Dynamic rendezvous control method for heterogeneous ocean robots

Abstract

The invention relates to the technical field of isomer control, in particular to a dynamic rendezvous control method of a heterogeneous ocean robot, which comprises the following steps of: reconstructing kinetic models of an unmanned ship and an unmanned submersible vehicle into a port Hamiltonian energy structure; expected performance constraint is applied to the floating depth of the unmanned submersible vehicle; an expected energy configuration function of the unmanned ship and the unmanned submersible vehicle is constructed, and an expected port Hamiltonian energy structure is obtained; the controller of the unmanned submersible vehicle adjusts the injection rate of kinetic energy in real time to enable the actual kinetic energy to reach expected kinetic energy; the controller adjusts the injection rate of kinetic energy in real time, so that the unmanned ship gradually gets close to the position of the unmanned submersible vehicle, and dynamic rendezvous is achieved; the change rate of the estimated value of the unmeasurable constant parameter in the model is adjusted in real time, and unbiased identification of the unmeasurable constant parameter is achieved; compared with the prior art, the control method provided by the invention can realize efficient, stable and safe collision-free dynamic rendezvous, and has a good application prospect.

Description

Technical Field

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

[0002] Among many ocean exploration technologies, marine robots have the advantages of being able to work for a long time, efficiently perform exploration tasks, and reduce personnel risks. Therefore, they are widely used in deep-sea exploration, shipwreck salvage, scientific research, seabed topography mapping and other fields. In some exploration tasks, in order to improve the efficiency of exploration tasks such as large-scale deep-sea exploration or scientific investigation under complex sea conditions, the control technology of multiple marine robots has attracted much attention. In a complete multi-marine robot operation cycle (i.e., launch, work, and recovery), rendezvous control plays a vital role. At present, the mainstream rendezvous control methods are mainly model predictive control and feedback linearization. However, the former requires a large number of iterative calculations on the nominal model to obtain the ideal control input. This condition brings a heavy computational burden, and the ideal control input acting on the actuator of the marine robot cannot guarantee the control accuracy under actual complex sea conditions. The latter designs the controller from the perspective of signal processing. This control method has high complexity and low portability. Considering the need for rendezvous safety, the difficulty of controller design is further increased, which hinders the practical application of this type of control method. Therefore, a control method that can ensure rendezvous accuracy and safety and is convenient for engineering application 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 purpose, 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, where 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 allocation 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 the desired performance constraints, the dynamics of the unmanned submersible with the performance constraints are remodeled energetically;

[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 safety guarantee conditions for buoyancy 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 buoyancy 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 to approach the unmanned submersible to achieve the conditions for a safe rendezvous;

[0010] S6. Unbiased identification of unmeasured constant parameters in 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 continuous variable ε(t) to be constrained that is 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 energy configuration function H of the desired form is determined id ,i=A,U and energy configuration weights, the desired port Hamiltonian energy structure of the unmanned boat and unmanned submersible can achieve the desired rendezvous performance.

[0014] Preferably, in step S5, the unmanned boat receives the position information η of the unmanned submersible. U After that, 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-regressive 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 the unmanned submersible respectively, so that the unmanned boat and the unmanned submersible can process the acquired position and speed information, analyze the distance from the expected 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 the unmanned submersible, so that the relative position of the unmanned submersible and the unmanned boat gradually approaches to meet the conditions for safe rendezvous, and the algorithm complexity is low.

[0018] 2. The present invention proposes a structure-preserving adaptive estimation algorithm based on the idea of ​​adaptation, so that the unmeasurable constant parameters inside the unmanned submersible and unmanned boat models can be accurately identified; 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 according to 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, and 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 drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings in the following description are only for the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

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

[0021] Figure 2 The figure 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 in conjunction with specific embodiments.

[0023] It should be noted that, unless otherwise defined, the technical terms or scientific terms used in the present invention should be 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 described object changes, the relative positional relationship may also change accordingly.

[0024] The embodiment of this specification provides a dynamic rendezvous control method for 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] S1. The dynamic models of unmanned boats and unmanned submersibles are time-varying and highly nonlinear. 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 unmanned boats and unmanned submersibles 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 the 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 ∞ ) -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, allowable error, maximum steady-state error and minimum convergence speed λ so that the floating depth z U Converges to the intersection depth at an exponential rate. In order to facilitate the control input to ensure that the unmanned submersible 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 port of the unmanned submersible is remodeled by introducing the constraint variable ε(t).

[0029] S3. Construct the desired energy configuration function H id ,i=A,U, which is the Hamiltonian energy structure of the ports of the unmanned boat and the unmanned submersible to distribute 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 calculates the degree of deviation between the current position and the next preset expected position. Compare the Hamiltonian energy structure of the expected port of the unmanned submersible, the degree of deviation between the reference and reference positions, and the current buoyancy depth information, and calculate the kinetic energy P required to reach the next preset expected position. Ud Next, 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 size P of the unmanned boat A Approach the required kinetic energy P Ad .

[0032] S6. The unmeasurable constant parameters in the unmanned boat and unmanned submersible models can be unbiasedly identified using the adaptive estimation algorithm proposed in the present 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 unmanned boat and unmanned submersible models respectively. The estimation error is defined as Calculate the estimated error of the unmeasurable constant parameter

[0033] After that, the adaptive estimation algorithm The speed of change of the estimated value can be adjusted according to 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 part of the energy will not affect the kinetic energy distribution.

[0034] Those skilled in the art should understand that the discussion of any of the above embodiments is only exemplary and is not intended to imply that the scope of the present invention is limited to these examples; under the concept of the present invention, the technical features in the above embodiments or different embodiments can also be combined, the steps can be implemented in any order, and there are many other changes in different aspects of the present invention as described above, which are not provided in detail for the sake of simplicity. Any omissions, modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in 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, where 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 allocation 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 the desired performance constraints, the dynamics of the unmanned submersible with the performance constraints are remodeled energetically; 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 safety guarantee conditions for buoyancy 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 buoyancy 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 to approach the unmanned submersible to achieve the conditions for a safe rendezvous; S6. Unbiased identification of unmeasured constant parameters in nonlinear models of unmanned submersibles and unmanned boats. First, the energy required for identification is allocated in the constructed energy allocation function, and ζ is defined as i , i=U, A are the real values ​​of the unmeasurable constant parameters in the unmanned submersible and unmanned boat models, 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 of heterogeneous marine robots according to claim 1, characterized in that: 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 continuous variable ε(t) to be constrained that is equivalent to the floating depth.

3. The dynamic rendezvous control method of 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 of 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 unmanned boat and unmanned submersible can achieve the desired rendezvous performance.

5. The dynamic rendezvous control method of 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 After that, 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 of 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-regressive 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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