum robot, ΔE represents the unmodeled dynamics, and d 0 represents the exogenous disturbance;

[0018] Transform the dynamic model of the soft continuum robot into a state-space model:

[0019]

[0020] Define x 1 = q, which respectively represent the pose angle of the soft continuum robot and its first-order time derivative, d represents the total uncertainty of the state space model formula (2), and Define the relationship between the actual input τ and the control input u as M 0 (q) is a symmetric positive definite matrix;

[0021] In the second step, the design process of the finite-time stability criterion is as follows:

[0022] For any nonlinear system with an initial value f(0) = 0, if there exists a Lyapunov function satisfying When the parameters therein satisfy the following conditions: 0 < m < 1, n > 1, m + n = 2, γ 0 , γ 1 , γ 2 > 0, and then the state x of the nonlinear system converges to zero in finite time, where the stabilization time satisfies t ≤ T;

[0023]

[0024] Simplified to:

[0025] Then

[0026] In the third step, the design process of the disturbance observer is as follows:

[0027] Define the observation error of the soft continuum robot according to the state space model formula (2) as:

[0028]

[0029] Among them, is the derivative of the estimated pose angle, is the estimated uncertainty, e 1 represents the estimation error of the pose angle derivative, e 2 represents the estimation error of the unknown uncertainty. The disturbance observer formula is designed as:

[0030]

[0031] Among them, η 1 , η 2 , η 3 , η 4, η 5 , η 6 , η 7 , a, b, l, h are observer parameters, and sign represents the sign function;

[0032] Considering the state - space model formula (2) of the soft continuum robot with uncertainties and the disturbance observer (5), when the parameters of the disturbance observer formula (5) satisfy the following conditions and assumptions, the observation error at any t ≥ 0, the norm value satisfies ||e 0 || ≤ ∈, and the estimation errors e 1 and e 2 will converge to zero at finite times T e1 and T e2 respectively, where e 0 (0), e 1 (0), e 2 (0) represent the initial - time values of the corresponding state vectors respectively, where the form of the function Ψ 1 is defined in claim 3(3), and the assumptions and conditions that the disturbance observer formula (5) needs to satisfy are as follows:

[0033] Assumption 1: is bounded and satisfies

[0034] Condition 1: a, b, l, h are all positive odd numbers and satisfy a < b, l > h,

[0035] Condition 2: The matrix satisfies that all its eigenvalues are positive;

[0036] Condition 3: The observer parameter η 1 ≥ ∈ + δ 0 , where δ 0 > 0, η 5 ≥ γ;

[0037] In the fourth step, the design process of the non - singular terminal sliding - mode controller is as follows:

[0038]

[0039] where the trajectory - tracking error of the soft continuum robot is defined as e = x 1 - x d , x d represents the desired trajectory, α, l, h, a 1 , b 1is the sliding mode surface parameter, where H(e) is a continuous switching function, and its specific form is: a, b, and ξ are the parameters of the switching function. To ensure the continuity of the function H(e), it is necessary to satisfy The sign variable in the switching function is defined as

[0040] To enable the trajectory tracking error e to reach the sliding mode surface, the following sliding mode reaching law is designed, and its specific form is:

[0041]

[0042] where ζ, k, ρ 1 , ρ 2 , are all parameters of the sliding mode reaching law formula (7);

[0043] Considering the sliding mode surface formula (6) with the sliding mode reaching law formula (7), when the parameters satisfy the following conditions, the sliding mode surface can converge to zero within a finite time Ts, where The function Ψ 2 is defined in the finite-time stability criterion formula (3);

[0044] Condition 1: ζ, k, ρ 1 , ρ 2 are all positive numbers, and satisfy 2ρ 1 k - ρ 2 > ||e|| max ;

[0045] Condition 2: l 2 , h 2 , p 2 , q 2 are all positive odd numbers, and satisfy

[0046] In the fifth step, considering the state space model formula (2) of the soft continuum robot with system uncertainties, based on the disturbance observer formula (5), the following form of the control law u is combined:

[0047]

[0048] The trajectory tracking error e converges to the set ∏ e3 within a finite time T e = {e|||e|| ≤ ξ}, where where The function Ψ 3 is defined in formula (3).

[0049] The beneficial effects of the present invention are as follows:

[0050] Considering the system uncertainty of the soft continuum robot caused by both unmodeled dynamics and exogenous disturbances in the dynamic modeling process, and ensuring accurate trajectory tracking within a finite time, the present invention can achieve accurate trajectory tracking control of the soft continuum robot under uncertain conditions, can achieve accurate tracking of the curvature of the soft continuum robot to the desired curvature, and at the same time achieve trajectory tracking within a finite time while ensuring tracking, thereby providing an effective control method for the finite-time requirements of soft continuum robots in actual industry.

[0051] A nonsingular terminal sliding mode controller is adopted to avoid the problem of singular points, and at the same time, the sliding mode structure is improved in combination with the finite-time stability criterion, thereby improving the control performance; for unmodeled dynamics and exogenous disturbances, a disturbance observer is proposed to ensure that the observation error converges within a finite time, and the observed estimated value is used to replace the unknown part, effectively improving the robustness of the soft continuum robot and the actual tracking control performance. BRIEF DESCRIPTION OF THE DRAWINGS

[0052] The present invention will be further described in detail below with reference to the drawings and specific implementation methods.

[0053] Figure 1 It is a schematic diagram of the finite-time tracking control method for the soft continuum robot of the present invention;

[0054] Figure 2 It is a curve graph showing the change of the curvature trajectory tracking error of the soft continuum robot of the present invention over time;

[0055] Figure 3 It is a curve graph showing the change of the curvature trajectory of the soft continuum robot of the present invention over time;

[0056] Figure 4 It is a curve graph showing the change of the curvature derivative and the estimated curvature derivative of the soft continuum robot of the present invention over time;

[0057] Figure 5 It is a curve graph showing the change of the curvature derivative estimation error of the soft continuum robot of the present invention over time;

[0058] Figure 6 It is a curve graph showing the change of the uncertainty and the estimated uncertainty of the soft continuum robot of the present invention over time;

[0059] Figure 7 It is a curve graph showing the change of the uncertainty estimation error of the soft continuum robot of the present invention over time;

[0060] Figure 8It is a curve graph showing the variation of the sliding mode surface of the soft continuum robot of the present invention over time. Detailed implementation manners

[0061] The present invention will be further described in detail below with reference to the accompanying drawings.

[0062] As Figures 1 to 8 shown, in order to solve the technical problem of "due to the system uncertainty caused by both the unmodeled dynamics in the dynamic modeling process and the exogenous disturbances in actual operation, it is difficult to achieve precise trajectory tracking control of the soft continuum robot within a finite time", the steps and functions of a finite-time robust trajectory tracking control method for a soft continuum robot will be described in detail below;

[0063] Compared with rigid robots, soft continuum robots often have infinite degrees of freedom and non-linear flexible time-varying characteristics. Therefore, the kinematics and dynamics of soft continuum robots are usually complex non-linear, making it difficult to establish accurate and efficient models, which will lead to the existence of unmodeled dynamics in the modeling process of soft continuum robots. In addition, in actual engineering applications, there are often exogenous disturbances, such as noise, etc., which will further cause uncertainty deviations between the dynamic model of the soft robot and the actual model. The current main dynamic methods are the Euler-Lagrange method and other variable curvature methods based on the piecewise constant curvature assumption. Under the assumption of piecewise constant curvature, the soft continuum robot is divided into multiple models with constant curvature segments, where the curvature of each segment is variable in time but invariant in space, and each segment is connected end to end and smooth;

[0064] A finite-time robust trajectory tracking control method for a soft continuum robot, the method comprising the following steps:

[0065] Step 1: Based on the piecewise constant curvature assumption of the soft continuum robot, considering the system uncertainty including unmodeled dynamics and exogenous disturbances, establish the dynamic model of the soft continuum robot and transform it into a state space model;

[0066] The dynamic model of a soft continuum robot with system uncertainty including unmodeled dynamics and exogenous disturbances and having n segments is:

[0067]

[0068] Wherein, represents the spatial pose angle of the soft continuum robot, represents the real number field, and respectively represent the first-order time derivative and the second-order time derivative of the pose angle, M 0 (q) represents the inertia matrix, aggregates the Coriolis force and the centrifugal force G0 (q) Simulate the gravity effect, K 0 (q) and D 0 (q) are the stiffness matrix and the damping matrix respectively, A q (q) will map the input containing forces and torques to the configuration space so that the continuum robot is fully actuated. ΔE represents the unmodeled dynamics, d 0 represents the exogenous disturbance;

[0069] Transform the dynamic model of the soft continuum robot into a state - space model:

[0070]

[0071] Define x 1 = q, which represent the pose angle of the soft continuum robot and its first - order time derivative respectively. d represents the total uncertainty of the state - space model formula (2), and For the convenience of control design, define the relationship between the actual input τ and the control input u as M 0 (q) is a symmetric positive - definite matrix;

[0072] Step 2: Based on the non - linearity of the soft continuum robot state - space model, design a finite - time stability criterion for the non - linear system;

[0073] The design process of the finite - time stability criterion is as follows:

[0074] For any non - linear system with the initial value f(0) = 0, if there exists a Lyapunov function satisfying When the parameters satisfy the following conditions: 0 < m < 1, n > 1, m + n = 2, γ 0 , γ 1 , γ 2 > 0, and Then the state x of the non - linear system is finite - time convergent, where the settling time satisfies t ≤ T;

[0075]

[0076] Simplify to:

[0077] Then

[0078] Step 3: Design a disturbance observer for the finite - time stability criterion to ensure the finite - time convergence of the estimation error;

[0079] The design process of the disturbance observer is as follows:

[0080] According to the state - space model formula (2), the observation error of the soft continuum robot is defined as:

[0081]

[0082] where, is the derivative of the estimated pose angle, is the estimated uncertainty, e 1 represents the estimation error of the pose - angle derivative, e 2 represents the estimation error of the unknown uncertainty. The disturbance - observer formula is designed as:

[0083]

[0084] where, η 1 , η 2 , η 3 , η 4 , η 5 , η 6 , η 7 , a, b, l, h are observer parameters, and sign represents the sign function;

[0085] Considering the state - space model formula (2) of the soft continuum robot with uncertainty and the disturbance observer (5), when the parameters of the disturbance - observer formula (5) satisfy the following conditions and assumptions, the observation error has a norm value that satisfies ||e 0 || ≤ ∈ for any t ≥ 0, and the estimation errors e 1 and e 2 will converge to zero within finite times T e1 and T e2 respectively, where, e 0 (0), e 1 (0), e 2 (0) represent the initial - moment values of the corresponding state vectors respectively, where the form of the function Ψ 1 is defined in claim 3(3). The assumptions and conditions that the disturbance - observer formula (5) needs to satisfy are as follows:

[0086] Assumption 1: is bounded and satisfies Condition 1: a, b, l, h are all positive odd numbers and satisfy a < b, l > h, Condition 2: The matrix satisfies that all its eigenvalues are positive;

[0087] Condition 3: Observer parameter η 1 ≥∈ + δ 0 , where δ 0 > 0, η 5 ≥ γ;

[0089] Step 4: Design a nonsingular terminal sliding mode controller based on the result of the estimation error, and achieve that the trajectory tracking error converges to the sliding surface within a finite time based on the nonsingular terminal sliding mode controller;

[0090] The design process of the nonsingular terminal sliding mode controller is as follows:

[0091]

[0092] where the trajectory tracking error of the soft continuum robot is defined as e = x 1 - x d , x d represents the desired trajectory, and α, l, h, a 1 , b 1 are sliding surface parameters, where H(e) is a continuous switching function, and its specific form is: a, b, ξ are parameters of the switching function. To ensure the continuity of the function H(e), it is necessary to satisfy The sign variable in the switching function is defined as

[0093] To enable the trajectory tracking error e to reach the sliding surface, the following sliding mode reaching law is designed, and its specific form is:

[0094]

[0095] where ζ, k, ρ 1 , ρ 2 , are all parameters of the sliding mode reaching law formula (7);

[0096] Considering the sliding surface formula (6) with the sliding mode reaching law formula (7), when the parameters satisfy the following conditions, the sliding surface can converge to zero within a finite time Ts, where The function Ψ 2 is defined in the finite-time stability criterion formula (3);

[0097] Condition 1: ζ, k, ρ 1 , ρ 2 are all positive numbers, and satisfy 2ρ 1 k - ρ 2 > ||e|| max ;

[0098] Condition 2: l 2 , h 2 , p 2 , q 2 are all positive odd numbers and satisfy

[0099] Step 5: Apply to the trajectory tracking control strategy of the soft continuum robot;

[0100] Consider the state - space model formula (2) of the soft continuum robot with system uncertainties. Based on the disturbance observer formula (5), combined with the control law u in the following form:

[0101]

[0102] The trajectory tracking error converges to the set Π e3 within the finite time T e ={e|||e||≤ξ}, where where The form of the function Ψ 3 is defined in formula (3);

[0103] As Figures 2 to 8 shown, in order to verify and demonstrate the efficiency of the sliding - mode controller based on the disturbance observer for the finite - time tracking control method of the soft continuum robot, a simulation experiment is carried out on the matlab simulation platform. By programming the dynamic model of the soft continuum robot and adding unknown uncertainty disturbances to the closed - loop feedback, the control law of the closed - loop system is constructed through the estimation of unknown uncertainties by the disturbance observer, and then the whole system is formulated. Consider a single - segment soft continuum robot with the central axis length of this segment being 0.1m, the single - point mass being 0.5kg, and the stiffness matrix K = 0.05N·m and the damping matrix D = 0.01N·s·m -1 . The sampling period of the simulation experiment is 0.01s and the duration is 20s. The initial conditions for designing the disturbance observer and the controller are as follows:

[0104] x 1 (0)=q 0 =0.5rad, Select the parameters of the observer and the controller as follows:

[0105] a 1 =5, b 1 =5, α = 1, l = 9, h = 7, a = 5, b = 7, ξ = 0.001, ζ = 1, k = 4, ρ 1 =1, ρ 2 =0.01, a 2 =5, b 2 =5, l2 = 9, h 2 = 7, p 2 = 5, q 2 = 7, η 1 = 10, η 2 = 81.2409, η 3 = 1650, η 4 = 5, η 5 = 100, η 6 = 2, η 7 = 3;

[0106] The designed desired trajectory is as follows:

[0107]

[0108] The uncertainties of the designed system are as follows:

[0109]

[0110] Then the trajectory tracking response curve of the soft continuum robot is as Figures 2 to 8 shown, and the theoretically finite convergence times obtained through parameter calculation are T e1 = 0.4 s, T e2 = 0.59 s, T s = 1.13 s, T e3 = 1.78 s. Observing Figure 2 and Figure 3 it can be obtained that the actual convergence time of the soft continuum robot is about 0.7 s < T e3 = 1.78 s, thus verifying the effectiveness of the theoretical analysis of finite-time stability. Through Figure 4 and Figure 5 it is observed that the convergence time of the observer error e 1 is about 0.1 s < T e1 = 0.4 s, and observing Figure 6 it can be obtained that the designed observer can still respond quickly and achieve precise robust tracking in the face of uncertain mutation factors. Similarly, through Figure 7 it is observed that the convergence time of the observer error e 2 is about 0.2 s < T e2 = 0.59 s, and through Figure 8 it is observed that the convergence time of the sliding mode surface s is about 0.3 s < T s = 1.13 s. By comparing the theoretical calculation and the simulation stable time, it can be seen that the designed control method can ensure finite-time stability, and the proposed control method realizes the robust tracking control of the soft continuum robot in finite time, verifying the effectiveness of the controller.

Claims

1. A finite-time robust trajectory tracking control method for a soft continuum robot, characterized in that: The method comprises the following steps: Step 1: Based on the piecewise constant curvature assumption of the soft continuum robot, considering the system uncertainty including unmodeled dynamics and exogenous disturbances, the dynamic model of the soft continuum robot is established and converted into a state space model; Step 2: Based on the nonlinearity of the state space model of the soft continuum robot, a finite-time stability criterion for the nonlinear system is designed; Step 3: Design a disturbance observer with a finite-time stability criterion to ensure the finite-time convergence of the estimation error; Step 4: Design a non-singular terminal sliding mode controller based on the result of the estimation error, and realize the trajectory tracking error converges to the sliding mode surface within a finite time based on the non-singular terminal sliding mode controller; Step 5: Apply trajectory tracking control strategy to the soft continuum robot.

2. The method for finite-time robust trajectory tracking control of a soft continuum robot according to claim 1, characterized in that: The piecewise constant curvature assumption of the soft continuum robot is as follows: under the piecewise constant curvature assumption, the soft continuum robot is divided into multiple constant curvature models, wherein the curvature of each segment is variable in time but constant in space, and each segment is connected end to end and is smooth.

3. The method for finite-time robust trajectory tracking control of a soft continuum robot according to claim 1, characterized in that: In step 1, the dynamic model of the soft continuum robot with n segments of system uncertainty including unmodeled dynamics and exogenous disturbances is: in, represents the spatial pose angle of the soft continuum robot, represents the field of real numbers, and They represent the first-order time derivative and the second-order time derivative of the posture angle, M0(q) represents the inertia matrix, The Coriolis force and centrifugal force G0(q) are combined to simulate the gravity effect. K0(q) and D0(q) are the stiffness matrix and damping matrix respectively. q (q) Mapping the input τ∈R2n consisting of forces and torques into the configuration space such that the continuum robot is fully actuated, ΔE represents the unmodeled dynamics, and d0 represents the exogenous perturbation.

4. The method for finite-time robust trajectory tracking control of a soft continuum robot according to claim 3, characterized in that: Convert the dynamics model of the soft continuum robot into a state-space model: Define x1 = q, They represent the posture angle of the soft continuum robot and its first-order time derivative, d represents the total uncertainty of the state space model formula (2), and The relationship between the actual input τ and the control input u is defined as M0(q) is a positive definite matrix.

5. The method for finite-time robust trajectory tracking control of a soft continuum robot according to claim 4, characterized in that: In the step 2, the design process of the finite time stability criterion is: For any nonlinear system With initial value f(0) = 0, if there exists a Lyapunov function satisfy When the parameters meet the following conditions 0 <m<1,n> 1, m+n=2, γ0, γ1, γ2>0, and Then the state x of the nonlinear system converges to zero in a finite time, where the stable time satisfies t≤T; Simplified to: but 6. The method for finite-time robust trajectory tracking control of a soft continuum robot according to claim 5, characterized in that: In step 3, the design process of the disturbance observer is: According to the state space model formula (2), the observation error of the soft continuum robot is defined as: in, is the derivative of the estimated pose angle, is the estimated uncertainty, e1 represents the estimated error of the attitude angle derivative, and e2 represents the estimated error of the unknown uncertainty. The design disturbance observer formula is: Among them, η1, η2, η3, η4, η5, η6, η7, a, b, l, h are observer parameters, and sign represents the sign function.

7. The method for finite-time robust trajectory tracking control of a soft continuum robot according to claim 6, characterized in that: Considering the state space model formula (2) and disturbance observer (5) of the uncertain soft continuum robot, when the parameters of the disturbance observer formula (5) meet the following conditions and assumptions, the observation error At any t≥0, the norm value satisfies ||e0||≤∈, and the estimation errors e1 and e2 will be respectively e1 and T e2 converges to zero, where e0(0), e1(0), e2(0) represent the initial time values ​​of the corresponding state vectors, respectively, wherein the form of the function ψ1 is defined in claim 3 (3), and the assumptions and conditions that the disturbance observer formula (5) needs to satisfy are as follows: Assumption 1: is bounded and satisfies Condition 1: a, b, l, h are all positive odd numbers and satisfy a<b,l> h, Condition 2: Matrix All its eigenvalues ​​are positive; Condition 3: Observer parameter η1≥∈+δ0, where δ0>0,η5≥γ.

8. The method for finite-time robust trajectory tracking control of a soft continuum robot according to claim 7, characterized in that: In step 4, the design process of the non-singular terminal sliding mode controller is: The trajectory tracking error of the soft continuum robot is defined as e = x1-x d , x d represents the desired trajectory, α, l, h, a1, b1 are sliding surface parameters, where H(e) is a continuous switching function, and its specific form is: a, b, ξ are the parameters of the switching function. To ensure the continuity of the function H(e), The symbolic variable in the switch function is defined as 9. The method for finite-time robust trajectory tracking control of a soft continuum robot according to claim 8, characterized in that: In order to make the trajectory tracking error e reach the sliding surface, the following sliding mode reaching law is designed, and its specific form is: where ζ, k, ρ1, ρ2, are the parameters of the sliding mode reaching law formula (7); Consider the sliding surface formula (6) with the sliding mode reaching law formula (7). When the parameters satisfy the following conditions, the sliding surface can converge to zero within a finite time Ts, where The form of the function Ψ2 is defined in the finite time stability criterion formula (3); Condition 1: ζ, k, ρ1, ρ2 are all positive numbers and satisfy 2ρ1k-ρ2>||e|| max ; Condition 2: l2, h2, p2, q2 are all positive odd numbers and satisfy 10. The method for finite-time robust trajectory tracking control of a soft continuum robot according to claim 9, characterized in that: In step 5, the state space model formula (2) of the soft continuum robot with system uncertainty is considered, and on the basis of the disturbance observer formula (5), the control rate u of the following form is combined: The trajectory tracking error e in a finite time T e3 Converges to the set Π e ={e|||e||≤ξ}, where in The form of function Ψ3 is defined in formula (3).

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