A dynamic rendezvous control method for heterogeneous marine robots

Abstract

The present invention relates to the field of heterogeneous control technology, and in particular to a dynamic rendezvous control method for heterogeneous marine robots. The method comprises the following steps: reconstructing the dynamic models of an unmanned boat and an unmanned submersible into a port Hamiltonian energy structure; imposing a desired performance constraint on the surfacing depth of the unmanned submersible; constructing an expected energy configuration function for the unmanned boat and the unmanned submersible to obtain an expected port Hamiltonian energy structure; a controller of the unmanned submersible adjusting the injection rate of kinetic energy in real time so that its actual kinetic energy reaches the desired kinetic energy; the controller adjusting the injection rate of kinetic energy in real time so that the unmanned boat gradually approaches the position of the unmanned submersible to achieve dynamic rendezvous; and adjusting the rate of change of an estimated value of an unmeasurable constant parameter in the model in real time to achieve unbiased identification of the unmeasurable constant parameter. Compared with the prior art, the control method proposed by the present invention can achieve efficient, stable and safe collision-free dynamic rendezvous, and has good application prospects.

Description

Technical Field

[0001] The present invention relates to the technical field of heterogeneous control, and in particular to a dynamic rendezvous control method for heterogeneous marine robots. Background Art

[0002] Among numerous ocean exploration technologies, marine robots offer advantages such as long-duration operation, efficient mission execution, and reduced personnel risk. Consequently, they are widely used in deep-sea exploration, shipwreck recovery, scientific research, and seafloor topography mapping. To improve the efficiency of certain exploration missions, such as large-scale deep-sea exploration or scientific expeditions under complex sea conditions, control technology for multiple marine robots has attracted considerable attention. Rendezvous control plays a crucial role in the complete multi-robot operation cycle (i.e., launch, operation, and recovery). Currently, the mainstream rendezvous control methods are mainly model predictive control and feedback linearization. However, the former requires extensive iterative calculations of the nominal model to obtain the ideal control input. This imposes a heavy computational burden, and the ideal control input cannot guarantee control accuracy when applied to the marine robot's actuators under complex sea conditions. The latter, which designs controllers based on signal processing, is highly complex and has low portability. Considering the need for rendezvous safety, controller design becomes even more challenging, hindering the practical application of these control methods. Therefore, a control method that ensures both rendezvous accuracy and safety while also being readily applicable in engineering applications is needed. Summary of the Invention

[0003] In view of this, the purpose of the present invention is to propose a dynamic rendezvous control method for heterogeneous marine robots to solve the problems of high complexity and low portability of existing methods.

[0004] Based on the above objectives, the present invention provides a dynamic rendezvous control method for heterogeneous marine robots, comprising the following steps:

[0005] S1. Based on the Port-Hamiltonian method, the dynamic models of the unmanned boat and the unmanned submersible are reconstructed into the port Hamiltonian energy structure, in which the position state variables η of the unmanned boat and the unmanned submersible are defined as i ,i=A,U and kinetic energy state variable P i =M i ν i , i=A, U is the energy output port, A and U represent the unmanned boat and unmanned submersible respectively, and the control input of each of the two marine robots is the energy injection port; the energy injection port and the energy output port are connected through the system energy interconnection structure and energy dissipation structure; the energy configuration function H i ,i=A,U is the expected energy distribution for the system energy interconnection structure and energy dissipation structure;

[0006] S2, based on the preset performance control technology, represents the floating depth z of the unmanned submersible U Imposing desired performance constraints, and re-energizing the dynamics of the unmanned underwater vehicle with the performance constraints;

[0007] S3. Construct the energy configuration function H in the desired form id ,i=A,U, allocates interconnected structure energy flow and dissipative structure energy flow to the port Hamiltonian energy structure of the unmanned submersible and unmanned boat, selects energy configuration weights according to demand, and constructs the expected port Hamiltonian energy structure of the unmanned boat and unmanned submersible;

[0008] S4. The unmanned submersible obtains the current position information η in real time U , calculate the next expected position η Ud The desired kinetic energy required to reach the next preset desired position and meet the ascent safety guarantee conditions is calculated by combining the desired port Hamiltonian energy structure, the degree of deviation from the desired position, and the real-time feedback of the ascent depth information. The designed controller adjusts the kinetic energy injection rate in real time so that the current actual kinetic energy reaches the desired kinetic energy, allowing the unmanned submersible to approach the desired position.

[0009] S5. After the unmanned boat obtains the position information of the unmanned submersible, it evaluates the distance between its current position and the horizontal position of the unmanned submersible, calculates the kinetic energy required to approach the unmanned submersible, and the controller adjusts the kinetic energy injection rate to drive the unmanned boat close to the unmanned submersible to achieve the conditions for a safe rendezvous;

[0010] S6. Unbiased identification of unmeasurable constant parameters in the nonlinear models of unmanned submersibles and unmanned boats. First, the energy required for identification is allocated in the constructed energy allocation function, and the definition is: are the real values ​​of the unmeasurable constant parameters in the unmanned submersible and unmanned boat models, It is the estimated value of the unmeasurable constant parameter. The speed of change of the estimated value depends on the deviation between the estimated value and the actual value and the energy configuration weight corresponding to the identification. Every time the control input generates an estimated value of an unknown constant parameter, it is compared with the actual value of the constant parameter. When the deviation between the estimated value and the actual value is greater than the set threshold, the auxiliary controller adaptively increases the rate of change of the estimated value so that the estimated value converges quickly to the actual value.

[0011] Preferably, in step S2, the floating depth z of the unmanned submersible is represented by U After applying the desired performance constraint, the method further includes: converting the inequality-form performance constraint into an equation form to obtain a time-varying and continuously constrained variable ε(t) equivalent to the floating depth.

[0012] Preferably, in step S2, the upper and lower bounds of the floating depth are determined by a preset performance function ρ and overshoot parameters ξ1 and ξ2 that vary with time, and the changing speed of the floating depth is constrained by the minimum convergence speed λ of the preset performance function.

[0013] Preferably, in step S3, the desired form of energy configuration function H is determined id ,i=A,U and energy configuration weights, the desired port Hamiltonian energy structure of the UAV and UUV can achieve the desired rendezvous performance.

[0014] Preferably, in step S5, the unmanned boat receives the position information η of the unmanned submersible. U Afterwards, through η A =J extract η U Extract the horizontal position information of the unmanned submersible, where J extract The non-zero elements in the matrix are J extract(1,1) =J extract(2,2) =J extract(6,1) =1.

[0015] Preferably, in step S6, the specific form of the adaptive auxiliary controller is in, and is the weight matrix, are non-regressive matrices related to the speed of the unmanned boat and the unmanned submersible, respectively. The estimation error is defined as Determine the weight coefficient and After that, the adaptive auxiliary controller can be used in real time according to the non-regression matrix and kinetic energy difference and the estimated error The rate of change of the estimate of an unmeasured constant parameter in the adjustment model.

[0016] Beneficial effects of the present invention:

[0017] 1. Based on the Port-Hamiltonian method, the present invention constructs the port Hamiltonian energy structure of the unmanned boat and unmanned submersible respectively, enabling the unmanned boat and unmanned submersible to process the acquired position and velocity information, analyze the distance from the desired position, the depth from the sea level, and the relative position with the unmanned boat, and adaptively update the injection rate of the kinetic energy of the unmanned boat and unmanned submersible, so that the relative positions of the unmanned submersible and the unmanned boat gradually approach each other to meet the conditions for safe rendezvous. The algorithm complexity is low.

[0018] 2. Based on the idea of ​​adaptation, the present invention proposes a structure-preserving adaptive estimation algorithm, which enables the accurate identification of the unmeasurable constant parameters inside the models of the unmanned submersible and unmanned boat. The control inputs of the unmanned submersible and unmanned boat will respectively generate an estimated value of the unmeasurable constant parameter, and the adaptive estimation algorithm can update the rate of change of the estimated value based on the kinetic energy difference and the estimation error. Structure preservation means that the energy configured by the energy configuration function will eventually flow out of the system as dissipated energy. The introduction of the adaptive estimation algorithm will not affect the adjustment of the kinetic energy of the unmanned boat and unmanned submersible, nor will it destroy the port Hamiltonian energy structure of the unmanned boat and unmanned submersible, and has high portability. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] In order to more clearly illustrate the technical solutions in the present invention or the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are only for the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0020] Figure 1 A schematic diagram of a marine robot rendezvous according to an embodiment of the present invention;

[0021] Figure 2 2 is a flow chart of a dynamic rendezvous control method according to an embodiment of the present invention. DETAILED DESCRIPTION

[0022] In order to make the objectives, technical solutions and advantages of the present invention more clearly understood, the present invention is further described in detail below with reference to specific embodiments.

[0023] It should be noted that, unless otherwise defined, the technical or scientific terms used in the present invention should have the usual meanings understood by people with ordinary skills in the field to which the present invention belongs. The "first", "second" and similar words used in the present invention do not indicate any order, quantity or importance, but are only used to distinguish different components. "Include" or "comprise" and similar words mean that the elements or objects appearing before the word include the elements or objects listed after the word and their equivalents, without excluding other elements or objects. "Connect" or "connected" and similar words are not limited to physical or mechanical connections, but may include electrical connections, whether direct or indirect. "Up", "down", "left", "right" and the like are only used to indicate relative positional relationships. When the absolute position of the object being described changes, the relative positional relationship may also change accordingly.

[0024] The present embodiment provides a method for controlling the dynamic rendezvous of a heterogeneous marine robot, wherein the heterogeneous marine robot system includes an unmanned boat and an unmanned submersible. The control method includes the following steps:

[0025] The dynamic models of S1, UAV and UUV have the characteristics of time-varying and highly nonlinearity. Directly describing the internal states of the two types of systems lacks clear physical meaning. Based on the Port-Hamiltonian theory, the original models of UAV and UUV are reconstructed into port Hamiltonian energy structures to describe the state changes of the two types of systems from the perspective of energy flow. The transformed model forms are

[0026]

[0027] Among them, J i ,i=A,U represents the internal energy interconnection structure of the two types of systems, -C i -D i , i=A,U represents the energy dissipation structure of the two types of systems. The two structures are connected by the energy configuration function H i ,i=A,U injection energy. η i , i=A, U represent the positions of the unmanned boat and unmanned submersible in the earth coordinate system respectively. i =M i ν i , i=A, U represent the kinetic energy of the unmanned boat and unmanned submersible respectively. τ i ,i=A,U represent the control inputs of the unmanned boat and unmanned submersible respectively.

[0028] S2, the floating depth z of the unmanned submersible based on the preset performance control technology U First, select the exponential form of the preset performance function β(t) = (β0-β ∞ )e -λt +β ∞ , where β0, β ∞ They represent the allowable error and maximum steady-state error at the initial moment. λ is the minimum convergence speed. The floating depth z U The upper and lower bounds of are determined by the overshoot parameters ξ1, ξ2 and the preset performance function, which is in the form of -ξ1β(t)<z U (t)<ξ2β(t). Determine the overshoot parameters ξ1, ξ2, the allowable error, the maximum steady-state error and the minimum convergence rate λ so that the floating depth z U Converges to the rendezvous depth at an exponential rate. In order to facilitate the control input to ensure that the unmanned submersible's surface depth meets the preset performance constraints, the constraints in the form of inequalities are converted into equations that change continuously over time and are equivalent to z U The variables to be constrained Where S satisfies the mapping The Hamiltonian energy structure of the unmanned underwater vehicle port is remodeled by introducing the unconstrained variable ε(t).

[0029] S3. Construct the desired energy configuration function H id ,i=A,U, is the Hamiltonian energy structure of the ports of the UAV and the UUV, which distributes the interconnected structure energy flow and the dissipative structure energy flow. The energy configuration weight W is selected according to different scenarios. i11 ,W i12 .W i22 ,i=A,U, and the expected port Hamiltonian energy structure of the unmanned boat and unmanned submersible is obtained.

[0030] S4, the unmanned submersible obtains the current position information in real time and sends it to the unmanned boat, and at the same time calculates the deviation between the current position and the next preset expected position. Compare the Hamiltonian energy structure of the desired port of the unmanned submersible, the deviation between the reference and reference positions and the current surfacing depth information, and calculate the kinetic energy P required to reach the next preset expected position. Ud Then, the actual kinetic energy P is calculated based on the current speed information. U , after analyzing the kinetic energy difference, the control input τ U The current kinetic energy change rate is adaptively adjusted to approach the desired kinetic energy.

[0031] S5. After receiving the position information of the unmanned submersible, the unmanned boat extracts its horizontal position information and uses it as the next expected position. Calculate the deviation between the current position and the next expected position. Refer to the Hamiltonian energy structure of the expected port of the unmanned boat to analyze the kinetic energy P required for the unmanned boat to reach the next expected position. Ad The designed control input τ A It can adaptively adjust the current kinetic energy change rate so that the current kinetic energy of the unmanned boat is P A Approximate the required kinetic energy P Ad .

[0032] S6, the unmeasured constant parameters in the unmanned boat and unmanned submersible models can be unbiasedly identified using the adaptive estimation algorithm proposed in this invention. First, the energy configuration function H of the two marine robots id ,i=A,U adds the energy required for identification. They represent the real values ​​of the unmeasurable constant parameters of the unmanned boat and unmanned submersible models respectively. They represent the estimated values ​​of the unmeasured constant parameters of the UAV and UUV models respectively. The estimation error is defined as Calculate the estimated error of the unmeasurable constant parameter

[0033] Then, the adaptive estimation algorithm The speed of change of the estimated value can be adjusted based on the kinetic energy difference. When the estimation error is large, the adaptive estimation algorithm increases the rate of change of the estimated value, thereby quickly converging to the real value. The energy used for identification is adjusted by the kinetic energy difference, and this energy does not affect the kinetic energy distribution.

[0034] Those skilled in the art will understand that the discussion of any of the above embodiments is merely illustrative and is not intended to limit the scope of the present invention to these examples. Within the spirit and principles of the present invention, the technical features of the above embodiments or different embodiments may be combined, the steps may be implemented in any order, and many other variations exist for the various aspects of the present invention described above, which are not provided in detail for the sake of clarity. Any omissions, modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention shall be included within the scope of protection of the present invention.

Claims

1. A dynamic rendezvous control method for heterogeneous marine robots, characterized in that: The following steps are involved: S1. Based on the Port-Hamiltonian method, the dynamic models of the unmanned boat and the unmanned submersible are reconstructed into the port Hamiltonian energy structure, in which the position state variables η of the unmanned boat and the unmanned submersible are defined as i ,i=A,U and kinetic energy state variable P i =M i ν i , i=A, U is the energy output port, A and U represent the unmanned boat and unmanned submersible respectively, and the control input of each of the two marine robots is the energy injection port; the energy injection port and the energy output port are connected through the system energy interconnection structure and energy dissipation structure; the energy configuration function H i ,i=A,U is the expected energy distribution for the system energy interconnection structure and energy dissipation structure; S2, based on the preset performance control technology, represents the floating depth z of the unmanned submersible U Imposing desired performance constraints, and re-energizing the dynamics of the unmanned underwater vehicle with the performance constraints; S3. Construct the energy configuration function H in the desired form id ,i=A,U, allocates interconnected structure energy flow and dissipative structure energy flow to the port Hamiltonian energy structure of the unmanned submersible and unmanned boat, selects energy configuration weights according to demand, and constructs the expected port Hamiltonian energy structure of the unmanned boat and unmanned submersible; S4. The unmanned submersible obtains the current position information η in real time U , calculate the next expected position η Ud The desired kinetic energy required to reach the next preset desired position and meet the ascent safety guarantee conditions is calculated by combining the desired port Hamiltonian energy structure, the degree of deviation from the desired position, and the real-time feedback of the ascent depth information. The designed controller adjusts the kinetic energy injection rate in real time so that the current actual kinetic energy reaches the desired kinetic energy, allowing the unmanned submersible to approach the desired position. S5. After the unmanned boat obtains the position information of the unmanned submersible, it evaluates the distance between its current position and the horizontal position of the unmanned submersible, calculates the kinetic energy required to approach the unmanned submersible, and the controller adjusts the kinetic energy injection rate to drive the unmanned boat close to the unmanned submersible to achieve the conditions for a safe rendezvous; S6. Unbiased identification of unmeasurable constant parameters in the nonlinear models of unmanned submersibles and unmanned boats. First, allocate the energy required for identification in the constructed energy allocation function and define ζ i , i=U, A are the real values ​​of the unmeasurable constant parameters in the UUV and UUV models respectively, A is the estimated value of the unmeasurable constant parameter. The speed of change of the estimated value depends on the deviation between the estimated value and the actual value and the energy configuration weight corresponding to the identification. Every time the control input generates an estimated value of an unknown constant parameter, it is compared with the actual value of the constant parameter. When the deviation between the estimated value and the actual value is greater than the set threshold, the auxiliary controller adaptively increases the rate of change of the estimated value so that the estimated value converges quickly to the actual value.

2. The dynamic rendezvous control method for heterogeneous marine robots according to claim 1, characterized in that: In step S2, the floating depth z of the unmanned submersible is U After applying the desired performance constraint, the method further includes: converting the inequality-form performance constraint into an equation form to obtain a time-varying and continuously constrained variable ε(t) equivalent to the floating depth.

3. The dynamic rendezvous control method for heterogeneous marine robots according to claim 2, characterized in that: In step S2 , the upper and lower bounds of the floating depth are determined by a preset performance function ρ and overshoot parameters ξ1 and ξ2 that vary with time, and the changing speed of the floating depth is constrained by the minimum convergence speed λ of the preset performance function.

4. The dynamic rendezvous control method for heterogeneous marine robots according to claim 1, characterized in that: In step S3, the desired energy configuration function H is determined. id ,i=A,U and energy configuration weights, the desired port Hamiltonian energy structure of the UAV and UUV can achieve the desired rendezvous performance.

5. The dynamic rendezvous control method for heterogeneous marine robots according to claim 1, characterized in that: In step S5, the unmanned boat receives the position information η of the unmanned submersible. U Afterwards, through η A =J extract η U Extract the horizontal position information of the unmanned submersible, where J extract The non-zero elements in the matrix are J extract(1,1) =J extract(2,2) =J extract(6,1) =1.

6. The dynamic rendezvous control method for heterogeneous marine robots according to claim 1, characterized in that: In step S6, the specific form of the adaptive auxiliary controller is Among them, K ζi and is the weight matrix, are non-regressive matrices related to the speed of the unmanned boat and the unmanned submersible, respectively. The estimation error is defined as Determine the weight coefficient and After that, the adaptive auxiliary controller can be used in real time according to the non-regression matrix and kinetic energy difference and the estimated error The rate of change of the estimate of an unmeasured constant parameter in the adjustment model.

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