Autonomous underwater robot system over-torque sliding mode control trajectory tracking method based on improved adaptive law

Abstract

The invention discloses an autonomous underwater robot system over-torque sliding mode control trajectory tracking method based on an improved adaptive law. The method comprises the following steps: establishing a six-degree-of-freedom autonomous underwater robot dynamic model; converting the six-degree-of-freedom autonomous underwater robot dynamical model, and constructing a six-degree-of-freedom autonomous underwater robot dynamical model based on lumped disturbance; designing a synchronization time estimator to estimate the lumped disturbance in the six-degree-of-freedom autonomous underwater robot kinetic model based on the lumped disturbance; and based on a sliding mode surface, a synchronization time estimator and a hyperbolic tangent function, designing a super-twist sliding mode controller based on an improved adaptive law, and realizing trajectory tracking of the autonomous underwater robot. According to the invention, buffeting of the system can be effectively suppressed while rapid convergence of the system is ensured.

Description

Technical Field

[0001] The invention relates to a hypertorsion sliding mode control trajectory tracking method of an autonomous underwater robot system based on an improved adaptive law, and belongs to the technical field of trajectory tracking of autonomous underwater robot systems. Background Art

[0002] In recent years, autonomous underwater robots have been widely used in various marine research tasks such as marine data collection, maritime search and rescue, and marine resource development due to their convenience and irreplaceability. However, since autonomous underwater robots are typical highly nonlinear systems, their inherent strongly coupled dynamic characteristics, model uncertainty, external disturbances (wind, waves, strong currents, etc.) and physical constraints of actuators may affect the system control performance. In order to achieve better tracking effects, various advanced motion control schemes have been proposed to solve the trajectory tracking control problem of autonomous underwater robots, including adaptive control, sliding mode control, backstepping control, model predictive control, and fuzzy logic control.

[0003] Among the above methods, sliding mode control is widely used due to its strong robustness. However, the traditional sliding mode control method has the problems of jitter and uncertain convergence time. In order to reduce the convergence time of the system, a terminal sliding mode control scheme is proposed. Chinese patent application CN113110532A proposes an adaptive terminal sliding mode control method, which effectively improves the convergence time of the system. However, due to the existence of switching terms in the control law, the jitter of the control becomes an unavoidable problem in the design process; Chinese patent application CN115903859A discloses an adaptive integral sliding mode control scheme, which adds an integral link and minimizes the jitter phenomenon of the controller.

[0004] Although the above-mentioned methods can improve the performance of the system, the influence of some unknown system dynamics is still inevitable. In order to solve this problem, a variety of observers and adaptive anti-disturbance methods have been proposed, such as nonlinear disturbance observers and. The nonlinear disturbance observer designed in Chinese patent application CN114895569A can obtain better tracking results for the centralized uncertainty of the system. Another adaptive algorithm is designed in Chinese patent application CN112859891A to ensure that the system has strong robustness and good performance. However, all these methods have the problem that the convergence speed is not fast enough, or the adaptive gain is easily overestimated. Summary of the invention

[0005] The present invention provides a hypertorsion sliding mode control trajectory tracking method for an autonomous underwater robot system based on an improved adaptive law. A hypertorsion sliding mode controller based on the improved adaptive law is designed based on a sliding surface, a synchronous time estimator and a hyperbolic tangent function to achieve trajectory tracking of the autonomous underwater robot. The method can effectively suppress the chattering of the system while ensuring rapid convergence of the system.

[0006] The technical solution of the present invention is:

[0007] A hypertorsion sliding mode control trajectory tracking method for an autonomous underwater robot system based on an improved adaptive law comprises the following steps:

[0008] S1. Establishing a 6-DOF autonomous underwater robot dynamics model; transforming the 6-DOF autonomous underwater robot dynamics model to construct a 6-DOF autonomous underwater robot dynamics model based on lumped disturbance;

[0009] S2. Design a synchronous time estimator to estimate the lumped disturbance in the 6-DOF autonomous underwater vehicle dynamics model based on lumped disturbance;

[0010] S3. Based on the sliding surface, synchronous time estimator and hyperbolic tangent function, a hypertorsion sliding mode controller based on the improved adaptive law is designed to achieve trajectory tracking of the autonomous underwater robot.

[0011] Furthermore, the 6-DOF autonomous underwater robot dynamics model based on lumped disturbance is expressed as follows:

[0012]

[0013] in, Defined as the lumped disturbance, represents the derivatives of the linear velocity and angular velocity vector υ in the motion coordinate system; They respectively represent the nominal parts of M, C(υ), D(υ), and g(η); ΔM, ΔC(υ), ΔD(υ), and Δg(η) respectively represent the uncertain parts of M, C(υ), D(υ), and g(η); M is the inertia matrix, C(υ) is the Coriolis centripetal force matrix, D(υ) is the dynamic resistance and buoyancy matrix due to the flow of water, g(η) is the restoring force vector caused by the combined action of buoyancy and gravity, d is the external disturbance caused by the environment, and τ is the control input torque.

[0014] Furthermore, the S2 includes:

[0015] The 6-degree-of-freedom autonomous underwater robot dynamics model based on lumped disturbance is converted to obtain the converted 6-degree-of-freedom autonomous underwater robot dynamics model based on lumped disturbance;

[0016] Based on the intermediate variable, design an auxiliary variable;

[0017] Based on the auxiliary variable, define an error variable; based on the error variable, define an output variable;

[0018] According to the error variables and the output variables, a synchronous time estimator is designed to obtain the estimated value of the lumped disturbance.

[0019] Furthermore, the S3 includes:

[0020] S3.1 Design the hyperbolic tangent function:

[0021]

[0022] Among them: i=1,2,...,6; u iM is a positive constant; τ is expressed as τ(u) = τ ε u and τ(u)∈R 6 , R 6 represents a 6th-order vector, τ i (u i ) represents the i-th element of τ(u), u i is the i-th element of u, where u represents the supertorsion sliding mode controller based on the improved adaptive law; τ ε =diag(τ 1ε ,τ 2ε ,…,τ 6ε ), u iε =εu i +(1-ε)u0, u0=0, ε is an unknown constant satisfying 0<ε<1;

[0023] S3.2. Design sliding surface:

[0024] The system tracking error e of the autonomous underwater vehicle is defined as:

[0025]

[0026] Among them, η d represents the expected value of η; η=[x,y,z,φ,θ,ψ] T , x, y, z are the positions of surge, sway, and heave, respectively; φ, θ, ψ represent the attitudes of roll, pitch, and pitch, respectively;

[0027] Given a recursive terminal sliding surface, this sliding surface is used to drive the autonomous underwater robot to track the desired trajectory:

[0028]

[0029] where \(s\) represents the sliding mode variable; \(\alpha,\beta,c_1\gt0\), \(\gamma,c_2\gt0\); \(a,b\) are positive integers satisfying \(a\lt b\); represents the derivative of the system tracking error \(e\) of the autonomous underwater vehicle; is an intermediate variable; sig γ (e)=|e| γ sign(e);

[0030] S3.3. Design the hyper-twisting sliding mode controller \(u\) based on the improved adaptive law based on the sliding mode surface, the synchronization time estimator, and the hyperbolic tangent function. The expression is:

[0031]

[0032] where represents the nominal part of \(M\), \(M\) is the inertia matrix; \(J\) represents the Jacobian matrix; i = 1,..., 6, e i represents the \(i\)-th element of the system tracking error \(e\) of the autonomous underwater vehicle; is the estimated value of the lumped disturbance obtained according to the synchronization time estimator; represents the hyper-twisting sliding mode adaptive law; \(F,\delta_1\) are intermediate variables;

[0033]

[0034] The beneficial effects of the present invention are as follows: For a 6-degree-of-freedom autonomous underwater vehicle system, the present invention designs an adaptive hyper-twisting sliding mode control trajectory tracking method for the autonomous underwater vehicle system based on the improved adaptive law. This method estimates the lumped disturbance by introducing auxiliary variables and output variables to design a synchronization time estimator, enabling the system convergence error to converge to zero within the synchronization time; further constructing a hyper-twisting sliding mode controller based on the improved adaptive law can suppress system chattering while accelerating system convergence; In summary, the adaptive hyper-twisting sliding mode controller based on the synchronization time estimator proposed by the present invention can effectively overcome the influence of the lumped disturbance on the control gain, thereby obtaining a smoother control input, achieving the effect of reducing chattering, and at the same time being able to reduce the system convergence time, ensuring that the system can maintain significant tracking performance when suffering from complex uncertainties. Description of the Drawings

[0035] Figure 1 is the schematic diagram of the control flow of the present invention;

[0036] Figure 2 is the schematic diagram of the position tracking effect of the 6 degrees of freedom of the autonomous underwater vehicle involved in the present invention under different desired trajectories;

[0037] Figure 3It is a schematic diagram of the position tracking error e effect of the six degrees of freedom of the autonomous underwater robot involved in the present invention under different expected trajectories;

[0038] Figure 4 It is a schematic diagram of the control input u effect of each degree of freedom of the autonomous underwater robot involved in the present invention;

[0039] Figure 5 It is a schematic diagram of the estimation effect of the synchronization time estimator involved in the present invention;

[0040] Figure 6 The estimated error μ of the synchronization time estimator of the present invention is e Schematic diagram of the effect. DETAILED DESCRIPTION

[0041] In order to make the purpose, technical scheme and advantages of the embodiments of the present invention clearer, the technical scheme in the embodiments of the present invention will be clearly and completely described below in conjunction with the accompanying drawings. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of the present invention. It should be noted that the embodiments in this application and the features in the embodiments can be combined with each other arbitrarily without conflict.

[0042] Example 1: Figure 1-6 As shown, a hypertorsion sliding mode control trajectory tracking method for an autonomous underwater robot system based on an improved adaptive law comprises the following steps:

[0043] S1. Establish a 6-DOF autonomous underwater robot dynamics model; transform the 6-DOF autonomous underwater robot dynamics model to construct a 6-DOF autonomous underwater robot dynamics model based on lumped disturbance; initialize the initial position information of the autonomous underwater robot and the parameters of the adaptive hypertorsion sliding mode controller;

[0044] S2. Design a synchronous time estimator to estimate the lumped disturbance in the 6-DOF autonomous underwater vehicle dynamics model based on lumped disturbance;

[0045] S3. Based on the sliding surface, synchronous time estimator and hyperbolic tangent function, a hypertorsion sliding mode controller based on the improved adaptive law is designed to achieve trajectory tracking of the autonomous underwater robot.

[0046] Furthermore, the S1 includes:

[0047] S1.1. In order to study the motion law of the autonomous underwater robot AUV and determine its position, posture and speed, two rectangular coordinate systems are used, namely the ground coordinate system and the motion coordinate system. The kinematic equation of the AUV needs to establish the conversion relationship between the two coordinate systems, that is, the linear velocity and angular velocity conversion matrix of the AUV. The kinematic equation of the AUV can be expressed as:

[0048]

[0049] Where: The Jacobian matrix J(η) represents the derivative of the position in the ground coordinate system The relationship between the linear velocity and angular velocity vector υ in the motion coordinate system; η = [x, y, z, φ, θ, ψ] T , x, y, z are the positions of surge, sway, and heave, respectively; φ, θ, ψ represent the roll, pitch, and pitch attitudes, respectively; υ=[u*,v,w,p,q,r] T , u*, v, w, p, q, and r are the speeds of surge, sway, heave, roll, pitch, and pitching respectively.

[0050] Establish a 6-DOF autonomous underwater robot dynamic model:

[0051]

[0052] Where: M is the inertia matrix, C(υ) is the Coriolis centripetal force matrix, D(υ) is the dynamic resistance and buoyancy matrix due to the flow of water, g(η) is the restoring force vector caused by the combined action of buoyancy and gravity, d is the external disturbance caused by the environment, and τ is the control input torque.

[0053] S1.2. In practical applications, accurate AUV dynamics are usually not available. Therefore, the parameter matrix and vector in the AUV dynamics model can be divided into a nominal term part and an uncertain term part. M, C(υ), D(υ), and g(η) can be expressed as:

[0054]

[0055] in: They represent the nominal parts of M, C(υ), D(υ), and g(η); ΔM, ΔC(υ), ΔD(υ), and Δg(η) represent the uncertain parts of M, C(υ), D(υ), and g(η). According to the above description, the original AUV dynamic model can be converted into a 6-DOF autonomous underwater robot dynamic model based on lumped disturbance, and the expression is as follows:

[0056]

[0057] in: Defined as the lumped disturbance, represents the derivative of υ.

[0058] Furthermore, the S2 specifically includes:

[0059] The 6-DOF autonomous underwater robot dynamics model based on lumped disturbance, that is, formula (4), is converted into the following:

[0060]

[0061] Among them: σ1 is a positive constant;

[0062] Let the intermediate variable Based on the intermediate variable, design an auxiliary variable υ a , the expression is:

[0063]

[0064] Based on the auxiliary variable, define an error variable υ e ; According to the error variable υ e Define an output variable y1, the specific expression is as follows:

[0065]

[0066] Among them: σ2 is a positive constant.

[0067] According to the error variable a and output variable y1, design the synchronization time estimator:

[0068]

[0069] in: is the estimated value of the lumped disturbance, is the error variable υ e The estimated value of for The derivative of; σ3 and σ4 are two positive constants; β1 and β2 are two positive odd integers, and satisfy is the error of the synchronization time estimator.

[0070] Furthermore, the stability proof of the synchronization time estimator proposed by the present invention is given:

[0071] Define the estimation error of the synchronization time estimator as μ e According to formula (7), we can get:

[0072]

[0073] Combining formula (8), we can get the estimation error expression of the synchronization time estimator:

[0074]

[0075] So we have:

[0076]

[0077] Correspondingly, the derivative of the estimation error of the synchronization time estimator can be obtained

[0078]

[0079] Choose the Lyapunov function as:

[0080]

[0081] Where T represents transpose;

[0082] V g Differentiate with respect to time t:

[0083]

[0084] Based on (14), we can obtain that for any t ≥ T g , the error of Lyapunov function and synchronization time estimator satisfies the following:

[0085]

[0086] So the synchronization time is T g for:

[0087]

[0088] according to It can be obtained that for any t ≥ T g , we have: μ e ≡0, indicating that the estimation error of the synchronization time estimator can converge to zero.

[0089] Furthermore, the S3 includes:

[0090] S3.1 Design of hyperbolic tangent function

[0091] The control input torque τ is defined as the actuator thrust of the unknown input saturation, which can be specifically expressed as:

[0092]

[0093] Among them: i=1,2,...,6; u iM is a positive constant; τ is expressed as τ(u) = τ ε u and τ(u)∈R 6 , R 6 represents a 6th-order vector, τi (u i ) represents the i-th element of τ(u), where u i is the i-th element of u, and u represents the super-twisting sliding mode controller based on the improved adaptive law; τ ε = diag(τ 1ε , τ 2ε , …, τ 6ε ). u iε = εu i + (1 - ε)u0, where u0 = 0 and ε is an unknown constant satisfying 0 < ε < 1.

[0094] S3.2. Design the sliding surface

[0095] The system tracking error e of the autonomous underwater vehicle is defined as:

[0096]

[0097] where η d represents the expected value of η;

[0098] Given a recursive terminal sliding surface, this sliding surface is used to drive the autonomous underwater vehicle to track the desired trajectory:

[0099]

[0100] where s represents the sliding mode variable; α, β, c1 > 0, γ, c2 > 0; a, b are positive integers satisfying a < b; represents the derivative of the system tracking error e of the autonomous underwater vehicle.

[0101] It can be seen from Equation (19) that when the initial condition of the integral term is set to the sliding mode variable s = 0. This means that the system can start directly from the sliding surface without going through the reaching phase. This feature speeds up the system's response speed and enhances the system's global robustness.

[0102] S3.3 Design the super-twisting sliding mode controller

[0103] Since τ = τ eq + τ sw ; according to the equivalent control principle, design the equivalent control law τ eq as:

[0104]

[0105] where: represents the nominal part of the inertia matrix M; J represents the Jacobian matrix; Λ = diag(|e iγ-1 ), i=1,...,6,e i represents the i-th element of the system error e of the autonomous underwater robot; υ is the linear velocity and angular velocity vector in the motion coordinate system, C is the Coriolis centripetal force matrix, D is the dynamic resistance and buoyancy matrix due to the flow of water, and g is the restoring force vector caused by the combined action of buoyancy and gravity;

[0106] The switching term is used to compensate for the difference between the expected dynamics and the actual dynamics caused by model uncertainty and external disturbances. In order to reduce the chattering of the system, an improved super-torsion sliding mode adaptive law is adopted as shown in Eqs. (23) and (24). Combined with this improved super-torsion sliding mode adaptive law, the controller robust term τ sw Can be designed as

[0107]

[0108] in, is the estimated value of the lumped disturbance;

[0109] Based on the problem that the gain of the ordinary adaptive law is easily overestimated, and in order to effectively reduce the chattering of the system, the above robust control term adopts the following super-torsion sliding mode adaptive law:

[0110]

[0111] in: i=1,...,6,ζ1,ζ2,γ1,k1 and k2 are all positive constants; is a very small number; s i represents the i-th element of s;

[0112] Based on the sliding surface, synchronous time estimator and hyperbolic tangent function, the hypertorsion sliding mode controller u based on the improved adaptive law is designed, and the expression is:

[0113]

[0114] Furthermore, we choose the Lyapunov function to prove the stability of the robot:

[0115] When s = 0, we can get This means and The convergence time of is the same. Therefore, the second term of formula (19) is equivalent to:

[0116]

[0117] Solving (26) this Bernoulli equation yields:

[0118]

[0119] Therefore, the robot moves from the outer sliding surface s to the inner sliding surface Time to meet:

[0120]

[0121] when When defining the system The Lyapunov function is V = 0.5e 2 , differentiating V with respect to time yields:

[0122]

[0123] Where: Λ2=α|e|+β|e| γ , according to the finite time stability theory, the time for the tracking error e to converge to zero satisfies:

[0124]

[0125] In order to prove the finite time convergence of the approximation phase, a new state variable is defined

[0126]

[0127] The derivative with respect to time is:

[0128]

[0129] in: is bounded and can be expressed as is a constant, and δ is a small constant (taken as 0.2 in the embodiment of the present invention): I represents the identity matrix.

[0130] Choose the following Lyapunov function:

[0131]

[0132] Among them: γ1, γ2 are positive constants; is the upper limit of the gain; P is a positive definite matrix.

[0133]

[0134] The derivative of V0 with respect to time is:

[0135]

[0136] in:

[0137]

[0138] In the formula, κ and μ represent positive constants;

[0139] According to formula (24), we can get:

[0140]

[0141] if If equation (38) is satisfied, the matrix Q is positive definite.

[0142]

[0143] It is easy to get Ω=QΩ1=Ω1Q, Ω1 is a positive definite symmetric matrix. When Q is a symmetric positive definite matrix, Ω is also a positive definite symmetric matrix. Therefore, when equation (38) is satisfied, we can get:

[0144]

[0145] Where: min (Q) represents the smallest eigenvalue of the matrix Q.

[0146] because You can get:

[0147]

[0148] Where: max (P) and λ min (P) are the maximum and minimum eigenvalues ​​of P, and

[0149]

[0150] Where: r2 = min(r1, k1, k2), is the upper limit of the gain; adaptive gain K 1i and K 2i is bounded, that is so:

[0151]

[0152] Then the derivative of V is:

[0153]

[0154] The derivative of can be divided into 3 cases for discussion:

[0155] Case 1: |s i|>ζ1 and Adaptive Law as well as By setting Can get Right now:

[0156]

[0157] The value of will change with Increase until equations (45) and (38) are satisfied, the sliding surface will reach a very small neighborhood in a finite time.

[0158] Case 2: |s j |<ζ1, j=1 or j=2, the adaptive law is:

[0159]

[0160] Lyapunov function V b satisfy:

[0161]

[0162] In the formula, is the upper limit of the gain;

[0163] when Will increase linearly with speed k2 until if Easy to get According to equation (43), the sign of the Lyapunov function may change, after which |s i | will be greater than ζ1, once |s i |>ζ1, same as case 1, the sliding surface will converge to a small neighborhood in a finite time |s i |≤ζ1.

[0164] Case 3: |s n |<ζ1, n=1,2, Lyapunov function satisfies:

[0165]

[0166] As in case 2, the sliding mode variable will converge to a small neighborhood in a finite time.

[0167] In summary, the tracking error can converge to zero in a finite time.

[0168] Example 2: In order to verify the feasibility of the method described in Example 1, this example provides a control simulation experiment of the above control method on a 6-DOF autonomous underwater robot, and the specific parameters are set as follows:

[0169] The matrices M, C(υ), D(υ) and g(η) include the physical constants m ii d ii ,g1 and g2 (i=1,...,6). It should be noted that these physical constants are assumed to be unknown in the design of control inputs. That is, there is no information about the physical constants of the 6-DOF AUV when designing control inputs.

[0170] M=diag(m 11 ,m 22 ,m 33 ,m 44 m 55 ,m 66 )

[0171] D(υ)=diag(d 11 ,d 22 ,d 33 ,d 44 ,d 55 ,d 66 )

[0172]

[0173] During the simulation, all nominal hydrodynamic values ​​were added with a 20% model uncertainty. The simulation was performed in a discrete form with a sampling time T s = 0.001s. These settings are common to all simulations. The required reference trajectory is a three-dimensional spiral diving curve, expressed as: η d =[2cos(0.3πt),-2sin(0.3πt),πt / 15,0,0,π / 6] T

[0174] The initial position information of AUV is The external disturbance d is set to: d = [0.2sin3t, 0.1cos4t, 0.1sin3t, 0.1cos4t, 0.15sin4t, 0.15sin6t] T .

[0175] The specific values ​​of the parameters of the adaptive supertorque sliding mode controller of the present invention are as shown in Table 1:

[0176] Table 1 Parameters of adaptive supertorsion sliding mode controller

[0177]

[0178] Substituting the above parameters into the controller u and the 6-DOF underwater robot dynamics model (4) of the present invention, the simulation results are as follows: The position tracking response curve and position tracking error response curve of the 6-DOF autonomous underwater robot are as follows: Figure 2 and Figure 3 As shown; the control input response curve of 6 degrees of freedom is as follows Figure 4 As shown; the estimation results and estimation errors of the synchronization time estimator are shown in Figure 5 , 6 shown.

[0179] pass Figure 2 and Figure 3 It can be seen that the system has a short rise time, fast response speed, small tracking error and good control performance.

[0180] pass Figure 4 It can be seen that the system has good tracking performance, and by using the adaptive hypertorsion sliding mode controller, the controller has less chattering.

[0181] from Figure 5 and Figure 6 It can be seen that the designed synchronous time estimator has good estimation performance and can effectively observe the disturbance. At the same time, the estimation errors of the lumped disturbances in the six degrees of freedom can converge to zero at the same time in about 1 s.

[0182] The specific implementation modes of the present invention are described in detail above in conjunction with the accompanying drawings, but the present invention is not limited to the above implementation modes, and various changes can be made within the knowledge scope of ordinary technicians in this field without departing from the purpose of the present invention.

Claims

1. A hypertorsion sliding mode control trajectory tracking method for an autonomous underwater robot system based on an improved adaptive law, characterized in that: The steps include: S1. Establishing a 6-DOF autonomous underwater robot dynamics model; transforming the 6-DOF autonomous underwater robot dynamics model to construct a 6-DOF autonomous underwater robot dynamics model based on lumped disturbance; S2. Design a synchronous time estimator to estimate the lumped disturbance in the 6-DOF autonomous underwater vehicle dynamics model based on lumped disturbance; S3. Based on the sliding surface, synchronous time estimator and hyperbolic tangent function, a hypertorsion sliding mode controller based on the improved adaptive law is designed to achieve trajectory tracking of the autonomous underwater robot.

2. The hypertorsion sliding mode control trajectory tracking method for an autonomous underwater robot system based on an improved adaptive law according to claim 1 is characterized in that: The 6-DOF autonomous underwater robot dynamics model based on lumped disturbance is expressed as follows: in, Defined as the lumped disturbance, represents the derivatives of the linear velocity and angular velocity vector υ in the motion coordinate system; They respectively represent the nominal parts of M, C(υ), D(υ), and g(η); ΔM, ΔC(υ), ΔD(υ), and Δg(η) respectively represent the uncertain parts of M, C(υ), D(υ), and g(η); M is the inertia matrix, C(υ) is the Coriolis centripetal force matrix, D(υ) is the dynamic resistance and buoyancy matrix due to the flow of water, g(η) is the restoring force vector caused by the combined action of buoyancy and gravity, d is the external disturbance caused by the environment, and τ is the control input torque.

3. The hypertorsion sliding mode control trajectory tracking method of an autonomous underwater robot system based on an improved adaptive law according to claim 1 is characterized in that: The S2 comprises: The 6-degree-of-freedom autonomous underwater robot dynamics model based on lumped disturbance is converted to obtain the converted 6-degree-of-freedom autonomous underwater robot dynamics model based on lumped disturbance; Based on the intermediate variable, design an auxiliary variable; Based on the auxiliary variable, define an error variable; based on the error variable, define an output variable; According to the error variables and the output variables, a synchronous time estimator is designed to obtain the estimated value of the lumped disturbance.

4. The hypertorsion sliding mode control trajectory tracking method of an autonomous underwater robot system based on an improved adaptive law according to claim 1 is characterized in that: The S3 includes: S3.1 Design the hyperbolic tangent function: Among them: i=1,2,...,6; u iM is a positive constant; τ is expressed as τ(u) = τ ε u and τ(u)∈R 6 , R 6 represents a 6th-order vector, τ i (u i ) represents the i-th element of τ(u), u i is the i-th element of u, where u represents the supertorsion sliding mode controller based on the improved adaptive law; τ ε =diag(τ 1ε ,τ 2ε ,…,τ 6ε ), u iε =εu i +(1-ε)u0, u0=0, ε is an unknown constant satisfying 0<ε<1; S3.

2. Design sliding surface: The system tracking error e of the autonomous underwater vehicle is defined as: Among them, η d represents the expected value of η; η=[x,y,z,φ,θ,ψ] T , x, y, z are the positions of surge, sway, and heave, respectively; φ, θ, ψ represent the attitudes of roll, pitch, and pitch, respectively; Given a recursive terminal sliding surface, this sliding surface is used to drive the autonomous underwater robot to track the desired trajectory: Among them, \(s\) represents the sliding mode variable; \(\alpha,\beta,c_1 > 0\), \(\gamma,c_2 > 0\); \(a,b\) are positive integers satisfying \(a < b\). represents the derivative of the system tracking error \(e\) of the autonomous underwater vehicle; is an intermediate variable; sig γ (e)=|e| γ sign(e); S3.

3. Based on the sliding surface, synchronous time estimator and hyperbolic tangent function, the hypertorsion sliding mode controller u based on the improved adaptive law is designed. The expression is: in, It represents the nominal part of M, where M is the inertia matrix; J represents the Jacobian matrix; Λ=diag(|e i | γ-1 ), i=1,...,6,e i represents the i-th element of the system tracking error e of the autonomous underwater robot; is the estimated value of the aggregate disturbance obtained by the synchronized time estimator; represents the hypertorsional sliding mode adaptive law; F and δ1 are intermediate variables;

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