Electric power double-body airship autonomous flight optimization control method

Abstract

The invention provides an autonomous flight optimization control method for an electric double-body airship, and relates to the technical field of electric double-body airships, and the method comprises the steps: obtaining pneumatic control parameters of the electric double-body airship based on a wind tunnel test and fluid dynamics simulation; establishing a translational motion equation and a rotational motion equation based on pneumatic control parameters of the electric double-body airship; according to the method, the pneumatic control parameters are adjusted, the dynamic response of the translational motion equation and the rotational motion equation of the electric double-body airship in the time domain is analyzed, optimal control is achieved, and the electric double-body airship can better adapt to different flight environments and task requirements by adjusting and optimizing the pneumatic control parameters.

Description

Technical Field

[0001] The invention proposes an autonomous flight optimization control method for an electric catamaran airship, and relates to the technical field of electric catamaran airships. Background Art

[0002] Electric catamaran airships need to perform a variety of complex tasks, such as accurately positioning and placing electric power materials during transportation, obtaining high-precision data by following a predetermined route and flying stably at a high altitude during inspections of electric power communication optical cables and transmission lines, power transmission professional drone motherships, and electric power communication emergency repair relay platforms. Different tasks have different requirements for flight attitude and trajectory control, which requires optimized control technology to ensure that the airship can flexibly adjust its flight status according to mission requirements.

[0003] The development of high-precision sensors provides strong support for the autonomous flight control of airships. Inertial measurement units (IMUs), global positioning systems (GPS), barometric altimeters, visual sensors, etc. can obtain information such as the attitude, position, and speed of airships in real time, providing accurate data input for flight control systems. The improvement of sensor accuracy and reliability enables airships to perceive their own status and surrounding environment more accurately, thereby achieving more precise control.

[0004] The continuous improvement and development of automatic control theory has provided a theoretical basis for the autonomous flight optimization control of electric catamaran airships. However, there are also technical defects, such as: the imperfection of the aerodynamic model, the aerodynamic interference effect of the catamaran airship is difficult to accurately model, resulting in control parameter errors, the influence of atmospheric turbulence and temperature changes on the aerodynamic characteristics of the airship has not been fully quantified, and the model robustness is insufficient; the real-time and adaptability of the autonomous control algorithm is insufficient, the calculation complexity is high, and the intelligent algorithm (such as deep reinforcement learning) requires a lot of computing resources and is difficult to run in real time on embedded hardware; the adaptability to dynamic environments is poor, and the existing algorithms have a lag in responding to sudden interference (such as strong wind shear), and control delays lead to decreased stability; hardware-software coordination is insufficient: the response speed of the control algorithm and the hardware actuator (such as motors and rudders) does not match, resulting in control command oscillation. When key airship components (such as thrusters) fail, there is a lack of redundant control strategies, which can easily lead to loss of control. Summary of the invention

[0005] In order to solve the above technical problems, the present invention proposes an electric catamaran airship autonomous flight optimization control method, comprising the following steps:

[0006] Step S1, obtaining aerodynamic control parameters of the electric catamaran airship based on wind tunnel tests and fluid dynamics simulations;

[0007] Step S2, establishing a translational motion equation and a rotational motion equation based on the aerodynamic control parameters of the electric catamaran airship; comprising the following steps:

[0008] S21. Calculate the aerodynamic force acting on the electric catamaran based on the lift coefficient, drag coefficient and side force coefficient in the aerodynamic control parameters;

[0009] S22, calculating the aerodynamic moment of the electric catamaran airship based on the pitch moment coefficient, the rolling moment coefficient and the yaw moment coefficient in the aerodynamic control parameters;

[0010] S23, establishing the translational motion equation and the rotational motion equation based on the aerodynamic force and aerodynamic moment acting on the electric catamaran airship;

[0011] Step S3, adjusting the aerodynamic control parameters, analyzing the dynamic response of the electric catamaran translational motion equation and the rotational motion equation in the time domain, obtaining the optimal aerodynamic control parameters, and realizing the optimal control of the electric catamaran autonomous flight; due to the coupled motion of the electric catamaran in the airflow, the natural frequency of the electric catamaran and the damping frequency it receives in the airflow have the following relationship:

[0012] ;

[0013] in, is the rolling damping coefficient, is the damping coefficient of pitch, is the yaw damping coefficient, is the damping frequency of the electric catamaran rolling motion in the airflow, is the damping frequency of the electric catamaran's pitching motion in the airflow, is the damping frequency of the electric catamaran's yaw motion in the airflow.

[0014] Furthermore, in step S21, the lift coefficient in the aerodynamic control parameter is assumed to be C L , the drag coefficient is C D , the lateral force coefficient is C Y , the aerodynamic forces on the electric catamaran include: lift L, drag D, and side force Y;

[0015] ;

[0016] in, is the air density, v is the speed of the electric catamaran, and S is the force-bearing area of ​​the electric catamaran.

[0017] Furthermore, in step S22, the pitch moment coefficient in the aerodynamic control parameter is assumed to be C M , rolling moment coefficient is C B , the yaw moment coefficient is C N ,The aerodynamic moments of the electric catamaran airship include: pitch moment M, rolling moment B, and rolling moment N;

[0018] ;

[0019] in, is the force characteristic length of the electric catamaran airship.

[0020] Furthermore, in the step S23, a translation motion equation is established, and the translation motion equation includes: a longitudinal translation motion equation, a lateral translation motion equation and a vertical translation motion equation;

[0021] The equation of motion for longitudinal translation is:

[0022] ;

[0023] The equation of motion for lateral translation is:

[0024] ;

[0025] The vertical translation equation of motion is:

[0026] ;

[0027] Among them, v1 is the longitudinal velocity, v2 is the lateral velocity, v3 is the vertical velocity, t is the time, g is the acceleration of gravity, L is the lift, D is the drag, Y is the side force, m is the mass of the electric catamaran airship, T is the thrust provided by the power system of the electric catamaran airship, and α is the angle between the thrust and the longitudinal axis of the electric catamaran airship.

[0028] Moreover, in the step S23, a rotational motion equation is established, and the rotational motion equation includes: a rolling motion equation, a pitching motion equation and a yaw motion equation:

[0029] The equation of motion for rolling is:

[0030] ;

[0031] The pitch motion equation is:

[0032] ;

[0033] The yaw motion equation is:

[0034] ;

[0035] Among them, I M is the pitch moment of inertia, I N is the yaw moment of inertia, I B is the rolling moment of inertia, is the yaw angular velocity, is the rolling angular velocity, is the pitch angular velocity.

[0036] Moreover, when the lift coefficient C L , drag coefficient C D , lateral force coefficient C Y When any one of them changes, use represents the instantaneous change in the speed at which changes occur, , then the control system response function y(t) is:

[0037] ;

[0038] in, is the damping ratio; draw the curve of the control system response function y(t), and get the rising and stabilizing time t from the curve r , when the rising stabilization time t r When it is below the threshold, it proves that the translational motion control ability is good.

[0039] 7. The autonomous flight optimization control method for an electric catamaran airship according to claim 1 is characterized in that the airflow drive parameter value is calculated based on the damping frequency of the electric catamaran airship in the airflow, and the calculated airflow drive parameter value includes: the roll drive parameter value f Bd , pitch drive parameter value f Md and the yaw drive parameter value f Nd , calculated by the following formula:

[0040] ;

[0041] The wave number of the airflow is k, and the arc length of the rolling path of the electric catamaran in the rolling direction is U Bd , the arc length of the pitch path in the pitch direction is U Md , the offset path length in the yaw direction is U Nd , time is t, the density of air is , the acceleration of the wave is a(t).

[0042] Moreover, when the pitching moment coefficient C M , rolling moment coefficient C B , Yaw moment coefficient C N When any one of them changes, use represents the instantaneous change of the driving parameter value that has changed, , then the driving fluctuation value is E:

[0043] ;

[0044] When the driving fluctuation value E value is in the target range, it proves that the non-translational motion control ability is good.

[0045] Compared with the prior art, the present invention has the following beneficial technical effects:

[0046] Improve the aerodynamic performance of electric catamarans: The aerodynamic control parameters obtained through wind tunnel tests and fluid dynamics simulations can more accurately reflect the aerodynamic characteristics of the airship in actual flight. This helps to optimize the control of electric catamarans, improve their aerodynamic efficiency, reduce drag, and enhance stability.

[0047] Accurate modeling and simulation: The translational motion equations and rotational motion equations established based on aerodynamic control parameters can more accurately describe the motion behavior of the electric catamaran airship, providing a reliable theoretical basis for subsequent control strategy design and optimization.

[0048] Dynamic response analysis and optimization: By adjusting the aerodynamic control parameters and analyzing the dynamic response of the electric catamaran in the time domain, the optimal control strategy can be found. This optimization process can significantly improve the control performance of the electric catamaran, making it stable and efficient under different flight conditions.

[0049] Achieve optimal control: Through dynamic response analysis, the optimal control of the electric catamaran airship can be achieved, that is, to minimize energy consumption or improve flight efficiency while meeting flight performance requirements. This is particularly important for electric catamaran airships, which rely on electricity, and can extend their flight time.

[0050] Enhance the adaptability and reliability of electric catamaran airships: By adjusting and optimizing aerodynamic control parameters, electric catamaran airships can better adapt to different flight environments and mission requirements. This adaptability not only improves the reliability of the airship, but also expands its application range. BRIEF DESCRIPTION OF THE DRAWINGS

[0051] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the drawings required for use in the description of the embodiments will be briefly introduced below. Obviously, the drawings in the following description are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without paying any creative labor.

[0052] Figure 1 The present invention is a flow chart of the electric catamaran airship autonomous flight optimization control method.

[0053] Figure 2 The present invention provides a flow chart for establishing the translational motion equation and the rotational motion equation.

[0054] Figure 3 The hardware structure diagram of the electric catamaran airship autonomous flight optimization control system of the present invention.

[0055] Figure 4 It is a module structure diagram of the industrial computer of the present invention. DETAILED DESCRIPTION

[0056] In order to make the purpose, technical solution and advantages of the embodiments of the present application clearer, the technical solution in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.

[0057] In the drawings of the specific embodiments of the present invention, in order to better and more clearly describe the working principles of the various components in the system, the connection relationship of the various parts in the device is shown, which only clearly distinguishes the relative position relationship between the various components, and cannot constitute a limitation on the signal transmission direction, connection sequence and size, dimensions and shape of the components or structures.

[0058] Example 1

[0059] like Figure 1 FIG. 1 is a flow chart of an electric catamaran airship autonomous flight optimization control method of the present invention, and the electric catamaran airship autonomous flight optimization control method comprises the following steps:

[0060] S1. Based on wind tunnel tests and fluid dynamics simulations, the aerodynamic control parameters of the electric catamaran airship are obtained.

[0061] Wind tunnel test: A scaled-down model of the electric catamaran airship is placed in a wind tunnel, and the wind speed, wind direction and airflow conditions are adjusted to simulate the aerodynamic conditions of the electric catamaran airship under different flight conditions.

[0062] Pressure sensors and other measuring equipment are arranged on the surface of the scaled model of the electric catamaran airship to measure the pressure distribution at different positions, and then the aerodynamic forces and moment coefficients such as lift, drag, and side force acting on the airship are calculated.

[0063] Based on fluid dynamics simulation: CFD software is used to perform numerical simulation calculations on the three-dimensional model of the electric catamaran airship. By establishing fluid mechanics equations and boundary conditions, the aerodynamic characteristics of the airship under different flight conditions in the wind tunnel test are simulated, the flow field details are analyzed, and the aerodynamic control parameters under different flight conditions are set in combination with the appearance characteristics, size and flight conditions of the electric catamaran airship.

[0064] Flight test: Install high-precision sensors on the actual electric catamaran, such as six-component force sensors, wind speed sensors, attitude sensors, etc. During the flight, directly measure the aerodynamic force, torque and flight state parameters of the airship. At the same time, record the data under different flight conditions, such as take-off, cruising, landing, etc. Through the analysis and processing of the measured data, the accuracy of the aerodynamic control parameter setting under different flight conditions is improved through correction coefficients and other methods, and accurate aerodynamic control parameters are obtained.

[0065] S2. Establish the translational motion equation and rotational motion equation based on the aerodynamic control parameters of the electric catamaran airship.

[0066] In the dynamic model describing the motion of an electric catamaran, aerodynamic control parameters are the key elements in constructing the dynamic model, providing the necessary physical quantities and constraints for the dynamic model. There is a close relationship between the two.

[0067] In the dynamic model, the motion of the electric catamaran in three-dimensional space is determined by the resultant force and torque, such as Figure 2 As shown, the specific steps of establishing the translational motion equation and the rotational motion equation based on the aerodynamic control parameters of the electric catamaran airship are as follows:

[0068] S21. Calculate the aerodynamic force acting on the electric catamaran based on the lift coefficient, drag coefficient and side force coefficient in the aerodynamic control parameters.

[0069] Assume the lift coefficient in the aerodynamic control parameters is C L , the drag coefficient is C D and the lateral force coefficient is C Y The aerodynamic forces acting on the electric catamaran include: lift L, drag D, and side force Y.

[0070] The specific formula is as follows:

[0071] ;

[0072] in, is the air density, v is the speed of the electric catamaran, S is the force area of ​​the electric catamaran, and lift L, drag D, and side force Y are important components of the electric catamaran's translational motion in the dynamic model.

[0073] S22. Calculate the aerodynamic moment of the electric catamaran based on the pitch moment coefficient, the roll moment coefficient and the yaw moment coefficient in the aerodynamic control parameters.

[0074] Assume the pitch moment coefficient in the aerodynamic control parameters is C M , rolling moment coefficient is C B and the yaw moment coefficient is C NThe aerodynamic moments of the electric catamaran airship include: pitch moment M, roll moment B, and roll moment N.

[0075] The specific formula is as follows:

[0076] ;

[0077] in, is the force characteristic length of the electric catamaran airship. Pitch moment M, rolling moment B, and rolling moment N are important components of the electric catamaran airship's rotational motion in the dynamic model.

[0078] S23. The translational motion equation and the rotational motion equation are established based on the aerodynamic force and aerodynamic torque acting on the electric catamaran airship.

[0079] S231. Establishing a translational motion equation, the translational motion equation includes: a longitudinal translational motion equation, a lateral translational motion equation and a vertical translational motion equation.

[0080] The equation of motion for longitudinal translation is:

[0081]

[0082] Among them, m is the mass of the electric catamaran airship, v1 is the longitudinal velocity, T is the thrust provided by the power system of the electric catamaran airship, α is the angle between the thrust and the longitudinal axis of the electric catamaran airship, and D is the resistance.

[0083] The equation of motion for lateral translation is:

[0084]

[0085] Among them, v2 is the lateral velocity and Y is the side force.

[0086] The vertical translation equation of motion is:

[0087]

[0088] Among them, v3 is the vertical velocity, g is the acceleration due to gravity, and L is the lift.

[0089] S232. Establish a rotational motion equation, which includes a rolling motion equation, a pitching motion equation, and a yaw motion equation.

[0090] The equation of motion for rolling is:

[0091]

[0092] Among them, I B is the rolling moment of inertia, is the rolling angular velocity, and B represents the rolling moment.

[0093] The equation of motion for pitch is:

[0094]

[0095] Among them, I M is the pitch moment of inertia, is the pitch angular velocity, and M represents the pitch moment.

[0096] The yaw motion equation is:

[0097]

[0098] Among them, I N is the yaw moment of inertia, is the yaw angular velocity, and N represents the rolling moment.

[0099] In a preferred embodiment, due to the coupled motion of the electric catamaran airship in the airflow, the natural frequency of the electric catamaran airship and the damping frequency it experiences in the airflow have the following relationship:

[0100] (13);

[0101] in, is the rolling damping coefficient, is the damping coefficient of pitch, is the yaw damping coefficient, is the damping frequency of the electric catamaran rolling motion in the airflow, is the damping frequency of the electric catamaran's pitching motion in the airflow, is the damping frequency of the electric catamaran's yaw motion in the airflow.

[0102] When airflow exhibits wave characteristics, such as some wave airflows in the atmosphere (such as gravity waves and Rossby waves propagating in airflow), they can be described by wave numbers. According to the definition that wave number is the reciprocal of wavelength (or the number of repetitions of fluctuations within a length of 2π), wave number can reflect the spatial variation characteristics of airflow fluctuations. When studying atmospheric wave phenomena, wave number can be used to analyze the spatial scale, propagation and other characteristics of airflow fluctuations.

[0103] The airflow drive parameter values ​​include: the roll drive parameter value f Bd , pitch drive parameter value f Md and the yaw drive parameter value f Nd , calculated by the following formula:

[0104]

[0105] The wave number of the airflow is k, and the arc length of the rolling path of the electric catamaran in the rolling direction is U Bd, the arc length of the pitch path in the pitch direction is U Md , the offset path length in the yaw direction is U Nd , time is t, the density of air is , the acceleration of the wave a(t).

[0106] The airflow drive parameter value will change with the natural damping frequency (pitch natural damping frequency, roll natural damping frequency, yaw natural damping frequency) of the electric catamaran airship and the wave number of the airflow. The change of the airflow drive parameter value will change the dynamic response characteristics of the airship to the control input. For example, a smaller yaw drive parameter value will make the airship respond faster when accelerating or decelerating, while a larger pitch drive parameter value will make the airship more sensitive when changing the pitch attitude.

[0107] S3. Adjust the aerodynamic control parameters, analyze the dynamic response of the translational motion equation and the rotational motion equation of the electric catamaran airship in the time domain, obtain the optimal aerodynamic control parameters, and realize the optimal control of the electric catamaran autonomous flight.

[0108] In the dynamic model, by adjusting the aerodynamic control parameters, the dynamic response of the electric catamaran airship dynamics model in the time domain is studied, and the dynamic performance indicators of the airship's response when subjected to different excitations are analyzed to provide a basis for the design of the flight control system.

[0109] When the lift coefficient C in the aerodynamic control parameters is increased L Or resistance coefficient C D Or lateral force coefficient C Y Observe the change of the airship's response function over time to determine its rapidity and stability. L , drag coefficient C D and the lateral force coefficient C Y Adjustments can be made through the control system of the electric catamaran, such as changing the angle of the wings or certain parts, the flight angle, etc.;

[0110] When the lift coefficient C L , drag coefficient C D , lateral force coefficient C Y When any one of them changes, according to formulas (1), (2), (3) and (7), (8), (9), it can be seen that the longitudinal translation motion equation, the lateral translation motion equation, and the vertical translation motion equation will change. and Will change, here use Represents the speed of change The instantaneous change of , the response function y(t) is:

[0111]

[0112] in, is the damping ratio.

[0113] Draw the response function y(t) curve and get the rising and stabilizing time t from the curve r , that is, the time required for the curve to reach 90% of the stable value from the starting value of the change. When the rising stable time t r When it is below the threshold, it proves that the translational motion control ability is good.

[0114] When the pitching moment coefficient C M , rolling moment coefficient C B and the yaw moment coefficient C N When any one of them changes, according to formulas (4), (5), (6) and (10), (11), (12), it can be seen that the pitch motion equation, roll motion equation, and yaw motion equation will change, then and will change. According to formulas (13) and (14), the roll drive parameter value f Bd , pitch drive parameter value f Md and the yaw drive parameter value f Nd Will change, here use Represents a driver parameter value that has changed ( , ), the driving fluctuation value is E:

[0115] ;

[0116] When the driving fluctuation value E value is in the target range, it proves that the non-translational motion control ability is good.

[0117] Finally, the adjusted data is transmitted to the electric catamaran airship for attitude calibration.

[0118] In a preferred embodiment, the flight control system calculates the control instructions to be applied to each aerodynamic control surface according to the optimal aerodynamic control parameters. The control instructions include the deflection angle of the control surface, the thrust or pull of the engine, etc.

[0119] The generated control instructions are transmitted to the actuators of the electric catamaran airship, such as rudders, elevators, ailerons, propellers, etc., to drive the actuators to move, change the aerodynamic shape and force state of the airship, and thus adjust the attitude of the airship.

[0120] After receiving the command, the actuator responds quickly and accurately to achieve effective control of the airship's attitude. During the attitude calibration process, the attitude changes of the airship are continuously monitored in real time, new attitude sensor data are continuously collected, and the above steps are repeated to form a closed-loop control circuit.

[0121] According to the changes in the actual attitude, the control instructions are adjusted in time to ensure that the airship can converge to the target attitude quickly and stably and remain within the allowable error range.

[0122] Example 2

[0123] like Figure 3 FIG. 1 is a hardware structure diagram of the electric catamaran airship autonomous flight optimization control system of the present invention.

[0124] Design the hardware structure diagram based on the control requirements, determine the hardware system design scheme and complete the physical construction, laying the foundation for the subsequent software design of the motion control method of the electric catamaran airship. The hardware control system is mainly composed of four parts: industrial computer, microcontroller, power supply, and wireless mobile communication device.

[0125] As the core of the hardware structure of the control system, the industrial computer plays a key role in the entire electric catamaran control process. Its powerful computing power can be used to process wind tunnel test data and run fluid dynamics simulation software to obtain the aerodynamic control parameters of the electric catamaran; run the modeling software to establish the dynamic model (translation motion equation and rotation motion equation) of the electric catamaran based on the obtained aerodynamic control parameters, run special analysis software, adjust the dynamic model parameters, calculate and analyze the dynamic response of the electric catamaran in the time domain, and provide a data processing and analysis platform for research.

[0126] The microcontroller is closely connected with the dynamic model. After the dynamic model (translation motion equation and rotation motion equation) is established, the control algorithm and related parameters in the model are transplanted into the microcontroller. During the actual flight, the microcontroller accurately controls the flight state of the electric catamaran airship based on the preset dynamic model logic and the real-time sensor data, so that the actual flight state of the airship is as consistent as possible with the expectations of the theoretical dynamic model.

[0127] The power supply provides power for the entire hardware system. During the operation of wind tunnel tests and fluid dynamics simulation equipment, and the establishment and analysis of dynamic models, the power supply provides power for hardware devices such as industrial computers. When the electric catamaran airship is actually flying, the power supply provides power for the microcontroller, the airship's power system, sensors and other equipment to ensure their normal operation and the actual application of the dynamic model.

[0128] Wireless mobile communication device: Realize remote data transmission. In the process of obtaining aerodynamic control parameters, establishing dynamic models, and conducting dynamic response analysis, the data in the industrial computer can be remotely transmitted to the researcher's terminal device through the wireless mobile communication device, which is convenient for real-time monitoring and control of the process. When the electric catamaran airship is actually flying, the wireless mobile communication device transmits the airship flight status data collected by the microcontroller to the remote server or the researcher's monitoring terminal, and at the same time receives the control instructions sent remotely and transmits them to the microcontroller, realizing remote monitoring and control of the airship. In this process, the application and verification of the dynamic model can also be carried out remotely.

[0129] In the preferred embodiment, the hardware configuration of the industrial computer needs to involve complex computing tasks such as wind tunnel test data processing, fluid dynamics simulation, dynamics modeling and analysis, and requires the processor to have strong computing power. Preferably, high-performance processors such as Intel Core i7 or i9 series, AMD Ryzen 7 or 9 series are selected for larger simulations and analysis; multi-core multi-threading is conducive to processing multiple tasks at the same time and accelerating parallel computing. For example, when performing large-scale fluid dynamics simulations, processors with 16 or more cores and 32 or more threads can significantly improve computing efficiency.

[0130] Memory capacity is critical to ensure that the industrial computer can run simulation software smoothly and process large amounts of data. 32GB is the basic configuration. For complex multitasking and large simulations, 64GB or higher memory can avoid system freezes or data processing interruptions due to insufficient memory. Higher memory frequency can increase data transmission speed, and combined with high-performance processors can improve overall system performance. Preferably, choose DDR4 or DDR5 memory with a frequency of 3200MHz or above.

[0131] like Figure 4 As shown in the figure, the industrial computer specifically includes the following modules:

[0132] Data acquisition module: responsible for collecting data from various sensors in wind tunnel tests, such as the surface pressure data of the electric catamaran measured by the pressure sensor and the airflow velocity data measured by the wind speed sensor, etc., to provide raw data support for subsequent processing.

[0133] Graphics processing module: When running fluid dynamics simulation software, this graphics processing module can accelerate the complex graphics calculation and display during the simulation process, helping researchers to intuitively observe the simulation results, such as the flow of air on the surface of the airship, so as to better understand and analyze aerodynamic characteristics.

[0134] High-speed computing module: uses its powerful computing power to filter, reduce noise, extract features, and process wind tunnel test data. It also executes complex algorithms in fluid dynamics simulation software to solve aerodynamic control parameters such as lift coefficient and drag coefficient.

[0135] Storage module: used to store pneumatic control parameters and various data, algorithms and intermediate results required in the modeling process, providing data support and storage environment for establishing dynamic models.

[0136] Logical operation module: Based on the obtained aerodynamic control parameters, combined with the physical characteristics and motion laws of the electric catamaran airship, logical judgment and mathematical operations are performed, such as analysis and calculation of forces and torques, to provide operational support for establishing accurate dynamic equations.

[0137] Communication module: It can exchange data with other devices or software, for example, obtain the structural parameters, mass distribution and other information of the airship from the outside, or transmit the established dynamic model data to other modules for further processing and verification.

[0138] Data processing module: organizes, analyzes and compiles statistics on the large amount of data generated after adjusting the dynamic model parameters, extracts key information, such as calculating the position, speed, acceleration and other state variables of the electric catamaran airship at different times, and provides a data basis for evaluating dynamic response.

[0139] Simulation and emulation module: Based on the adjusted dynamic model, dynamic simulation is carried out in the time domain to simulate the movement process of the airship under different working conditions, and to intuitively display the dynamic response of the electric catamaran airship, such as attitude changes, trajectory tracking, etc.

[0140] Display and output module: The analysis results are displayed intuitively in the form of graphics, charts, curves, etc., which is convenient for researchers to observe and understand the dynamic response characteristics of the electric catamaran in the time domain. At the same time, the results can be output as reports or data files for easy storage and sharing.

[0141] In one embodiment, a computer device is further provided, including a memory and a processor, wherein a computer program is stored in the memory, and the processor implements the steps in the above method embodiments when executing the computer program.

[0142] In one embodiment, a computer-readable storage medium is provided, storing a computer program, which implements the steps in the above method embodiments when executed by a processor.

[0143] In one embodiment, a computer program product or computer program is provided, the computer program product or computer program includes computer instructions, the computer instructions are stored in a computer-readable storage medium. A processor of a computer device reads the computer instructions from the computer-readable storage medium, and the processor executes the computer instructions, so that the computer device performs the steps in the above-mentioned method embodiments.

[0144] Those skilled in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be completed by instructing the relevant hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to the memory, database or other medium used in the embodiments provided in this application may include at least one of non-volatile and volatile memory. The database involved in the embodiments provided in this application may include at least one of a relational database and a non-relational database. Non-relational databases may include distributed databases based on blockchains, etc., but are not limited thereto. The processors involved in the embodiments provided in this application may be general-purpose processors, central processing units, graphics processors, digital signal processors, programmable logic devices, data processing logic devices based on quantum computing, etc., but are not limited thereto.

[0145] The technical features of the above embodiments may be combined arbitrarily. To make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0146] The above-described embodiments only express several implementation methods of the present application, and the descriptions thereof are relatively specific and detailed, but they cannot be understood as limiting the scope of the present application. It should be pointed out that, for a person of ordinary skill in the art, several variations and improvements can be made without departing from the concept of the present application, and these all belong to the protection scope of the present application. Therefore, the protection scope of the present application shall be subject to the attached claims.

Claims

1. An electric catamaran airship autonomous flight optimization control method, characterized in that: The steps include: Step S1, obtaining aerodynamic control parameters of the electric catamaran airship based on wind tunnel tests and fluid dynamics simulations; Step S2, establishing a translational motion equation and a rotational motion equation based on the aerodynamic control parameters of the electric catamaran airship; comprising the following steps: S21. Calculate the aerodynamic force acting on the electric catamaran based on the lift coefficient, drag coefficient and side force coefficient in the aerodynamic control parameters; S22, calculating the aerodynamic moment of the electric catamaran airship based on the pitch moment coefficient, the rolling moment coefficient and the yaw moment coefficient in the aerodynamic control parameters; S23, establishing the translational motion equation and the rotational motion equation based on the aerodynamic force and aerodynamic moment acting on the electric catamaran airship; Step S3, adjusting the aerodynamic control parameters, analyzing the dynamic response of the electric catamaran translational motion equation and the rotational motion equation in the time domain, obtaining the optimal aerodynamic control parameters, and realizing the optimal control of the electric catamaran autonomous flight; due to the coupled motion of the electric catamaran in the airflow, the natural frequency of the electric catamaran and the damping frequency it receives in the airflow have the following relationship: ; in, is the rolling damping coefficient, is the damping coefficient of pitch, is the yaw damping coefficient, is the damping frequency of the electric catamaran rolling motion in the airflow, is the damping frequency of the electric catamaran's pitching motion in the airflow, is the damping frequency of the electric catamaran's yaw motion in the airflow.

2. The autonomous flight optimization control method for electric catamaran airship according to claim 1, characterized in that: In step S21, the lift coefficient in the aerodynamic control parameter is assumed to be C L , the drag coefficient is C D , the lateral force coefficient is C Y , the aerodynamic forces on the electric catamaran include: lift L, drag D, and side force Y; ; in, is the air density, v is the speed of the electric catamaran, and S is the force-bearing area of ​​the electric catamaran.

3. The autonomous flight optimization control method for electric catamaran airship according to claim 1, characterized in that: In step S22, the pitch moment coefficient in the aerodynamic control parameter is assumed to be C M , rolling moment coefficient is C B , the yaw moment coefficient is C N ,The aerodynamic moments of the electric catamaran airship include: pitch moment M, rolling moment B, and rolling moment N; ; in, is the force characteristic length of the electric catamaran airship.

4. The autonomous flight optimization control method for electric catamaran airship according to claim 1, characterized in that: In the step S23, a translation motion equation is established, wherein the translation motion equation includes: a longitudinal translation motion equation, a lateral translation motion equation and a vertical translation motion equation; The equation of motion for longitudinal translation is: ； The equation of motion for lateral translation is: ； The vertical translation equation of motion is: ； Among them, v1 is the longitudinal velocity, v2 is the lateral velocity, v3 is the vertical velocity, t is the time, g is the acceleration of gravity, L is the lift, D is the drag, Y is the side force, m is the mass of the electric catamaran airship, T is the thrust provided by the power system of the electric catamaran airship, and α is the angle between the thrust and the longitudinal axis of the electric catamaran airship.

5. The autonomous flight optimization control method for electric catamaran airship according to claim 1, characterized in that: In the step S23, a rotational motion equation is established, and the rotational motion equation includes: a rolling motion equation, a pitching motion equation and a yaw motion equation: The equation of motion for rolling is: ； The pitch motion equation is: ； The yaw motion equation is: ； Among them, I M is the pitch moment of inertia, I N is the yaw moment of inertia, I B is the rolling moment of inertia, is the yaw angular velocity, is the rolling angular velocity, is the pitch angular velocity.

6. The autonomous flight optimization control method for electric catamaran airship according to claim 2, characterized in that: When the lift coefficient C L , drag coefficient C D , lateral force coefficient C Y When any one of them changes, use represents the instantaneous change in the speed at which changes occur, , then the control system response function y(t) is: ； in, is the damping ratio; draw the curve of the control system response function y(t), and get the rising and stabilizing time t from the curve r , when the rising stabilization time t r When it is below the threshold, it proves that the translational motion control ability is good.

7. The autonomous flight optimization control method for electric catamaran airship according to claim 1, characterized in that: The airflow drive parameter values ​​are calculated based on the damping frequency of the electric catamaran in the airflow. The calculated airflow drive parameter values ​​include: the roll drive parameter value f Bd , pitch drive parameter value f Md and the yaw drive parameter value f Nd , calculated by the following formula: ； The wave number of the airflow is k, and the arc length of the rolling path of the electric catamaran in the rolling direction is U Bd , the arc length of the pitch path in the pitch direction is U Md , the offset path length in the yaw direction is U Nd , time is t, the density of air is , the acceleration of the wave is a(t).

8. The autonomous flight optimization control method for electric catamaran airship according to claim 7, characterized in that: When the pitching moment coefficient C M , rolling moment coefficient C B , Yaw moment coefficient C N When any one of them changes, use represents the instantaneous change of the driving parameter value that has changed, , then the driving fluctuation value is E: ; When the driving fluctuation value E value is in the target range, it proves that the non-translational motion control ability is good.

Images