A longitudinal adaptive control method, device and storage medium for a wide-speed-range aircraft

Abstract

The embodiment of the present specification provides a kind of wide speed domain aircraft longitudinal self-adapting control method, device and storage medium, the method comprises: obtaining flight state parameter;According to the flight state parameter, the longitudinal motion model of target aircraft is determined based on short cycle motion;The longitudinal motion model includes interference term and non-interference term;According to the flight state parameter, the linear state feedback control model corresponding to the non-interference term is determined;According to the flight state parameter, the compensation model corresponding to the interference term is determined;According to the linear state feedback control model and compensation model, the nonlinear adaptive control law of the target aircraft is determined;According to the nonlinear adaptive control law, the target aircraft is controlled.The technical scheme provided in the present application is used to solve the problem that the existing calculation model is not high in calculation precision.

Description

Technical Field

[0001] This document relates to the field of aircraft flight control technology, and in particular to a longitudinal adaptive control method, device and storage medium for a wide-speed-range aircraft. Background Technology

[0002] To address the challenges in designing flight control systems for wide-speed-range aircraft, research into active control technology based on adaptive control methods is crucial. Designing flight control systems based on adaptive control methods across the entire flight profile, a wide speed range, and with deviations in aerodynamic parameters is key to solving the difficulties in flight control for wide-speed-range aircraft.

[0003] L1 adaptive control is an improved model reference adaptive control method, also known as fast robust adaptive control. Controllers designed based on this method can ensure that the system output tracks the reference signal, exhibiting good transient and steady-state performance. Compared to traditional model reference adaptive methods, L1 adaptive control incorporates a low-pass filter and high-gain feedback, which can suppress high-frequency components in the control signal, achieving rapid adaptive adjustment. Furthermore, it utilizes the gain stability requirement based on the L1 norm to determine the filter bandwidth, thus achieving good transient control performance while avoiding high-frequency oscillations, provided that the tracking error asymptotically converges. Benefiting from the simplicity and ease of implementation of linear system design, L1 adaptive control has been applied to some extent in the longitudinal flight control schemes of wide-speed-range aircraft.

[0004] However, the L1 adaptive control method still has the following problems to be solved: 1) It requires that the upper bound of the uncertainty in the aircraft model be known, and that the system reference input and controller coefficients satisfy different bounded conditions; 2) It is difficult to select the feedback gain and feedback transfer function; 3) The design of the flight control law depends heavily on the model information. Summary of the Invention

[0005] In view of the above analysis, this application aims to provide a longitudinal adaptive control method, apparatus and storage medium for a wide speed range aircraft to solve at least one of the above-mentioned technical problems.

[0006] Firstly, one or more embodiments of this specification provide a longitudinal adaptive control method for a wide-speed-range aircraft, including:

[0007] Obtain flight status parameters;

[0008] Based on the flight state parameters, a longitudinal motion model of the target aircraft is determined based on short-period motion; the longitudinal motion model includes interference and non-interference terms.

[0009] Based on the flight state parameters, determine the linear state feedback control model corresponding to the non-interference term;

[0010] Based on the flight state parameters, determine the compensation model corresponding to the interference term;

[0011] Based on the linear state feedback control model and the compensation model, the nonlinear adaptive control law of the target aircraft is determined;

[0012] The target aircraft is controlled according to the nonlinear adaptive control law.

[0013] Furthermore, determining the disturbance term based on the flight state parameters and short-period motion includes:

[0014] Based on the flight state parameters, an interference estimation model is determined based on short-period motion;

[0015] Based on the disturbance estimation model, determine the error between the true value and the estimated value of the flight state parameter;

[0016] The interference term is determined based on the error.

[0017] Furthermore, the disturbance estimation model is as follows:

[0018]

[0019] in, Let denot be the time-varying diagonal dominant matrix used for unknown parameter estimation at step k, η and μ be the disturbance estimator parameters, ΔY be the deviation between the estimated and measured values ​​of the state to be estimated, and ΔU be the error between the estimated and measured values ​​of the input quantity.

[0020] Furthermore, the longitudinal motion model is specifically as follows:

[0021]

[0022] In the above formula, α is the angle of attack, q is the pitch angular velocity, and δ e For elevator, f α For the force interference term of the angle-of-attack channel, f q For the torque disturbance term of the pitch angular velocity channel, b q To improve pitch control efficiency.

[0023] Furthermore, the linear state feedback control model is specifically as follows:

[0024]

[0025] Where, δ e1 To obtain the elevator deflection for linear state feedback calculation, k α k is the angle-of-attack tracking error feedback coefficient. α >0, k qk is the pitch angular velocity feedback coefficient. q >0, x is the state variable, e is the tracking error, and q is the pitch angular velocity.

[0026] Furthermore, the compensation model is as follows:

[0027]

[0028] Among them, K d K represents the interference compensation gain. x For linear feedback gain, f α For the force interference term of the angle-of-attack channel, f q For the torque disturbance term of the pitch angular velocity channel, δ e2 Indicates the compensation interference term f α and f q Required elevator deflection; b = [0 b q ] T ,b d =[1 0] T c = [1 0].

[0029] Secondly, embodiments of this application provide a longitudinal adaptive control device for a wide-speed-range aircraft, comprising:

[0030] The module consists of an acquisition module, a data processing module, and a control module.

[0031] The acquisition module is used to acquire flight status parameters;

[0032] The data processing module is used to determine the longitudinal motion model of the target aircraft based on the flight state parameters and short-period motion; the longitudinal motion model includes disturbance and non-disturbance terms; determine the linear state feedback control model corresponding to the non-disturbance terms based on the flight state parameters; determine the compensation model corresponding to the disturbance terms based on the flight state parameters; and determine the nonlinear adaptive control law of the target aircraft based on the linear state feedback control model and the compensation model.

[0033] The control module is used to control the target aircraft according to the nonlinear adaptive control law.

[0034] Furthermore, the device also includes a preprocessing module;

[0035] The data processing module is also used to determine the interference estimation model based on the flight state parameters. The interference estimation model can simultaneously calculate the angle-of-attack interference term and the pitch angular velocity torque interference term.

[0036] Furthermore, the disturbance estimation model is as follows:

[0037]

[0038] in, Let denot be the time-varying diagonal dominant matrix used for unknown parameter estimation at step k, η and μ be the disturbance estimator parameters, ΔY be the deviation between the estimated and measured values ​​of the state to be estimated, and ΔU be the error between the estimated and measured values ​​of the input quantity.

[0039] Thirdly, embodiments of this application provide a storage medium, including:

[0040] Used to store computer-executable instructions, which, when executed, implement the method described in any one of the first aspects.

[0041] Compared with the prior art, this application can achieve at least the following technical effects:

[0042] Based on short-period motion, disturbance and non-disturbance terms are defined in the longitudinal motion model. Then, a compensation model is created for the disturbance terms, and a linear state feedback control model is created for the non-disturbance terms. This allows the compensation model and the linear state feedback control model to replace the low-pass filter and parameter adaptive law, transforming the entire control scheme from being applicable to linear adaptive control laws to being applicable to nonlinear adaptive control laws, thus eliminating the need to set upper bounds for the parameters. Attached Figure Description

[0043] To more clearly illustrate the technical solutions in one or more embodiments of this specification or in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments recorded in this specification. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0044] Figure 1 A flowchart of a longitudinal adaptive control method for a wide-speed-range aircraft provided for one or more embodiments of this specification;

[0045] Figure 2 Angle of attack commands and responses provided in one or more embodiments of this specification;

[0046] Figure 3 Pitch rate response provided for one or more embodiments of this specification;

[0047] Figure 4 Pitch response provided for one or more embodiments of this specification;

[0048] Figure 5 Elevator deflection angles provided in one or more embodiments of this specification;

[0049] Figure 6 Angle-of-attack mismatch interference provided for one or more embodiments of this specification;

[0050] Figure 7 Pitch rate matching interference provided for one or more embodiments of this specification. Detailed Implementation

[0051] To enable those skilled in the art to better understand the technical solutions in one or more embodiments of this specification, the technical solutions in one or more embodiments of this specification will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of this specification, and not all of the embodiments. Based on one or more embodiments of this specification, all other embodiments obtained by those skilled in the art without creative effort should fall within the protection scope of this document.

[0052] Wide-speed-range aircraft have a wide flight range and a large speed span, exhibiting characteristics such as strong coupling, high nonlinearity, static instability, non-minimum phase, and model uncertainty caused by parameter measurement / calculation deviations during flight. This makes existing L1 adaptive control significantly inadequate. While low-pass filters can accelerate adaptive adjustment and facilitate subsequent linear adaptive control laws, restricting high-frequency signals is not well-suited to the strong coupling and high nonlinearity characteristics of wide-speed-range aircraft. The model uncertainty caused by parameter measurement / calculation deviations makes it difficult to select feedback gain and feedback transfer function, even though high-gain feedback can accelerate convergence. Furthermore, while determining the upper bound of uncertainty simplifies calculations, it also makes the design of flight control laws heavily reliant on model information. If the model information is flawed, the upper bound of uncertainty can further negatively impact the model's computational accuracy.

[0053] To address the aforementioned problems, embodiments of this application provide a longitudinal adaptive control method for a wide-speed-range aircraft, such as... Figure 1 As shown, it includes the following steps:

[0054] Step 1: Obtain flight status parameters.

[0055] In this embodiment of the application, the flight state parameters include: angle of attack, pitch rate, elevator, and pitch control efficiency.

[0056] Step 2: Based on the flight state parameters and short-period motion, determine the longitudinal motion model of the target aircraft.

[0057] In this embodiment, the longitudinal control design of the wide-speed-range aircraft focuses on short-period motion. Therefore, the simplified short-period motion of the aircraft can be used for control design. To facilitate the algorithm derivation and design of the improved adaptive control method, the longitudinal second-order short-period model of the aircraft is transformed into a longitudinal motion model:

[0058]

[0059] In the above formula, α is the angle of attack, q is the pitch angular velocity, and δ e For elevator, f α For the force interference term of the angle-of-attack channel, f q For the torque disturbance term of the pitch angular velocity channel, b q For pitch control efficiency. To ensure the safety of the aircraft throughout its long-range flight, the longitudinal attitude control is designed with the angle of attack as the control variable, assuming the tracked desired angle of attack signal α. d It is a constant value. Where f is... α and f q As a distractor, remove f. α and f q All other parameters are non-interference items.

[0060] In this embodiment of the application, in order to reduce the dependence on an accurate aircraft model, an interference estimation method is used to estimate the angle-of-attack interference term f. α And pitch angular velocity torque disturbance term f q Make an estimate and design a method to simultaneously estimate f. α with f q The estimator. The process of determining the interference terms is as follows:

[0061] Based on the flight state parameters and short-period motion, an interference estimation model is determined; based on the interference estimation model, the error between the true and estimated values ​​of the flight state parameters is determined; based on the error, the interference term is determined.

[0062] Specifically, the following angle-of-attack and pitch rate estimation models are selected:

[0063]

[0064] In the above formula, α m This represents the estimated angle of attack, where T is the sampling period and q is the value. m This represents the estimated pitch angular velocity, where k represents the current time step in the estimation algorithm.

[0065] Based on the estimation model, the calculation method for the interference term is designed as follows:

[0066]

[0067] In the above formula, Δε AOAThis represents the error between the true value and the estimated value of the signal. This is an interference estimator. 1 and 2 are the index values ​​of the elements in the vector.

[0068] in, The calculation formula is as follows:

[0069]

[0070] In the above formula, Let denot be the time-varying diagonal dominant matrix used for unknown parameter estimation at step k, η and μ be the disturbance estimator parameters, ΔY be the deviation between the estimated and measured values ​​of the state to be estimated, and ΔU be the error between the estimated and measured values ​​of the input quantity.

[0071] Step 3: Determine the linear state feedback control model corresponding to the non-interference term based on the flight state parameters.

[0072] In this embodiment of the application, the linear state feedback control model is specifically as follows:

[0073]

[0074] Where, δ e1 To obtain the elevator deflection for linear state feedback calculation, k α k is the angle-of-attack tracking error feedback coefficient. α >0, k q k is the pitch angular velocity feedback coefficient. q >0.

[0075] Specifically, the angle-of-attack force interference term f in the short-period model is ignored. α And pitch angular velocity torque disturbance term f q Subsequently, the short-period motion model simplifies to the following quasi-linear system:

[0076]

[0077] Define the tracking error e = α - α d The error equation for the above quasi-linear system is:

[0078]

[0079] Define the state variable x = [eq] T And the following matrix:

[0080] b = [0 b q ] T ,b d =[1 0] T c = [1 0]

[0081] The error equation can then be rewritten in the following form:

[0082]

[0083] To design a linear state feedback controller based on the above formula, we have:

[0084]

[0085] Step 4: Determine the compensation model corresponding to the interference term based on the flight state parameters.

[0086] In the embodiments of this application, the angle-of-attack interference term f α This is a mismatch interference and cannot be compensated for using input feedback. (Regarding f) α and f q The compensation models are designed as follows:

[0087]

[0088] Among them, K d K represents the interference compensation gain. x For linear feedback gain, f α For the force interference term of the angle-of-attack channel, f q For the torque disturbance term of the pitch angular velocity channel, δ e2 Indicates the compensation interference term f α and f q Required elevator deflection; b = [0 b q ] T ,b d =[1 0] T c = [1 0].

[0089] Step 5: Determine the nonlinear adaptive control law of the target aircraft based on the linear state feedback control model and the compensation model.

[0090] In this embodiment, by combining the linear state feedback controller and the disturbance term compensation controller, a nonlinear adaptive control law of the following form is obtained:

[0091]

[0092] Step 6: Control the target aircraft according to the nonlinear adaptive control law.

[0093] To illustrate the feasibility of the above embodiments, the following example is given:

[0094] Taking a typical flight state of a wide-speed-range aircraft as an example, the design process of the longitudinal adaptive controller is illustrated. The longitudinal short-period motion model of this aircraft at a flight altitude of 8 km, Mach number of 0.7, and trim angle of attack α of approximately 2° is as follows:

[0095]

[0096] In the above formula, α is the angle of attack (in rad), q is the pitch angular velocity (in rad / s), and δ e Elevator (unit: rad).

[0097] Design a linear state feedback controller.

[0098] Ignoring matched and unmatched disturbances in the short-period motion model, it simplifies to the following quasi-linear system:

[0099]

[0100] Define the tracking error e = α - α d State variable x = [eq] T Subsequently, the linear state feedback controller was designed as follows:

[0101]

[0102] Take k α =18, k q =6, then the feedback control gain K is obtained. x =[0.2511 0.0837].

[0103] Design an interference compensator

[0104] Compensators are designed separately for mismatched interference and matched interference, where the mismatched interference f is... α The feedback gain is calculated as follows:

[0105] K d =-[c(A+bK)] x )b] -1 c(A+bK x ) -1 b d =0.0047

[0106] For matching interference f q and mismatch interference f α The interference compensator is:

[0107]

[0108] Determine the parameters of the interference estimator

[0109] Matching interference f qand mismatch interference f α An interference estimator is needed for compensation. The parameters of the interference estimator are selected as η = 1.1 and μ = 0.6.

[0110] Constructing a longitudinal nonlinear adaptive control law

[0111] By combining the linear state feedback controller and the disturbance compensator, the following longitudinal nonlinear adaptive control law is obtained:

[0112]

[0113] Simulation verification

[0114] The effectiveness of the longitudinal nonlinear adaptive control law for the longitudinal flight control of a wide-speed-range aircraft was verified by simulation. The simulation results are as follows: Figures 2-7 As shown. By Figure 2 It can be seen that the proposed longitudinal nonlinear adaptive controller can ensure that the wide-speed-range aircraft accurately tracks the angle-of-attack command. Figure 3 and Figure 4 It can be seen that the longitudinal attitude change of the wide-speed-range aircraft is relatively small during flight. Figure 5 The elevator deflection during the test was smooth, without any drastic changes in amplitude. Figure 6 and Figure 7 The paper presents online estimation results for longitudinal unmatched and matched disturbances of a wide-speed-range aircraft during flight. The results of angle-of-attack command tracking show that the estimator accurately estimates the disturbances. In conclusion, the simulation results verify the effectiveness of the proposed longitudinal nonlinear adaptive control method for longitudinal flight control of a wide-speed-range aircraft.

[0115] This application provides a longitudinal adaptive control device for a wide-speed-range aircraft, including: an acquisition module, a data processing module, and a control module;

[0116] The acquisition module is used to acquire flight status parameters;

[0117] The data processing module is used to determine the longitudinal motion model of the target aircraft based on the flight state parameters and short-period motion; the longitudinal motion model includes disturbance and non-disturbance terms; determine the linear state feedback control model corresponding to the non-disturbance terms based on the flight state parameters; determine the compensation model corresponding to the disturbance terms based on the flight state parameters; and determine the nonlinear adaptive control law of the target aircraft based on the linear state feedback control model and the compensation model.

[0118] The control module is used to control the target aircraft according to the nonlinear adaptive control law.

[0119] In this embodiment of the application, the device further includes a preprocessing module; the data processing module is further configured to determine an interference estimation model based on the flight state parameters, wherein the interference estimation model is capable of simultaneously calculating the angle-of-attack interference term and the pitch angular velocity torque interference term.

[0120] In this embodiment of the application, the interference estimation model is specifically as follows:

[0121]

[0122] in, Let denot be the time-varying diagonal dominant matrix used for unknown parameter estimation at step k, η and μ be the disturbance estimator parameters, ΔY be the deviation between the estimated and measured values ​​of the state to be estimated, and ΔU be the error between the estimated and measured values ​​of the input quantity.

[0123] This application provides a storage medium, including:

[0124] Used to store computer-executable instructions, which, when executed, implement the following process:

[0125] The foregoing has described specific embodiments of this specification. Other embodiments are within the scope of the appended claims. In some cases, the actions or steps recited in the claims may be performed in a different order than that shown in the embodiments and may still achieve the desired result. Furthermore, the processes depicted in the drawings do not necessarily require the specific or sequential order shown to achieve the desired result. In some embodiments, multitasking and parallel processing are possible or may be advantageous.

[0126] In the 1930s, improvements to a technology could be clearly distinguished as either hardware improvements (e.g., improvements to the circuit structure of diodes, transistors, switches, etc.) or software improvements (improvements to the methodology). However, with technological advancements, many improvements to the methodology today can be considered direct improvements to the hardware circuit structure. Designers almost always obtain the corresponding hardware circuit structure by programming the improved methodology into the hardware circuit. Therefore, it cannot be said that an improvement to the methodology cannot be implemented using a hardware physical module. For example, a Programmable Logic Device (PLD) (e.g., a Field Programmable Gate Array (FPGA)) is such an integrated circuit whose logic function is determined by the user programming the device. Designers can program a digital system themselves to "integrate" it onto a PLD, without needing chip manufacturers to design and manufacture dedicated integrated circuit chips. Furthermore, nowadays, instead of manually manufacturing integrated circuit chips, this programming is mostly implemented using "logic compiler" software. Similar to the software compiler used in program development, the original code before compilation must be written in a specific programming language, called a Hardware Description Language (HDL). There are many HDLs, such as ABEL (Advanced Boolean Expression Language), AHDL (Altera Hardware Description Language), Confluence, CUPL (Cornell University Programming Language), HDCal, JHDL (Java Hardware Description Language), Lava, Lola, MyHDL, PALASM, and RHDL (Ruby Hardware Description Language). Currently, the most commonly used are VHDL (Very-High-Speed ​​Integrated Circuit Hardware Description Language) and Verilog. Those skilled in the art should understand that by simply performing some logic programming on the method flow using one of these hardware description languages ​​and programming it into an integrated circuit, the hardware circuit implementing the logical method flow can be easily obtained.

[0127] The controller can be implemented in any suitable manner. For example, it can take the form of a microprocessor or processor and a computer-readable medium storing computer-readable program code (e.g., software or firmware) executable by the (micro)processor, logic gates, switches, application-specific integrated circuits (ASICs), programmable logic controllers, and embedded microcontrollers. Examples of controllers include, but are not limited to, the following microcontrollers: ARC 625D, Atmel AT91SAM, Microchip PIC18F26K20, and Silicon Labs C8051F320. A memory controller can also be implemented as part of the control logic of the memory. Those skilled in the art will also recognize that, in addition to implementing the controller in purely computer-readable program code form, the same functionality can be achieved by logically programming the method steps to make the controller take the form of logic gates, switches, application-specific integrated circuits, programmable logic controllers, and embedded microcontrollers. Therefore, such a controller can be considered a hardware component, and the means included therein for implementing various functions can also be considered as structures within the hardware component. Alternatively, the means for implementing various functions can be considered as both software modules implementing the method and structures within the hardware component.

[0128] The systems, devices, modules, or units described in the above embodiments can be implemented by computer chips or entities, or by products with certain functions. A typical implementation device is a computer. Specifically, a computer can be, for example, a personal computer, laptop computer, cellular phone, camera phone, smartphone, personal digital assistant, media player, navigation device, email device, game console, tablet computer, wearable device, or any combination of these devices.

[0129] For ease of description, the above apparatus is described by dividing it into various functional units. Of course, when implementing the embodiments of this specification, the functions of each unit can be implemented in one or more software and / or hardware.

[0130] Those skilled in the art will understand that one or more embodiments of this specification can be provided as a method, system, or computer program product. Therefore, one or more embodiments of this specification may take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, this specification may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0131] This specification is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of this specification. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create a machine for implementing the flowchart illustrations and / or block diagrams. Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0132] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0133] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0134] In a typical configuration, a computing device includes one or more processors (CPU), input / output interfaces, network interfaces, and memory.

[0135] Memory may include non-persistent storage in computer-readable media, such as random access memory (RAM) and / or non-volatile memory, such as read-only memory (ROM) or flash RAM. Memory is an example of computer-readable media.

[0136] Computer-readable media includes both permanent and non-permanent, removable and non-removable media that can store information using any method or technology. Information can be computer-readable instructions, data structures, modules of programs, or other data. Examples of computer storage media include, but are not limited to, phase-change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technologies, CD-ROM, digital versatile optical disc (DVD) or other optical storage, magnetic tape, magnetic magnetic disk storage or other magnetic storage devices, or any other non-transferable medium that can be used to store information accessible by a computing device. As defined herein, computer-readable media does not include transient computer-readable media, such as modulated data signals and carrier waves.

[0137] It should also be noted that the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes said element.

[0138] One or more embodiments of this specification can be described in the general context of computer-executable instructions, such as program modules, that are executed by a computer. Generally, program modules include routines, programs, objects, components, data structures, etc., that perform a particular task or implement a particular abstract data type. One or more embodiments of this specification can also be practiced in distributed computing environments where tasks are performed by remote processing devices connected via a communication network. In distributed computing environments, program modules can reside in local and remote computer storage media, including storage devices.

[0139] The various embodiments in this specification are described in a progressive manner. Similar or identical parts between embodiments can be referred to interchangeably. Each embodiment focuses on describing the differences from other embodiments. In particular, the system embodiments are basically similar to the method embodiments, so the description is relatively simple; relevant parts can be referred to the descriptions in the method embodiments.

[0140] The above description is merely an embodiment of this document and is not intended to limit the scope of this document. Various modifications and variations can be made to this document by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of this document should be included within the scope of the claims of this document.

Claims

1. A longitudinal adaptive control method for a wide-speed-range aircraft, characterized in that, include: Obtain flight status parameters; Based on the flight state parameters, a longitudinal motion model is established based on short-period motion. The longitudinal motion model includes interference terms and non-interference terms. The interference term is estimated using an interference estimation model; Based on the flight state parameters, determine the linear state feedback control model corresponding to the non-interference term; Based on the flight state parameters, determine the compensation model corresponding to the interference term; Based on the linear state feedback control model and the compensation model, the nonlinear adaptive control law of the target aircraft is determined; The target aircraft is controlled according to the aforementioned nonlinear adaptive control law; The estimation of the interference term using the interference estimation model includes: Establish disturbance estimation models for angle of attack and pitch angular velocity; The estimated values ​​of the flight state parameters are calculated based on the disturbance estimation model of the angle of attack and pitch angular velocity, and the error between the true value and the estimated value of the flight state parameters is determined. Based on the error, the interference term is determined by the interference estimator; The specific disturbance estimation model is as follows: in, This represents the time-varying diagonally dominant matrix with the k-th step size used for unknown parameter estimation. and For the interference estimator parameters, The deviation between the estimated value and the measured value of the state to be estimated. This indicates the error between the estimated input value and the measured value.

2. The method according to claim 1, characterized in that, The longitudinal motion model is specifically as follows: In the above formula, For the angle of attack, The pitch angular velocity, For elevators, For the force interference term of the angle of attack channel, For the torque disturbance term of the pitch angular velocity channel, To improve pitch control efficiency.

3. The method according to claim 1, characterized in that, The linear state feedback control model is specifically as follows: in, Elevator deflection is obtained through linear state feedback calculation. This is the angle-of-attack tracking error feedback coefficient. , The pitch angular velocity feedback coefficient, x is the state variable, e is the tracking error, and q is the pitch angular velocity. This is the linear feedback gain.

4. The method according to claim 1, characterized in that, The compensation model is as follows: in, Indicates the interference compensation gain. For linear feedback gain, For the force interference term of the angle of attack channel, For the torque disturbance term of the pitch angular velocity channel, Indicates compensation for interference terms and Required elevator deflection; .

5. A longitudinal adaptive control device for a wide-speed-range aircraft, characterized in that, include: The module consists of an acquisition module, a data processing module, and a control module. The acquisition module is used to acquire flight status parameters; The data processing module is used to establish a longitudinal motion model based on short-period motion according to the flight state parameters. The longitudinal motion model includes disturbance and non-disturbance terms. The disturbance terms are estimated using a disturbance estimation model. The compensation model corresponding to the disturbance terms is determined according to the flight state parameters. The nonlinear adaptive control law of the target aircraft is determined according to the linear state feedback control model and the compensation model. The control module is used to control the target aircraft according to the nonlinear adaptive control law; The device also includes a preprocessing module; The data processing module is also used to establish an interference estimation model for angle of attack and pitch angular velocity; The estimated values ​​of the flight state parameters are calculated based on the disturbance estimation model of the angle of attack and pitch angular velocity, and the error between the true value and the estimated value of the flight state parameters is determined. Based on the error, the interference term is determined by the interference estimator; The specific disturbance estimation model is as follows: in, This represents the time-varying diagonally dominant matrix with the k-th step size used for unknown parameter estimation. and For the interference estimator parameters, The deviation between the estimated value and the measured value of the state to be estimated. This indicates the error between the estimated input value and the measured value.

6. A storage medium, characterized in that, include: Used to store computer-executable instructions, which, when executed, implement the method of any one of claims 1 to 4.

Images