Unmanned aerial vehicle path tracking control method based on chaotic encryption and disturbance observation

Abstract

The invention provides an unmanned aerial vehicle path tracking control method based on chaotic encryption and disturbance observation, and belongs to the technical field of unmanned aerial vehicle control, data encryption and interference resistance. Comprising the steps that measurement data of an aircraft is encrypted through a key stream, and the key stream is obtained through Logistic map chaotic nesting encryption, chaotic system switching and random key stream coefficient distribution; transmitting the ciphertext measurement data to a controller of the aircraft for decryption based on the communication interface; generating a control instruction according to the decrypted measurement data; a chaos encryption algorithm and a disturbance observer control strategy are combined, and the dual requirements of the VTOL-FW for measurement data secure transmission and anti-disturbance control in a dynamic flight scene are met.

Description

Technical Field

[0001] This application belongs to the technical fields of UAV control, data encryption, and anti-interference, and specifically relates to a UAV path tracking control method based on chaotic encryption and disturbance observation. Background Art

[0002] Vertical takeoff and landing fixed-wing aircraft (VTOL-FW) have broad application prospects in military reconnaissance, logistics transportation, disaster monitoring, etc. due to their combination of vertical takeoff and landing flexibility and fixed-wing high-speed cruising capabilities. However, when operating in complex dynamic environments (such as low-altitude urban areas, meteorological interference, communication interference), they face the following core challenges: The aircraft relies on high-precision sensors (attitude angle, acceleration, position, etc.) to provide real-time feedback of state information. However, traditional communication protocols (such as encryption algorithms based on AES-256) have problems such as high computational latency (usually > 50 ms) and static key distribution that is easily reverse-cracked, resulting in attackers being able to induce actuator saturation by tampering with or forging measurement data, leading to flight out of control or even crashing.

[0003] During the mode switching phase, the aerodynamic characteristics of the aircraft change drastically, and the coupling effect of external disturbances (crosswind, sensor noise) and actuator physical limits (rudder surface deflection angle, thrust vector adjustment) is significant. Existing control algorithms (such as PID control) are difficult to balance robustness and real-time performance, resulting in an increase in path tracking error or even system instability.

[0004] Most existing technologies design the encryption module and the control module independently, without considering the relevance of the aircraft's dynamic state (such as communication frequency hopping, topology reorganization) to key distribution and control law adjustment, resulting in a disconnect between the security architecture and control performance. Summary of the Invention

[0005] To solve at least one aspect of the technical problems in the background art, this application provides a UAV path tracking control method based on chaotic encryption and disturbance observation.

[0006] The technical solution adopted in this application is as follows: The first aspect of the embodiments of this application provides a UAV path tracking control method based on chaotic encryption and disturbance observation, including: Encrypt the measurement data of the aircraft through a key stream, and the key stream is obtained through Logistic map chaotic nesting encryption, a switched chaotic system, and randomly distributed key stream coefficients; Transmit the encrypted measurement data to the controller of the aircraft through a communication interface for decryption; Generate a control instruction based on the decrypted measurement data.

[0007] According to an embodiment of the present application, the encryption of the measurement data of the aircraft by the key stream is specifically as follows: Input the measurement data into the Logistic Map chaotic system to generate preliminary encrypted data; According to the preset switching strategy, select the Lorenz chaotic system or the Chen chaotic system to generate the key stream, and perform secondary encryption on the preliminary encrypted data in combination with the randomly allocated key stream coefficient to generate the ciphertext measurement data; Generate the key stream coefficient through the seed random number generator, and distribute the key stream coefficient and the chaotic system parameters to the decryption end; In the aircraft mode switching stage, dynamically adjust the switching strategy of the switching chaotic system and the key stream coefficient according to the flight state.

[0008] According to an embodiment of the present application, the transmission of the ciphertext measurement data to the controller of the aircraft through the communication interface for decryption is specifically as follows: Synchronize the switching strategy of the chaotic system and the Logistic Map parameters according to the decryption key; Restore the plaintext measurement data by subtracting the key stream.

[0009] According to an embodiment of the present application, the seed random number generator generates the key stream coefficient based on the real-time state parameters of the aircraft to ensure that the key is bound to the flight phase.

[0010] According to an embodiment of the present application, the switching strategy dynamically adjusts the switching period of the switching chaotic system based on the communication frequency hopping and topological structure reorganization of the aircraft.

[0011] According to an embodiment of the present application, the generation of the control instruction according to the decrypted measurement data is specifically as follows: Estimate the external disturbance and introduce the external disturbance into the control law; Design the anti-saturation state feedback control law of the aircraft controller; Reduce the steady-state error and suppress the disturbance through the proportional term and the integral term.

[0012] According to an embodiment of the present application, the estimation of the external disturbance and the introduction of the external disturbance into the control law are specifically as follows: Construct an extended system dynamic model and regard the disturbance as an unknown input; Design the disturbance observer gain matrix to make the observation error converge to zero; Output the disturbance estimation value and feedback it to the control law.

[0013] According to an embodiment of the present application, the key stream coefficient and the disturbance estimation value share the same seed random number generator; The controller adjusts the sampling period of the disturbance observer according to the dynamic update frequency of the encryption end.

[0014] The second aspect of the embodiments of this application provides a computer-readable storage medium, on which a program is stored, and when the program is executed by a processor, the steps in the method are implemented.

[0015] The third aspect of the embodiments of this application provides an electronic device, including a memory, a processor, and a computer program stored on the memory and executable on the processor. When the processor executes the program, the steps in the method are implemented.

[0016] Due to the adoption of the above technical solutions, the beneficial effects obtained by this application are as follows: This application performs preliminary chaotic encryption on the plaintext measurement data, uses the initial value sensitivity of the Logistic Map to scatter the data features, and significantly increases the cracking difficulty. Through the dynamic switching of the Lorenz / Chen / Rossler chaotic systems (based on a preset strategy) and the random distribution of the key stream coefficients (dynamically generated by a seed random number generator), the private key length is extended and the key space complexity is increased, making it difficult for attackers to crack the key through static analysis or brute force.

[0017] Based on the dynamic update of the key stream coefficients and the chaotic system parameters, this application ensures that the encrypted data can still maintain low-latency transmission (<50 ms) during the aircraft mode switching stage (such as hovering to level flight), avoiding attitude instability caused by encryption delay.

[0018] This application expands the system dynamic model, introduces the estimated values of external disturbances (such as crosswinds, sensor noise) into the control law, and dynamically adjusts the control instructions to reduce the path tracking error. Using the nonlinear characteristics of the hyperbolic tangent function (tanh), an actuator anti-saturation state feedback control law is designed to limit the output range of the control instructions and prevent the actuator from entering the physical limit state due to incorrect measurement data (such as tampered attitude angles). Combining the proportional term (rapid response to errors) and the integral term (eliminating steady-state errors) further improves the control accuracy and suppresses the accumulation of disturbances.

[0019] This application synchronizes the key stream coefficients of the encryption module and the sampling period of the disturbance observer of the control module through a seed random number generator to ensure the dynamic adaptation of the encryption algorithm and the control strategy when the aircraft state changes (such as communication frequency hopping). The full-link closed-loop design from measurement data encryption → ciphertext transmission → decryption → control instruction generation enables the aircraft to resist malicious attacks (such as replay attacks, data forgery) and maintain stable flight performance in complex environments. Description of the Drawings

[0020] The accompanying drawings described herein are used to provide a further understanding of the present application, and constitute a part of the present application. The schematic embodiments of the present application and their descriptions are used to explain the present application, and do not constitute an improper limitation of the present application. In the drawings: Figure 1 It is a schematic flowchart of a method for controlling the path tracking of an unmanned aerial vehicle based on chaotic encryption and disturbance observation provided by an embodiment of the present application; Figure 2 It is a schematic structural diagram of an electronic device provided by an embodiment of the present application.

[0021] Reference numerals: 810, processor; 820, communication interface; 830, memory; 840, communication bus. Detailed implementation manners

[0022] In order to more clearly illustrate the overall concept of the present application, the following will be described in detail by way of examples in conjunction with the accompanying drawings of the specification.

[0023] In the following description, many specific details are set forth in order to fully understand the present application. However, the present application may also be implemented in other ways different from those described herein. Therefore, the protection scope of the present application is not limited by the specific embodiments disclosed below. It should be noted that, without conflict, the embodiments of the present application and the features in each embodiment may be combined with each other.

[0024] In the present application, unless otherwise clearly defined and limited, the first feature being "on" or "under" the second feature may be that the first and second features are in direct contact, or the first and second features are in indirect contact through an intermediate medium. In the description of this specification, the description of reference terms such as "one embodiment", "some embodiments", "example", "specific example", or "some examples" etc. means that the specific features, structures, materials or characteristics described in connection with the embodiment or example are included in at least one embodiment or example of the present application. In this specification, the schematic representations of the above terms do not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described may be combined in any one or more embodiments or examples in a suitable manner.

[0025] Embodiment 1 As Figure 1 shown, an embodiment of the first aspect of the present application provides a method for controlling the path tracking of an unmanned aerial vehicle based on chaotic encryption and disturbance observation, including: S100. Encrypt the measurement data of the aircraft through a key stream, and the key stream is obtained through Logistic map chaotic nesting encryption, switching chaotic system and randomly distributing key stream coefficients.

[0026] As described above, the measurement data of the aircraft (such as attitude angles, speed, acceleration, etc.) is protected through a complex encryption process. First, the plaintext measurement data is input into the Logistic Map chaotic system for preliminary encryption. Due to its high sensitivity to initial conditions, the Logistic Map can effectively disrupt the original data structure, providing a basis for subsequent encryption. Then, according to a preset strategy, either the Lorenz chaotic system or the Chen chaotic system is selected to generate a key stream, and the preliminarily encrypted data is encrypted a second time in combination with a randomly assigned key stream coefficient. This multi-level encryption mechanism not only increases the difficulty of cracking but also improves the security of encryption.

[0027] For example, assume that the aircraft is currently in the level flight phase, and its sensors have collected a series of attitude angle data. This data, as plaintext, first enters the Logistic Map module. Based on specific parameter settings, such as r = 3.99 (close to the chaotic region of the Logistic Map), this data is preliminarily encrypted. Then, depending on the flight state (such as whether a mode switch is being executed), either the Lorenz or Chen chaotic system is dynamically selected for further encryption. If the Lorenz system is chosen, the final key stream for encryption is generated according to the preset parameters σ, ρ, β and the randomly generated key stream coefficient. In this way, even if an attacker obtains some encrypted information, they cannot easily decrypt the original measurement data because they do not know the specific chaotic system parameters and key stream coefficients.

[0028] It should be noted that in a specific implementation scenario, on the basis of the above solution, in addition to the Lorenz and Chen chaotic systems, the Rossler chaotic system or other new chaotic models can also be introduced to enhance the complexity and randomness of the key stream and further improve the security of the encryption algorithm.

[0029] In a specific implementation scenario, on the basis of the above solution, the generation rule of the key stream coefficient can be dynamically adjusted according to the real-time working environment of the aircraft (such as communication frequency hopping, flight state changes, etc.), making the key stream more in line with the requirements of the actual application scenario, thereby enhancing the flexibility and security of the entire encryption system.

[0030] In a specific implementation scenario, on the basis of the above solution, it can also be considered to combine this encryption method with other existing security measures, such as digital signatures, hash functions, etc., to form a multi-level security protection system to ensure the integrity and non-repudiation of the aircraft measurement data during transmission.

[0031] In a specific implementation scenario, based on the above solution, the strength of the encryption algorithm can also be automatically adjusted according to the importance of the flight mission or the threat level faced (such as changing the parameter r value of the Logistic Map or the parameters of the chaotic system) to achieve the effective utilization of resources and the maximization of security.

[0032] S200. Transmit the encrypted measurement data to the controller of the aircraft through the communication interface for decryption.

[0033] As described above, the measurement data of the aircraft first undergoes an encryption process to generate ciphertext. These encrypted measurement data are then securely transmitted to the controller of the aircraft through the communication interface module for decryption. The design of the communication interface ensures the security and real-time nature of data transmission. It not only supports different types of communication protocols (such as wireless networks, Bluetooth, or dedicated short-range communication, etc.), but also can dynamically adjust the communication parameters according to the working state of the aircraft to adapt to different flight environments and mission requirements. Once the encrypted measurement data reaches the controller, the decryption module will reverse-process the ciphertext based on the pre-allocated key stream coefficient and the parameters of the chaotic system to restore the original measurement data for use in subsequent path tracking control algorithms.

[0034] For example, assume that the aircraft is performing a low-altitude patrol mission in the city. During this process, the sensor collects data on the aircraft's attitude angle. These data are encrypted to form ciphertext and transmitted to the main controller of the aircraft through a preset communication interface (such as an encrypted Wi-Fi signal). When the encrypted measurement data arrives at the controller, the decryption module starts to work. First, the decryption module synchronizes the switching strategy of the chaotic system and the Logistic Map parameters according to the received key stream coefficient, and then uses this information to accurately reverse the encryption process to finally obtain the original attitude angle data. In this way, even if there are potential threats in the network environment, attackers cannot easily obtain or tamper with the real measurement data of the aircraft.

[0035] It should be noted that in a specific implementation scenario, based on the above solution, in addition to the basic encrypted transmission, additional security measures can be introduced. For example, a data integrity verification mechanism (such as hash verification) and identity authentication technology (such as digital certificates) can be added at the communication interface level to further improve the security of data transmission.

[0036] In a specific implementation scenario, based on the above solution, a technology can also be developed that can automatically select the best communication method according to the environment where the aircraft is located. For example, in a high-interference area, a communication protocol with strong anti-interference ability is preferentially selected; or it can be intelligently switched to a more effective communication channel according to the current network load situation to ensure the stability and efficiency of data transmission.

[0037] In a specific implementation scenario, based on the above solution, during the processing stage of the decrypted measurement data, it is possible to consider combining information from other sources (such as instructions from a ground station, satellite positioning data, etc.) to enhance the state perception ability and decision-making accuracy of the aircraft through advanced data fusion algorithms.

[0038] In a specific implementation scenario, based on the above solution, a real-time monitoring system can also be established to monitor the quality of the communication link and any abnormalities during the decryption process, and can respond quickly (such as automatically retransmitting lost data packets or adjusting communication parameters) to ensure the reliability of the entire data transmission and decryption process.

[0039] S300. Generate a control command based on the decrypted measurement data.

[0040] As described above, after being encrypted, transmitted, and decrypted, the measurement data of the aircraft is restored to the original state data. These data include but are not limited to key parameters such as attitude angles, speeds, and accelerations. The controller receives and processes these data, and calculates the required control commands through a pre-designed algorithm (such as an anti-saturation path tracking control algorithm combining a disturbance observer and a hyperbolic tangent function). This process first estimates external disturbances (such as crosswinds or sensor noise), and then uses this information to adjust the control law to compensate for the disturbance effects and prevent the actuator from entering the saturation state. The finally generated control commands will be used to adjust the attitude, thrust, etc. of the aircraft to ensure its stable flight along the predetermined path.

[0041] For example, assume that the aircraft is performing a mode switching task from hovering to level flight. During this process, the sensor collects data on the current attitude angles and speeds. These data are encrypted and securely transmitted to the aircraft's controller through the communication interface. After the controller receives the decrypted measurement data, it starts running a disturbance observer to estimate the influence of the crosswind in the current environment. Based on this estimated value and the current state information of the aircraft (such as attitude angles, speeds), the controller uses a PI controller including a proportional term and an integral term to calculate the necessary correction commands. In addition, in order to prevent the actuator from entering the saturation state due to excessive control commands, a hyperbolic tangent function is used to limit the control commands. In this way, even in the case of large external disturbances, the aircraft can smoothly transition to the level flight state without losing control.

[0042] It should be noted that in a specific implementation scenario, based on the above solution, a technology can also be further developed to dynamically adjust control parameters according to the real-time state of the aircraft (such as changes in battery power, payload weight, etc.). For example, when the aircraft approaches its maximum load, the system can automatically reduce the control gain to reduce the workload of the actuator and extend the equipment life.

[0043] In a specific implementation scenario, based on the above solution, a multi-objective optimization algorithm can also be introduced, so that the control instruction can not only ensure that the aircraft flies along the predetermined path, but also simultaneously meet other performance indicators, such as minimizing energy consumption or maximizing flight stability. This method is particularly applicable to mission scenarios that require long-term cruising.

[0044] In a specific implementation scenario, based on the above solution, for the multi-aircraft formation flight mission, a cooperative control mechanism can be considered to be developed, so that each aircraft not only generates control instructions relying on its own measurement data, but also can refer to the information from neighboring aircraft for cooperative decision-making, improving the coordination and robustness of the entire formation.

[0045] In a specific implementation scenario, based on the above solution, by combining historical data and machine learning techniques, the health status of each component of the aircraft can be predicted, and a maintenance warning can be issued in advance. This can be achieved by analyzing the change trend of the control instruction. For example, if an actuator frequently approaches its physical limit, it may mean that inspection or replacement is required.

[0046] In some embodiments of the present application, the encryption of the measurement data of the aircraft by the key stream is specifically as follows: Input the measurement data into the Logistic Map chaotic system to generate preliminary encrypted data; According to the preset switching strategy, select the Lorenz chaotic system or the Chen chaotic system to generate the key stream, and perform secondary encryption on the preliminary encrypted data in combination with the randomly assigned key stream coefficient to generate the ciphertext measurement data; Generate the key stream coefficient through the seed random number generator, and distribute the key stream coefficient and the chaotic system parameters to the decryption end; In the aircraft mode switching stage, dynamically adjust the switching strategy of the switching chaotic system and the key stream coefficient according to the flight state.

[0047] As described above, the measurement data generated by the aircraft (such as attitude angle, speed, etc.) is input into the Logistic Map chaotic system. The Logistic Map is a simple but effective chaotic system, which is characterized by being highly dependent on the change of the initial conditions. By adjusting the parameters in the Logistic Map (such as the r value), a sequence that seems random but is actually determined by the initial conditions can be generated, and this sequence is used to perform preliminary encryption on the original measurement data, thereby disrupting the original data structure and increasing the cracking difficulty.

[0048] Based on the preliminary encryption, the Lorenz chaotic system or Chen chaotic system is selected according to the preset switching strategy to generate the key stream. These two chaotic systems each have unique dynamic characteristics and can generate complex chaotic sequences. Combined with the randomly assigned key stream coefficients, these chaotic sequences are used to further encrypt the preliminarily encrypted data to form the final ciphertext measurement data. This multi-level encryption mechanism not only increases the encryption intensity but also improves the security of the system.

[0049] To ensure that the decryption end can accurately recover the original data, the key stream coefficients and chaotic system parameters need to be securely distributed to the decryption end. Here, a seed random number generator is used to generate the key stream coefficients and they are sent together with the chaotic system parameters. This method can not only extend the private key length but also increase the complexity of the key space, thereby improving the security of the entire encryption system. At the same time, by dynamically updating the key stream coefficients, it can adapt to different flight state changes and ensure that the key is bound to the flight phase.

[0050] During the flight mode switching stage of the aircraft (such as from hovering to level flight or from level flight to hovering), the state of the aircraft will change significantly. To adapt to this change and maintain the effectiveness of encryption, the system will dynamically adjust the switching strategy of the switching chaotic system and the key stream coefficients according to the current flight state. This means that different combinations of chaotic systems and different key stream coefficients may be used in different flight phases to cope with various possible security threats. This flexibility enables the encryption scheme to remain efficient and reliable in a high-dynamic environment.

[0051] In some embodiments of the present application, the ciphertext measurement data is transmitted to the controller of the aircraft through the communication interface for decryption, specifically: Synchronize the switching strategy of the chaotic system and the Logistic Map parameters according to the decryption key; Restore the plaintext measurement data by subtracting the key stream.

[0052] As described above, at the controller end of the aircraft, in order to correctly decrypt the received ciphertext measurement data, first, according to the pre-agreed decryption key information, the switching strategy of the chaotic system used in the encryption process and the initial parameters of the Logistic Map need to be restored. Specifically, the controller will parse the key stream coefficients and chaotic system parameters distributed from the encryption end and reconstruct the Lorenz or Chen chaotic system structure used to generate the key stream accordingly, and at the same time set the initial conditions (such as the initial value and r parameter) of the Logistic Map. Only when the encryption end and the decryption end are completely synchronized can the accuracy of the subsequent decryption process be ensured.

[0053] Once the switching strategy of the chaotic system and the Logistic Map parameters are synchronized, the controller will regenerate the corresponding key stream sequence according to the same process as the encryption end. This key stream sequence is then used to perform reverse operations on the transmitted ciphertext measurement data. Specifically, by subtracting this key stream from the ciphertext data, the original plaintext measurement data is gradually restored. This process is the inverse of the encryption process and requires the decryption end to have a time synchronization mechanism and parameter consistency guarantee consistent with the encryption end to avoid decryption failure due to minor deviations.

[0054] In some embodiments of the present application, the seed random number generator generates a key stream coefficient based on the real-time state parameters of the aircraft to ensure that the key is bound to the flight phase.

[0055] As described above, the aircraft will continuously generate various real-time state parameters during operation, including but not limited to attitude angle, speed, acceleration, thrust vector direction, etc. These state parameters reflect the current dynamic characteristics of the aircraft and its flight environment (such as whether there is crosswind interference). The seed random number generator first needs to obtain these real-time state parameters from the aircraft's sensor system.

[0056] The seed random number generator uses the above-mentioned collected real-time state parameters as inputs and generates a key stream coefficient through a specific algorithm. Here, the specific algorithm can be a pseudo-random number generation algorithm (PRNG), which dynamically adjusts the output random sequence according to the input state parameters. Since the state parameters of the aircraft vary significantly in different flight phases (for example, the attitude angle and speed during hovering are very different from those during level flight), the generated key stream coefficient will also change accordingly, thus achieving a tight binding of the key stream coefficient to the flight phase.

[0057] The generated key stream coefficient is then applied to the key stream generation step in the encryption process. Specifically, based on the preliminarily encrypted data, a key stream for finally encrypting the plaintext measurement data is generated by combining the key stream coefficient and a selected chaotic system (such as the Lorenz or Chen chaotic system). Since the key stream coefficient is dynamically updated with the change of the aircraft state, the encryption scheme has high flexibility and adaptability, and can maintain high security even in different phases of the same flight mission.

[0058] To ensure that the decryption end can correctly restore the original data, the generated key stream coefficient needs to be securely distributed to the decryption end. This is usually accomplished through a pre-established secure communication channel to ensure that the key stream coefficient can be synchronized between the encryption end and the decryption end. In addition, considering that the state parameters of the aircraft may change frequently in different flight phases, the key stream coefficient also needs to be dynamically updated and synchronized to the decryption end in a timely manner to maintain the consistency and reliability of the entire encryption-decryption process.

[0059] In some embodiments of the present application, the switching strategy dynamically adjusts the switching period of the switched chaotic system based on the communication frequency hopping and topological structure reorganization of the aircraft.

[0060] As described above, during flight, the aircraft may experience different communication environments or network conditions, which can cause changes in its communication frequency (i.e., so-called communication frequency hopping). In addition, when the aircraft participates in a multi-aircraft cooperative mission, the topological structure of the entire aircraft group may also be reorganized due to changes in the relative positions of the aircrafts. To adapt to these changes and maintain the security and stability of data transmission, the system needs to monitor the changes of these factors in real time.

[0061] When a communication frequency hopping or topological structure reorganization is detected, the system will evaluate the impact of these changes on the current encryption scheme. For example, an increase in communication frequency may require a higher encryption processing speed to avoid delays; while the reorganization of the topological structure may lead to changes in the security requirements between some nodes. Based on these evaluation results, the system can determine whether it is necessary to adjust the key parameters in the encryption algorithm, such as the switching period of the chaotic system.

[0062] Based on the above evaluation, the system will dynamically adjust the switching strategy of the chaotic system used to generate the key stream. Specifically, this includes selecting when to switch from one chaotic system (such as the Lorenz system) to another chaotic system (such as the Chen system), and how to adjust the switching time interval. In this way, even in a highly dynamic environment, the effectiveness and security of the encryption algorithm can be ensured. For example, when the communication frequency is high, the switching period of the chaotic system can be shortened to update the key stream more frequently, thereby enhancing the ability to resist attacks; while when the topological structure changes, it is possible to reconfigure which aircrafts should use stronger encryption measures according to the new network layout.

[0063] To ensure that the decryption end can correctly interpret the received data, any adjustment to the switching strategy needs to be synchronized to the decryption end in a timely manner. This means that whenever the encryption end makes an adjustment based on the communication frequency hopping or topological structure reorganization, it will send the new switching strategy and the corresponding key stream coefficients to the decryption end through a secure channel. In this way, the decryption end can perform the decryption operation according to the latest parameter settings, ensuring the consistency and reliability of the entire encryption-decryption process.

[0064] In some embodiments of the present application, generating a control instruction according to the decrypted measurement data specifically includes: Estimate the external disturbance and introduce the external disturbance into the control law; Design the anti-saturation state feedback control law of the aircraft controller; Reduce the steady-state error and suppress the disturbance through the proportional term and the integral term.

[0065] As described above, after obtaining the decrypted measurement data, the control system of the aircraft first needs to estimate the possible external disturbances. These disturbances can include environmental factors such as crosswinds and airflow changes, and may also come from sensor noise or other non-ideal conditions. To achieve this, the system employs a disturbance observer that estimates the current external disturbance situation in real time based on the measurement data and the dynamic model of the system. Once the disturbances are accurately estimated, this information is introduced into the control law so that the influence of these disturbances can be taken into account when generating control commands, thereby improving the robustness of the system.

[0066] To prevent the actuator from entering the saturation state (i.e., the actuator output reaches the physical limit) due to excessive control commands, the system designs an anti-saturation state feedback control law. This control law typically combines the hyperbolic tangent function (tanh) to limit the magnitude of the control commands. For example, after calculating the preliminary control commands, they are limited within a reasonable range by applying the hyperbolic tangent function, ensuring that even in extreme cases, the control commands do not exceed the capabilities of the actuator, thus avoiding system instability or out-of-control problems caused by actuator saturation.

[0067] The core part of the control system is a proportional-integral (PI) controller. This controller utilizes the proportional term to quickly respond to the current error and gradually eliminates any remaining steady-state error through the integral term. Specifically, the proportional term acts directly on the current error value to provide an immediate correction signal, enabling the aircraft to quickly respond to the deviation; while the integral term accumulates all past errors to gradually reduce or even completely eliminate long-existing deviations. This combination not only helps to quickly adjust the attitude or speed of the aircraft to track the predetermined path but also effectively suppresses the influence of various disturbances on the system performance, ensuring that the aircraft can operate stably in a complex environment.

[0068] In some embodiments of the present application, the estimation of external disturbances and the introduction of external disturbances into the control law are specifically as follows: Construct an extended system dynamic model with the disturbance as an unknown input; Design a disturbance observer gain matrix to make the observation error converge to zero; Output the disturbance estimation value and feedback it to the control law.

[0069] As described above, first, an extended system dynamic model needs to be established for the aircraft. This model not only includes the dynamic equations of the aircraft itself (such as attitude angles, speeds, etc.), but also treats external disturbances as unknown inputs and adds them to the model. For example, when describing the motion state of the aircraft, there is usually a state equation to represent the speed, position of the aircraft and their rates of change. Now, by introducing additional terms in these equations to represent the effects of external disturbances (such as crosswinds or airflow changes), the model can more accurately reflect the dynamic characteristics under actual flight conditions.

[0070] To estimate these external disturbances from the measurement data, a disturbance observer needs to be designed. The core of this observer is a gain matrix, whose purpose is to make the observation error (i.e., the difference between the true disturbance and the estimated disturbance) converge to zero as quickly as possible. Specifically, by analyzing the extended system dynamic model, appropriate gain values are selected to adjust the behavior of the observer. The ideal gain matrix should be able to track the changes of the disturbance quickly and accurately without affecting the stability of the system. This usually involves some mathematical tools and techniques, such as pole placement or linear matrix inequality (LMI) methods, to optimize the design of the gain matrix.

[0071] When the disturbance observer operates successfully, it will output the estimated values of the external disturbances in real time. These estimated values are then fed back into the control law to correct the original control commands. For example, if a large crosswind effect is detected, the control system can appropriately adjust the attitude angle or thrust vector of the aircraft according to the disturbance estimate, so as to compensate for the deviation caused by the crosswind. In this way, even in the presence of significant external disturbances, the aircraft can still maintain a stable flight path and reduce the risk of performance degradation or loss of control due to uncompensated disturbances.

[0072] In some embodiments of the present application, the key stream coefficient shares the same seed random number generator with the disturbance estimated value; The controller adjusts the sampling period of the disturbance observer according to the dynamic update frequency of the encryption end.

[0073] As described above, to ensure the consistency and synchronization between the encryption module and the control module, the same seed random number generator is used to generate the key parameters required for the key stream coefficient and the disturbance estimated value. This seed random number generator generates a series of pseudo-random numbers based on the real-time state parameters of the aircraft (such as attitude angles, speeds, etc.). These pseudo-random numbers are not only used to generate the key stream coefficient in the encryption process, but also used in some calculation steps of the disturbance observer, such as initialization or adjustment of the gain matrix.

[0074] By using the same seed random number generator, it can be ensured that the key stream coefficients between the encryption end and the decryption end can be dynamically updated and remain synchronized. At the same time, at the control end, the random numbers generated by the same seed random number generator are used as part of the input of the disturbance observer, which helps to improve the accuracy and robustness of disturbance estimation. This design not only simplifies the overall architecture of the system, but also enhances the security of data transmission and the consistency of control decisions.

[0075] The encryption module needs to dynamically update the key stream coefficients according to the state changes of the aircraft to maintain high security. Therefore, there will be a specific dynamic update frequency at the encryption end, which usually depends on the current operating environment of the aircraft and the rate of change it has experienced (such as communication frequency hopping, topology restructuring, etc.). The controller needs to monitor this update frequency in real time and adjust the working parameters of its internal components accordingly.

[0076] After receiving the dynamic update information from the encryption end, the controller will correspondingly adjust the sampling period of the disturbance observer. Specifically, when the update frequency at the encryption end increases (indicating that the aircraft is in a higher dynamic or more complex environment), the controller will also increase the sampling frequency of the disturbance observer to obtain the latest measurement data more frequently and estimate the disturbance. On the contrary, if the update frequency at the encryption end is low, the sampling frequency of the disturbance observer can be appropriately reduced to save computing resources.

[0077] This method of adjusting the sampling period of the disturbance observer based on the update frequency at the encryption end enables the control system to more flexibly respond to different flight conditions. It not only improves the response speed of the system to a rapidly changing environment, but also ensures that resources are not over-consumed under relatively stable conditions. In addition, through this collaborative mechanism, the entire system can find a good balance between security and performance, ensuring that the aircraft can operate stably in both high-dynamic and low-dynamic environments.

[0078] The second aspect embodiment of this application provides an electronic device, including a memory, a processor, and a computer program stored on the memory and executable on the processor. When the processor executes the program, it implements the cigarette case image recognition method in any of the above first aspect embodiments.

[0079] Figure 2 An entity structure diagram of an electronic device is exemplified, as Figure 2 shown, the electronic device may include: a processor 810, a communication interface 820, a memory 830, and a communication bus 840. Among them, the processor 810, the communication interface 820, and the memory 830 communicate with each other through the communication bus 840. The processor 810 can call the logical instructions in the memory 830 to execute the method in any of the above first aspect embodiments, and the method includes: Encrypt the measurement data of the aircraft through a key stream, where the key stream is obtained through Logistic map chaotic nested encryption, a switched chaotic system, and randomly distributing key stream coefficients; Transmit the encrypted measurement data to the controller of the aircraft through a communication interface for decryption; Generate a control instruction according to the decrypted measurement data.

[0080] In addition, when the logical instructions in the above-mentioned memory 830 can be implemented in the form of a software functional unit and sold or used as an independent product, they can be stored in a computer-readable storage medium. Based on such an understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art, or a part of this technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions for causing a computer device (which can be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the methods described in various embodiments of the present invention. The foregoing storage medium includes: various media such as USB flash drives, mobile hard disks, read-only memories, random access memories, magnetic disks, or optical discs that can store program codes.

[0081] On the other hand, the present invention also provides a computer program product, where the computer program product includes a computer program. The computer program can be stored on a non-transitory computer-readable storage medium. When the computer program is executed by a processor, the computer can execute the methods provided by the above-mentioned various methods. The method includes: Encrypt the measurement data of the aircraft through a key stream, where the key stream is obtained through Logistic map chaotic nested encryption, a switched chaotic system, and randomly distributing key stream coefficients; Transmit the encrypted measurement data to the controller of the aircraft through a communication interface for decryption; Generate a control instruction according to the decrypted measurement data.

[0082] On yet another aspect, the present invention also provides a non-transitory computer-readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, it is configured to execute the methods provided by the above-mentioned various methods. The method includes: Encrypt the measurement data of the aircraft through a key stream, where the key stream is obtained through Logistic map chaotic nested encryption, a switched chaotic system, and randomly distributing key stream coefficients; Transmit the encrypted measurement data to the controller of the aircraft through a communication interface for decryption; Generate a control instruction according to the decrypted measurement data.

[0083] Finally, the present invention also provides a non-volatile computer storage medium, on which computer-executable instructions are stored. When the computer program is executed by a processor, it implements the methods provided by the above-mentioned various methods, and the method includes: Encrypt the measurement data of the aircraft through a key stream, and the key stream is obtained through Logistic map chaotic nesting encryption, switching chaotic system and randomly distributing key stream coefficients; Transmit the encrypted measurement data to the controller of the aircraft based on the communication interface for decryption; Generate control instructions according to the decrypted measurement data.

[0084] Embodiment 2 Model of the vertical takeoff and landing fixed-wing aircraft after encryption and decryption: The vertical takeoff and landing fixed-wing aircraft is an innovative aircraft that combines the vertical takeoff and landing capabilities of multi-rotors with the long endurance and high-speed flight characteristics of fixed wings. Its core design realizes vertical takeoff and landing through a multi-rotor or tilting power system, and then switches to the fixed-wing mode for efficient cruising. For example, the VOYAGER UAV uses 16 vertical motors and 4 cruising motors, which can not only take off and land without a runway, but also fly continuously at a speed of 200 km / h for more than 1 hour, and its endurance far exceeds that of traditional multi-rotor UAVs. Such aircraft are widely used in fields such as traffic supervision, oilfield inspection, and large-area mapping, and their payload capacity and wind resistance performance further broaden the application scenarios. The state equation of a classic vertical takeoff and landing fixed-wing aircraft is as follows:

[0085] Among them, is the mass, is the acceleration due to gravity, respectively represent the angular velocities of the three axes, represents the translational velocities of the three axes, and the inertia matrix of the fuselage is:

[0086] Among them, each element in the inertia matrix, such as , represents the moment of inertia in the corresponding direction; : represents the moment of inertia when the object rotates around the x-axis. It measures the ability of the object to resist rotation around the x-axis.

[0087] : represents the moment of inertia when the object rotates around the y-axis. It measures the ability of the object to resist rotation around the y-axis.

[0088] : represents the moment of inertia when the object rotates around the z-axis. It measures the ability of the object to resist rotation around the z-axis.

[0089] Off-diagonal elements (products of inertia): = : Represents the product of inertia between the x and y axes of the object. It reflects the asymmetry of the mass distribution of the object with respect to the x and y axes.

[0090] = : Represents the product of inertia between the x and z axes of the object. It reflects the asymmetry of the mass distribution of the object with respect to the x and z axes.

[0091] = : Represents the product of inertia between the y and z axes of the object. It reflects the asymmetry of the mass distribution of the object with respect to the y and z axes.

[0092] Represents the resultant force in three directions; Represents the resultant moment in three directions; , , respectively represent the forces on the rotor , , components in three directions, , , respectively represent the forces on the fixed wing , , components in three directions, , , respectively represent the moments on the rotor in , , components in three directions, , ,[[ID=...]] respectively represent the moments on the fixed wing in , , components in three directions.

[0093] Typically, a vertical takeoff and landing fixed-wing aircraft is characterized by 12 states for its dynamic and kinematic models, namely , respectively represent the positions in three directions the velocities in three directions , the attitude angles in three directions and the angular velocities in three directions 。Due to the coupling between the states of a vertical takeoff and landing fixed-wing aircraft, the dynamic system of the vertical takeoff and landing fixed-wing aircraft has strong nonlinear characteristics. Affected by factors such as aerodynamic force changes, large attitude adjustments, and propulsion system coupling, directly designing a controller for the complete nonlinear model usually faces problems such as complex modeling, difficult analysis, and unsolvable control laws. To simplify the controller design, system linearization can be performed near a specific operating point related to the flight mission. Through operating point linearization, a local linear approximation model can be obtained, enabling the application of traditional linear control theories (such as pole placement, optimal control, robust control, etc.), thereby greatly reducing the complexity of controller design and stability analysis, and facilitating efficient engineering deployment and performance verification. Therefore, the linear system obtained after operating point linearization is described as follows:

[0094] where, is the system state, is the derivative of the state, is the control input, is the system state matrix, is the system input matrix, is the mass, is the gravitational acceleration.

[0095] The output equation of the system is:

[0096] where, is the system output matrix, is the system output. Note that is the output before encryption.

[0097] This scheme defines the encryption function as , R is the set of real numbers, 6 is the space dimension, that is

[0098] and the decryption function , that is

[0099] where, is the ciphertext output, is the decryption output.

[0100] This scheme assumes that the decryption error is zero and considers the need to limit the amplitude of the actuators of the vertical takeoff and landing fixed-wing aircraft. In addition, the problem studied in this scheme considers bounded external disturbances Therefore, it is necessary to study the actuator saturation problem and the design problem of disturbance rejection controller. In this problem, the linearized equation of the vertical takeoff and landing fixed-wing aircraft is changed to:

[0101] The saturation function is expressed as follows:

[0102] where, is the upper bound of the saturated input, is the sign function.

[0103] This scheme uses the hyperbolic tangent function to limit the amplitude of the state control input. This scheme defines a function with smooth characteristics:

[0104] Then, the saturation function can be expressed as:

[0105] is the saturation function, and the approximation error is a bounded unknown function. Assuming the upper bound is , then . The linearized equation of the vertical takeoff and landing fixed-wing aircraft is transformed into:

[0106] For the sake of description, this scheme defines the bounded uncertainty as:

[0107] Then the linearized equation of the vertical takeoff and landing fixed-wing aircraft is transformed into:

[0108] Since is a vector, the hyperbolic tangent here means performing hyperbolic tangent operations on each dimensional input element.

[0109] Hyperbolic tangent saturation control algorithm based on disturbance observer: This scheme considers the aircraft path tracking problem and defines the tracking path as , then the tracking error is defined as:

[0110] where, is the tracking error; The integral error is introduced:

[0111] where, where is the integral error, τ is the integral variable, and the goal is to design a saturation tracking controller such that and . We define the extended state variable . Its dynamic equation is:

[0112] where . Taking the derivative of both sides with respect to the tracking error gives:

[0113] Therefore, the dynamic representation of the extended system is:

[0114] Simplified to:

[0115] where, , , .

[0116] For the dynamic of the extended system, the disturbance rejection control law is designed as follows:

[0117] where, is the integral gain matrix, is the proportional gain matrix, is the feedforward term, and the feedforward term is designed as: <00oo

[0118] According to the aircraft model, the input matrix is column full rank, so the left inverse of the input matrix can be calculated, i.e., .

[0119] Therefore, substituting into the extended system gives:

[0120] After expansion, it gives: [[ID=??]]

[0121] Since and<oo000000441>are two components of, so the above equation can be changed to:

[0122] The compensator is designed as: Please note that there seems to be an error in the original text where <oo000000441> is used. It should probably be a proper tag like . Also, the expansion in line 72 is not fully shown in the original text, so I've left it as for now.

[0123] Then the expanded variable equation is:

[0124] in ,and is an estimate of uncertainty.

[0125] The uncertainty observer designed in this scheme is as follows:

[0126] in, The state of the observer system, is the derivative of the state, and the observation error dynamic equation is:

[0127] in Is a constant greater than 0. The above formula is simplified to:

[0128] Then the saturated disturbance rejection tracking controller is designed as:

[0129]

[0130]

[0131] The symbol arcth = arctanh. Then we get the tracking error converges asymptotically and is robust to disturbances. In the process of adjusting the control system parameters, as long as the control gain is selected Make The real part of the eigenvalue of is less than 0. Stability proves that the tracking error converges asymptotically, and increasing the integral gain can effectively reduce the steady-state error.

[0132] Anything not described in this application can be achieved by adopting or drawing on existing technologies.

[0133] The various embodiments in this specification are described in a progressive manner, and the same or similar parts between the various embodiments can be referred to each other. Each embodiment focuses on the differences from other embodiments.

[0134] The foregoing is merely an embodiment of the present application and is not intended to limit the present application. For those skilled in the art, the present application may have various modifications and variations. Any modifications, equivalent replacements, improvements, etc. made within the spirit and principles of the present application should all be included in the protection scope of the present application.

Claims

1. A method for controlling the path tracking of an unmanned aerial vehicle based on chaotic encryption and disturbance observation, characterized in that Including: Encrypt the measurement data of the aircraft through a key stream, where the key stream is obtained by encrypting Logistic map chaos nesting, switching chaos systems, and randomly distributing key stream coefficients; Transmit the encrypted measurement data to the controller of the aircraft through a communication interface for decryption; Generate a control instruction according to the decrypted measurement data.

2. The method according to claim 1, wherein The encrypting the measurement data of the aircraft through a key stream is specifically: Input the measurement data into the Logistic Map chaos system to generate preliminary encrypted data; According to a preset switching strategy, select the Lorenz chaos system or the Chen chaos system to generate a key stream, and combine the randomly allocated key stream coefficients to perform secondary encryption on the preliminary encrypted data to generate encrypted measurement data; Generate key stream coefficients through a seed random number generator, and distribute the key stream coefficients and chaos system parameters to the decryption end; During the aircraft mode switching stage, dynamically adjust the switching strategy of the switching chaos system and the key stream coefficients according to the flight state.

3. The method according to claim 1, characterized in that, The transmitting the encrypted measurement data to the controller of the aircraft through a communication interface for decryption is specifically: Synchronize the switching strategy of the chaos system and the Logistic Map parameters according to the decryption key; Restore the plaintext measurement data by subtracting the key stream.

4. The method according to claim 2, wherein The seed random number generator generates key stream coefficients based on the real-time state parameters of the aircraft to ensure that the key is bound to the flight phase.

5. The method according to claim 2, characterized in that, The switching strategy dynamically adjusts the switching period of the switching chaos system based on the communication frequency hopping and topological structure reorganization of the aircraft.

6. The method according to claim 1, characterized in that, The generating a control instruction according to the decrypted measurement data is specifically: Estimate the external disturbance and introduce the external disturbance into the control law; Design the anti-saturation state feedback control law of the aircraft controller; Reduce the steady-state error and suppress the disturbance through the proportional term and the integral term.

7. The method according to claim 6, characterized in that, The estimating the external disturbance and introducing the external disturbance into the control law is specifically: Construct an extended system dynamic model with the disturbance as an unknown input; Design the disturbance observer gain matrix to make the observation error converge to zero; Output the disturbance estimation value and feedback it to the control law.

8. The method according to claim 2, wherein The key stream coefficients and the disturbance estimation value share the same seed random number generator; The controller adjusts the sampling period of the disturbance observer according to the dynamic update frequency of the encryption end.

9. A computer-readable storage medium having a program stored thereon, characterized in that, When the program is executed by the processor, it implements the steps in the method described in any one of claims 1-8.

10. An electronic device, comprising a memory, a processor, and a computer program stored on the memory and executable on the processor, characterized in that, When the processor executes the program, it implements the method described in any one of claims 1-<0000001>.

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