An autonomous flight optimization control method for electric catamaran airship

Abstract

The present invention proposes an autonomous flight optimization control method for an electric catamaran airship, which relates to the technical field of electric catamaran airships. The method comprises the following steps: obtaining aerodynamic control parameters of the electric catamaran airship based on wind tunnel tests and fluid dynamics simulations; establishing translational motion equations and rotational motion equations based on the aerodynamic control parameters of the electric catamaran airship; adjusting the aerodynamic control parameters, analyzing the dynamic responses of the translational motion equations and rotational motion equations of the electric catamaran airship in the time domain, and achieving optimal control. By adjusting and optimizing the aerodynamic control parameters, the electric catamaran airship can better adapt to different flight environments and mission requirements.

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 are required to perform a variety of complex missions, such as precisely positioning and dropping off power supplies during transportation, inspecting power communication cables and transmission lines, operating as specialized transmission drone motherships, and acting as relay platforms for emergency repairs in power communications. These airships must maintain stable altitude and maintain predetermined routes to acquire high-precision data. Different missions require different flight attitude and trajectory control, necessitating optimized control technology to ensure the airship can flexibly adjust its flight state based on mission requirements.

[0003] The development of high-precision sensors provides strong support for autonomous flight control of airships. Inertial measurement units (IMUs), global positioning systems (GPS), barometric altimeters, and visual sensors can acquire real-time information about the airship's attitude, position, and speed, providing accurate data input for the flight control system. Improved sensor accuracy and reliability enable airships to more precisely perceive their own state and surrounding environment, enabling more precise control.

[0004] The continuous improvement and development of automatic control theory has provided a theoretical foundation for the autonomous flight optimization control of electric catamaran airships. However, technical deficiencies exist. For example, the imperfect aerodynamic model makes it difficult to accurately model the aerodynamic interference effects of catamaran airships, leading to control parameter errors. The impact of atmospheric turbulence and temperature changes on the airship's aerodynamic characteristics has not been fully quantified, resulting in insufficient model robustness. Autonomous control algorithms lack real-time performance and adaptability, and their computational complexity is high. Intelligent algorithms (such as deep reinforcement learning) require extensive computing resources, making them difficult to run in real time on embedded hardware. Existing algorithms have poor adaptability to dynamic environments, with delayed responses to sudden disturbances (such as strong wind shear), resulting in control delays and reduced stability. Hardware-software coordination is insufficient: the response speed of the control algorithm and hardware actuators (such as motors and control surfaces) is mismatched, leading to oscillation of control commands. The lack of redundant control strategies in the event of failure of key airship components (such as propellers) 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 autonomous flight optimization control method for an electric catamaran airship, 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 airship based on the lift coefficient, drag coefficient, and side force coefficient in the aerodynamic control parameters;

[0009] S22. Calculate the aerodynamic torque acting on the electric catamaran airship based on the pitching moment coefficient, the rolling moment coefficient, and the yaw moment coefficient in the aerodynamic control parameters;

[0010] S23. Establish translational motion equations and rotational motion equations based on the aerodynamic forces and aerodynamic moments acting on the electric catamaran airship;

[0011] Step 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 achieve optimal control of the electric catamaran autonomous flight. 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:

[0012]

[0013] Among them, Z B is the rolling damping coefficient, Z M is the damping coefficient of pitch, Z N is the yaw damping coefficient, ω Bd is the damping frequency of the electric catamaran rolling motion in the airflow, ω Md is the damping frequency of the electric catamaran pitching motion in the airflow, ω Nd is the damping frequency of the electric catamaran yaw motion in the airflow; ω N is the yaw angular velocity, ω B is the roll angular velocity, ω M is the pitch angular velocity;

[0014] In step S21, the lift coefficient in the aerodynamic control parameter is set to C L , the drag coefficient is C D , the lateral force coefficient is C Y ,The aerodynamic forces acting on the electric catamaran airship include: lift L, drag D, and side force Y;

[0015]

[0016] Where, ρ is the air density, v is the speed of the electric catamaran airship, and S is the force-bearing area of the electric catamaran airship;

[0017] When the lift coefficient C L , drag coefficient C D , lateral force coefficient C YWhen any one of the parameters changes, Δv is used to represent the instantaneous change of the speed of change, Δv = {Δv1, Δv2, Δv3}, then the control system response function y(t) is:

[0018]

[0019] Where t is time and ε is the damping ratio; draw the curve of the control system response function y(t) and obtain 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;

[0020] 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 using the following formula:

[0021]

[0022] 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 pitch path arc length in the pitch direction is U Md , the offset path length in the yaw direction is U Nd , time is t, density of air is ρ, acceleration of wave is a(t);

[0023] When the pitching moment coefficient C M , rolling moment coefficient C B , yaw moment coefficient C N When any one of them changes, Δf is used to represent the instantaneous change of the driving parameter value that has changed, Δf={Δf Bd , Δf Md , Δf Nd}, then the driving fluctuation value is E:

[0024]

[0025] When the driving fluctuation value E is within the target range, it proves that the non-translational motion control ability is good.

[0026] Furthermore, in step S22, the pitch moment coefficient in the aerodynamic control parameters is set to C M , the 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;

[0027]

[0028] Where l is the characteristic length of the electric catamaran airship, ρ is the air density, v is the speed of the electric catamaran airship, and S is the force-bearing area of the electric catamaran airship.

[0029] Furthermore, 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;

[0030] The longitudinal translation motion equation is:

[0031]

[0032] The equation of motion for lateral translation is:

[0033]

[0034] The vertical translation motion equation is:

[0035]

[0036] Where v1 is the longitudinal velocity, v2 is the lateral velocity, v3 is the vertical velocity, t is the time, g is the acceleration due to 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.

[0037] Furthermore, in step S23, a rotational motion equation is established, which includes a rolling motion equation, a pitching motion equation, and a yaw motion equation:

[0038] The equation of motion for rolling is:

[0039]

[0040] The pitch motion equation is:

[0041]

[0042] The yaw motion equation is:

[0043]

[0044] 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, ω N is the yaw angular velocity, ω B is the roll angular velocity, ω Mis the pitch angular velocity, M is the pitch moment, B is the roll moment, and N is the roll moment.

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

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

[0047] Accurate modeling and simulation: The translational 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 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] Achieving Optimal Control: Dynamic response analysis enables optimal control of electric catamaran airships, minimizing energy consumption or maximizing flight efficiency while still meeting flight performance requirements. This is particularly important for electric catamarans, which rely on electricity, as it can extend their flight time.

[0050] Enhanced 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 following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative work.

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

[0053] Figure 2 The flowchart of establishing the translational motion equation and the rotational motion equation of the present invention.

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

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

[0056] To make the purpose, technical solutions, and advantages of the embodiments of this application more clear, the technical solutions in the embodiments of this application will be clearly and completely described below in conjunction with the drawings in the embodiments of this application. Obviously, the described embodiments are part of the embodiments of this application, not all of the embodiments. Based on the embodiments in this application, all other embodiments obtained by ordinary technicians in this field without making creative efforts 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 does not constitute a limitation on the signal transmission direction, connection sequence and size, dimension and shape of the components or structures.

[0058] Example 1

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

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

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

[0062] Pressure sensors and other measuring equipment are arranged on the surface of the scaled-down 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: Using CFD software, numerical simulations were performed on the three-dimensional model of the electric catamaran airship. By establishing fluid dynamics equations and boundary conditions, the aerodynamic characteristics of the airship under different flight conditions corresponding to wind tunnel tests were simulated. The flow field details were analyzed, and the aerodynamic control parameters were set under different flight conditions based on the electric catamaran's appearance, dimensions, and flight conditions.

[0064] Flight Test: High-precision sensors, such as six-component force sensors, wind speed sensors, and attitude sensors, are installed on an actual electric catamaran airship. During flight, the aerodynamic forces, torques, and flight parameters acting on the airship are directly measured. Data is also recorded under various flight conditions, such as takeoff, cruise, and landing. By analyzing and processing the measured data and applying correction coefficients and other methods, the accuracy of aerodynamic control parameter settings under different flight conditions is improved, resulting in accurate aerodynamic control parameters.

[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 airship, 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 it receives, such as Figure 2 As shown in FIG, the specific steps for 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 airship based on the lift coefficient, drag coefficient, and side force coefficient among the aerodynamic control parameters.

[0069] Assume that 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 airship include: lift L, drag D, and side force Y.

[0070] The specific formula is as follows:

[0071]

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

[0073] S22. Calculate the aerodynamic torque acting on the electric catamaran airship based on the pitching moment coefficient, the rolling moment coefficient, and the yaw moment coefficient in the aerodynamic control parameters.

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

[0075] The specific formula is as follows:

[0076]

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

[0078] S23. Based on the aerodynamic forces and aerodynamic moments acting on the electric catamaran airship, the translational motion equation and the rotational motion equation are established.

[0079] S231. Establish translational motion equations, which include longitudinal translational motion equations, lateral translational motion equations, and vertical translational motion equations.

[0080] The longitudinal translation motion equation is:

[0081]

[0082] Where 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 drag.

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

[0084]

[0085] Where v2 is the lateral velocity and Y is the lateral force.

[0086] The vertical translation motion equation is:

[0087]

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

[0089] S232. Establish the rotational motion equations, which include the rolling motion equation, the pitching motion equation, and the yaw motion equation.

[0090] The equation of motion for rolling is:

[0091]

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

[0093] The pitch motion equation is:

[0094]

[0095] Among them, I M is the pitch moment of inertia, ω M 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, ω N 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]

[0101] Among them, Z B is the rolling damping coefficient, Z M is the damping coefficient of pitch, Z N is the yaw damping coefficient, ω Bd is the damping frequency of the electric catamaran rolling motion in the airflow, ω Md is the damping frequency of the electric catamaran pitching motion in the airflow, ω Nd is the damping frequency of the electric catamaran yaw motion in the airflow.

[0102] When airflow exhibits wave characteristics, such as some fluctuating atmospheric flows (such as gravity waves and Rossby waves propagating in airflow), it can be described using wavenumbers. Since wavenumber is the inverse of wavelength (or the number of repetitions per 2π length), wavenumbers can reflect the spatial variations in airflow fluctuations. When studying atmospheric wave phenomena, wavenumbers 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 using 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 pitch path arc length in the pitch direction is U Md , the offset path length in the yaw direction is U Nd , time is t, density of air is ρ, acceleration of wave is a(t).

[0106] The values of the airflow drive parameters vary with factors such as the electric catamaran's natural damping frequencies (pitch, roll, and yaw), as well as the airflow wave number. These changes in the airflow drive parameter values alter the airship's dynamic response to control inputs. For example, smaller yaw drive parameter values make the airship more responsive to acceleration and deceleration, while larger pitch drive parameter values make the airship more sensitive to pitch attitude changes.

[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 dynamic 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 When the airship's response function changes with time, we can judge the rapidity and stability of its response. 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 components, 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), (7), (8), and (9), the longitudinal translation motion equation, the lateral translation motion equation, and the vertical translation motion equation will change. and will change, where Δv represents the instantaneous change of the speed of change (Δv1, Δv2, Δv3), then the response function y(t) is:

[0111]

[0112] Where ε is the damping ratio.

[0113] Draw the response function y(t) curve and get the rising and settling time t from the curve r , that is, the time required for the curve to reach 90% of the stable value from the start of the change value. 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), (10), (11), and (12), it will cause the pitch motion equation, roll motion equation, and yaw motion equation to 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, where Δf represents a driving parameter value that has changed (Δf Bd , Δf Md , Δf Nd ), the driving fluctuation value is E:

[0115]

[0116] When the driving fluctuation value E is within 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, based on the optimal aerodynamic control parameters, the flight control system calculates the control instructions that need to be applied to each aerodynamic control surface. 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 change the aerodynamic shape and force state of the airship, thereby adjusting 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 airship's attitude changes are continuously monitored in real time, new attitude sensor data is 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 The figure shows the hardware structure of the electric catamaran airship autonomous flight optimization control system of the present invention.

[0124] Based on the control requirements, a hardware structure diagram was designed, and the hardware system design plan was finalized and completed. This laid the foundation for the subsequent software design of the electric catamaran motion control method. The hardware control system consists of four main components: an industrial computer, a microcontroller, a power supply, and a wireless mobile communication device.

[0125] As the core of the control system's hardware structure, 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. Modeling software can be used to establish the dynamic model (translational and rotational equations of motion) of the electric catamaran based on the obtained aerodynamic control parameters. Specialized analysis software can then be used to adjust the dynamic model parameters and calculate and analyze the dynamic response of the electric catamaran in the time domain, providing a data processing and analysis platform for research.

[0126] The microcontroller is closely linked to the dynamics model. After establishing the dynamics model (translational and rotational equations of motion), the control algorithm and related parameters from the model are ported to the microcontroller. During actual flight, the microcontroller precisely controls the flight state of the electric catamaran airship based on the preset dynamics model logic and real-time sensor data, ensuring that the actual flight state of the airship closely matches the expectations of the theoretical dynamics model.

[0127] The power supply powers the entire hardware system. During wind tunnel testing and fluid dynamics simulation, as well as during dynamics model development and analysis, it provides power to hardware devices such as industrial computers. During actual flight, the power supply provides power to the microcontroller, the airship's power system, sensors, and other equipment, ensuring their proper operation and enabling the practical application of the dynamics model.

[0128] Wireless mobile communication device: Enables remote data transmission. During the process of acquiring aerodynamic control parameters, establishing dynamic models, and conducting dynamic response analysis, the wireless mobile communication device can remotely transmit data from the industrial computer to the researcher's terminal device, facilitating real-time monitoring and control of the process. During the actual flight of the electric catamaran airship, the wireless mobile communication device transmits the airship's flight status data, collected by the microcontroller, to a remote server or the researcher's monitoring terminal. It also receives remotely sent control commands and transmits them to the microcontroller, enabling remote monitoring and control of the airship. During this process, the dynamic model can also be applied and verified remotely.

[0129] In a preferred embodiment, the industrial computer hardware configuration requires a processor with powerful computing power for complex computing tasks such as wind tunnel test data processing, fluid dynamics simulation, and dynamic modeling and analysis. Preferably, a high-performance processor such as the Intel Core i7 or i9 series or the AMD Ryzen 7 or 9 series is selected. For larger simulations and analyses, multi-core and multi-threaded processors facilitate simultaneous processing of multiple tasks and accelerate parallel computing. For example, when conducting 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 crucial to ensure that industrial computers can smoothly run simulation software and process large amounts of data. 32GB is a minimum requirement. For complex multitasking and large simulations, 64GB or higher can prevent system lags and data processing interruptions caused by insufficient memory. A higher memory frequency increases data transfer speeds, and when paired with a high-performance processor, it improves overall system performance. Ideally, choose DDR4 or DDR5 memory with a frequency of 3200MHz or higher.

[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 the wind tunnel test, 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 simulation results, such as the flow of airflow over the surface of the airship, so as to better understand and analyze aerodynamic characteristics.

[0134] High-speed computing module: Utilizes its powerful computing power to filter, reduce noise, and extract features from 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 and combined with the physical characteristics and motion laws of the electric catamaran airship, it performs logical judgment and mathematical operations, such as analyzing and calculating 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, to obtain information such as the structural parameters and mass distribution of the airship from the outside, or to 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 in the time domain is carried out 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 and trajectory tracking.

[0140] Display and output module: The analysis results are displayed intuitively in the form of graphics, charts, curves, etc., which makes it easier for researchers to observe and understand the dynamic response characteristics of the electric catamaran airship 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. The memory stores a computer program, 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-mentioned 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 including computer instructions stored in a computer-readable storage medium. A processor of a computer device reads the computer instructions from the computer-readable storage medium and executes the computer instructions, causing the computer device to perform the steps of each of the above-described method embodiments.

[0144] Those skilled in the art will understand that all or part of the processes in the above-mentioned embodiment methods can be implemented by instructing the relevant hardware through a computer program. 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 memory, database or other media 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. The non-relational database may include a distributed database based on blockchain, etc., but is not limited to this. The processor involved in the embodiments provided in this application may be a general-purpose processor, a central processing unit, a graphics processing unit, a digital signal processor, a programmable logic unit, a data processing logic unit based on quantum computing, etc., but is not limited to this.

[0145] The technical features of the above embodiments can 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 merely represent several implementation methods of the present application. While the descriptions are relatively specific and detailed, they should not be construed as limiting the scope of the present application. It should be noted that a person of ordinary skill in the art may make various modifications and improvements without departing from the spirit of the present application, and these modifications and improvements fall within the scope of protection of the present application. Therefore, the scope of protection of the present application shall be determined by the appended claims.

Claims

1. A method for optimizing the autonomous flight control of an electric catamaran airship, 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 airship based on the lift coefficient, drag coefficient, and side force coefficient in the aerodynamic control parameters; S22. Calculate the aerodynamic torque acting on the electric catamaran airship based on the pitching moment coefficient, the rolling moment coefficient, and the yaw moment coefficient in the aerodynamic control parameters; S23. Establish translational motion equations and rotational motion equations based on the aerodynamic forces and aerodynamic moments acting on the electric catamaran airship; Step 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 achieve optimal control of the electric catamaran autonomous flight. 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: in, is the damping coefficient of roll, 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 yaw motion in the airflow; ; When the lift coefficient C L , drag coefficient C D , lateral force coefficient C Y When any one changes, use represents the instantaneous change in the rate at which change occurs, , then the control system response function y(t) is: Where t is time, is the damping ratio; draw the curve of the control system response function y(t), and obtain 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.

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

3. The electric catamaran airship autonomous flight optimization control method according to claim 1, characterized in that: In step S22, the pitch moment coefficient in the aerodynamic control parameters is set to C M , the 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 characteristic length of the electric catamaran airship under load, is the air density, v is the speed of the electric catamaran airship, and S is the force-bearing area of the electric catamaran airship.

4. The electric catamaran airship autonomous flight optimization control method according to claim 1, characterized in that: In 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 longitudinal translation motion equation is: The equation of motion for lateral translation is: The vertical translation motion equation is: Where v1 is the longitudinal velocity, v2 is the lateral velocity, v3 is the vertical velocity, t is the time, g is the acceleration due to 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 a is the angle between the thrust and the longitudinal axis of the electric catamaran airship.

5. The electric catamaran airship autonomous flight optimization control method according to claim 1, characterized in that: In step S23, a rotational motion equation is established, which 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 roll angular velocity, is the pitch angular velocity, M is the pitch moment, B is the roll moment, and N is the roll moment.

6. The electric catamaran airship autonomous flight optimization control method 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 using 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 pitch path arc length 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).

7. The electric catamaran airship autonomous flight optimization control method according to claim 6, characterized in that: When the pitching moment coefficient C M , rolling moment coefficient C B , yaw moment coefficient C N When any one 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 is within the target range, it proves that the non-translational motion control ability is good.

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