A bionic robotic fish control method and system based on fish body wave optimization

Abstract

The present invention provides a bionic robot fish control method and system based on fish body wave optimization, belonging to the field of robot control technology. The method comprises the following steps: obtaining the swing angle and swing angular velocity of the head of the bionic robot fish, as well as the joint angle and joint angular velocity of the tail in real time; generating the expected swing angle of the head of the fish, and the expected angle and expected angular velocity of each joint in the tail according to the preset expected trajectory of the bionic robot fish; obtaining the dynamic parameters of the bionic robot fish in the fluid; establishing an optimal control model, and obtaining the current optimal joint acceleration of the tail of the bionic robot fish as the control amount of the bionic robot fish. The method proposed by the present invention can effectively reduce the swing of the fish head during the swimming of the robot fish, and is more robust to parameter changes. When the parameters of the bionic robot fish change, stable control can still be achieved, and migration application can be achieved by simply modifying the joint parameters.

Description

Technical Field

[0001] The present invention belongs to the technical field of robot control, and in particular relates to a bionic robot fish control method and system based on fish body wave optimization. Background Art

[0002] With the development of integrated circuits, micro-electromechanical technology, and AI algorithms, robot-related technologies have become more mature. Compared with land and air robots, underwater robots are more difficult to control due to the influence of water flow. At present, most underwater robots (cabled / cableless autonomous vehicles) use brushless motor thrusters as actuators, which have low propulsion efficiency and poor concealment. Underwater bionic robot fish imitates the structure and propulsion method of fish, and has many advantages such as high propulsion efficiency, flexible movement, and strong concealment. It is increasingly favored by domestic and foreign research institutions.

[0003] A tail fin-driven bionic robotic fish pectoral fin-assisted driving motion method is proposed in the patent document with publication number CN 118651389 A. By sacrificing part of the thrust of flapping wings backward, the resistance of flapping wings forward is minimized, thereby increasing the average thrust generated by the pectoral fins in one cycle and obtaining a better driving effect. However, this improvement requires the introduction of additional pectoral fins as an aid, and the method does not have generalization capabilities.

[0004] In the patent document with publication number CN 118579243 A, a bionic robot fish with tail self-sensing and a tail swing curve optimization method are proposed. By adjusting the distribution spacing of the robot fish's lamellar joints, the bending posture of the robot fish's tail is optimized to make the robot fish conform to the swimming characteristics of the croaker fish. This invention requires the use of additional flexible sensors and does not model the dynamics of the robot fish. In order to take into account the passive influence of the fish tail on the fish head, the control method has limitations.

[0005] Currently, most robot fish use a CPG controller, which requires setting the coupling matrix between different joints. The parameter adjustment is relatively complex, and when the robot structure changes, the coupling parameters need to be readjusted, which is very unfavorable for the migration application of the controller. Summary of the invention

[0006] In order to solve the problems in the prior art, the present invention proposes a bionic robotic fish control method and system based on fish body wave optimization.

[0007] The technical solution adopted by the present invention is as follows:

[0008] In a first aspect, the present invention discloses a bionic robotic fish control method based on fish body wave optimization, comprising the following steps:

[0009] 1) Obtain the swing angle and swing angular velocity of the bionic robotic fish head in real time, and obtain the joint angle and joint angular velocity of the bionic robotic fish tail in real time;

[0010] 2) Generate the expected swing angle of the head of the bionic robotic fish, and the expected angle and expected angular velocity of each joint in the tail of the bionic robotic fish according to the preset expected trajectory of the bionic robotic fish;

[0011] 3) Based on the swing angle and expected swing angle of the bionic robotic fish head and the joint angular velocity of the bionic robotic fish tail, the dynamic parameters of the bionic robotic fish in the fluid are obtained in combination with model reference adaptive control;

[0012] 4) The dynamic parameters of the bionic robotic fish in the fluid are introduced into the linearized kinematic model of the bionic robotic fish. The real-time result obtained in step 1) is used as the current state input of the kinematic model. The optimal control model is established based on the state of the next moment output by the kinematic model and the expected state obtained in step 2), and the current optimal joint acceleration of the bionic robotic fish's tail is obtained as the control variable of the bionic robotic fish.

[0013] In a second aspect, the present invention discloses a bionic robotic fish control system based on fish body wave optimization, comprising:

[0014] A state estimation module, which is used to obtain the swing angle and swing angular velocity of the bionic robotic fish head in real time, and to obtain the joint angle and joint angular velocity of the bionic robotic fish tail in real time;

[0015] An expected trajectory generation module, which is used to generate an expected swing angle of the head of the bionic robotic fish, and an expected angle and an expected angular velocity of each joint in the tail of the bionic robotic fish according to a preset expected trajectory of the bionic robotic fish;

[0016] An adaptive control module, which is used to obtain the dynamic parameters of the bionic robotic fish in the fluid based on the swing angle and expected swing angle of the bionic robotic fish head and the joint angular velocity of the bionic robotic fish tail in combination with model reference adaptive control;

[0017] The fish body wave optimization module is used to introduce the dynamic parameters of the bionic robotic fish in the fluid into the linearized kinematic model of the bionic robotic fish, and use the real-time results obtained by the state estimation module as the current state input of the kinematic model. The optimal control model is established based on the state of the next moment output by the kinematic model and the expected state obtained by the expected trajectory generation module, and the current optimal joint acceleration of the bionic robotic fish's tail is obtained as the control quantity of the bionic robotic fish.

[0018] Compared with the prior art, the present invention has the following beneficial effects:

[0019] The head stability of the bionic robot fish during swimming has a significant impact on the trajectory tracking and visual detection effects. The traditional controller based on CPG or fish body wave model only considers the swing of the fish tail, but does not model the swing of the fish head. The present invention estimates the dynamic parameters of the bionic robot fish body by using model reference adaptive control to compensate for the movement of the bionic robot fish head, and determines the parameter adaptive update rate based on Lyapunov theory, so that the stability of the controller is theoretically supported.

[0020] The present invention linearizes the bionic robotic fish model, converts the control problem of the bionic robotic fish into a quadratic programming problem, and improves the stability of the bionic robotic fish head during swimming by minimizing the swing angle of the bionic robotic fish head.

[0021] The present invention introduces model reference adaptive control and does not completely rely on the dynamic model of the bionic robotic fish. Even if the dynamic parameters or environmental parameters of the bionic robotic fish change, a better control effect can be achieved.

[0022] The present invention is applicable to all bionic robots with tail fin serial drive modes. When the number of tail fin drive joints changes, the algorithm migration can be achieved by simply modifying the geometric parameters. BRIEF DESCRIPTION OF THE DRAWINGS

[0023] Figure 1 It is the control flow chart of the bionic robot fish;

[0024] Figure 2 This is the architecture diagram of the bionic robot fish control system;

[0025] Figure 3 It is the curve of the change of the rolling angle of the fish head during the swimming of the bionic robot fish;

[0026] Figure 4 It is the curve of the pitch angle change of the fish head during the bionic robot fish swimming;

[0027] Figure 5 It is the curve of the change of the yaw angle of the fish head during the swimming of the bionic robot fish;

[0028] Figure 6 It is the curve of the change of joint 1 angle during the swimming of the bionic robot fish;

[0029] Figure 7 It is the curve of the change of the angle of joint 2 during the swimming of the bionic robot fish;

[0030] Figure 8 It is the curve of changes in the three joint angles of the bionic robot fish during swimming. DETAILED DESCRIPTION

[0031] The present invention is further described and illustrated below in conjunction with specific embodiments. The embodiments are merely exemplary of the present disclosure and do not define the scope of limitation. The technical features of each embodiment of the present invention may be combined accordingly without conflicting with each other.

[0032] The present invention proposes a bionic robotic fish control method based on fish body wave optimization. The method uses model reference adaptive control (MRAC) to estimate the dynamic parameters of the bionic robotic fish in the fluid, and achieves stable control of the bionic robotic fish by minimizing the swing angle of the fish head. The control method is applicable to all bionic underwater robots of tail fin drive type (BCF). When the robotic fish model changes, only the corresponding geometric parameters need to be modified to achieve algorithm migration. Compared with traditional controllers based on CPG controllers or fish body wave models, the optimization-based method can improve the stability of the fish body during swimming and is more robust to parameter changes.

[0033] The bionic robotic fish control method based on fish body wave optimization of the present invention is as follows: Figure 1 As shown, the following steps are included:

[0034] S1: Use the attitude sensor to obtain the swing angle and swing angular velocity of the bionic robotic fish head in real time, and use the joint encoder to obtain the joint angle and joint angular velocity of the bionic robotic fish tail in real time, and then use a low-pass filter to filter out the high-frequency components of the obtained data;

[0035] S2: Use the preset fish body wave model as the reference trajectory of the bionic robot fish tail, and then introduce the central pattern generator (CPG) with a nonlinear self-excited oscillator into the fish body wave model. By setting the parameters of the CPG, the amplitude, frequency and steering of the reference trajectory of the bionic robot fish tail can be adjusted. The expected angle and expected angular velocity of each joint in the bionic robot fish tail are obtained through the inverse kinematic solution;

[0036] S3: Based on the swing angle and expected swing angle of the bionic robot fish head and the joint angular velocity of the bionic robot fish tail, some parameters in the angular acceleration formula of the bionic robot fish head are used as state feedback, and the expected swing angle of the bionic robot fish head is used as the reference state to set the adaptive control rate of the bionic robot fish head swing; the parameters are determined using the Lyapunov stability theory. The adaptive update rate of the parameter Adaptively update to obtain updated parameters, that is, the dynamic parameters of the bionic robotic fish in the fluid; wherein, , Estimation of the coefficient of the swing angle of the bionic robot fish head; To estimate the coefficient of the swing angular velocity of the bionic robot fish head; Estimation of the coefficient of joint angular acceleration of the bionic robot fish tail joint, To estimate the parameters of nonlinear action on the head of bionic robotic fish;

[0037] S4: Introducing the dynamic parameters of the bionic robotic fish in the fluid into the linearized kinematic model of the bionic robotic fish, using the real-time result obtained in step S1 as the current state input of the kinematic model, establishing an optimal control model according to the state of the next moment output by the kinematic model and the expected state obtained in step S2, and obtaining the current optimal joint acceleration of the tail of the bionic robotic fish as the control amount of the bionic robotic fish;

[0038] S5: Integrate the optimal joint acceleration to obtain the joint angle and send it to the lower computer. The lower computer is used to control the execution of the joint control task to achieve control of the bionic robotic fish.

[0039] In a specific embodiment of the present invention, when a brushless reduction motor is used as a lower computer to perform joint control tasks, the desired angle, desired angular velocity, and desired angular acceleration of each joint in the tail of the bionic robotic fish are sent to the lower computer to improve control accuracy.

[0040] The present invention also discloses a bionic robotic fish control system based on fish body wave optimization, such as Figure 2 As shown, including:

[0041] A state estimation module, which is used to obtain the swing angle and swing angular velocity of the bionic robotic fish head in real time, and to obtain the joint angle and joint angular velocity of the bionic robotic fish tail in real time;

[0042] An expected trajectory generation module, which is used to generate an expected swing angle of the head of the bionic robotic fish, and an expected angle and an expected angular velocity of each joint in the tail of the bionic robotic fish according to a preset expected trajectory of the bionic robotic fish;

[0043] An adaptive control module, which is used to obtain the dynamic parameters of the bionic robotic fish in the fluid based on the swing angle and expected swing angle of the bionic robotic fish head and the joint angular velocity of the bionic robotic fish tail in combination with model reference adaptive control;

[0044] The fish body wave optimization module is used to introduce the dynamic parameters of the bionic robotic fish in the fluid into the linearized kinematic model of the bionic robotic fish, and use the real-time results obtained by the state estimation module as the current state input of the kinematic model. The optimal control model is established based on the state of the next moment output by the kinematic model and the expected state obtained by the expected trajectory generation module, and the current optimal joint acceleration of the bionic robotic fish's tail is obtained as the control quantity of the bionic robotic fish.

[0045] In the present invention, the state estimation module is configured as a module for obtaining the swing angle and swing angular velocity of the bionic robotic fish head in real time, and obtaining the joint angle and joint angular velocity of the bionic robotic fish tail in real time; after obtaining the results, a low-pass filter is used to filter out high-frequency noise, and the state of the bionic robotic fish can be fully expressed by the swing angle and swing angular velocity of the bionic robotic fish head, and the joint angle and joint angular velocity of the bionic robotic fish tail. The swing angle and swing angular velocity of the bionic robotic fish head after filtering, and the joint angle and joint angular velocity of the bionic robotic fish tail are used as state feedback of the bionic robotic fish and provided to the adaptive control module and the fish body wave optimization module.

[0046] In the present invention, the expected trajectory generation module is configured to generate the expected swing angle of the bionic robotic fish head, and the expected angle and expected angular velocity of each joint in the bionic robotic fish tail according to the preset expected trajectory of the bionic robotic fish.

[0047] In order to realize the swimming control of the bionic robot fish, the preset fish body wave model is combined with the CPG control model to establish the kinematic model of the bionic robot fish as the reference trajectory of the fish tail swing. The nonlinear oscillator model used in the CPG control model is as follows:

[0048] ;

[0049] in, The angle offset of the tail of the bionic robot fish. is the swing amplitude of the bionic robot fish’s tail, is the swing frequency of the bionic robot fish’s tail, , , , and All are preset parameters. , , They are used to adjust the maximum deflection angle, maximum swing amplitude and time ratio of the bionic robot fish's tail. and As a weight parameter for bias and amplitude; is the phase of the swing position of the tail of the bionic robot fish; is the switching function, when When greater than 0, The output is 1 when When it is equal to 0, The output is 0 when When it is less than 0, The output is -1.

[0050] Substituting the CPG control model (see formula (1)) into the fish body wave model, the expression of the reference trajectory of the tail of the bionic robotic fish can be obtained:

[0051] ;

[0052] The junction of the fish head and the fish tail is taken as the origin, the direction from the fish head to the fish tail along the fish body is the z-axis, and the direction perpendicular to the z-axis and from the left side of the fish to the right side is the h-axis, where: is the swing position of the bionic robotic fish tail at time t when the bionic robotic fish tail is at position z; , , and All are preset parameters; is the angle offset of the tail of the bionic robot fish at time t; is the swing amplitude of the tail of the bionic robot fish at time t; is the phase of the swing position of the tail of the bionic robot fish at time t.

[0053] By changing , , and The four parameters can adjust the offset, amplitude, frequency and time ratio of the motion model of the bionic robot fish respectively, so as to imitate the gait of fish. Finally, the inverse kinematics solution is performed using the iterative method to obtain the expected angle and expected angular velocity of each joint of the bionic robot fish.

[0054] In the present invention, the adaptive control module is configured as a module for obtaining the dynamic parameters of the bionic robotic fish in the fluid based on the swing angle and expected swing angle of the head of the bionic robotic fish and the joint angular velocity of the tail of the bionic robotic fish in combination with the model reference adaptive control. The parameters are updated through the adaptive parameter adjustment rate so that the preset dynamic model of the bionic robotic fish is as close as possible to the real dynamic model of the bionic robotic fish, thereby using the updated parameters to correct the dynamic model of the robotic fish.

[0055] The bionic robot fish model is simplified into a multi-link series structure. The forces acting on the fish head include fluid force and joint constraint force. Under the combined effect of these forces, the dynamic model of the bionic robot fish head can be expressed as:

[0056] ;

[0057] ;

[0058] ;

[0059] in, is the moment of inertia of the bionic robot fish head; is the swing angular acceleration of the bionic robot fish head; is the swing angular velocity of the bionic robot fish head; and The constraint force of the joint in the tail of the bionic robot fish, Control volume for bionic robotic fish; is the length of the head of the bionic robot fish; is the torque acting on the fluid; The main diagonal is The diagonal matrix of ; The main diagonal is The diagonal matrix of ; , and is a parameter related to the fluid force acting on the bionic robotic fish; N is the dimension.

[0060] Among them, the torque of the fluid and the constraint force of the joint are difficult to measure directly, but the swing angular acceleration of the bionic robot fish head is related to the swing angle, swing angular velocity and joint angular acceleration of the bionic robot fish tail. Therefore, the swing angular acceleration of the bionic robot fish head can be expressed as:

[0061] ;

[0062] in, is the swing angular acceleration of the bionic robot fish head; is the swing angle of the head of the bionic robot fish; is the coefficient of the swing angle of the bionic robot fish head; is the swing angular velocity of the bionic robot fish head; is the coefficient of the swing angular velocity of the bionic robot fish head; is the joint angular acceleration of the joint in the tail of the bionic robotic fish; is the coefficient of the joint angular acceleration of the joint in the tail of the bionic robotic fish; is the nonlinear action parameter on the head of the bionic robotic fish; , , , are parameters to be estimated; is represented as the transpose of the parameter sequence to be estimated; is the middle value, .

[0063] Combined with the model reference adaptive control, the adaptive control rate of the fish head swing is set based on the angular acceleration formula of the bionic robot fish head and the expected swing angle of the bionic robot fish head:

[0064] ;

[0065] ;

[0066] in, For parameters An estimated value of For parameters An estimated value of For parameters An estimated value of For parameters An estimated value of is the expected swing angle of the head of the bionic robot fish; The expected swing angle and feedback angle (actual swing angle) of the bionic robot fish head ) error; Error The differential of is a parameter greater than 0; is the expected swing angular velocity of the bionic robotic fish head; is the expected swing angular velocity and feedback angular velocity (actual swing angular velocity) of the bionic robot fish head ) error; is the proportional gain coefficient; is the middle value, ; is the parameter to be updated, .

[0067] According to the Lyapunov function, The adaptive update rate is:

[0068] ;

[0069] in, For parameters Update speed; is the inverse matrix of the preset positive definite matrix; for The transpose of

[0070] By updating the adaptive parameters, we can get , , , The estimated parameters of , the parameters are the dynamic parameters of the bionic robotic fish in the fluid.

[0071] In the present invention, the fish body wave optimization module is configured as a module for obtaining the control amount of the bionic robotic fish.

[0072] First, the kinematic model of the linearized bionic robotic fish is obtained, and the obtained dynamic parameters of the bionic robotic fish in the fluid are introduced to correct the swing of the bionic robotic fish head. The corrected linearized model of the bionic robotic fish is expressed as:

[0073] ;

[0074] in, is the state of the bionic robot fish at time k; is the state quantity of the bionic robot fish, , is the joint angle of the i-th joint in the tail of the bionic robot fish, is the joint angular velocity of the i-th joint in the tail of the bionic robotic fish, and n is the total number of joints in the tail of the bionic robotic fish; is the control value of the bionic robot fish at time k; is the control value of the bionic robot fish, , is the joint angular acceleration of the i-th joint in the tail of the bionic robotic fish.

[0075] The other parameters are:

[0076] ;

[0077] in, is the state parameter matrix; is the identity matrix with n+1 rows and n+1 columns, is n+1 rows and n+1 columns and the main diagonal is The matrix of Control cycle for bionic robotic fish; is the control parameter matrix; is a zero matrix with n+1 rows and n columns, is n rows and n columns with a main diagonal of Matrix of is the nonlinear parameter compensation matrix, is a zero matrix with n rows and 1 column, is the intermediate variable, .

[0078] The desired angle and angular velocity of each joint in the tail of the bionic robot fish are used as state input, and the swing angle and angular velocity of the head of the bionic robot fish after filtering, as well as the joint angle and angular velocity of the tail of the bionic robot fish are used as state feedback. The above problem is constructed as a minimization QP problem, and the cost function is configured to minimize the quadratic functional of the reference state and state feedback and minimize the quadratic functional of the input quantity. The expression of the optimal control model of the bionic robot fish is:

[0079] ;

[0080] in, is the state of the bionic robot fish at time k+1, is the expected state of the bionic robot fish at time k+1, is the L2 norm; Q and R are the weighted matrices of the state and control variables, respectively. The constraints include the limits of joint angles, joint angular velocities, and joint angular accelerations.

[0081] In order to more clearly show the experimental effect of the method proposed in the present invention, the compliant control method proposed in the present invention is compared and analyzed with the existing pure position method.

[0082] In detail, the method proposed by the present invention (i.e. Figures 3 to 8 The optimized fish body wave model in the paper is used to estimate the parameters of the robotic fish using the model reference adaptive controller, and the reference fish body wave trajectory is optimized using the quadratic programming method. Figures 3 to 8 The fish body wave model before optimization in the experiment is to use the fish body wave model to obtain the desired joint angle through kinematic inverse solution, which is directly used for the joint control of the robot fish. The experimental platform uses a three-joint series tail fin swinging bionic robot fish, and the control cycle of the two algorithms is 20ms. The robot fish is controlled to move in a straight line, and the swing of the fish head and the joint angle of the fish tail are analyzed during the experiment. Figures 3 to 8 The numerical comparison of the experimental results of the two algorithms is shown, including the roll angle, pitch angle and yaw angle (swing angle of the fish head) of the fish head, as well as the data of the 1st to 3rd joints of the bionic robot fish. As can be seen from Figures 6, 7 and 8, the method proposed by the present invention reduces the oscillation amplitude of the joints close to the fish head, thereby reducing the interference to the fish head, reducing the swing angle of the fish head, and making the swimming more stable. In addition, the optimized joint movement changes are smoother. Figure 3 , 4 , 5 show that compared with the traditional control algorithm based on the fish body wave model, after optimization, the swing of the robot fish in the three directions of roll, pitch and yaw is significantly reduced. Therefore, the method proposed in the present invention greatly reduces the swing of the fish's head during swimming.

[0083] The above-mentioned embodiments only express several implementation modes of the present invention, and the description is relatively specific and detailed, but it cannot be understood as limiting the scope of the present invention. For those of ordinary skill in the art, several modifications and improvements can be made without departing from the concept of the present invention, which all belong to the protection scope of the present invention.

Claims

1. A bionic robotic fish control method based on fish body wave optimization, characterized in that: The following steps are involved: 1) Obtain the swing angle and swing angular velocity of the bionic robotic fish head in real time, and obtain the joint angle and joint angular velocity of the bionic robotic fish tail in real time; 2) Generate the expected swing angle of the head of the bionic robotic fish, and the expected angle and expected angular velocity of each joint in the tail of the bionic robotic fish according to the preset expected trajectory of the bionic robotic fish; 3) Based on the swing angle and expected swing angle of the bionic robotic fish head and the joint angular velocity of the bionic robotic fish tail, the dynamic parameters of the bionic robotic fish in the fluid are obtained in combination with model reference adaptive control; 4) The dynamic parameters of the bionic robotic fish in the fluid are introduced into the linearized kinematic model of the bionic robotic fish. The real-time result obtained in step 1) is used as the current state input of the kinematic model. The optimal control model is established based on the state of the next moment output by the kinematic model and the expected state obtained in step 2), and the current optimal joint acceleration of the bionic robotic fish's tail is obtained as the control variable of the bionic robotic fish.

2. The bionic robotic fish control method based on fish body wave optimization according to claim 1, characterized in that: The expected angle and expected angular velocity of each joint in the tail of the bionic robotic fish are obtained by establishing a reference trajectory of the tail of the bionic robotic fish; the expression of the reference trajectory of the tail of the bionic robotic fish is: ； in, is the swing position of the bionic robotic fish tail at time t when the bionic robotic fish tail is at position z; , , and All are preset parameters; is the angle offset of the tail of the bionic robot fish at time t; is the swing amplitude of the tail of the bionic robot fish at time t; is the phase of the swing position of the tail of the bionic robot fish at time t.

3. The bionic robotic fish control method based on fish body wave optimization according to claim 1, characterized in that: Step 3) includes: Based on the swing angle of the bionic robot fish head and the joint angular velocity of the bionic robot fish tail, the swing angular acceleration formula of the bionic robot fish head is obtained; combined with the model reference adaptive control, the adaptive control rate of the bionic robot fish head swing is set based on the angular acceleration formula of the bionic robot fish head and the expected swing angle of the bionic robot fish head; then the parameters to be updated are determined based on the Lyapunov function Adaptive update rate, and then treat the updated parameters Adaptively update to obtain updated parameters, that is, the dynamic parameters of the bionic robotic fish in the fluid; wherein, , Estimation of the coefficient of the swing angle of the bionic robot fish head; To estimate the coefficient of the swing angular velocity of the bionic robot fish head; Estimation of the coefficient of joint angular acceleration of the bionic robot fish tail joint, Estimation of the nonlinear action parameters acting on the head of the bionic robotic fish.

4. The bionic robotic fish control method based on fish body wave optimization according to claim 3 is characterized in that: The swing angular acceleration formula of the bionic robotic fish head is: ； in, is the swing angular acceleration of the bionic robot fish head; is the swing angle of the head of the bionic robot fish; is the coefficient of the swing angle of the bionic robot fish head; is the swing angular velocity of the bionic robot fish head; is the coefficient of the swing angular velocity of the bionic robot fish head; is the joint angular acceleration of the joint in the tail of the bionic robotic fish; is the coefficient of the joint angular acceleration of the joint in the tail of the bionic robotic fish; is the nonlinear action parameter on the head of the bionic robotic fish; , , , are parameters to be estimated; is represented as the transpose of the parameter sequence to be estimated.

5. The bionic robotic fish control method based on fish body wave optimization according to claim 4, characterized in that: The formula for the adaptive control rate of the bionic robotic fish head swing is: ； ； in, For parameters An estimated value of For parameters An estimated value of For parameters An estimated value of For parameters An estimated value of is the expected swing angle of the head of the bionic robot fish; is the error between the expected swing angle and the actual swing angle of the bionic robot fish head; is the expected swing angular velocity of the bionic robotic fish head; Error The differential of is a parameter greater than 0; is the expected swing angular velocity of the bionic robotic fish head; is the error between the expected swing angular velocity and the actual swing angular velocity of the bionic robot fish head; is the proportional gain coefficient.

6. The bionic robotic fish control method based on fish body wave optimization according to claim 5, characterized in that: The parameters The formula for the adaptive update rate is: ； in, For parameters Update speed; is the inverse matrix of the preset positive definite matrix; By adaptive parameter update, the updated parameters are obtained , the parameters are the dynamic parameters of the bionic robotic fish in the fluid.

7. The bionic robotic fish control method based on fish body wave optimization according to claim 6, characterized in that: In step 4), the specific formula for introducing the dynamic parameters of the bionic robotic fish in the fluid into the linearized kinematic model of the bionic robotic fish is: ； in, is the state of the bionic robot fish at time k; is the state quantity of the bionic robot fish, , is the joint angle of the i-th joint in the tail of the bionic robot fish, is the joint angular velocity of the i-th joint in the tail of the bionic robotic fish, and n is the total number of joints in the tail of the bionic robotic fish; is the control value of the bionic robot fish at time k; is the control value of the bionic robot fish, , is the joint angular acceleration of the i-th joint in the tail of the bionic robotic fish; is the state parameter matrix, , is the identity matrix with n+1 rows and n+1 columns, is n+1 rows and n+1 columns and the main diagonal is The matrix of Control cycle for bionic robotic fish; is the control parameter matrix, , is a zero matrix with n+1 rows and n columns, is n rows and n columns with a main diagonal of Matrix of is the nonlinear parameter compensation matrix, , is a zero matrix with n rows and 1 column.

8. The bionic robotic fish control method based on fish body wave optimization according to claim 7, characterized in that: In step 4), the formula of the optimal control model is: ； in, is the state of the bionic robot fish at time k+1, is the expected state of the bionic robot fish at time k+1, is the L2 norm; Q is the weighted matrix of the state quantity; R is the weighted matrix of the control quantity.

9. A bionic robotic fish control system based on fish body wave optimization, characterized in that: include: A state estimation module, which is used to obtain the swing angle and swing angular velocity of the bionic robotic fish head in real time, and to obtain the joint angle and joint angular velocity of the bionic robotic fish tail in real time; An expected trajectory generation module, which is used to generate an expected swing angle of the head of the bionic robotic fish, and an expected angle and an expected angular velocity of each joint in the tail of the bionic robotic fish according to a preset expected trajectory of the bionic robotic fish; An adaptive control module, which is used to obtain the dynamic parameters of the bionic robotic fish in the fluid based on the swing angle and expected swing angle of the bionic robotic fish head and the joint angular velocity of the bionic robotic fish tail in combination with model reference adaptive control; The fish body wave optimization module is used to introduce the dynamic parameters of the bionic robotic fish in the fluid into the linearized kinematic model of the bionic robotic fish, and use the real-time results obtained by the state estimation module as the current state input of the kinematic model. The optimal control model is established based on the state of the next moment output by the kinematic model and the expected state obtained by the expected trajectory generation module, and the current optimal joint acceleration of the bionic robotic fish's tail is obtained as the control quantity of the bionic robotic fish.

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