An adaptive trajectory tracking control method for intelligent ships based on virtual input

Abstract

This invention discloses an intelligent ship adaptive trajectory tracking control method based on virtual input, belonging to the field of intelligent ship automatic control technology. The method includes: constructing an intelligent ship motion control model for intelligent ships with uncertain model parameters and unknown external disturbances, while also considering excessive actuator wear; based on the intelligent ship motion control model, applying an adaptive backstepping method design framework, introducing the concept of virtual input, transforming the original ship motion mathematical model into a standard-level integral cascade form, linearly representing uncertain parameters and external disturbances, estimating unknown parameters online through an adaptive update law, and introducing a dynamic event triggering mechanism to reduce actuator mechanical wear. This method can effectively reduce controller energy consumption and improve trajectory tracking speed and accuracy.

Description

Technical Field

[0001] This invention belongs to the field of intelligent ship automatic control technology, and more specifically, relates to an intelligent ship adaptive trajectory tracking control method based on virtual input. Background Technology

[0002] Intelligent ships have non-integrable constraints on roll acceleration and cannot be directly transformed into a drift-free chain structure. The motion control system of intelligent ships is a second-order nonholonomic constraint nonlinear system, characterized by high nonlinearity, strong coupling, and susceptibility to uncertainties in internal parameter models and external disturbances. To address the problems caused by these uncertainties, a large number of intelligent algorithms have been applied to the field of intelligent ship control, including adaptive control, PID (Proportional Integral Derivative) control, fuzzy adaptive control, neural network adaptive control, and adaptive sliding mode control.

[0003] Current intelligent ship trajectory tracking designs mostly employ state feedback control schemes, which require accurate information about the intelligent ship's motion state. However, in practical engineering, collecting this information presents various challenges, making it impossible to obtain completely accurate motion state data. Consequently, the control algorithm's performance falls short of expectations. Therefore, the aforementioned algorithms cannot meet the control requirements of intelligent ship trajectory tracking and are not conducive to engineering practice. Summary of the Invention

[0004] To address the aforementioned deficiencies or improvement needs of existing technologies, this invention proposes an intelligent ship adaptive trajectory tracking control method based on virtual input to meet the control requirements of intelligent ship trajectory tracking.

[0005] To achieve the above objectives, the present invention provides an intelligent ship adaptive trajectory tracking control method based on virtual input, comprising:

[0006] S1: Construct an intelligent ship motion control model for intelligent ships with uncertain parameters;

[0007] S2: Based on the intelligent ship motion control model, the uncertain parameters and external disturbances are linearly represented. Based on the linear representation function of the uncertain parameters and external disturbances of the intelligent ship, the adaptive backstepping method is applied to design the framework and perform coordinate transformation.

[0008] S3: Design an adaptive trajectory tracking controller based on coordinate substitution;

[0009] S4: Based on the adaptive trajectory tracking controller, a dynamic event triggering mechanism is introduced, and dynamic event triggering conditions are designed.

[0010] In some alternative implementations, step S1 includes:

[0011] The intelligent ship motion control model is established, and its expression is:

[0012]

[0013]

[0014] f u =(m 22 vr-d 11 u) / m 11

[0015] f v =(-m 11 ur-d 22 v) / m 22

[0016] f r =((m) 11 -m 22 )uv-d 33 r) / m 33

[0017] Where (x,y) and These represent the intelligent ship's position and heading in the northeast coordinate system, respectively, and are vectors [u,v,r]. T In the intelligent ship's appendage coordinate system, these represent the forward velocity u, the lateral velocity v, and the bow roll rate r, respectively; τ u ,τ r These represent forward thrust and yaw torque, respectively; m 11 ,m 22 ,m 33 The hydrodynamic mass additionally included in the inertial mass of intelligent ships; d 11 ,d 22 ,d 33 This represents the hydrodynamic damping coefficient; v d,κ (κ=u,v,r) represents the equivalent disturbance force and torque caused by unknown time-varying marine environmental disturbances to intelligent ships.

[0018] In some optional implementations, in step S2, based on the intelligent ship motion control model, uncertain parameters and external disturbances are linearly characterized, including:

[0019] The actual trajectory of the intelligent ship is η = [x, y]. T The intelligent ship's reference trajectory is η d =[x d ,y d ] T x d ,y dRepresenting the horizontal and vertical coordinates of the reference trajectory, for the intelligent ship motion control model, the function for simplifying the uncertain parameters of the intelligent ship is obtained: Where, τ=[τ u ,r] T F xy =[-d 11 u / m 11 ,d 22 v / m 22 ] T ,

[0020] Define χ1 = η, pass The original intelligent ship motion control model is transformed into a standard integral cascade form, H = (m 11 -m 22 )uv / m 33 , ∈(r)=r / m 33 g = 1 / m 33 d3=τ d,r / m 33 .

[0021] In some optional implementations, in step S2, based on the linear representation function of the uncertain parameters of the intelligent ship and external disturbances, an adaptive backstepping design framework is applied to perform coordinate transformation, including:

[0022] Define the error functions as s1, s2, and s3, where s1 = χ1 - χ d , s3=r-β,χ d =η d α and β are the virtual control laws in the u and r directions, respectively. k 11 ∈R 2×2 It is a positive definite matrix designed. and s2=[-s 22 ,s 21 ] T ;

[0023] F xy It is unknown, F xy After sorting, we obtained make Θ][θ1,θ2] T ξ(z)=diag[u / m 11 ,v / m 22 ], to obtain Fxy =ξ(z)Θ.

[0024] In some alternative implementations, step S3 includes:

[0025] The adaptive update law is: Where, Λ∈R 2×2 To design a positive definite symmetric matrix, c1 > 0 is a design parameter. It is an estimate of Θ;

[0026] Depend on Design intelligent ship trajectory tracking control law : k 22 ∈R 2×2 It is the positive definite matrix of the design;

[0027] The adaptive update rate law is: Where ι>0 and c2>0 are design parameters. For the design of a positive definite symmetric matrix, This is an estimate of σ, where σ is an unknown normal vector;

[0028] Design intelligent ship trajectory tracking control law Where, H=(m 11 -m 22 )uv / m 33 g = 1 / m 33 k3 > 0 is a design parameter;

[0029] The adaptive update law is: ρ>0, B>0, D>0, c3>0, c4>0 are design parameters. They represent The estimated value, It is an unknown normal vector.

[0030] In some alternative implementations, step S4 includes:

[0031] The conditions for triggering dynamic events are: k∈N,i=u,r, Among them, a i and b i All of these are design parameters, where N represents the set of natural numbers and R represents the set of real numbers.

[0032] The dynamic variables are: q i (0) = 0, where p i >0 is a design parameter, q i (0) is qi Initial value.

[0033] According to another aspect of the present invention, a computer-readable storage medium is provided having a computer program stored thereon, which, when executed by a processor, implements the steps of any of the methods described above.

[0034] In summary, compared with the prior art, the above-described technical solutions conceived by this invention can achieve the following beneficial effects:

[0035] (1) Based on virtual input, coordinate transformation is introduced, and the original motion control model of the intelligent ship is transformed into a standard integral cascade form. Combining the adaptive vector backstepping method design framework, an adaptive trajectory tracking control method based on virtual input is designed, which can effectively reduce controller energy consumption, reduce actuator wear, and improve trajectory tracking speed and accuracy.

[0036] (2) By combining the adaptive vector backstepping design framework, a trajectory tracking controller suitable for intelligent ships is proposed, which can effectively solve the problem of unknown parameters of intelligent ships.

[0037] (3) The concept of virtual input is introduced into the backstepping design control, which solves the problem of relative dimension of intelligent ships, simplifies the control design process, and reduces the computational burden. In addition, this invention overcomes the limitations of implicit assumptions in LOS-based schemes and avoids the additional dynamic inputs required in additional control schemes.

[0038] (4) On this basis, a dynamic event triggering mechanism is introduced, which reduces the number of control commands sent to the actuator and the actuator's action time. Attached Figure Description

[0039] Figure 1 This is a flowchart illustrating a control method provided in an embodiment of the present invention;

[0040] Figure 2 This is a reference trajectory and actual trajectory curve diagram of an intelligent ship provided in an embodiment of the present invention, wherein (a) represents the horizontal axis trajectory and (b) represents the vertical axis trajectory;

[0041] Figure 3 This is an intelligent ship tracking trajectory error diagram provided in an embodiment of the present invention, where (a) represents the tracking error on the horizontal axis and (b) represents the tracking error on the vertical axis.

[0042] Figure 4 This is a control input curve diagram of an intelligent ship propeller provided in an embodiment of the present invention, wherein (a) represents the actual control force τ. u (b) represents the control torque τ r ;

[0043] Figure 5 This is a parameter provided in an embodiment of the present invention. Estimated curve;

[0044] Figure 6 This is a parameter provided in an embodiment of the present invention. Estimated curve;

[0045] Figure 7 This is a parameter provided in an embodiment of the present invention. Estimated curve;

[0046] Figure 8 This is a parameter provided in an embodiment of the present invention. Estimated curve;

[0047] Figure 9 This is a diagram illustrating the dynamic event triggering effect provided in an embodiment of the present invention, where (a) represents the triggering instance τ. u (b) indicates that instance τ is triggered. r . Detailed Implementation

[0048] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the invention. Furthermore, the technical features involved in the various embodiments of this invention described below can be combined with each other as long as they do not conflict with each other.

[0049] like Figure 1 As shown, an intelligent ship adaptive trajectory tracking control scheme based on virtual input includes the following steps:

[0050] S1: Construct an intelligent ship motion control model for intelligent ships with uncertain parameters;

[0051] S2: Based on the intelligent ship motion control model, the uncertain parameters and external disturbances are linearly represented. Based on the linear representation function of the uncertain parameters and external disturbances of the intelligent ship, the adaptive backstepping method is applied to design the framework and perform coordinate transformation.

[0052] S3: Design an adaptive trajectory tracking controller based on coordinate substitution;

[0053] S4: Based on the adaptive trajectory tracking controller, a dynamic event triggering mechanism is introduced, and dynamic event triggering conditions are designed.

[0054] Furthermore, step S1 specifically includes:

[0055] The intelligent ship motion control model is established, and its expression is:

[0056]

[0057]

[0058] f u =(m 21 vr-d 11 u) / m 11 (3)

[0059] f v =(-m 11 ur-d 22 v) / m 22 (4)

[0060] f r =((m) 11 -m 22 )uv-d 33 r) / m 33 (5)

[0061] Where (x,y) and These represent the position and heading of the intelligent ship in the northeast coordinate system, respectively. In particular, the vector [u,v,r] T In the intelligent ship's appendage coordinate system, these represent the forward velocity u, the lateral velocity v, and the bow roll rate r, respectively; τ u ,τ r These represent forward thrust and yaw torque, respectively; m 11 ,m 22 ,m 33 The hydrodynamic mass additionally included in the inertial mass of intelligent ships; d 11 ,d 22 ,d 33 This represents the hydrodynamic damping coefficient; τ d,κ (κ=u,v,r) represents unknown time-varying marine environmental disturbances, mainly the equivalent interference forces and moments caused by environmental disturbances such as wind, waves, and currents to intelligent ships.

[0062] For the trajectory tracking control law to be designed for the intelligent ship, assumptions are made about the parameters of the intelligent ship.

[0063] Assumption 1: Intelligent ship parameter d (·) unknown.

[0064] Assumption 2: External ocean disturbance τ d,κ (κ=u,v,r) is time-varying and bounded, and has an unknown positive constant d. κ Satisfy |τ d,κ |<d κ .

[0065] Intelligent ship reference trajectory ηd =[x d ,y d ] T x d ,y d The horizontal and vertical coordinates represent the reference trajectory.

[0066] The actual trajectory η of an intelligent ship can track the reference trajectory χ d =η d Furthermore, it can guarantee that the tracking error can converge to a very small residual set within a finite time, while ensuring that all signals in the closed-loop tracking control system of the intelligent ship are bounded.

[0067] Furthermore, an adaptive backstepping design framework is applied to perform coordinate transformation. Step S2 specifically includes:

[0068] The actual trajectory of the intelligent ship is η = [x, y]. T x, y represent the horizontal and vertical coordinates of the actual trajectory, and the intelligent ship's reference trajectory is η. d =[x d ,y d ] T For the intelligent ship motion control model, the following function for simplifying uncertain parameters of the intelligent ship is obtained:

[0069]

[0070] In the formula, τ=[τ u ,r] T F xy =[-d 11 u / m 11 ,d 22 v / m 22 ] T ,

[0071]

[0072] Define χ1 = η,

[0073]

[0074] In the formula, H=(m 11 -m 22 )uv / m 33 , ∈(r)=r / m 33 g = 1 / m 33 d3=τ d,r / m 33 .

[0075] According to equation (7), the original intelligent ship motion control model is transformed into a standard integral cascade form. The relative dimension in the above equation is 2. Therefore, it can be seen that the system described by the above equation is controllable. Based on the simplification function in step S2, the following coordinate substitution is performed:

[0076] Define the error functions as s1, s2, and s3.

[0077] s1=χ1-χ d (8)

[0078]

[0079] s3=r-β (10)

[0080] Where α and β are the virtual control laws in the u and r directions, respectively.

[0081]

[0082] k 11 ∈R 2×2 It is the positive definite matrix of the design.

[0083]

[0084]

[0085] in, and s2=[-s 22 ,s 21 ] T .

[0086]

[0087] F xy It is unknown, F xy By organizing, we can obtain

[0088] make Θ = [θ1, θ2] T ,

[0089] ξ(z)=diag[u / m 11 ,v / m 22 ].

[0090] F xy =ξ(z)Θ (15)

[0091] Furthermore, step S3 specifically includes:

[0092] From equation (10), we can obtain:

[0093]

[0094] According to hypothesis 2, there exists an unknown normal vector σ = [σ1, σ2]. T ,|d i |≤σ i , i = 1, 2.

[0095] Design intelligent ship trajectory tracking control law

[0096]

[0097] k 22 ∈R 2×2 It is the positive definite matrix of the design.

[0098] The adaptive update rate law is:

[0099]

[0100]

[0101] In the formula, Λ∈R 2×2 , All are positive definite symmetric matrices for design. ι>0, c1>0, c2>0 are design parameters. These are the estimated values ​​of Θ and σ, respectively, and the estimation errors are respectively

[0102] Similarly, according to hypothesis 2, there exists an unknown normal vector.

[0103] Design intelligent ship trajectory tracking control law Its expression is:

[0104]

[0105] In the formula, H=(m 11 -m 22 )uv / m 33 g = 1 / m 33 k3 > 0 is a design parameter.

[0106] The adaptive update law is:

[0107]

[0108]

[0109] In the formula, ρ>0, B>0, D>0, c3>0, and c4>0 are design parameters. They represent The estimated values ​​have estimation errors of respectively.

[0110] Figure 2 As shown, Figure 2 In the middle (a), the x-axis trajectory is represented. Figure 2 (b) represents the ordinate trajectory. Despite the influence of parameter uncertainties, the control scheme enables the intelligent ship's actual position η to track the designed reference trajectory η. d And it achieved satisfactory control performance. Figure 3 As shown, the time-varying curve of the intelligent ship trajectory tracking error vector can be observed. Figure 3 In the middle (a), the tracking error on the horizontal axis is represented. Figure 3 In the figure (b), the tracking error on the vertical axis is shown. The results show that the tracking error under this control scheme is bounded and reasonable. Figure 4 As shown, the actual control force τ can be seen. u With control torque τ r The duration curve, where, Figure 4 In the middle (a), τ represents the actual control force. u , Figure 4 In the middle (b), the control torque τ is represented. r Due to the heading control, there is a certain adjustment process, and the actual control input tends to stabilize after about 5 seconds. The results show that the actual control force and torque are bounded and reasonable. Figures 5-6 Adaptive technology is used to analyze the unknown parameters Θ of intelligent ships. The estimation was performed, and since the adaptive technique requires a certain adjustment process, it basically tracked the unknown parameters to be estimated after about 5 seconds. The results show that... It is bounded. Similarly, Figure 7-Figure 8 For the unknown parameters σ of intelligent ships, After approximately 5 seconds, the system basically tracks the unknown parameters to be estimated, and it can be seen that... as well as It is bounded. Figure 9 The trigger instance and trigger time are displayed. Figure 9 In the middle (a), it represents the triggering instance τ. u , Figure 9 In the middle (b), it represents the triggering instance τ. r In a short period of time, τ i The control commands (i = u, r) are not transmitted indefinitely. The simulation results above show that all signals in the closed-loop trajectory tracking control system are bounded.

[0111] The conditions for triggering dynamic events are: k∈N,i=u,r, Among them, a i and b iAll of these are design parameters.

[0112] The dynamic variables are: q i (0) = 0. Where, p i >0 is a design parameter, q i (0) is q i Initial value.

[0113] S5: Conduct simulation studies on the system model of the intelligent ship adaptive trajectory tracking control scheme and the intelligent ship tracking controller to verify its effectiveness.

[0114] It should be noted that, depending on the implementation needs, the various steps / components described in this application can be broken down into more steps / components, or two or more steps / components or parts of the operation of steps / components can be combined into new steps / components to achieve the purpose of this invention.

[0115] Those skilled in the art will readily understand that the above description is merely a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of the present invention should be included within the scope of protection of the present invention.

Claims

1. A method for intelligent ship adaptive trajectory tracking control based on virtual input, characterized in that, include: S1: Construct an intelligent ship motion control model for intelligent ships with uncertain parameters; S2: Based on the intelligent ship motion control model, the uncertain parameters and external disturbances are linearly represented. Based on the linear representation function of the uncertain parameters and external disturbances of the intelligent ship, the adaptive backstepping method is applied to design the framework and perform coordinate transformation. S3: Design an adaptive trajectory tracking controller based on coordinate substitution; S4: Based on the adaptive trajectory tracking controller, a dynamic event triggering mechanism is introduced, and dynamic event triggering conditions are designed; In step S2, based on the linear representation function of the uncertain parameters of the intelligent ship and external disturbances, an adaptive backstepping method design framework is applied to perform coordinate transformation, including: Define the error functions as s1, s2, and s3, where s1 = χ1 - χ d , s3=r-β,χ d =η d α and β are the virtual control laws in the directions of forward velocity u and yaw rate r in the appendage coordinate system of the intelligent ship, respectively, and χ1 = η. η represents the actual trajectory of the intelligent ship. d For intelligent ship reference trajectory, Represents the heading of intelligent ships in the northeast coordinate system. k 11 ∈R 2×2 It is a positive definite matrix designed. and s2=[-s 22 ,s 21 ] T , τ=[τ u ,r] T , m 11 ,m 22 ,m 33 For the additional hydrodynamic mass included in the inertial mass of intelligent ships, τ = [τ u ,r] T v is the lateral velocity in the intelligent ship's appendage coordinate system, and τ is the lateral velocity. u It represents the driving force for progress. τ d,κ κ=u,v,r represents the equivalent disturbance force and torque caused by unknown time-varying marine environmental disturbances to intelligent ships, H=(m 11 -m 22 )uv / m 33 , ∈(r)=r / m 33 g = 1 / m 33 d3=τ d,r / m 33 ; F xy It is unknown, F xy After sorting, we obtained make Θ = [θ1, θ2] T ξ(z)=diag[u / m 11 ,v / m 22 ], to obtain F xy =ξ(z)Θ,d 11 ,d 22 ,d 33 This represents the hydrodynamic damping coefficient.

2. The method according to claim 1, characterized in that, Step S1 includes: The intelligent ship motion control model is established, and its expression is: f u =(m 22 vr-d 11 u) / m 11 f v =(-m 11 ur-d 22 v) / m 22 f r =((m 11 -m 22 )uv-d 33 r) / m 33 Where (x,y) represents the position of the intelligent ship in the northeast coordinate system; τ r This represents the bow roll torque.

3. The method according to claim 2, characterized in that, In step S2, based on the intelligent ship motion control model, uncertain parameters and external disturbances are linearly characterized, including: The actual trajectory of the intelligent ship is η = [x, y]. T The intelligent ship's reference trajectory is η d =[x d ,y d ] T x d ,y d Representing the horizontal and vertical coordinates of the reference trajectory, for the intelligent ship motion control model, the linear characterization functions of the intelligent ship's uncertain parameters and external disturbances are obtained: in, pass The original intelligent ship motion control model was transformed into a standard integral cascade form.

4. The method according to claim 3, characterized in that, Step S3 includes: The adaptive update law is: Where, Λ∈R 2×2 To design a positive definite symmetric matrix, c1>0 is a design parameter. It is an estimate of Θ; Depend on Design intelligent ship trajectory tracking control law k 22 ∈R 2×2 It is the positive definite matrix of the design; The adaptive update rate law is: Where ι>0 and c2>0 are design parameters. For the design of a positive definite symmetric matrix, This is an estimate of σ, where σ is an unknown normal vector, and σ = [σ1, σ2]. T ,|d i |≤σ i , i = 1, 2; Design intelligent ship trajectory tracking control law Where, H=(m 11 -m 22 )uv / m 33 g = 1 / m 33 k3>0 is a design parameter; The adaptive update law is: ρ>0, B>0, D>0, c3>0, c4>0 are design parameters. They represent The estimated value, Given an unknown positive constant vector, 5. The method according to claim 4, characterized in that, Step S4 includes: The conditions for triggering dynamic events are: k∈N,i=u,r, Among them, a i and b i All of these are design parameters, where N represents the set of natural numbers and R represents the set of real numbers. The dynamic variables are: q i (0) = 0, where p i >0 is a design parameter, q i (0) is q i Initial value.

6. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by a processor, it implements the steps of the method according to any one of claims 1 to 5.

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