A tilt-rotor attitude control method, device, medium and product

Abstract

The application discloses a tilt-rotor attitude control method, device, medium and product, relates to the field of aviation control, and comprises the following steps: acquiring a desired attitude angle signal of a tilt-rotor aircraft and a real-time feedback attitude angle state quantity; inputting the desired attitude angle signal and the attitude angle state quantity into an improved active disturbance rejection controller to calculate a control increment; wherein the improved active disturbance rejection controller comprises a tracking differentiator, an extended state observer and a nonlinear state error feedback law; combining the control increment with an initial state trimming control quantity of a tilt-rotor model to obtain a final model control quantity; and performing attitude control on the tilt-rotor aircraft according to the final model control quantity; the attitude control comprises pitch channel control, roll channel control and yaw channel control, the application can quickly adapt to dynamic changes in the transition stage, avoid control quantity chattering or slow response, and realize high-precision stable control of the tilt-rotor unmanned aerial vehicle.

Description

Technical Field

[0001] This application relates to the field of aviation control, and in particular to a tiltrotor attitude control method, device, medium, and product. Background Technology

[0002] With the current trend of aviation technology developing towards vertical takeoff and landing, high-speed cruise, and multi-mission adaptability, tiltrotor aircraft, due to their unique advantages of combining the vertical takeoff and landing / hovering capabilities of helicopters with the high-speed forward flight efficiency of fixed-wing aircraft, have become an important development direction for next-generation flight platforms. They have shown great application potential in military reconnaissance, troop deployment, civilian emergency rescue, and rapid logistics. However, their unique tilt transition flight phase—the continuous rotation of the rotor cabin from a vertical to a horizontal state—presents unprecedented challenges to the flight control system. During this process, the stability of attitude control is not only the foundation for achieving precise control and mission execution, but also a core prerequisite for ensuring flight safety and successful mode transitions. Drastic time-varying changes in the aircraft's aerodynamic configuration, center of gravity, and handling characteristics can easily lead to attitude instability, making the need for a highly robust attitude control system extremely urgent, thus forming the direct premise of this research and development concept.

[0003] While Active Disturbance Rejection Control (ADRC) technology has advantages in handling uncertain nonlinear systems, standard ADRC still has limitations when applied to tiltrotor attitude control: First, the dynamic changes during the transition phase are extremely rapid, posing challenges to the real-time estimation accuracy and speed of the Extended State Observer (ESO) of complex disturbances; Second, the parameter tuning of the nonlinear state error feedback law is complex and lacks adaptability to drastically changing system dynamics, which can easily lead to control quantity chattering or slow response. Summary of the Invention

[0004] The purpose of this application is to provide a tilt rotor attitude control method, device, medium, and product to solve the problem.

[0005] To achieve the above objectives, this application provides the following solution: In a first aspect, this application provides a tilt rotor attitude control method, including: Acquire the desired attitude angle signal and real-time feedback attitude angle state variables of the tiltrotor aircraft; The desired attitude angle signal and the attitude angle state quantity are input into the improved active disturbance rejection controller (ADRC) to calculate the control increment. The improved ADRC includes a tracking differentiator, an extended state observer, and a nonlinear state error feedback law. The tracking differentiator is used to arrange a transition process for the input signal. The extended state observer uses a new gain function for state observation. The new gain function, composed of a hyperbolic tangent function and an exponential function, is used to achieve variable gain control. The nonlinear state error feedback law uses a chatter suppression function to process the incoming error signal and suppress control chatter. The control increments are combined with the initial state trim control values ​​of the tilt rotor model to obtain the control values ​​of the final model. The tiltrotor aircraft is subjected to attitude control based on the control parameters of the final model; the attitude control includes pitch channel control, roll channel control and yaw channel control.

[0006] Secondly, this application provides a computer device, including: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the above-described tilt rotor attitude control method.

[0007] Thirdly, this application provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the above-described tilt rotor attitude control method.

[0008] Fourthly, this application provides a computer program product, including a computer program that, when executed by a processor, implements the above-described tilt rotor attitude control method.

[0009] According to the specific embodiments provided in this application, this application has the following technical effects: This application inputs the desired attitude angle signal and attitude angle state quantity into an improved active disturbance rejection controller. After processing the difference between the desired value and the state quantity, the control increment is calculated. The improved active disturbance rejection controller includes a tracking differentiator, an extended state observer, and a nonlinear state error feedback law. The extended state observer uses a new gain function for state observation to achieve variable gain control, thereby enabling rapid adaptation to dynamic changes during the transition phase. The nonlinear state error feedback law uses a chatter suppression function to process the input error signal, suppressing control chatter and avoiding control quantity chatter or slow response. The control increment is combined with the initial state trim control quantity of the tilt rotor model to form the control quantity of the final model, achieving high-precision and stable control of the tilt rotor UAV. Attached Figure Description

[0010] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0011] Figure 1 This is a schematic flowchart of a tilt rotor attitude control method provided in an embodiment of this application; Figure 2 This is a schematic diagram of a tilt rotor attitude loop control framework provided in an embodiment of this application; Figure 3 A basic structural diagram of an improved active disturbance rejection controller provided in an embodiment of this application; Figure 4 A comparison diagram of the anti-interference capability of the new gain function provided in an embodiment of this application; wherein, Figure 4 (a) in the figure is a comparison of the response results of the system under large disturbance; Figure 4 (b) in the figure is a comparison chart of cumulative errors under large disturbances; Figure 4 (c) in the figure is a comparison of the response results of the small disturbance system; Figure 4 (d) in the figure is a comparison chart of cumulative errors with small disturbances; Figure 5 This is a comparative diagram of shake suppression provided in an embodiment of this application; wherein, Figure 5 (a) in the text represents ESO. Comparison chart of response results; Figure 5 (b) in the text represents ESO. Response result comparison chart; Figure 5 (c) in the text represents ESO. Response result comparison chart; Figure 5 (d) in the figure is a comparison chart of control results; Figure 6 This is a schematic diagram of the roll angle response of a sinusoidal signal test according to an embodiment of this application; Figure 7 This is a schematic diagram of a sinusoidal signal test pitch angle response provided in an embodiment of this application; Figure 8 This is a schematic diagram of a sinusoidal signal test yaw angle response provided in an embodiment of this application. Detailed Implementation

[0012] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0013] To make the objectives, features and advantages of this application more apparent and understandable, the application will be further described in detail below with reference to the accompanying drawings and specific embodiments.

[0014] Example 1 like Figure 1 As shown in the figure, this application provides a tilt rotor attitude control method, including: S1: Acquire the desired attitude angle signal and real-time feedback attitude angle state variables of the tiltrotor aircraft.

[0015] S2: The desired attitude angle signal and the attitude angle state quantity are input into the improved active disturbance rejection controller to calculate the maneuvering control increment; wherein, the improved active disturbance rejection controller includes a tracking differentiator, an extended state observer, and a nonlinear state error feedback law; the tracking differentiator is used to arrange the transition process for the input signal; the extended state observer uses a new gain function for state observation; the new gain function is composed of a hyperbolic tangent function part and an exponential function part, and is used to realize variable gain control; the nonlinear state error feedback law uses a jitter suppression function to process the incoming error signal and is used to suppress control jitter.

[0016] S3: Combine the control increment with the initial state trim control amount of the tilt rotor model to obtain the control amount of the final model.

[0017] S4: Perform attitude control on the tiltrotor aircraft based on the control values ​​of the final model; the attitude control includes pitch channel control, roll channel control and yaw channel control.

[0018] This application aims to address the problem of flight stability issues caused by internal control coupling and state coupling in tilt-rotor unmanned aerial vehicles (UAVs), which are highly coupled multi-input multi-output systems, and to improve their attitude stability during flight.

[0019] The above method is implemented based on a tilt rotor attitude loop control framework, which is as follows: Figure 2 As shown.

[0020] Attitude loop control is the process of transferring the desired attitude angle signal value ( , , ) and the attitude angle state variables of the tilt rotor in real time ( , , ), input to the improved active disturbance rejection controller of the design ( In ), such as Figure 3 As shown, after processing the difference between the expected value and the state variable, the control increment of the manipulation is calculated. This increment, combined with the trim manipulation of the initial state of the tilt rotor model, becomes the final manipulation of the model, thus achieving high-precision stable control of the tilt rotor UAV.

[0021] in, Figure 3 In The input is the desired signal value, i.e., the attitude angle signal value. , , In the disturbance compensation section The tracking value of the input signal. for Tracking value of the differential signal, perturbation estimation part , , For the output variables of the ESO observation object, As a compensation factor, y out For the controlled object (i.e. The state variables of the response.

[0022] In an exemplary embodiment, the tracking differentiator (TD) of the active disturbance rejection controller arranges a suitable "transition process" for the input signal, which can effectively resolve the contradiction between overshoot and speed, increase the parameter range of the feedback gain adaptation, and improve the robustness of the controller.

[0023] The differential tracker extracts the differential signal by tracking the input signal, and then arranges a suitable signal transition process according to the tolerance of the controlled system. The discrete form of the differential tracker is shown below: (1) (2) (3) (4) in, For the first k Tracking value of the input signal sampled +1 times; For the first k The tracked value of the input signal sampled once; for Tracking value of the differential signal; for Tracking value of the differential signal; This is the sampling step size; The filter factor; The speed factor determines the tracking speed; Number of samples; This is the fastest control synthesis function; a、a 0 is an intermediate variable; d and d0 are intermediate values ​​with no specific meaning; y is the attitude signal of the tilt rotor response.

[0024] In one exemplary embodiment, such as Figure 3 The new gain function controller ESO-Tf for the disturbance estimation part shown is: (5) in, and is the adjustment factor of the function; e is the tracking error value; The tracked value output by the extended state observer; for The iteration value; The differential signal output by the extended state observer; These are the parameters that need to be adjusted; for The iteration value; The extended state variables output by the extended state observer; These are the parameters that need to be adjusted; As a regulating factor; u The amount of manipulation obtained; for The iteration value; These are the parameters that need to be adjusted; For the new gain function; This is the new gain function.

[0025] From ESO tradition The function gain can be known as follows: The function gain is The timing is better, therefore in the new state observer The parameters that need to be adjusted for the function are: , .

[0026] Specifically, the expression for the new gain function is as follows: (6) In the formula, and It can adjust the gain trend for small perturbations and the gain capability for large perturbations.

[0027] The new gain function consists of two parts; the first part is composed of the hyperbolic tangent function. Its structure, characterized by origin symmetry and bidirectional saturation, is as follows: (7) in, e 0 is a constant with a value of approximately 2.71828; in equation (7), x = .

[0028] The advantage of this function lies in its unique properties of "finite amplitude + global smoothness," which can effectively solve the problems of control saturation and chattering suppression. In systems with high reliability and low noise requirements, its performance far exceeds that of traditional nonlinear functions, thus exhibiting significant advantages in control systems, neural networks, and optimization algorithms.

[0029] The latter half of the new gain function is composed of Composition, regulatory factors Always greater than zero Ensure that the latter half always aligns with the overall gain direction, where, When the error e is small, Therefore, it has little impact on the gain for small errors; when the error e is large, At this point, the gain of a large error is adjusted by the factor. control.

[0030] The reconstructed gain function achieves variable gain control: high gain with small errors (due to...). Adjustment), gain decreases with large errors (by (Adjustment), while retaining The function exhibits the characteristics of small perturbation resulting in large gain and large gain resulting in small perturbation, leading to smooth function transitions, avoiding abrupt changes, and enhancing robustness.

[0031] The new gain function can be adjusted for large and small error gains via parameters. The influence of the function parameters on the error is as follows: Parameters The larger the value, the greater the gain of the function with small errors; the parameter The smaller the value, the greater the gain of the large error of the function. Therefore, in actual control, it is possible to effectively adjust the gain of each part to achieve a good control effect.

[0032] In one exemplary embodiment, disturbance compensation is an important part of the active disturbance rejection controller, such as... Figure 3 The specific details of the chatter suppression function controller (NLSEF-Te) are as follows: (8) in, The error in tracking the input signal; and For the chattering function; The error in tracking the differential signal is denoted by ; T is the compensation factor. For the calculated control quantity; , , and Parameters that need to be adjusted; and It is a nonlinear function; It is a regulating factor.

[0033] Flicker suppression function Te () Adds a new function to process the error signal, as follows: (9) In the formula, relative to the initial NLSEF, the addition is The function processes the error signal input to NLSEF by adjusting... The gain can be adjusted.

[0034] Te The () function smoothly limits the gain under large errors while maintaining the response sensitivity under small errors. When the error is large, In the () function Approaching 1, the gain remains unchanged from the original NLSEF, preserving the original error characteristics and preventing the output from increasing infinitely; when the error e is small, ,but The function is approximately equal to It is proportional to the error amplitude, therefore it is highly sensitive to small errors and responds quickly. This is achieved through a compensation factor. Adjust the gain. When the function value is less than 1, the actual small error gain is reduced, thus achieving the effect of suppressing chattering. Taking the derivative of (9) yields: (10) Where sech is the hyperbolic secant function.

[0035] The above formula is When the gain approaches zero, the gain also approaches zero, indicating that chattering in the small error region can be eliminated near the zero point.

[0036] The gain of the function changes with the parameters as a result of the compensation factor of the function. Reducing the gain significantly lowers the small signal gain, which helps to solve the jitter problem caused by excessively high small gain.

[0037] In an exemplary embodiment, by adding the new gain function and the jitter suppression function to the active disturbance rejection controller, the following is obtained: Figure 3 The improved active disturbance rejection controller shown has better noise immunity and robustness, and is referred to as... The specific form is as follows: (12) in, and The parameters need to be adjusted.

[0038] In one exemplary embodiment, the tiltrotor UAV attitude control loop is a three-channel circuit, such as... Figure 2 As shown, it includes: pitch channel, roll channel and yaw channel.

[0039] use Controller structure design, including the control law for pitch angle channel control. The specific format is as follows: (13) In the formula, For the desired pitch angle signal, The longitudinal periodic pitch control amount for initial state trim; This represents the change in longitudinal periodic pitch. This represents the actual longitudinal periodic pitch value; These are the state variables after control has been applied; For dynamic models; x For tilt rotor state variables, u is the control variable; w External disturbances; t For time. This is the controller parameter. It is determined by the required transition speed and the system's tolerance. The sampling step size of the system determines the sampling step size; the other channels are similar to the above.

[0040] Control law for roll angle channel control The specific format is as follows: (14) In the formula, For the desired roll angle signal, The lateral periodic pitch control amount for initial state trim. This represents the change in the transverse periodic pitch. This represents the actual lateral periodic pitch value. This refers to the state variables after control is applied. These are the controller parameters. It is determined by the required transition speed and the system's tolerance. It is determined by the sampling step size of the system.

[0041] Control law for yaw angle channel control The specific format is as follows: (15) In the formula, For the desired yaw angle signal, This refers to the tail rotor pitch control amount for initial trim. This represents the change in tail rotor pitch. This is the actual tail rotor pitch value. This refers to the state variables after control is applied. These are the controller parameters. It is determined by the required transition speed and the system's tolerance. The sampling step size of the system determines the sampling step size; the other channels are similar to the above.

[0042] Example 2 Taking a second-order controlled object system model as an example, the technical solution of this application is further illustrated.

[0043] The second-order controlled object system model is: (16) In a simulation environment with a sampling frequency of 100Hz and a fixed step size, the ESO parameters are: , , , , , ESO- Tf The parameters are , , , , If the system's stable response is 1, then disturbances of magnitude 5 and 0.5 are applied, and their effects are observed and compared. Figure 4 In (a) and (c), it can be clearly seen that, under the same response speed, ESO- Tf Because its gain function exhibits superior performance under both large and small errors, it decays rapidly under large disturbances, enabling it to quickly recover to a stable value; its decay rate under small disturbances is also superior to that of traditional ESOs; from Figure 4 In the data, (b) and (d) correspond to the tracking cumulative error results under perturbation conditions. It can be seen that under large perturbation conditions, ESO- Tf The tracking error is smaller, outperforming traditional ESO results by 68%, and ESO- under small perturbations. Tf It has smaller tracking error, outperforming traditional ESO results by 33%, and has better anti-interference capabilities.

[0044] The novel gain function controller (ESO-Tf) constructed in this application has the advantages of high control accuracy and strong anti-disturbance capability compared with existing technologies.

[0045] Taking the same second-order controlled object as an example, the controller parameters are set as follows: , , , , , , , The response at this time is as follows Figure 5 The traditional NLSEF shown will produce oscillations, then after the parameter The dynamic adjustment preprocesses the error, and the response result is as follows: Figure 5 As shown in the NLSEF-Te figure, it can be seen from the figure that by adjusting the compensation factor... , Figure 5 Observers in (a), (b) and (c) , , The tracking value response jitter is reduced, and Figure 5 The time response result of channel (d) in the middle is weakened, and the control effect tends to be stable.

[0046] This application adds a chatter suppression function controller (NLSEF-Te), which, compared with existing technologies, has the advantage of reducing chatter effects and improving control accuracy.

[0047] The embodiments relate to a simulation verification method for the attitude control system of a tiltrotor aircraft. In the simulation, the sampling frequency is set to 100Hz, and the total simulation time is 10 seconds. Continuous sinusoidal reference signal tracking control tests are performed on the roll angle channel, pitch angle channel, and yaw angle channel, respectively. The Tetf-ADRC controller proposed in this application is compared and analyzed with conventional proportional-integral-differential (PID) controllers and standard ADRC controllers.

[0048] Simulation results show that all three control algorithms can basically track the overall trend of the sinusoidal command signal. Specifically, in the roll angle channel (corresponding to...) Figure 6 In the enlarged view, the PID controller shows a significant overshoot phenomenon; both the ADRC controller and the Tetf-ADRC controller can follow the reference command relatively closely, but from the tracking details, it can be seen that the response curve of the PID controller is above the reference signal, indicating that there is still overshoot, while the outputs of the ADRC and Tetf-ADRC controllers are slightly lagging behind the reference signal. Among them, the Tetf-ADRC controller has smaller phase lag and amplitude deviation, and has the highest tracking accuracy.

[0049] Tracking results of the pitch angle channel (corresponding) Figure 7 The Tetf-ADRC controller exhibits a consistent pattern with the roll angle channel, meaning it outperforms the other two in terms of tracking accuracy and dynamic fit.

[0050] In the yaw angle channel (corresponding to) Figure 8In this context, the overshoot phenomenon of the PID controller is more obvious, further highlighting its shortcomings in handling highly coupled, nonlinear systems.

[0051] In summary, the Tetf-ADRC controller provided in this application demonstrates superior tracking performance, smaller overshoot, and higher command fit in continuous sinusoidal signal tracking control of tilt rotor attitude, verifying its significant control quality advantages in full envelope and high-dynamic flight scenarios.

[0052] Example 3 In an exemplary embodiment, a computer device is provided, including a memory and a processor. The memory stores a computer program, and the processor executes the computer program to implement the steps in the above-described method embodiments. The computer device can be a server or a terminal. The computer device includes a processor, a memory, an input / output interface (I / O), and a communication interface. The processor, memory, and I / O interface are connected via a system bus, and the communication interface is connected to the system bus via the I / O interface. The processor of the computer device provides computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and internal memory. The non-volatile storage medium stores an operating system, a computer program, and a database. The internal memory provides an environment for the operation of the operating system and computer program in the non-volatile storage medium. The database of the computer device stores data to be processed. The I / O interface of the computer device is used for exchanging information between the processor and external devices. The communication interface of the computer device is used for communicating with an external terminal via a network connection. When the computer program is executed by the processor, it implements the above-described methods.

[0053] In one exemplary embodiment, a computer-readable storage medium is provided storing a computer program that, when executed by a processor, implements the steps in the above-described method embodiments.

[0054] In one exemplary embodiment, a computer program product is provided, including a computer program that, when executed by a processor, implements the steps in the above-described method embodiments.

[0055] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, data stored, data displayed, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties, and the collection, use and processing of the relevant data must comply with relevant regulations.

[0056] Those skilled in the art will understand that all or part of the processes in the above embodiments can be implemented by hardware related to computer program instructions. The computer program can be stored in a non-volatile computer-readable storage medium, and when executed, it can include the processes of the embodiments described above. Any references to memory, databases, or other media used in the embodiments provided in this application can include at least one of non-volatile and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetic random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. By way of illustration and not limitation, RAM can take many forms, such as Static Random Access Memory (SRAM) or Dynamic Random Access Memory (DRAM).

[0057] The databases involved in the embodiments provided in this application may include at least one type of relational database and non-relational database. Non-relational databases may include, but are not limited to, blockchain-based distributed databases. The processors involved in the embodiments provided in this application may be general-purpose processors, central processing units, graphics processing units, digital signal processors, programmable logic devices, quantum computing-based data processing logic devices, etc., and are not limited to these.

[0058] The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0059] This document uses specific examples to illustrate the principles and implementation methods of this application. The descriptions of the above embodiments are only for the purpose of helping to understand the methods and core ideas of this application. Furthermore, those skilled in the art will recognize that, based on the ideas of this application, there will be changes in the specific implementation methods and application scope. Therefore, the content of this specification should not be construed as a limitation of this application.

Claims

1. A tilt rotor attitude control method, characterized in that, include: Acquire the desired attitude angle signal and real-time feedback attitude angle state variables of the tiltrotor aircraft; The desired attitude angle signal and the attitude angle state quantity are input into the improved active disturbance rejection controller (ADRC) to calculate the control increment. The improved ADRC includes a tracking differentiator, an extended state observer, and a nonlinear state error feedback law. The tracking differentiator is used to arrange a transition process for the input signal. The extended state observer uses a new gain function for state observation. The new gain function, composed of a hyperbolic tangent function and an exponential function, is used to achieve variable gain control. The nonlinear state error feedback law uses a chatter suppression function to process the incoming error signal and suppress control chatter. The control increments are combined with the initial state trim control values ​​of the tilt rotor model to obtain the control values ​​of the final model. The tiltrotor aircraft is subjected to attitude control based on the control parameters of the final model; the attitude control includes pitch channel control, roll channel control and yaw channel control.

2. The tilt rotor attitude control method according to claim 1, characterized in that, The discrete form of the tracking differentiator is: in, This is the tracking value of the input signal sampled for the (k+1)th time. For the first k The tracked value of the input signal sampled once; for Tracking value of the differential signal; for Tracking value of the differential signal; This is the sampling step size; The filter factor; The speed factor determines the tracking speed; Number of samples; This is the fastest control synthesis function.

3. The tilt rotor attitude control method according to claim 2, characterized in that, The new gain function for: in, and It is the adjustment factor of the function; It is the hyperbolic tangent function; e This is the tracking error value.

4. The tilt rotor attitude control method according to claim 3, characterized in that, The jitter suppression function for: in, This is a compensation factor.

5. The tilt rotor attitude control method according to claim 4, characterized in that, The control law for the pitch channel control is: in, The iterative value of the tracked input signal; The tracking value of the input signal; This is the tracking value of the differential signal; The iterative value of the tracking value of the differential signal; The desired pitch angle signal; r For controller parameters; The tracked value output by the extended state observer; y The attitude signal for the tilt rotor response; for The iteration value; The differential signal output by the extended state observer; , , , , , and These are the parameters that need to be adjusted; for The iteration value; The extended state variables output by the extended state observer; As a regulating factor; u The amount of manipulation obtained; for The iteration value; The error in tracking the input signal; and For the chattering function; The error is the tracking value of the differential signal; For the calculated control quantity; , and It is the gain function; This represents the change in longitudinal periodic pitch. This represents the actual longitudinal periodic pitch value; The longitudinal periodic pitch control amount for initial state trim; These are the state variables after control has been applied; For dynamic models; x For the state variables of the tilt rotor; u For manipulation quantity; w External disturbances; t For time.

6. The tilt rotor attitude control method according to claim 5, characterized in that, The control law for the roll channel control is: in, The desired roll angle signal; The lateral periodic pitch control amount for initial state trim; This represents the change in the transverse periodic pitch. This represents the actual lateral periodic pitch value.

7. The tilt rotor attitude control method according to claim 6, characterized in that, The control law for the yaw channel control is: in, The desired yaw angle signal; The tail rotor pitch control amount for initial trim. This represents the change in tail rotor pitch. This is the actual tail rotor pitch value.

8. A computer device, comprising: A memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that the processor executes the computer program to implement the tilt rotor attitude control method according to any one of claims 1-7.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by the processor, it implements the tilt rotor attitude control method according to any one of claims 1-7.

10. A computer program product, comprising a computer program, characterized in that, When the computer program is executed by the processor, it implements the tilt rotor attitude control method according to any one of claims 1-7.

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