Adaptive Propulsion Control Method for Amphibious Aircraft Based on Intelligent Algorithm

Abstract

The invention relates to the technical field of water-air amphibious aircraft, and in particular to an adaptive propulsion control method for water-air amphibious aircraft based on an intelligent algorithm. The method comprises: obtaining historical energy consumption data and historical propulsion state data during n historical propulsion processes of the water-air amphibious aircraft, and constructing an energy consumption prediction model; monitoring real-time energy consumption data and real-time propulsion state data during the real-time propulsion process of the water-air amphibious aircraft, outputting a curve of the change of the real-time propulsion state data with time nodes and inputting the curve into the energy consumption prediction model, and predicting the energy consumption data of the water-air amphibious aircraft after j time nodes; adjusting the structure of the energy consumption prediction model, performing an inverse operation on the energy consumption prediction model, obtaining a propulsion state correction model, inputting ideal energy consumption data into the propulsion state correction model, and outputting propulsion state correction data under the ideal energy consumption data; and adjusting and controlling the real-time propulsion state data of the water-air amphibious aircraft according to the propulsion state correction data.

Description

Background Art

[0002] The adaptive propulsion control method for amphibious water and air vehicles based on intelligent algorithms is a technology that combines artificial intelligence and control engineering to optimize and enhance the propulsion system performance of amphibious water and air vehicles in different environments. Amphibious water and air vehicles can travel on the water surface and fly in the air, so its propulsion control needs to take into account two completely different operating environments: water and air. Each environment has different fluid mechanics characteristics, resulting in different requirements for aircraft in terms of propulsion, resistance, stability, etc. Traditional propulsion control methods often find it difficult to achieve optimal control effects in complex environments.

[0003] Machine learning algorithms, especially neural networks, can autonomously learn how to adjust the propulsion system's operating parameters according to the current environment based on the aircraft's sensor data (such as speed, position, thrust, drag, etc.). This data-driven approach can adapt to different operating conditions and continuously optimize propulsion efficiency.

[0004] Problems in the prior art: When an amphibious aircraft is flying or sneaking, there are currently few methods to timely adjust the propulsion state based on the energy consumption data of the amphibious aircraft, and it is impossible to obtain the optimal propulsion state while saving energy. Summary of the invention

[0005] The main purpose of the present invention is to provide an adaptive propulsion control method for an amphibious aircraft based on an intelligent algorithm, by acquiring historical energy consumption data and historical propulsion state data during the n-time propulsion process of the amphibious aircraft, and building an energy consumption prediction model based on the historical energy consumption data and historical propulsion state data; monitoring the real-time energy consumption data and real-time propulsion state data during the real-time propulsion process of the amphibious aircraft, outputting the change curve of the real-time propulsion state data with time nodes and inputting it into the energy consumption prediction model, and predicting the energy consumption data of the amphibious aircraft after j time nodes; adjusting the structure of the energy consumption prediction model, inversely calculating the energy consumption prediction model, obtaining a propulsion state correction model, inputting the ideal energy consumption data into the propulsion state correction model, and outputting the propulsion state correction data under the ideal energy consumption data; adjusting and controlling the real-time propulsion state data of the amphibious aircraft according to the propulsion state correction data. The propulsion state is adjusted in time based on the energy consumption data of the amphibious aircraft, and the optimal propulsion state is obtained while saving energy consumption, which effectively solves the above-mentioned problems mentioned in the background technology.

[0006] The technical solution of the present invention is as follows:

[0007] In the first aspect, an adaptive propulsion control method for an amphibious aircraft based on an intelligent algorithm is proposed, and the method comprises the following steps:

[0008] S1. Obtain the historical energy consumption data and historical propulsion state data during the historical n - time propulsion process of the water - air amphibious aircraft, and construct an energy consumption prediction model based on the historical energy consumption data and historical propulsion state data;

[0009] S2. Monitor the real - time energy consumption data and real - time propulsion state data during the real - time propulsion process of the water - air amphibious aircraft, output the change curve of the real - time propulsion state data with respect to time nodes and input it into the energy consumption prediction model to predict the energy consumption data of the water - air amphibious aircraft after j time nodes;

[0010] S3. Adjust the structure of the energy consumption prediction model, perform inverse operations on the energy consumption prediction model to obtain a propulsion state correction model, input the ideal energy consumption data into the propulsion state correction model, and output the propulsion state correction data under the ideal energy consumption data;

[0011] S4. Adjust the real - time propulsion state data for controlling the water - air amphibious aircraft according to the propulsion state correction data.

[0012] A further improvement of the present invention is that the S1 includes the following specific steps:

[0013] S11. Obtain the change curves of historical energy consumption, historical pitch angle change speed, historical propulsion speed, propulsion resistance, and historical total load with respect to time nodes during the historical propulsion process of the water - air amphibious aircraft;

[0014] S12. Construct an energy consumption prediction model, divide the change curves of historical energy consumption, historical pitch angle change speed, historical propulsion speed, propulsion resistance, and historical total load with respect to time nodes during the historical n - time propulsion process of the water - air amphibious aircraft into a training set and a test set according to a ratio of 9:1, use 90% of the training set to train the energy consumption prediction model to obtain a preliminary energy consumption prediction model, use 30% of the test set to test the preliminary energy consumption prediction model, and output the preliminary energy consumption prediction model with the highest prediction accuracy for the change curve of historical energy consumption with respect to time nodes to complete the construction of the energy consumption prediction model.

[0015] A further improvement of the present invention is that the S2 includes the following specific steps:

[0016] S21. Obtain the real - time energy consumption during the real - time propulsion process of the water - air amphibious aircraft , and at the same time obtain the pitch angle change speed , propulsion speed , propulsion resistance and total load during the real - time propulsion process of the water - air amphibious aircraft, where represents the current i - th time node;

[0017] S22. Take the real - time energy consumption , pitch angle change speed 、 Propulsion speed 、 Propulsion resistance and total load Input the energy consumption prediction model to predict the energy consumption after j future time nodes; among them, the output strategy formula of the energy consumption prediction model is:

[0018] ;

[0019] Among them, represents the energy consumption after j future time nodes, represents the energy consumption at the current i-th time node, is the preset pitch angle change speed, is the preset propulsion speed, F is the preset resistance value, m is the preset total load, 、 、 、 are the weight factors of the pitch angle change speed, propulsion speed, propulsion resistance and total load respectively.

[0020] A further improvement of the present invention is that the energy consumption prediction model in S2 is a deep neural network model, and the deep neural network model includes an input layer, a hidden layer, and an output layer, where the number of nodes in the input layer, hidden layer, and output layer are 4, 9, and 1 respectively.

[0021] A further improvement of the present invention is that S3 includes the following specific steps:

[0022] S31. Obtain the ideal energy consumption range during the propulsion of the water-air amphibious aircraft, compare the energy consumption data after j time nodes output by the energy consumption prediction model with the ideal energy consumption range, and extract the value in the ideal energy consumption range that is closest to the predicted energy consumption data after j time nodes as the ideal energy consumption value;

[0023] S32. Adjust the structure of the energy consumption prediction model, adjust the number of nodes in the input layer, hidden layer, and output layer of the energy consumption prediction model to 3, 9, and 2 respectively to obtain a propulsion state correction model, input the ideal energy consumption value, propulsion resistance, and total load into the propulsion state correction model, and output the maximum propulsion speed under the ideal energy consumption, and at the same time output the pitch angle change speed adjustment value.

[0024] A further improvement of the present invention is that S3 further includes:

[0025] S33. Obtain the wind speed, wind direction or water flow speed, water flow direction in the current environment. When the propulsion direction of the water-air amphibious aircraft is the same as the wind direction or water flow direction, adjust the propulsion speed to the maximum propulsion speed, and at the same time adjust the pitch angle change speed according to the pitch angle change speed adjustment value;

[0026] S34. When the propulsion direction of the amphibious aircraft is opposite to the wind direction or water flow direction, compare the maximum propulsion speed below the ideal energy consumption with the wind speed or water flow speed in the current environment; if the output maximum propulsion speed is less than the wind speed or water flow speed in the current environment, send a path adjustment command to the remote control terminal. If the output maximum propulsion speed is greater than the wind speed or water flow speed in the current environment, adjust the propulsion speed to the maximum propulsion speed, and at the same time adjust the pitch angle change speed according to the pitch angle change speed adjustment value.

[0027] In a second aspect, a computer-readable storage medium is proposed, on which a computer program is stored. When the computer program is executed by a processor, the above-mentioned adaptive propulsion control method for an amphibious aircraft based on an intelligent algorithm is implemented.

[0028] In a third aspect, an electronic device is proposed, including a memory for storing instructions; a processor for executing the instructions, so that the device executes the above-mentioned adaptive propulsion control method for an amphibious aircraft based on an intelligent algorithm.

[0029] The technical effects of the present invention are as follows:

[0030] An adaptive propulsion control method for an amphibious aircraft based on an intelligent algorithm is constructed. By obtaining the historical energy consumption data and historical propulsion state data during the historical n propulsion processes of the amphibious aircraft, and constructing an energy consumption prediction model based on the historical energy consumption data and historical propulsion state data; monitoring the real-time energy consumption data and real-time propulsion state data during the real-time propulsion process of the amphibious aircraft, outputting the change curve of the real-time propulsion state data with time nodes and inputting it into the energy consumption prediction model to predict the energy consumption data of the amphibious aircraft after j time nodes; adjusting the structure of the energy consumption prediction model, performing inverse operations on the energy consumption prediction model to obtain a propulsion state correction model, inputting the ideal energy consumption data into the propulsion state correction model, and outputting the propulsion state correction data under the ideal energy consumption data; according to the propulsion state correction data, adjusting and controlling the real-time propulsion state data of the amphibious aircraft, and timely adjusting the propulsion state based on the energy consumption data of the amphibious aircraft, and obtaining the optimal propulsion state while saving energy. BRIEF DESCRIPTION OF THE DRAWINGS

[0031] By reading the detailed description of the non-limiting embodiments with reference to the following drawings, other features, objectives and advantages of the present invention will become more obvious:

[0032] Figure 1 It is a schematic flow chart of the adaptive propulsion control method for an amphibious aircraft based on an intelligent algorithm according to Embodiment 1 of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0033] Embodiment 1

[0034] This embodiment proposes an adaptive propulsion control method for a water-air amphibious aircraft based on an intelligent algorithm. By obtaining the historical energy consumption data and historical propulsion state data during the historical n propulsion processes of the water-air amphibious aircraft, and constructing an energy consumption prediction model based on the historical energy consumption data and historical propulsion state data; monitoring the real-time energy consumption data and real-time propulsion state data during the real-time propulsion process of the water-air amphibious aircraft, outputting the change curve of the real-time propulsion state data with time nodes and inputting it into the energy consumption prediction model to predict the energy consumption data of the water-air amphibious aircraft after j time nodes; adjusting the structure of the energy consumption prediction model, performing an inverse operation on the energy consumption prediction model to obtain a propulsion state correction model, inputting the ideal energy consumption data into the propulsion state correction model, and outputting the propulsion state correction data under the ideal energy consumption data; according to the propulsion state correction data, adjusting and controlling the real-time propulsion state data of the water-air amphibious aircraft, and timely adjusting the propulsion state based on the energy consumption data of the water-air amphibious aircraft, and obtaining the optimal propulsion state while saving energy consumption.

[0035] Specifically, as Figure 1 shown, the adaptive propulsion control method for a water-air amphibious aircraft based on an intelligent algorithm proposed in this embodiment includes the following specific steps:

[0036] S1. Obtain the historical energy consumption data and historical propulsion state data during the historical n propulsion processes of the water-air amphibious aircraft, and construct an energy consumption prediction model based on the historical energy consumption data and historical propulsion state data;

[0037] S2. Monitor the real-time energy consumption data and real-time propulsion state data during the real-time propulsion process of the water-air amphibious aircraft, output the change curve of the real-time propulsion state data with time nodes and input it into the energy consumption prediction model to predict the energy consumption data of the water-air amphibious aircraft after j time nodes;

[0038] S3. Adjust the structure of the energy consumption prediction model, perform an inverse operation on the energy consumption prediction model to obtain a propulsion state correction model, input the ideal energy consumption data into the propulsion state correction model, and output the propulsion state correction data under the ideal energy consumption data;

[0039] S4. According to the propulsion state correction data, adjust and control the real-time propulsion state data of the water-air amphibious aircraft.

[0040] In this embodiment, S1 includes the following specific steps:

[0041] S11. Obtain the change curves of the historical energy consumption, historical pitch angle change speed, historical propulsion speed, propulsion resistance, and historical total load of the water-air amphibious aircraft during the historical propulsion process with time nodes;

[0042] S12. Construct an energy consumption prediction model. Divide the historical energy consumption, historical pitch angle change rate, historical propulsion speed, propulsion resistance, and historical total load during the historical n propulsion processes of the water-air amphibious aircraft over time nodes into a training set and a test set at a ratio of 9:1. Use 90% of the training set to train the energy consumption prediction model to obtain a preliminary energy consumption prediction model. Use 30% of the test set to test the preliminary energy consumption prediction model, and output the preliminary energy consumption prediction model with the highest prediction accuracy for the change curve of historical energy consumption over time nodes, thus completing the construction of the energy consumption prediction model.

[0043] In this embodiment, S2 includes the following specific steps:

[0044] S21. Obtain the real-time energy consumption during the real-time propulsion process of the water-air amphibious aircraft , and at the same time obtain the pitch angle change rate during the real-time propulsion process of the water-air amphibious aircraft , propulsion speed , propulsion resistance and total load , where represents the current i-th time node;

[0045] S22. Input the real-time energy consumption , pitch angle change rate , propulsion speed , propulsion resistance and total load into the energy consumption prediction model to predict the energy consumption after the next j time nodes; where the output strategy formula of the energy consumption prediction model is:

[0046] ;

[0047] where represents the energy consumption after the next j time nodes, represents the energy consumption at the current i-th time node, is the preset pitch angle change rate, is the preset propulsion speed, F is the preset resistance value, m is the preset total load, , , , are the weight factors of the pitch angle change rate, propulsion speed, propulsion resistance, and total load respectively, and the specific values are determined by those skilled in the art through a large number of experiments.

[0048] In this embodiment, the energy consumption prediction model in S2 is a deep neural network model. The deep neural network model includes an input layer, a hidden layer, and an output layer, where the number of nodes in the input layer, hidden layer, and output layer are 4, 9, and 1 respectively.

[0049] In this embodiment, S3 includes the following specific steps:

[0050] S31. Obtain the ideal energy consumption range during the propulsion of the amphibious aircraft, compare the energy consumption data after j time nodes output by the energy consumption prediction model with the ideal energy consumption range, and extract the value closest to the predicted energy consumption data after j time nodes in the ideal energy consumption range as the ideal energy consumption value;

[0051] S32. Adjust the structure of the energy consumption prediction model, adjust the number of nodes in the input layer, hidden layer, and output layer of the energy consumption prediction model to 3, 9, and 2 respectively to obtain the propulsion state correction model. Input the ideal energy consumption value, propulsion resistance, and total load into the propulsion state correction model, output the maximum propulsion speed under the ideal energy consumption, and at the same time output the adjustment value of the pitch angle change speed.

[0052] In this embodiment, the ideal energy consumption range refers to the range of the expected energy consumption level during the propulsion of the amphibious aircraft. This range is comprehensively determined by those skilled in the art according to factors such as the performance of the aircraft, operating environment, and mission requirements. The ideal energy consumption range can be determined by referring to the energy consumption levels of similar aircraft and industry standards or specifications.

[0053] In this embodiment, S3 further includes:

[0054] S33. Obtain the wind speed, wind direction, water flow speed, or water flow direction in the current environment. When the propulsion direction of the amphibious aircraft is the same as the wind direction or water flow direction, adjust the propulsion speed to the maximum propulsion speed, and at the same time adjust the pitch angle change speed according to the pitch angle change speed adjustment value;

[0055] S34. When the propulsion direction of the amphibious aircraft is opposite to the wind direction or water flow direction, compare the maximum propulsion speed under the ideal energy consumption with the wind speed or water flow speed in the current environment; if the output maximum propulsion speed is less than the wind speed or water flow speed in the current environment, send a path adjustment command to the remote control terminal. If the output maximum propulsion speed is greater than the wind speed or water flow speed in the current environment, adjust the propulsion speed to the maximum propulsion speed, and at the same time adjust the pitch angle change speed according to the pitch angle change speed adjustment value.

[0056] Embodiment 2

[0057] This embodiment provides an electronic device, including: a processor and a memory. Among them, the memory stores a computer program that can be called by the processor; the processor executes the above-mentioned adaptive propulsion control method for the amphibious aircraft based on the intelligent algorithm by calling the computer program stored in the memory.

[0058] The electronic device may vary greatly due to different configurations or performances, and can include one or more processors (Central Processing Units, CPUs) and one or more memories. Among them, at least one computer program is stored in the memory, and this computer program is loaded and executed by the processor to implement the adaptive propulsion control method of the water-air amphibious aircraft based on the intelligent algorithm provided by the above method embodiment. The electronic device can also include other components for realizing the functions of the device. For example, the electronic device can also have components such as wired or wireless network interfaces and input / output interfaces for data input and output. This embodiment will not be elaborated here.

[0059] Those skilled in the art of the present technology know that the present invention can be implemented as a system, a method or a computer program product. Therefore, the present disclosure can be specifically implemented in the following forms, that is: it can be completely hardware, can also be completely software (including firmware, resident software, microcode, etc.), and can also be in the form of a combination of hardware and software, which is generally referred to as "circuit", "module" or "system" in this article. In addition, in some embodiments, the present invention can also be implemented in the form of a computer program product in one or more computer-readable media, and the computer-readable media contains computer-readable program code.

[0060] Any combination of one or more computer-readable media can be adopted. The computer-readable media can be computer-readable signal media or computer-readable storage media. The computer-readable storage media can be, for example, but not limited to - an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, device or component, or any combination of the above. More specific examples (non-exhaustive list) of the computer-readable storage media include: an electrical connection having one or more wires, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above. In this document, the computer-readable storage media can be any tangible medium that contains or stores a program, and this program can be used by or in combination with an instruction execution system, device or component.

[0061] The present invention is described with reference to the flowcharts and block diagrams of methods, apparatuses (systems), and computer program products according to embodiments of the present invention. It should be understood that each flow or block in the flowcharts and block diagrams, as well as the combination of flows and blocks in the flowcharts or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to the processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing devices to generate a machine, such that the instructions executed by the processor of the computer or other programmable data processing devices generate means for implementing the functions specified in the Figure 1 one or more of the flows and blocks Figure 1 one or more of the blocks.

[0062] These computer program instructions can also be loaded onto a computer or other programmable data processing devices, such that a series of operation steps are executed on the computer or other programmable devices to generate a computer-implemented process, so that the instructions executed on the computer or other programmable devices provide steps for implementing the functions specified in the Figure 1 one or more of the flows and blocks Figure 1 one or more of the blocks.

[0063] The embodiments of the present invention have been described above in conjunction with the accompanying drawings. However, the present invention is not limited to the above specific embodiments. The above specific embodiments are merely illustrative and not restrictive. Under the inspiration of the present invention, those of ordinary skill in the art can also make many forms without departing from the spirit of the present invention and the scope protected by the claims. All of these fall within the protection scope of the present invention.

Claims

1. An adaptive propulsion control method for water-air amphibious aircraft based on intelligent algorithm, characterized in that: The specific steps include: S1. Obtain historical energy consumption data and historical propulsion state data of the water-air amphibious aircraft during n historical propulsion processes, wherein the historical propulsion state data includes the curves of historical pitch angle change speed, historical propulsion speed, propulsion resistance and historical total load change with time nodes, and construct an energy consumption prediction model based on the historical energy consumption data and historical propulsion state data; S2, monitoring the real-time energy consumption data and real-time propulsion state data of the water-air amphibious aircraft during the real-time propulsion process, outputting the change curve of the real-time propulsion state data with time nodes and inputting it into the energy consumption prediction model, and predicting the energy consumption data of the water-air amphibious aircraft after j time nodes; The S2 comprises the following specific steps: S21. Obtaining the real-time energy consumption of the water-air amphibious aircraft during real-time propulsion , and at the same time obtain the pitch angle change speed of the water-air amphibious aircraft during real-time propulsion , Advance speed , propulsion resistance and total load ,in, Indicates the current i-th time node; S22, real-time energy consumption , Pitch angle change speed , Advance speed , propulsion resistance and total load Input the energy consumption prediction model to predict the energy consumption after j time nodes in the future; the output strategy formula of the energy consumption prediction model is: ； in, represents the energy consumption after j time nodes in the future, represents the energy consumption of the current i-th time node, is the preset pitch angle change speed, is the preset propulsion speed, F is the preset resistance value, m is the preset total load, , , , are the weight factors of pitch angle change rate, propulsion speed, propulsion resistance and total load respectively; S3, adjusting the structure of the energy consumption prediction model, performing inverse operation on the energy consumption prediction model to obtain a propulsion state correction model, inputting the ideal energy consumption data into the propulsion state correction model, and outputting the propulsion state correction data under the ideal energy consumption data; S4. According to the propulsion state correction data, adjust and control the real-time propulsion state data of the water-air amphibious aircraft.

2. The adaptive propulsion control method for water-air amphibious aircraft based on intelligent algorithm according to claim 1 is characterized by: The S1 comprises the following specific steps: S11, obtaining the curves of the change of historical energy consumption, historical pitch angle change speed, historical propulsion speed, propulsion resistance and historical total load with time nodes in the historical propulsion process of the water-air amphibious aircraft; S12. Construct an energy consumption prediction model, divide the historical energy consumption, historical pitch angle change speed, historical propulsion speed, propulsion resistance and historical total load change curves during the n historical propulsion processes of the water-air amphibious aircraft into training set and test set in a ratio of 9:1, use 90% of the training set to train the energy consumption prediction model to obtain a preliminary energy consumption prediction model, use 30% of the test set to test the preliminary energy consumption prediction model, output the preliminary energy consumption prediction model that satisfies the highest prediction accuracy of the historical energy consumption change curves with time nodes, and complete the construction of the energy consumption prediction model.

3. The adaptive propulsion control method for water-air amphibious aircraft based on intelligent algorithm according to claim 2 is characterized by: The energy consumption prediction model in S2 is a deep neural network model, which includes an input layer, a hidden layer, and an output layer, wherein the number of nodes in the input layer, the hidden layer, and the output layer are 4, 9, and 1, respectively.

4. The adaptive propulsion control method for water-air amphibious aircraft based on intelligent algorithm according to claim 3 is characterized by: The S3 includes the following specific steps: S31, obtaining an ideal energy consumption range during the propulsion process of the water-air amphibious aircraft, comparing the energy consumption data after j time nodes output by the energy consumption prediction model with the ideal energy consumption range, and extracting the value of the energy consumption data after j time nodes closest to the prediction in the ideal energy consumption range as the ideal energy consumption value; S32. Adjust the structure of the energy consumption prediction model, adjust the number of nodes of the input layer, hidden layer and output layer of the energy consumption prediction model to 3, 9 and 2 respectively, obtain the propulsion state correction model, input the ideal energy consumption value, propulsion resistance and total load into the propulsion state correction model, output the maximum propulsion speed under the ideal energy consumption, and output the pitch angle change speed adjustment value at the same time.

5. The adaptive propulsion control method for water-air amphibious aircraft based on intelligent algorithm according to claim 4 is characterized by: The S3 further includes: S33, obtaining the wind speed, wind direction or water flow speed, and water flow direction in the current environment; when the propulsion direction of the water-air amphibious aircraft is the same as the wind direction or the water flow direction, adjusting the propulsion speed to the maximum propulsion speed, and adjusting the pitch angle change speed according to the pitch angle change speed adjustment value; S34. When the propulsion direction of the water-air amphibious aircraft is opposite to the wind direction or the water flow direction, the maximum propulsion speed under the ideal energy consumption is compared with the wind speed or the water flow speed in the current environment; if the output maximum propulsion speed is less than the wind speed or the water flow speed in the current environment, a path adjustment command is sent to the remote control end; if the output maximum propulsion speed is greater than the wind speed or the water flow speed in the current environment, the propulsion speed is adjusted to the maximum propulsion speed, and the pitch angle change speed is adjusted according to the pitch angle change speed adjustment value.

6. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the adaptive propulsion control method for water-air amphibious aircraft based on intelligent algorithms as described in any one of claims 1 to 5 is implemented.

7. An electronic device, characterized in that: It includes a memory for storing instructions; a processor for executing the instructions, so that the device implements the adaptive propulsion control method for water-air amphibious aircraft based on intelligent algorithm as described in any one of claims 1 to 5.

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