High-maneuverability bionic robotic fish kinetic model and parameter identification method

Abstract

The invention relates to the technical field of underwater robotic fishes, in particular to a high-maneuverability bionic robotic fish kinetic model and parameter identification method, which comprises the following steps: constructing a kinetic model; determining power parameters needing to be identified; and determining parameters of the kinetic model. According to the method, the motion state of the robotic fish in water can be better described and predicted by constructing accurate dynamic modeling and performing parameter identification of the dynamic model, so that the motion control precision and maneuverability of the robotic fish are improved, and a foundation is laid for the expression of the robotic fish in practical application.

Description

Technical Field

[0001] The present invention relates to the technical field of underwater robotic fish, and particularly to a dynamic model and parameter identification method for a highly maneuverable bionic robotic fish. Background Art

[0002] With the continuous development of underwater robot technology, bionic robotic fish have become a hot research and application field in recent years. Bionic robotic fish improve their flexibility and maneuverability by imitating the swimming mode of fish, and can perform detection, rescue, and environmental monitoring tasks in complex underwater environments, having broad application prospects in multiple fields such as environmental protection and ocean engineering. Most existing robotic fish use caudal fins or thrusters for movement. However, robotic fish using pectoral fin propulsion have characteristics such as high control accuracy and strong flexibility, enabling the robotic fish to move more quickly and flexibly in complex underwater environments. Different from traditional caudal fin propulsion, the dynamic characteristics of pectoral fin propulsion are more complex, involving more motion parameters and complex mechanical models.

[0003] Currently, there are no systematic research results on the dynamic model and parameter identification method for highly maneuverable robotic fish with pectoral fin propulsion. Most existing dynamic models and control strategies of robotic fish are mainly based on caudal fin propulsion and cannot be directly applied to the case of pectoral fin propulsion. In addition, due to the more complex hydrodynamic characteristics and multi-degree-of-freedom motion modes involved in pectoral fin propulsion, existing models and algorithms cannot effectively describe its complex dynamic behavior. Especially in practical applications, how to accurately establish the dynamic model of highly maneuverable robotic fish with pectoral fin propulsion and accurately identify relevant parameters has become a technical problem to be solved urgently.

[0004] Therefore, it is necessary to provide a dynamic model and parameter identification method for a highly maneuverable bionic robotic fish to solve the above problems. Summary of the Invention

[0005] The present invention provides a dynamic model and parameter identification method for a highly maneuverable bionic robotic fish. Through accurate dynamic modeling and an efficient parameter identification method, it can better describe and predict the motion state of the robotic fish in water, thereby improving the motion control accuracy and maneuverability of the robotic fish and laying a foundation for its performance in practical applications to solve existing problems.

[0006] The dynamic model of a highly maneuverable bionic robotic fish of the present invention adopts the following technical solutions, including: Design a dynamic model for a highly maneuverable bionic robotic fish based on the Newton-Euler equation.

[0007] Preferably, the expression of the dynamic model of the highly maneuverable bionic robotic fish is:

[0008] Wherein, is the speed of the high - mobility bionic robotic fish; is the mass of the high - mobility bionic robotic fish; is the angular velocity of the high - mobility bionic robotic fish; is the gravity force received by the high - mobility bionic robotic fish; is the buoyancy force received by the high - mobility bionic robotic fish; is the resistance force received by the high - mobility bionic robotic fish; is the force generated by the left pectoral fin of the high - mobility bionic robotic fish; is the force generated by the right pectoral fin of the high - mobility bionic robotic fish; is the inertia matrix, the torque generated by the left pectoral fin of the high - mobility bionic robotic fish; is the torque generated by the left pectoral fin of the high - mobility bionic robotic fish; is the torque generated by the resistance force; is the torque generated by the buoyancy force.

[0009] Preferably, the steps to obtain the buoyancy force and the torque generated by the buoyancy force received by the high - mobility bionic robotic fish are: wherein, the high - mobility bionic robotic fish is in a zero - buoyancy state, that is, the gravity is equal to the buoyancy; Then there is:

[0010] Wherein, is the density of the liquid; is the acceleration due to gravity; is the drainage volume of the prototype of the high - mobility bionic robotic fish; is the center - of - gravity offset of the prototype of the high - mobility bionic robotic fish.

[0011] Preferably, the expressions for the resistance force and the torque generated by the resistance force received by the high - mobility bionic robotic fish are:

[0012] Wherein, is the resistance coefficient; is the cross - sectional area of the prototype of the high - mobility bionic robotic fish; is the resistance - torque coefficient.

[0013] Preferably, the expressions for the force and torque generated by the pectoral fins of the high - mobility bionic robotic fish are:

[0014] Wherein, is the force generated by the pectoral fin of the high - mobility bionic robotic fish wherein, takes when it is the left pectoral fin, Take When it is the right pectoral fin; It is the pectoral fin of a highly maneuverable bionic robot fish The moment generated; It is the transformation matrix for transferring force from the pectoral fin To the body of the highly maneuverable bionic robot fish; It is the pectoral fin The length of the moment arm; It is the density of the liquid; It is the pectoral fin The corresponding dynamic parameter; It is the pectoral fin The normal velocity at the center.

[0015] Preferably, it further includes: verifying the dynamic model, and the verification steps include: Input the optimal dynamic parameters into the dynamic model, and conduct a high-maneuver pitch simulation of the bionic robot fish according to the preset pitch angle, and obtain the theoretical pitch angle output by the dynamic model; Conduct a high-maneuver pitch experiment of the bionic robot fish in the pool according to the preset pitch angle, and obtain the actual pitch angle output by the experiment; When the pitch angle difference between the theoretical pitch angle and the actual pitch angle is less than the difference threshold, the dynamic model is qualified.

[0016] A method for identifying the dynamic model and parameters of a highly maneuverable bionic robot fish adopts the following technical solutions, including: Based on the Morison equation, obtain the forces and moments generated by the pectoral fins of the highly maneuverable bionic robot fish, and determine the dynamic parameters to be identified for the highly maneuverable bionic robot fish according to the forces and moments generated by the pectoral fins of the highly maneuverable bionic robot fish; the dynamic parameters include: pectoral fin thrust parameter, pectoral fin lateral force parameter, and pectoral fin lift parameter; Conduct a high-maneuver pitch experiment on the highly maneuverable bionic robot fish, and obtain the angular velocity of the highly maneuverable bionic robot fish during the experiment; According to the angular velocity of the highly maneuverable bionic robot fish, and based on the crow algorithm, optimize the dynamic parameters to obtain the optimal dynamic parameters generated by the pectoral fins; take the optimal dynamic parameters as the parameters of the dynamic model.

[0017] Preferably, the fitness function of the crow algorithm is:

[0018] In the formula, Is the fitness value of the j th crow, j = 1, 2,..., m , m Is the number of crow individuals in the population; Is the theoretical pitch angle output by the dynamic model under the dynamic parameters corresponding to the pectoral fin at the current iteration; is the actual pitch angle; is the number of samples.

[0019] Preferably, the high-maneuver pitch includes: rapid diving and rapid surfacing.

[0020] A parameter identification system for the dynamics model of a high-maneuver biomimetic robotic fish adopts the following technical solution, including: A dynamic parameter determination module, which is used to obtain the forces and torques generated by the pectoral fins of the high-maneuver biomimetic robotic fish based on the Morison equation, and obtain the dynamic parameters to be identified for the high-maneuver biomimetic robotic fish according to the forces and torques generated by the pectoral fins of the high-maneuver biomimetic robotic fish; the dynamic parameters include: pectoral fin thrust parameters, pectoral fin lateral force parameters, and pectoral fin lift parameters; A parameter optimization module, which is used to conduct an experiment on the rapid surfacing of the high-maneuver biomimetic robotic fish and obtain the angular velocity of the high-maneuver biomimetic robotic fish during the experiment; according to the angular velocity of the high-maneuver biomimetic robotic fish, and based on the crow algorithm, optimize the dynamic parameters to obtain the optimal dynamic parameters generated by the pectoral fins; use the optimal dynamic parameters as the parameters of the dynamics model.

[0021] The beneficial effects of the present invention are: By designing the dynamics model of the high-maneuver biomimetic robotic fish through the Newton-Euler equation, the problem that it is difficult to establish the dynamics model of the robotic fish in the high-maneuver motion state by conventional methods is avoided. Secondly, the dynamics model established by the present invention can calculate the magnitudes of the forces and torques generated by the pectoral fins and predict the pitch angle of the entire robotic fish, and can be used for the high-maneuver motion control simulation of the robotic fish; the problem that the parameter calculation of the forces and torques generated by the pectoral fins of the robotic fish in the high-maneuver motion state is large in calculation amount and prone to divergence when using the computational fluid dynamics simulation method is avoided, and the calculation amount of the present invention is small and more accurate. Description of the Drawings

[0022] In order to more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the following will briefly introduce the drawings required for the description of the embodiments or the prior art. Obviously, the following drawings are only some embodiments of the present invention. For those of ordinary skill in the art, without creative efforts, other drawings can also be obtained according to these drawings.

[0023] Figure 1 is the flowchart of a method for the dynamics model and parameter identification of a high-maneuver biomimetic robotic fish of the present invention; Figure 2 is the schematic diagram of the prototype of the high-maneuver biomimetic robotic fish in the embodiment of the present invention; Figure 3 is the angular velocity curve graph of the rapid surfacing experiment of the high-maneuver biomimetic robotic fish in the embodiment of the present invention; Figure 4 This is a comparison curve graph of the actual angle in the rapid upward floating experiment of the highly maneuverable bionic fish in the embodiment of the present invention and the theoretical angular velocity obtained by simulating with the dynamic model. Specific implementation manner

[0024] Next, the technical solutions in the embodiments of the present invention will be clearly and completely described in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts shall fall within the protection scope of the present invention.

[0025] An embodiment of a dynamic model and parameter identification method for a highly maneuverable bionic fish of the present invention is as Figure 1 shown, including: S1. Construct a dynamic model; Specifically, a dynamic model of a highly maneuverable bionic fish is designed based on the Newton-Euler equation.

[0026] Exemplarily, the highly maneuverable fish targeted in this embodiment is as Figure 2 shown, where the expression of the dynamic model of the highly maneuverable fish is:

[0027] In the formula, is the speed of the highly maneuverable bionic fish; is the mass of the highly maneuverable bionic fish; is the angular velocity of the highly maneuverable bionic fish; is the gravity received by the highly maneuverable bionic fish; is the buoyancy received by the highly maneuverable bionic fish; is the resistance received by the highly maneuverable bionic fish; is the force generated by the left pectoral fin of the highly maneuverable bionic fish; is the force generated by the right pectoral fin of the highly maneuverable bionic fish; is the inertia matrix, the torque generated by the left pectoral fin of the highly maneuverable bionic fish; is the torque generated by the left pectoral fin of the highly maneuverable bionic fish; is the torque generated by the resistance; is the torque generated by the buoyancy.

[0028] Among them, it should be noted that the zero buoyancy state designed in this embodiment means that the gravity is equal to the buoyancy, and it can be deduced that:

[0029] In the formula, is the density of the liquid; is the acceleration due to gravity; is the displacement volume of the high - mobility bionic robotic fish prototype; is the center - of - gravity offset of the high - mobility bionic robotic fish prototype.

[0030] Among them, the expressions for the resistance and the moment generated by the resistance of the high - mobility bionic robotic fish are:

[0031] In the formula, is the drag coefficient; is the cross - sectional area of the high - mobility bionic robotic fish prototype; is the drag - moment coefficient.

[0032] S2. Determine the dynamic parameters to be identified; Specifically, based on the Morison equation, obtain the forces and moments generated by the pectoral fins of the high - mobility bionic robotic fish, and determine the dynamic parameters to be identified for the high - mobility bionic robotic fish according to the forces and moments generated by the pectoral fins of the high - mobility bionic robotic fish; the dynamic parameters include: pectoral - fin thrust parameter, pectoral - fin lateral - force parameter, and pectoral - fin lift parameter.

[0033] Exemplarily, in this embodiment, the expressions for the forces and moments generated by the pectoral fins of the high - mobility bionic robotic fish are:

[0034] In the formula, is the pectoral fin of the high - mobility bionic robotic fish generates a force, where, takes when it is the left pectoral fin, takes when it is the right pectoral fin; is the moment generated by the pectoral fin of the high - mobility bionic robotic fish ; is the transformation matrix for converting the force from the pectoral fin to the body of the high - mobility bionic robotic fish; is the pectoral fin arm - length of the force; is the density of the liquid; is the pectoral fin corresponding dynamic parameter; is the pectoral fin normal velocity at the center.

[0035] That is, the expressions for the forces and moments generated by the left pectoral fin of the high - mobility bionic robotic fish are:

[0036] In the formula, is the force generated by the left pectoral fin; is the torque generated by the left pectoral fin; is the transformation matrix; is the lever arm length of the left pectoral fin; is the normal velocity of the center of the left pectoral fin; is the dynamic parameter corresponding to the left pectoral fin; , where, is the thrust parameter of the left pectoral fin; is the lateral force parameter of the left pectoral fin; is the lift parameter of the left pectoral fin.

[0037] That is, the expressions for the force and torque generated by the right pectoral fin of the highly maneuverable biomimetic robotic fish are:

[0038] where, is the force generated by the right pectoral fin; is the torque generated by the right pectoral fin; is the transformation matrix; is the lever arm length of the right pectoral fin; is the normal velocity of the center of the right pectoral fin; is the dynamic parameter corresponding to the right pectoral fin; , where, is the thrust parameter of the right pectoral fin; is the lateral force parameter of the right pectoral fin; is the lift parameter of the right pectoral fin.

[0039] So far, the dynamic parameters that the highly maneuverable biomimetic robotic fish needs to identify are shown in Table 1.

[0040] Table 1

[0041] S3. Determine the parameters of the dynamic model; Specifically, conduct a high-maneuver pitch experiment on the highly maneuverable biomimetic robotic fish and obtain the angular velocity of the highly maneuverable biomimetic robotic fish during the experiment; based on the angular velocity of the highly maneuverable biomimetic robotic fish, optimize the dynamic parameters using the crow algorithm to obtain the optimal dynamic parameters generated by the pectoral fins; use the optimal dynamic parameters as the parameters of the dynamic model, where the high-maneuver pitch includes: rapid diving and rapid surfacing.

[0042] Exemplarily, in this embodiment, the high-maneuver pitch experiment is a rapid surfacing experiment, that is, conduct a rapid surfacing experiment on the highly maneuverable biomimetic robotic fish in the experimental pool, and obtain the angular velocity of the robotic fish using a motion capture system , and the angular velocity curve is as Figure 3 shown. Take the angular velocity As the input of the crow algorithm, the crow algorithm is used to optimize the dynamic parameters generated by the pectoral fin.

[0043] Exemplarily, the steps for the crow algorithm to optimize the dynamic parameters generated by the pectoral fin are as follows: S1: Parameter initialization.

[0044] Initialize a population composed of multiple crow individuals. In this case, the selected population contains m = 50 crow individuals. Since the parameters to be determined include 6 variables, namely , , , , , , a crow individual represents a possible solution, that is, the position of each crow should be a 6-dimensional vector , corresponding to the 6 parameters to be determined. The initial position of each individual (i.e., the initial value of the dynamic parameters of the pectoral fin) is randomly initialized within a reasonable range. In this case, the initialization range is [0, 10]. At the same time, the maximum number of iterations and the random factor and are initialized.

[0045] S2: Calculate the individual fitness.

[0046] In each iteration of the crow algorithm, according to the dynamic parameters corresponding to the pectoral fin at the current iteration , the theoretical pitch angle output by the model is obtained through the established model; the actual pitch angle is obtained by numerical integration of the angular velocity and used as the input for calculating the fitness function of the crow algorithm. Finally, the fitness can be calculated. The expression for the fitness of each crow individual is:

[0047] In the formula, is the fitness value of the j th crow, j = 1, 2,..., m , m is the number of crow individuals in the population; is the theoretical pitch angle output by the dynamic model under the dynamic parameters corresponding to the pectoral fin at the current iteration; is the actual pitch angle; is the number of samples, represents the number of pitch angle data points used to evaluate the error in the experimental data. In this case n = 200, indicating that 200 experimental data points need to be compared with the theoretical pitch angle output by the model, and the fitness of each data point (i.e., the error between the actual pitch angle of the experimental data and the theoretical pitch angle output by the model) is calculated.

[0048] S3: Update the position of individual crows.

[0049] Individual crows update their positions according to the fitness value based on the following rules:

[0050] where, is the dynamic parameter vector of the pectoral fin of the j th individual crow at the current iteration; is the historical optimal pectoral fin parameter vector, i.e., the one with the smallest fitness calculation result; is one of the individuals with better performance in the population at the current iteration, i.e., the one with a smaller fitness calculation result; and are random factors that control the degree of exploration and exploitation. In this case, and are selected.

[0051] S4: Iterative search.

[0052] Through steps S2 and S3, after 100 rounds of iteration with the maximum number of iterations, the crow algorithm determines the optimal dynamic parameters of the pectoral fin as shown in Table 2.

[0053] Table 2

[0054] It also includes: validating the dynamic model. The validation steps include: inputting the optimal dynamic parameters into the dynamic model, and performing a simulation of the highly maneuverable upward floating of the bionic robotic fish according to the preset pitch angle, and obtaining the theoretical pitch angle output by the model; performing an experiment on the highly maneuverable upward floating of the bionic robotic fish in the pool according to the preset pitch angle, and obtaining the actual pitch angle output by the experiment; when the pitch angle difference between the theoretical pitch angle and the actual pitch angle is less than or equal to the difference threshold, in this embodiment, the difference threshold is 1°, then the dynamic model is qualified.

[0055] Exemplarily, in this embodiment, the optimal dynamic parameters in Table 2 are input into the dynamic model for a simulation of highly maneuverable motion, that is, the optimal dynamic parameters in Table 2 are input into the dynamic model for a simulation of highly maneuverable upward floating with a pitch angle of 60°. At the same time, an experiment on the highly maneuverable upward floating of the robotic fish prototype with a pitch angle of 60° is carried out in the experimental pool. The comparison graph of the experimental results and the simulation results is as shown in Figure 4 As can be seen from Figure 4 , the pitch angle difference between the theoretical pitch angle and the actual pitch angle after stabilization is 1°, that is, the dynamic model is qualified.

[0056] A parameter identification system for the dynamic model of a highly maneuverable bionic fish, comprising: a dynamic model construction module, a dynamic parameter determination module, and a parameter optimization module. The dynamic model construction module is used to design the dynamic model of the highly maneuverable bionic fish based on the Newton-Euler equation; the dynamic parameter determination module is used to obtain the forces and torques generated by the pectoral fins of the highly maneuverable bionic fish based on the Morison equation, and obtain the dynamic parameters to be identified for the highly maneuverable bionic fish according to the forces and torques generated by the pectoral fins of the highly maneuverable bionic fish; the dynamic parameters include: pectoral fin thrust parameters, pectoral fin lateral force parameters, and pectoral fin lift parameters; the parameter optimization module is used to conduct an experiment on the rapid upward floating of the highly maneuverable bionic fish and obtain the angular velocity of the highly maneuverable bionic fish during the experiment; according to the angular velocity of the highly maneuverable bionic fish, and based on the crow algorithm, optimize the dynamic parameters to obtain the optimal dynamic parameters generated by the pectoral fins; and use the optimal dynamic parameters as the parameters of the dynamic model.

[0057] The above are only the preferred embodiments of the present invention and are not intended to limit the present invention. Any modifications, equivalent replacements, improvements, etc. made within the spirit and principle of the present invention shall be included in the protection scope of the present invention.

Claims

1. A high-mobility bionic robotic fish dynamics model, characterized in that: include: The dynamic model of a highly maneuverable bionic robotic fish is designed based on the Newton-Euler equation.

2. A high-mobility bionic robotic fish dynamic model according to claim 1, characterized in that: The dynamic model of the highly maneuverable bionic robotic fish is expressed as: In the formula, It is a high-maneuverability bionic robot fish speed; The quality of a highly maneuverable bionic robot fish; The angular velocity of the highly maneuverable bionic robotic fish; The gravity exerted on the highly maneuverable bionic robot fish; The buoyancy of the highly maneuverable bionic robotic fish; The resistance experienced by the highly maneuverable bionic robotic fish; The force generated by the left pectoral fin of the highly maneuverable bionic robotic fish; The forces generated for the right pectoral fin of the highly maneuverable bionic robotic fish; is the inertia matrix, The torque generated by the left pectoral fin of the highly maneuverable bionic robotic fish; The torque generated by the left pectoral fin of the highly maneuverable bionic robotic fish; is the torque generated by the resistance; is the moment due to buoyancy.

3. A high-mobility bionic robotic fish dynamic model according to claim 2, characterized in that: The steps for obtaining the buoyancy and torque generated by the buoyancy of the highly maneuverable bionic robotic fish are as follows: Among them, the highly maneuverable bionic robot fish is in a zero buoyancy state, that is, gravity is equal to buoyancy; Then we have: In the formula, is the density of the liquid; is the acceleration due to gravity; The displacement volume of the high-mobility bionic robotic fish prototype; This is the center of gravity offset of the highly maneuverable bionic robotic fish prototype.

4. The high-mobility bionic robotic fish dynamic model according to claim 2, characterized in that: The expressions of the resistance and torque generated by the resistance of the highly maneuverable bionic robotic fish are: In the formula, is the drag coefficient; The cross-sectional area of ​​the high-mobility bionic robotic fish prototype; is the resistance torque coefficient.

5. The high-mobility bionic robotic fish dynamic model according to claim 2, characterized in that: The expressions of force and torque generated by the pectoral fins of the highly maneuverable bionic robotic fish are: In the formula, Pectoral fins for highly maneuverable bionic robotic fish The force generated is, Pick When is the left pectoral fin, Pick When is the right pectoral fin; Pectoral fins for highly maneuverable bionic robotic fish The torque generated; To transfer force from the pectoral fin Transformation matrix converted to the main body of the highly maneuverable bionic robotic fish; For pectoral fin The length of the lever arm; is the density of the liquid; For pectoral fin Corresponding dynamic parameters; For pectoral fin Normal velocity at the center.

6. The high-mobility bionic robotic fish dynamic model according to claim 1, characterized in that: Also includes: Verification of the kinetic model. The verification steps include: The optimal dynamic parameters are input into the dynamic model, and the high-maneuverability pitch simulation of the bionic robotic fish is performed according to the preset pitch angle, and the theoretical pitch angle output by the dynamic model is obtained; Conduct a high-maneuverability pitching experiment of a bionic robotic fish in a water pool according to a preset pitching angle, and obtain the actual pitching angle outputted by the experiment; When the pitch angle difference between the theoretical pitch angle and the actual pitch angle is less than the difference threshold, the dynamic model is qualified.

7. A parameter identification method for a high-mobility bionic robotic fish dynamics model, characterized in that: include: The force and torque generated by the pectoral fins of the highly maneuverable bionic robotic fish are obtained based on the Morison equation, and the power parameters that need to be identified by the highly maneuverable bionic robotic fish are determined according to the force and torque generated by the pectoral fins of the highly maneuverable bionic robotic fish; The power parameters include: pectoral fin thrust parameter, pectoral fin lateral force parameter and pectoral fin lift parameter; Conduct high-maneuverability pitch experiments on the high-maneuverability bionic robotic fish and obtain the angular velocity of the high-maneuverability bionic robotic fish during the experiment; According to the angular velocity of the highly maneuverable bionic robotic fish, the power parameters are optimized based on the crow algorithm to obtain the optimal power parameters generated by the pectoral fins; the optimal power parameters are used as the parameters of the dynamic model.

8. The parameter identification method of the high-mobility bionic robotic fish dynamics model according to claim 7 is characterized in that: The fitness function of the crow algorithm is: In the formula, For the j The fitness value of a crow, j=1,2,…, m , m is the number of crows in the population; is the theoretical pitch angle output by the dynamic model under the dynamic parameters corresponding to the pectoral fin at the current iteration number; is the actual pitch angle; is the sample size.

9. The parameter identification method of the high-mobility bionic robotic fish dynamics model according to claim 7, characterized in that: High maneuverability pitch includes: rapid diving and rapid ascent.

10. A parameter identification system for a high-mobility bionic robotic fish dynamics model, characterized in that: include: A power parameter determination module is used to obtain the force and torque generated by the pectoral fins of the highly maneuverable bionic robotic fish based on the Morison equation, and to obtain the power parameters that need to be identified by the highly maneuverable bionic robotic fish according to the force and torque generated by the pectoral fins of the highly maneuverable bionic robotic fish; The power parameters include: pectoral fin thrust parameter, pectoral fin lateral force parameter and pectoral fin lift parameter; The parameter optimization module is used to conduct a rapid floating experiment on the highly maneuverable bionic robot fish and obtain the angular velocity of the highly maneuverable bionic robot fish during the experiment; according to the angular velocity of the highly maneuverable bionic robot fish and based on the crow algorithm, the power parameters are optimized to obtain the optimal power parameters generated by the pectoral fins; and the optimal power parameters are used as the parameters of the dynamic model.

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