Method and system for determining flight path and joystick quantity in helicopter autorotation landing process
By optimizing the flight trajectory through extended Kalman filtering and expert knowledge base, and combining the inverse simulation method to calculate the joystick amount, the accuracy and real-time problems of trajectory and joystick amount calculation during helicopter autorotation and landing are solved, and fast and accurate joystick amount calculation is achieved.
Patent Information
- Application Number
- CN202510869354.8
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2025-06-26
- Publication Date
- 2025-09-26
AI Technical Summary
During the autorotation landing process of a helicopter, existing methods have difficulty in achieving accurate and real-time calculation of flight trajectory and joystick amount, which are limited by complex dynamic characteristics and dependence on real-time data.
The extended Kalman filter algorithm is used to filter the flight status data, and the recommended flight trajectory is determined by combining the expert knowledge base and the SQP optimization algorithm. The inverse simulation method is used to calculate the joystick amount. By combining the expert knowledge base and the inverse simulation method, the joystick amount can be calculated quickly and accurately.
The accuracy and real-time performance of flight trajectory planning and joystick amount determination during autorotation landing are improved, calculation errors are reduced, and the requirements for emergency landing of helicopters are met.
Smart Images
Figure CN120704305A_ABST
Abstract
Description
Technical Field
[0001] The present application relates to the technical field of helicopters, and in particular to a method and system for determining a flight trajectory and a joystick amount during the autorotation and landing process of a helicopter. Background Art
[0002] An autorotation landing is a unique unpowered landing process for rotorcraft. During this state, the helicopter relies on inflow from below to propel the rotors. After the helicopter engine shuts down mid-air, the available energy is limited, necessitating precise maneuvering at the right time to ensure a safe landing. However, accurate modeling of helicopters is difficult due to the complex, strongly coupled, and highly nonlinear dynamics of the helicopter. This makes it difficult to accurately calculate the control stick movement during an autorotation landing.
[0003] While some methods currently attempt to calculate trajectories and control variables using flight dynamics models, these methods suffer from the following limitations: 1) Poor real-time performance: Traditional calculation methods require significant computing resources and struggle to quickly provide accurate control variables in a real-time environment. 2) Large errors: Due to the nonlinear and coupled characteristics of helicopters, traditional calculation methods struggle to accurately predict flight trajectories and control variables. 3) Reliance on real-time data: Traditional calculation methods require the acquisition of large amounts of flight data in real time, placing extremely high demands on sensor accuracy and reliability.
[0004] Therefore, it is necessary to provide a method for determining the flight trajectory and joystick amount during the autorotation landing process of a helicopter to solve the above problems. Summary of the Invention
[0005] The purpose of this application is to provide a method and system for determining the flight trajectory and joystick amount during the autorotation and landing of a helicopter, so as to improve the accuracy and real-time performance of flight trajectory planning and joystick amount determination during the autorotation and landing of a helicopter.
[0006] To achieve the above objectives, this application provides the following solutions:
[0007] In a first aspect, the present application provides a method for determining a flight trajectory and a joystick amount during a helicopter autorotation and landing process, the method comprising:
[0008] When the helicopter is preparing to autorotate and land, obtain the flight status data of the helicopter at the current moment;
[0009] The extended Kalman filter algorithm is used to filter the flight status data of the helicopter at the current moment to obtain the filtered flight status data of the helicopter at the current moment;
[0010] Using the expert knowledge base, based on the filtered flight status data of the helicopter at the current moment, the recommended flight trajectory of the helicopter in the preset future period is obtained;
[0011] Based on the recommended flight trajectory of the helicopter in the preset future period, a recommended three-axis flight speed and a recommended yaw angular velocity of the helicopter in the preset future period are obtained;
[0012] The inverse simulation method is used to obtain the recommended joystick amount of the helicopter in the preset future period based on the recommended three-axis flight speed and recommended yaw angular velocity of the helicopter in the preset future period.
[0013] Optionally, after obtaining the recommended joystick amount for the helicopter in the preset future time period based on the recommended three-axis flight speed and the recommended yaw angular velocity of the helicopter in the preset future time period by using the inverse simulation method, the method further includes:
[0014] The recommended flight trajectory of the helicopter in a preset future period and the recommended joystick amount of the helicopter in the preset future period are presented in a visual form to assist the pilot in controlling the helicopter to autorotate and land.
[0015] Optionally, the flight status data includes flight position data and flight attitude data; the flight position data includes: latitude and longitude data, altitude data, and three-axis acceleration data; the three-axis acceleration data includes: xyz-axis acceleration under the body axis system; the flight attitude data includes: attitude angle data and three-axis angular velocity data; the attitude angle data includes pitch angle, roll angle, and yaw angle; the three-axis angular velocity data includes the xyz-axis angular velocity under the body axis system.
[0016] Optionally, the expert knowledge base is used to obtain a recommended flight trajectory for the helicopter in a preset future time period based on the filtered flight status data of the helicopter at the current moment, specifically including:
[0017] Input the filtered flight status data and flight phase of the helicopter at the current moment into the expert knowledge base to search for matching flight scenarios for the helicopter;
[0018] Load the flight dynamics constraints corresponding to the helicopter's matching flight scenario to obtain multiple historical flight trajectories;
[0019] The SQP optimization algorithm is used to iteratively optimize multiple historical flight trajectories to obtain the recommended flight trajectory of the helicopter in the preset future period.
[0020] Optionally, based on the recommended flight trajectory of the helicopter in a preset future time period, obtaining the recommended three-axis flight speed and recommended yaw angular velocity of the helicopter in the preset future time period specifically includes:
[0021] Derivative the position of the helicopter in the Earth's axis system in the recommended flight trajectory for the preset future period with respect to time to obtain the recommended three-axis flight speed of the helicopter for the preset future period;
[0022] The yaw angle of the helicopter in the recommended flight trajectory of the preset future period is derived with respect to time in the earth axis system to obtain a recommended yaw angular velocity of the helicopter in the preset future period.
[0023] Optionally, an inverse simulation method is used to obtain a recommended joystick amount for the helicopter in the preset future period based on the recommended three-axis flight speed and recommended yaw angular velocity of the helicopter in the preset future period, specifically including:
[0024] Any future moment in the preset future period is taken as the current future moment, and the next future moment after the current future moment is taken as the next future moment;
[0025] Obtaining the actual three-axis flight speed, the actual yaw angular velocity, and the preset joystick amount of the helicopter at the current future moment; when the current future moment is the first future moment of the preset future period, the current future moment is the current moment;
[0026] An inverse simulation method is adopted, using the flight dynamics model of the helicopter, to determine the predicted three-axis flight speed and the predicted yaw rate of the helicopter at the next future moment based on the actual three-axis flight speed of the helicopter at the current future moment, the actual yaw rate of the helicopter at the current future moment, and the preset joystick amount at the current future moment;
[0027] Determining an objective function value at a current future time based on the predicted three-axis flight speed and the predicted yaw rate of the helicopter at the next future time, the recommended three-axis flight speed and the recommended yaw rate at the next future time;
[0028] Determine whether the objective function value at the current future moment is less than the preset function value;
[0029] If so, the preset joystick amount at the current future time is used as the recommended joystick amount at the current future time;
[0030] If not, the Newton iteration method is used to correct the preset joystick amount at the current future moment, and the corrected preset joystick amount at the current future moment is updated to the preset joystick amount at the current future moment, until the objective function value at the current future moment is less than the preset function value, and the preset joystick amount at the current future moment is used as the recommended joystick amount at the current future moment.
[0031] In a second aspect, the present application further provides a system for determining a flight trajectory and a joystick amount during a helicopter autorotation and landing process. The system for determining a flight trajectory and a joystick amount during a helicopter autorotation and landing process is used to implement the method for determining a flight trajectory and a joystick amount during a helicopter autorotation and landing process. The system for determining a flight trajectory and a joystick amount during a helicopter autorotation and landing process includes:
[0032] A data acquisition unit, used to acquire the flight status data of the helicopter at the current moment when the helicopter is preparing for autorotation landing;
[0033] A filtering unit is used to filter the flight status data of the helicopter at the current moment by using an extended Kalman filter algorithm to obtain filtered flight status data of the helicopter at the current moment;
[0034] a recommended flight trajectory determination unit, configured to obtain a recommended flight trajectory for the helicopter in a preset future period based on the filtered flight state data of the helicopter at the current moment, using an expert knowledge base;
[0035] a recommended three-axis flight speed and recommended yaw rate determination unit, configured to obtain a recommended three-axis flight speed and a recommended yaw rate of the helicopter in a preset future period based on the recommended flight trajectory of the helicopter in the preset future period;
[0036] The recommended joystick amount determination unit is used to obtain the recommended joystick amount of the helicopter in the preset future period based on the recommended three-axis flight speed and recommended yaw angular velocity of the helicopter in the preset future period by adopting an inverse simulation method.
[0037] Optionally, the system further comprises:
[0038] The display unit is used to present the recommended flight trajectory of the helicopter in a preset future period and the recommended joystick amount of the helicopter in the preset future period in a visual form to assist the pilot in controlling the helicopter to autorotate and land.
[0039] Optionally, the recommended flight trajectory determination unit specifically includes:
[0040] A matching flight scenario determination module is used to input the filtered flight status data and flight phase of the helicopter at the current moment into the expert knowledge base to search for a matching flight scenario for the helicopter;
[0041] A historical flight trajectory determination module is used to load the flight mechanics constraints corresponding to the helicopter's matching flight scenario to obtain multiple historical flight trajectories;
[0042] The recommended flight trajectory determination module is used to iteratively optimize multiple historical flight trajectories using the SQP optimization algorithm to obtain the recommended flight trajectory of the helicopter in a preset future period.
[0043] Optionally, the recommended three-axis flight speed and recommended yaw angular velocity determination unit specifically includes:
[0044] A recommended three-axis flight speed determination module is used to perform a time derivative of the position of the helicopter in the earth axis system in the recommended flight trajectory for a preset future period to obtain the recommended three-axis flight speed of the helicopter for the preset future period;
[0045] The recommended yaw rate determination module is used to derive the yaw angle of the helicopter in the earth axis system in the recommended flight trajectory of the helicopter in the preset future period with respect to time to obtain the recommended yaw rate of the helicopter in the preset future period.
[0046] According to the specific embodiments provided in this application, this application has the following technical effects:
[0047] This application discloses a method and system for determining the flight trajectory and joystick amount during a helicopter autorotation and landing process. The method first uses an expert knowledge base to provide a recommended flight trajectory, which has the advantages of reliable data and offline calculation, and can quickly calculate the recommended flight trajectory based on real-time flight status data. The inverse simulation method is then used to calculate the recommended joystick amount, which has a fast solution speed and small error, thereby improving the speed of calculating the recommended joystick amount. The method of jointly calculating the recommended joystick amount using the expert knowledge base and the inverse simulation method has the advantages of faster speed and higher accuracy compared to the method of calculating the trajectory through a flight dynamics model and then optimizing the joystick amount through the trajectory. This application improves the accuracy and real-time performance of flight trajectory planning and joystick amount determination during a helicopter autorotation and landing process. BRIEF DESCRIPTION OF THE DRAWINGS
[0048] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.
[0049] Figure 1 A flowchart of a method for determining a flight trajectory and joystick amount during a helicopter autorotation landing process provided by one embodiment of the present application;
[0050] Figure 2 A block diagram of the control process of a helicopter during autorotation landing provided in one embodiment of the present application;
[0051] Figure 3 A schematic diagram of a process for determining a recommended flight trajectory for a helicopter in a preset future time period based on an expert knowledge base provided in one embodiment of the present application;
[0052] Figure 4 A schematic diagram of a flight dynamics model provided in one embodiment of the present application;
[0053] Figure 5 A schematic diagram of a process for calculating a recommended joystick amount according to an embodiment of the present application;
[0054] Figure 6 A schematic diagram of a display interface of a display screen in a stable sliding section provided by an embodiment of the present application;
[0055] Figure 7 A schematic diagram of the display interface of a display screen during deceleration, leveling, and landing stages provided in one embodiment of the present application. DETAILED DESCRIPTION
[0056] The following will be combined with the drawings in the embodiments of this application to clearly and completely describe the technical solutions in the embodiments of this application. Obviously, the embodiments described are only part of the embodiments of this application, not all of the embodiments. Based on the embodiments in this application, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of this application.
[0057] In order to make the above-mentioned purposes, features and advantages of the present application more obvious and easy to understand, the present application is further described in detail below with reference to the accompanying drawings and specific implementation methods.
[0058] In an exemplary embodiment, Figure 1 and Figure 2 As shown, a method for determining the flight trajectory and joystick amount during the autorotation landing of a helicopter is provided, comprising the following steps.
[0059] Step S1: When the helicopter is preparing to autorotate and land, the flight status data of the helicopter at the current moment is obtained.
[0060] As an optional implementation, the flight status data includes flight position data and flight attitude data; the flight position data includes: latitude and longitude data, altitude data, and three-axis acceleration data; the three-axis acceleration data includes: xyz-axis acceleration under the body axis system; the flight attitude data includes: attitude angle data and three-axis angular velocity data; the attitude angle data includes pitch angle, roll angle, and yaw angle; the three-axis angular velocity data includes the xyz-axis angular velocity under the body axis system.
[0061] Specifically, the helicopter's flight status data is collected through a variety of sensors, including GPS, which collects latitude and longitude data; a barometer, which collects altitude data; an accelerometer, which collects three-axis acceleration data; a magnetometer, which collects attitude angle data; and a gyroscope, which collects three-axis angular velocity data.
[0062] Step S2: Using an extended Kalman filter algorithm, the flight status data of the helicopter at the current moment is filtered to obtain the filtered flight status data of the helicopter at the current moment.
[0063] Specifically, the electrical signals measured by helicopter sensors (i.e., flight status data) can generate erroneous signals due to internal sensor disturbances (such as voltage and power fluctuations) and external disturbances (such as mechanical vibration and installation bias). Therefore, filtering the directly measured electrical signals is necessary. This filtering significantly reduces the impact of these internal and external disturbances, allowing for the acquisition of high-confidence data.
[0064] The Extended Kalman Filter (EKF) algorithm is a matrix operation process that predicts current data using data calculated in the past and proportionally integrates it with the current actual measured data to obtain current data with high confidence. The core of the EKF algorithm is the Jacobian matrix F and the covariance matrix. The Jacobian matrix is the derivative between the input values and is an offline calculated matrix. For example, if the input is the Earth axis position measured by GPS and the body axis acceleration measured by the accelerometer, the acceleration in the body axis must be rotated to the Earth axis, and then integrated twice to be equal to the Earth axis position. The Jacobian matrix is constructed using this type of formula. The covariance matrix is used to quantify uncertainty. Larger uncertainties will lead to higher Kalman gains, thereby trusting new measurements more; conversely, lower uncertainties will lead to less trust in new measurements. The Extended Kalman Filter algorithm process is as follows:
[0065] 1) Define the Jacobian matrix F based on the laws of physics. The Jacobian matrix contains the reciprocal relationships between 24 state quantities: quaternions, Earth-axis velocity in the N direction, Earth-axis velocity in the E direction, Earth-axis velocity in the D direction, Earth-axis position in the N direction, Earth-axis position in the E direction, Earth-axis position in the D direction, roll angle change, pitch angle change, yaw angle change, body-axis x-axis velocity change, body-axis y-axis velocity change, body-axis z-axis velocity change, Earth-axis wind speed in the N direction, Earth-axis wind speed in the E direction, body-axis x-axis magnetic field strength, body-axis y-axis magnetic field strength, body-axis z-axis magnetic field strength, Earth-axis magnetic field strength in the N direction, Earth-axis magnetic field strength in the E direction, and Earth-axis magnetic field strength in the D direction. Quaternions represent rotations and are more efficient in mathematical operations than rotation matrices using attitude angles.
[0066] 2) Offline gives the process noise covariance matrix Q and the measurement noise covariance matrix R. Initialize the state covariance matrix P according to the control system simulation, and initialize the flight state data x at time k-1 according to the current flight state. k-1 (The initial value is obtained through control system simulation calculation).
[0067] 3) (Prediction): P = FPF T +Q, the state covariance matrix of the current moment is calculated by the state covariance matrix of the previous moment; T represents the transpose of the matrix.
[0068] 4) (Update): Get the measured value z of the current flight status data, through K = P (P + R) -1 Calculate the Kalman gain K by x k =x k-1 +K(zx k-1 ) Calculate the measurement value x of the current flight status data with high confidence k , the final calculation P=(IK H )P -1 Update P again; I is the identity matrix and H is the measurement matrix.
[0069] Step S3, using the expert knowledge base, based on the filtered flight status data of the helicopter at the current moment, obtains a recommended flight trajectory of the helicopter in a preset future time period.
[0070] As an optional implementation, step S3 specifically includes:
[0071] In step S31 , the filtered flight status data and flight phase of the helicopter at the current moment are input into the expert knowledge base to search for a matching flight scene of the helicopter.
[0072] Step S32 : loading the flight mechanics constraints corresponding to the matching flight scene of the helicopter to obtain multiple historical flight trajectories.
[0073] In step S33 , a Sequential Quadratic Programming (SQP) optimization algorithm is used to iteratively optimize the multiple historical flight trajectories to obtain a recommended flight trajectory for the helicopter in a preset future period.
[0074] Specifically, the expert knowledge base, built from test data, stores historical flight scenarios, including expert pilot flight paths and autorotation landing requirements at different altitudes, speeds, and attitudes. The expert knowledge base is a dynamic optimization decision-making system implemented through the collaborative efforts of three components: a pilot operation case library, flight dynamics constraints, and fuzzy control rules.
[0075] After inputting the real-time flight status and the current flight phase (stable descent phase or deceleration, leveling, and landing phase) into the expert knowledge base, the expert knowledge base will match historical flight scenarios with high similarity and load the flight mechanics constraints of the corresponding scenarios to obtain multiple historical flight trajectories. Finally, the SQP optimization algorithm (i.e., sequential quadratic programming algorithm) is applied to the multiple historical flight trajectories to obtain a recommended flight trajectory for the entire future flight (stable descent phase) or a recommended flight trajectory for the next 10 seconds (deceleration, leveling, and landing phase) that is suitable for the current flight status. The specific process is as follows: Figure 3 The SQP algorithm combines the advantages of the Newton method and the Lagrange multiplier method and is capable of handling optimization problems with constraints. The expert knowledge base is updated every 1-2 seconds based on current flight data to ensure accurate flight trajectories. This periodic update of recommended trajectories prevents cumulative errors caused by unpredictable disturbances.
[0076] Step S4: Based on the recommended flight trajectory of the helicopter in the preset future time period, a recommended three-axis flight speed and a recommended yaw angular velocity of the helicopter in the preset future time period are obtained.
[0077] As an optional implementation, step S4 specifically includes:
[0078] Step S41 , performing a time derivative of the position of the helicopter in the earth axis system in the recommended flight trajectory for the preset future period, to obtain the recommended three-axis flight speed of the helicopter for the preset future period.
[0079] Step S42 , performing a time derivative of the yaw angle of the helicopter in the earth axis system in the recommended flight trajectory of the helicopter in the preset future period, to obtain a recommended yaw angular velocity of the helicopter in the preset future period.
[0080] Specifically, the recommended flight trajectory given by the expert knowledge base is derivatized with respect to time, and the recommended flight trajectory [x, y, z, ψ] (x, y, z represent the three-axis position coordinates in the earth axis system, and ψ represents the yaw angle of the helicopter) for the next period of time is converted into the recommended three-axis flight speed and yaw angular velocity V for the next period of time. (0-T) =[u, v, w, r] (u, v, w represent the three-axis velocities in the earth's axis system, and r represents the helicopter's yaw angular velocity), and the flight guidance rate is determined.
[0081] Step S5: using an inverse simulation method, based on the recommended three-axis flight speed and the recommended yaw rate of the helicopter in the preset future period, obtain the recommended joystick amount of the helicopter in the preset future period.
[0082] As an optional implementation, Figure 5 As shown, step S5 specifically includes:
[0083] In step S51 , any future moment in a preset future time period is used as the current future moment, and the next future moment after the current future moment is used as the next future moment.
[0084] Step S52: Obtain the actual three-axis flight speed and the actual yaw rate of the helicopter at the current future time (the actual three-axis flight speed and the actual yaw rate correspond to the actual yaw rate). Figure 5 the flight status in the current future time) and the preset joystick amount at the current future time; when the current future time is the first future time of the preset future time period, the current future time is the current time.
[0085] Step S53, adopting the inverse simulation method and utilizing the flight dynamics model of the helicopter, based on the actual three-axis flight speed of the helicopter at the current future moment, the actual yaw rate at the current future moment and the preset joystick amount at the current future moment, determines the predicted three-axis flight speed of the helicopter at the next future moment and the predicted yaw rate at the next future moment.
[0086] Step S54, determining the objective function value at the current future time based on the predicted three-axis flight speed and the predicted yaw rate of the helicopter at the next future time, the recommended three-axis flight speed and the recommended yaw rate at the next future time.
[0087] Among them, the three-axis flight speed error (including errors in three directions) is determined based on the predicted three-axis flight speed of the helicopter at the next future moment and the recommended three-axis flight speed at the next future moment, and the yaw angular velocity error is determined based on the predicted yaw angular velocity of the helicopter at the next future moment and the recommended yaw angular velocity at the next future moment, and the three-axis flight speed error and the yaw angular velocity error are recorded as the state error ef, and the objective function f=ef is defined.
[0088] Step S55: determine whether the target function value at the current future moment is less than the preset function value.
[0089] Step S56: If yes, the preset joystick amount at the current future time is used as the recommended joystick amount at the current future time.
[0090] Step S57: If not, use the Newton iteration method to correct the preset joystick amount at the current future time, and update the corrected preset joystick amount at the current future time as the preset joystick amount at the current future time, until the objective function value at the current future time is less than the preset function value, and use the preset joystick amount at the current future time as the recommended joystick amount at the current future time.
[0091] The partial derivatives of the objective function f at the current future time with respect to the preset joystick amount uinit at each current future time are calculated, and these partial derivatives are used to construct the partial derivative matrix J. The gradient equation Jeu = ef is then solved to obtain the output difference, which is used to correct the preset joystick amount at the current future time. In other words, the recommended joystick amount for each current future time in the preset future period is calculated using the Newton iteration method. Repeating the iterations continuously yields a combination of recommended joystick amounts for different current future times in the preset future period, forming the recommended joystick amount u(0-T) for the preset future period, where T represents the length of the preset future period.
[0092] Specifically, the inverse simulation method (also called inverse model) is the inverse solution process of the flight dynamics model. Figure 4 As shown in the figure, the flight dynamics model is a mathematical model used to describe and analyze the behavior and performance of a helicopter in flight. The model comprehensively considers the rotor dynamics, fuselage dynamics and six-degree-of-freedom motion equations of the helicopter; the rotor dynamics describes how the main rotor and tail rotor interact with the surrounding air to generate forces and torques, and the fuselage dynamics describes how the fuselage, horizontal tail and vertical tail interact with the surrounding air to generate forces and torques; the six-degree-of-freedom motion equations are established based on Newton's second law and are the basic set of equations that describe the changes in the helicopter's position, velocity, acceleration, attitude angle, angular velocity and angular acceleration.
[0093] The inverse simulation method requires the recommended three-axis flight speed and recommended yaw rate V(0-T) = [u, v, w, r] obtained from the flight guidance rate to calculate the recommended four joystick values (recommended main rotor collective pitch joystick value, recommended tail rotor collective pitch joystick value, recommended longitudinal joystick value, and recommended lateral joystick value). The solution method is the Newton iteration method, and the corresponding flow diagram is as follows: Figure 5 The inverse simulation method requires continuous internal updates and fixed-cycle reinitialization to ensure that the mathematical model attitude angle is correct.
[0094] As an optional implementation manner, after step S5, the method further includes:
[0095] Step S6: presenting the recommended flight trajectory of the helicopter in the preset future period and the recommended joystick amount of the helicopter in the preset future period in a visual form to assist the pilot in controlling the helicopter to autorotate and land.
[0096] Based on the same inventive concept, embodiments of the present application also provide a system for determining a flight trajectory and a joystick amount during a helicopter autorotation and landing process, for implementing the aforementioned method for determining a flight trajectory and a joystick amount during a helicopter autorotation and landing process. The solution provided by this system is similar to the solution described in the aforementioned method. Therefore, the specific limitations of one or more embodiments of the system for determining a flight trajectory and a joystick amount during a helicopter autorotation and landing process provided below can be found in the aforementioned limitations of the method for determining a flight trajectory and a joystick amount during a helicopter autorotation and landing process, and will not be further elaborated here.
[0097] In an exemplary embodiment, a system for determining a flight trajectory and a joystick amount during an autorotation landing of a helicopter is provided, comprising:
[0098] The data acquisition unit is used to acquire the flight status data of the helicopter at the current moment when the helicopter is preparing for autorotation landing.
[0099] The filtering unit is used to filter the flight status data of the helicopter at the current moment by using an extended Kalman filter algorithm to obtain the filtered flight status data of the helicopter at the current moment.
[0100] The recommended flight trajectory determination unit is used to obtain a recommended flight trajectory of the helicopter in a preset future period based on the filtered flight status data of the helicopter at the current moment by using the expert knowledge base.
[0101] The recommended three-axis flight speed and recommended yaw rate determination unit is used to obtain the recommended three-axis flight speed and recommended yaw rate of the helicopter in a preset future period based on the recommended flight trajectory of the helicopter in the preset future period.
[0102] The recommended joystick amount determination unit is used to obtain the recommended joystick amount of the helicopter in the preset future period based on the recommended three-axis flight speed and recommended yaw angular velocity of the helicopter in the preset future period by adopting an inverse simulation method.
[0103] As an optional implementation, the system further includes:
[0104] The display unit is used to present the recommended flight trajectory of the helicopter in a preset future period and the recommended joystick amount of the helicopter in the preset future period in a visual form to assist the pilot in controlling the helicopter to autorotate and land.
[0105] As an optional implementation, it is recommended that the flight trajectory determination unit specifically includes:
[0106] The matching flight scene determination module is used to input the filtered flight status data and flight phase of the helicopter at the current moment into the expert knowledge base to search for the matching flight scene of the helicopter.
[0107] The historical flight trajectory determination module is used to load the flight mechanics constraints corresponding to the matching flight scene of the helicopter to obtain multiple historical flight trajectories.
[0108] The recommended flight trajectory determination module is used to iteratively optimize multiple historical flight trajectories using the SQP optimization algorithm to obtain the recommended flight trajectory of the helicopter in a preset future period.
[0109] As an optional implementation manner, the recommended three-axis flight speed and recommended yaw angular velocity determination unit specifically includes:
[0110] The recommended three-axis flight speed determination module is used to perform a time derivative of the position of the helicopter in the earth axis system in the recommended flight trajectory of the preset future time period to obtain the recommended three-axis flight speed of the helicopter in the preset future time period.
[0111] The recommended yaw rate determination module is used to derive the yaw angle of the helicopter in the earth axis system in the recommended flight trajectory of the helicopter in the preset future period with respect to time to obtain the recommended yaw rate of the helicopter in the preset future period.
[0112] Specifically, the helicopter's flight computer must host an expert knowledge base, flight guidance parameters, and other information, as well as provide guidance from the display screen. Due to the high computational complexity, a CPU with at least eight cores and a maximum operating frequency of at least 2.4 GHz is required to ensure the stability of the real-time simulation running in conjunction with the expert knowledge base and flight dynamics model. The computer requires at least 16 GB of memory and at least 512 GB of storage to meet the necessary operational requirements.
[0113] The display screen uses a high-hardness, high-brightness display screen, requiring a touch screen hardness of 7H, a display size of no less than 10 inches, a resolution of 1920×1080, a display refresh rate of 60Hz, and a maximum brightness of no less than 500nits to meet the information acquisition capabilities during the helicopter flight.
[0114] The display shows the helicopter's recommended flight trajectory for a predetermined future period, its recommended three-axis flight speed and yaw rate, the recommended joystick position u, and real-time flight status data measured by sensors. Sideslip angle, a parameter of the airframe's dynamics, cannot be measured by sensors and is instead obtained indirectly through inverse simulation.
[0115] Pilots need quick access to visual data. During the different stages of an autorotation landing, pilots require different methods to obtain the necessary flight data. Therefore, different data display methods are designed for different flight processes. Pilots will receive recommended attitudes and flight paths during the steady glide phase, and recommended stick adjustments during the deceleration, leveling, and landing phases. The following describes the display screen content in detail, stage by stage.
[0116] 1) Stable decline
[0117] When the helicopter is in a stable descent, the collective pitch is reduced to save the energy of the helicopter rotor as much as possible. The display shows the calculated recommended flight path and the current attitude and speed of the helicopter. Figure 6 shown.
[0118] Figure 6 The interface shown includes boxes 1 to 6. Box 1 displays the current autorotation landing stage, and the stable descent stage is displayed as "stable descent section"; box 2 displays the current yaw angle and sideslip angle of the helicopter; box 3 displays the forward speed difference, right speed difference and descent speed difference. The data in the round brackets in each formula is the target speed, and the data in the square brackets is the current speed. The corresponding speed difference is calculated; box 4 displays the pitch angle difference. The data in the round brackets in the formula is the target pitch angle, and the data in the square brackets is the current pitch angle. The pitch angle difference is calculated; box 5 displays the current position information of the helicopter in the xy plane, the recommended flight trajectory in the xy plane and the xy plane deviation; box 6 displays the current height H and current distance information L of the helicopter, the height and distance information of the recommended flight trajectory, the height deviation and the distance deviation. Figure 6 In the figure, the recommended flight trajectory of the helicopter is a black solid line, the current position is a black dot, and the error is a black dotted line.
[0119] The pilot can obtain some helicopter flight attitude information through the information in boxes 2 to 4, and obtain helicopter flight position information, recommended flight trajectory and deviation information through the information in boxes 5 and 6.
[0120] 2) Deceleration, leveling and landing phase
[0121] When the helicopter is decelerating, leveling off, and landing, the helicopter's touchdown speed is minimized by increasing the collective pitch, while ensuring that the helicopter's attitude angle is within a safe range. The display shows the calculated recommended main rotor collective pitch stick amount and the recommended longitudinal stick amount, and also shows the helicopter's current main rotor collective pitch stick amount and the current longitudinal stick amount. The interface is as follows: Figure 7 shown.
[0122] Figure 7In the interface shown, box 1 displays the current autorotation landing phase, and the deceleration, leveling, and landing phase is displayed as "Deceleration, leveling, and landing phase"; in box 2, the black segmented line is a zoomed-out view of the recommended main rotor collective pitch stick amount for the helicopter in the next 7 seconds, and the black dot is the main rotor collective pitch stick amount of the helicopter at the current moment; in box 3, the black segmented line is a zoomed-out view of the recommended longitudinal stick amount for the helicopter in the next 7 seconds, and the black dot is the longitudinal stick amount of the helicopter at the current moment; in box 4, under normal circumstances, the position of the thick line segment remains unchanged, and this segment is defined as the main rotor collective pitch control amount and the longitudinal stick amount of the helicopter at the current moment; in box 5, an enlarged view of the recommended main rotor collective pitch control amount and the recommended longitudinal stick amount for the helicopter in the next 7 seconds is displayed; box 6 is a scale line, and one scale is defined as 1 cm.
[0123] The pilot adjusts the stick by measuring the error in the main rotor collective pitch and longitudinal stick values. If the intersection of the black segmented line and the scale line is below the bold line, the value should be increased; if the intersection of the black segmented line and the scale line is above the bold line, the value should be decreased. The left side of the interface shows the main rotor collective pitch stick value, and the right side shows the longitudinal stick value. Both curves have zoomed-out views above them. Both curves represent the recommended stick position for the final 7 seconds, calculated by the expert system. The pilot should adjust the stick position so that the left and right black segmented lines intersect with the bold line.
[0124] When the error in the main rotor collective pitch or longitudinal stick segment lines is too large to display, the bold line in the interface will move up or down to raise the upper limit of the error in that direction, resulting in a black segment line. If the difference between the front and back segments is significant and the segment lines are incomplete, the pilot can use the zoomed-out view above to determine the next maneuver.
[0125] The pilot obtains the recommended attitude and route (stable descent phase) or recommended joystick amount (deceleration leveling and landing phase), and controls the helicopter to complete the autorotation landing based on his own experience and the recommended values.
[0126] In order to solve the problem that it is difficult to accurately model helicopters and that the joystick amount in the autorotation landing process is difficult to calculate due to the complex, strongly coupled, and strongly nonlinear characteristics, the present application adopts an expert knowledge base and an inverse model method to first give a recommended flight trajectory and then calculate the recommended joystick amount. The expert knowledge base integrates the historical flight data of expert pilots and the boundary conditions that must exist during autorotation landing, and has the advantages of reliable data and fast calculation. The recommended flight trajectory can be quickly calculated based on real-time flight status data. The inverse simulation method has a fast solution speed and small error, which improves the speed of calculating the recommended joystick amount. The method of jointly calculating the recommended joystick amount using the expert knowledge base and the inverse simulation method has the advantages of faster speed and higher accuracy compared to the method of calculating the trajectory through a flight dynamics model and then optimizing the joystick amount through the trajectory.
[0127] In addition, this application is designed for helicopter pilots to obtain information during an emergency autorotation landing process, and different display interfaces are designed for the stable descent phase, deceleration and leveling, and landing phases, which meets the pilot's requirements for quickly obtaining useful information and improves the practicality of this application.
[0128] 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, stored data, displayed data, 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 relevant data must comply with relevant regulations.
[0129] Those skilled in the art will understand that all or part of the processes in the above-mentioned embodiment methods can be implemented by instructing the relevant hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to memory, database or other media used in the embodiments provided in this application may include at least one of non-volatile and volatile memory. Non-volatile memory may 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 may include random access memory (RAM) or external cache memory, etc. By way of illustration and not limitation, RAM may be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM).
[0130] The databases involved in the various embodiments provided herein may include at least one of a relational database and a non-relational database. Non-relational databases may include, but are not limited to, distributed databases based on blockchains. The processors involved in the various embodiments provided herein may include, but are not limited to, general-purpose processors, central processing units, graphics processing units, digital signal processors, programmable logic units, data processing logic units based on quantum computing, and the like.
[0131] The technical features of the above embodiments can be combined arbitrarily. To make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.
[0132] This document uses specific examples to illustrate the principles and implementation methods of this application. The description of the above examples is only intended to help understand the method, system, and core concept of this application. At the same time, those skilled in the art will find that the specific implementation methods and application scopes may vary based on the concept of this application. In summary, the contents of this specification should not be construed as limiting this application.
Claims
1. A method for determining the flight trajectory and joystick amount during the autorotation landing of a helicopter, characterized in that: The method for determining the flight trajectory and joystick amount during the helicopter autorotation landing process includes: When the helicopter is preparing to autorotate and land, obtain the flight status data of the helicopter at the current moment; The extended Kalman filter algorithm is used to filter the flight status data of the helicopter at the current moment to obtain the filtered flight status data of the helicopter at the current moment; Using the expert knowledge base, based on the filtered flight status data of the helicopter at the current moment, the recommended flight trajectory of the helicopter in the preset future period is obtained; Based on the recommended flight trajectory of the helicopter in the preset future period, a recommended three-axis flight speed and a recommended yaw angular velocity of the helicopter in the preset future period are obtained; The inverse simulation method is used to obtain the recommended joystick amount of the helicopter in the preset future period based on the recommended three-axis flight speed and recommended yaw angular velocity of the helicopter in the preset future period.
2. The method for determining the flight trajectory and joystick amount during the autorotation landing of a helicopter according to claim 1, characterized in that: After obtaining the recommended joystick amount for the helicopter in the preset future period based on the recommended three-axis flight speed and the recommended yaw rate of the helicopter in the preset future period using the inverse simulation method, the method further includes: The recommended flight trajectory of the helicopter in a preset future period and the recommended joystick amount of the helicopter in the preset future period are presented in a visual form to assist the pilot in controlling the helicopter to autorotate and land.
3. The method for determining the flight trajectory and joystick amount during the autorotation landing of a helicopter according to claim 1, characterized in that: Flight status data includes flight position data and flight attitude data; flight position data includes: latitude and longitude data, altitude data, and three-axis acceleration data; three-axis acceleration data includes: xyz-axis acceleration under the aircraft axis system; flight attitude data includes: attitude angle data and three-axis angular velocity data; attitude angle data includes pitch angle, roll angle, and yaw angle; three-axis angular velocity data includes xyz-axis angular velocity under the aircraft axis system.
4. The method for determining the flight trajectory and joystick amount during the autorotation landing of a helicopter according to claim 1, characterized in that: Using the expert knowledge base and the filtered flight status data of the helicopter at the current moment, the recommended flight trajectory of the helicopter in the preset future period is obtained, including: Input the filtered flight status data and flight phase of the helicopter at the current moment into the expert knowledge base to search for matching flight scenarios for the helicopter; Load the flight dynamics constraints corresponding to the helicopter's matching flight scenario to obtain multiple historical flight trajectories; The SQP optimization algorithm is used to iteratively optimize multiple historical flight trajectories to obtain the recommended flight trajectory of the helicopter in the preset future period.
5. The method for determining the flight trajectory and joystick amount during the autorotation landing of a helicopter according to claim 4, characterized in that: Based on the recommended flight trajectory of the helicopter in the preset future period, the recommended three-axis flight speed and recommended yaw angular velocity of the helicopter in the preset future period are obtained, specifically including: Derivative the position of the helicopter in the Earth's axis system in the recommended flight trajectory for the preset future period with respect to time to obtain the recommended three-axis flight speed of the helicopter for the preset future period; The yaw angle of the helicopter in the recommended flight trajectory of the preset future period is derived with respect to time in the earth axis system to obtain a recommended yaw angular velocity of the helicopter in the preset future period.
6. The method for determining the flight trajectory and joystick amount during the autorotation landing of a helicopter according to claim 5, characterized in that: The inverse simulation method is used to obtain the recommended joystick amount of the helicopter in the preset future period based on the recommended three-axis flight speed and recommended yaw rate of the helicopter in the preset future period, including: Any future moment in the preset future period is taken as the current future moment, and the next future moment after the current future moment is taken as the next future moment; Obtaining the actual three-axis flight speed, the actual yaw angular velocity, and the preset joystick amount of the helicopter at the current future moment; when the current future moment is the first future moment of the preset future period, the current future moment is the current moment; An inverse simulation method is adopted, using the flight dynamics model of the helicopter, to determine the predicted three-axis flight speed and the predicted yaw rate of the helicopter at the next future moment based on the actual three-axis flight speed of the helicopter at the current future moment, the actual yaw rate of the helicopter at the current future moment, and the preset joystick amount at the current future moment; Determining an objective function value at a current future time based on the predicted three-axis flight speed and the predicted yaw rate of the helicopter at the next future time, the recommended three-axis flight speed and the recommended yaw rate at the next future time; Determine whether the objective function value at the current future moment is less than the preset function value; If so, the preset joystick amount at the current future time is used as the recommended joystick amount at the current future time; If not, the Newton iteration method is used to correct the preset joystick amount at the current future moment, and the corrected preset joystick amount at the current future moment is updated to the preset joystick amount at the current future moment, until the objective function value at the current future moment is less than the preset function value, and the preset joystick amount at the current future moment is used as the recommended joystick amount at the current future moment.
7. A system for determining the flight trajectory and joystick amount during the autorotation landing of a helicopter, characterized in that: The system for determining the flight trajectory and joystick amount during the helicopter autorotation and landing process is used to implement the method for determining the flight trajectory and joystick amount during the helicopter autorotation and landing process according to any one of claims 1 to 6, and the system for determining the flight trajectory and joystick amount during the helicopter autorotation and landing process comprises: A data acquisition unit, used to acquire the flight status data of the helicopter at the current moment when the helicopter is preparing for autorotation landing; A filtering unit is used to filter the flight status data of the helicopter at the current moment by using an extended Kalman filter algorithm to obtain filtered flight status data of the helicopter at the current moment; a recommended flight trajectory determination unit, configured to obtain a recommended flight trajectory for the helicopter in a preset future period based on the filtered flight state data of the helicopter at the current moment, using an expert knowledge base; a recommended three-axis flight speed and recommended yaw rate determination unit, configured to obtain a recommended three-axis flight speed and a recommended yaw rate of the helicopter in a preset future period based on the recommended flight trajectory of the helicopter in the preset future period; The recommended joystick amount determination unit is used to obtain the recommended joystick amount of the helicopter in the preset future period based on the recommended three-axis flight speed and recommended yaw angular velocity of the helicopter in the preset future period by adopting an inverse simulation method.
8. The system for determining the flight trajectory and joystick amount during the autorotation landing of a helicopter according to claim 7, characterized in that: The system further comprises: The display unit is used to present the recommended flight trajectory of the helicopter in a preset future period and the recommended joystick amount of the helicopter in the preset future period in a visual form to assist the pilot in controlling the helicopter to autorotate and land.
9. The system for determining the flight trajectory and joystick amount during the autorotation landing of a helicopter according to claim 7, characterized in that: The recommended flight trajectory determination unit includes: A matching flight scenario determination module is used to input the filtered flight status data and flight phase of the helicopter at the current moment into the expert knowledge base to search for a matching flight scenario for the helicopter; A historical flight trajectory determination module is used to load the flight mechanics constraints corresponding to the helicopter's matching flight scenario to obtain multiple historical flight trajectories; The recommended flight trajectory determination module is used to iteratively optimize multiple historical flight trajectories using the SQP optimization algorithm to obtain the recommended flight trajectory of the helicopter in a preset future period.
10. The system for determining the flight trajectory and joystick amount during the autorotation landing of a helicopter according to claim 9, characterized in that: The recommended three-axis flight speed and recommended yaw rate determination unit specifically includes: A recommended three-axis flight speed determination module is used to perform a time derivative of the position of the helicopter in the earth axis system in the recommended flight trajectory for a preset future period to obtain the recommended three-axis flight speed of the helicopter for the preset future period; The recommended yaw rate determination module is used to derive the yaw angle of the helicopter in the earth axis system in the recommended flight trajectory of the helicopter in the preset future period with respect to time to obtain the recommended yaw rate of the helicopter in the preset future period.