An agile intelligent flying car

Abstract

This application provides an agile configuration intelligent flying car, relating to the field of flying car technology, including: a cycloidal rotor aircraft and a control chip; a servo motor is installed in the cycloidal rotor aircraft for achieving level flight turning behavior by changing the yaw angle of the flying car; the control chip includes a mode switching module and an airborne mode control module; the airborne mode control module is used to calculate the optimal total lift and optimal torque in three directions from the current moment to the next moment based on the current state parameters of the flying car using the airborne state equation, and to calculate the lift of the four rotors of the cycloidal rotor aircraft from the current moment to the next moment using the dynamic model of airborne flight, and send the lift of the four rotors to the cycloidal rotor aircraft. This application can achieve level flight turning behavior by changing the yaw angle of the flying car without experiencing altitude loss when reaching the desired position.

Description

Technical Field

[0001] This application relates to the field of flying car technology, and in particular to an agile configuration of intelligent flying car. Background Technology

[0002] While a flying car is in flight, the yaw angle cannot be changed directly. The yaw angle is usually changed by changing the roll and pitch angles. This method may result in a drop in altitude when reaching the desired position, making it impossible to achieve level flight and turning behavior. Summary of the Invention

[0003] In view of this, this application provides an agile configuration of intelligent flying car to solve the above-mentioned technical problems.

[0004] This application provides an agile configuration intelligent flying car, including: a cycloidal rotor aircraft and a control chip; the cycloidal rotor aircraft is equipped with a servo motor for achieving level flight and turning behavior in the air by changing the yaw angle of the flying car; the control chip is equipped with a mode switching module and an air mode control module;

[0005] The mode switching module is used to respond to the mode switching command, use a state machine to switch the flying car mode to the air mode, and start the air mode control module.

[0006] The aerial modal control module is used to determine whether the flying car's behavior is ascent, descent, or level flight turn based on the starting point and target point of the pre-set flight path. Based on the flying car's state parameters at the current moment, it uses the aerial state equation to calculate the optimal total lift and the optimal torque in three directions from the current moment to the next moment. Based on the optimal total lift and the optimal torque in three directions from the current moment to the next moment, it uses the dynamic model of aerial flight to calculate the lift of the four rotors of the cycloidal rotor aircraft from the current moment to the next moment, and sends the lift of the four rotors to the cycloidal rotor aircraft.

[0007] Furthermore, when the flying car behaves as a level flight turn;

[0008] Based on the flying car's state parameters from the previous moment, the optimal total lift and optimal torque in three directions from the current moment to the next moment are calculated using the air state equations, including:

[0009] When the flying car's behavior is a level flight turn, the flying car's state equation in the air is:

[0010]

[0011] Where A, B, and C are all matrices; x k Let t be the current time.k Flying car state parameters: x k =[p k,x ;p k,y ;p k,z ;v k,x ;v k,y ;v k,z ;w k,x ;w k,y ;w k,z ;q k,w ;q k,x ;q k,y ;q k,z ] T Among them, (p k,x ;p k,y ;p k,z (t) represents the current time. k The three components of the flying car's position, (v k,x ;v k,y ;v k,z (t) represents the current time. k The three components of the speed of the flying car, w k,x w k,y and w k,z They are the current time t. k The roll angle, pitch angle, and yaw angle of the flying car; [q k,w ;q k,x ;q k,y ;q k,z ] T Let t be the current time. k The quaternion of flying cars;

[0012] x k+1 For the predicted next time t k+1 The flying car's status parameters;

[0013] u k→k+1 Let t be the current time. k At the next moment t k+1 Control input:

[0014] u k→k+1 =[Thrust;M x M y M z ] T

[0015] Where Thrust is the total lift from the current moment to the next moment, M x M y and M z These represent the torques in three directions of the flying car from the current moment to the next moment;

[0016] y k+1 For the next moment t k+1 Output:

[0017] y k+1 =[p k+1,x ;p k+1,y ;p k+1,z yaw k+1 ] T

[0018] Among them, (p k+1,x ;p k+1,y ;p k+1,z ) represents the next time step t k+1 The three components of the flying car's position, yaw k+1 For the next moment t k+1 The yaw angle of the flying car;

[0019]

[0020] Where p is the position vector of the flying car. Let p be the first derivative of p, and v be the velocity vector of the flying car. Let v be the first derivative of v, and w be the angular velocity component of the flying car. Let w be the first differential of w, and q be the quaternion of the flying car. The first differential of q; The derivative of the flying car's state parameters;

[0021] The system of equations for calculation is as follows:

[0022]

[0023] Where c is the lift vector: c = [0; 0; Thrust] T g is the gravity vector: g = [0; 0; 9.8] T M is the torque vector: M = [M x M y M z ] T J is the moment of inertia vector: J = [J xx J yy J zz ] T J xx J yy and J zz These represent the moments of inertia of the flying car in three directions; T represents the transpose.

[0024] Define the loss function minJ as:

[0025] minJ=(y k+1 -y ref ) T ·Q·(y k+1 -y ref )+u k→k+1 T ·R·u k→k+1

[0026] Among them, y ref For the next moment t k+1 The expected value of the output:

[0027] y ref =[p ref,x ;p ref,y ;p ref,z yaw ref ] T

[0028] (p ref,x ;p ref,y ;p ref,z ) represents the next time step t k+1 The desired positions of the flying car in three directions, yaw ref For the next moment t k+1 The expected yaw angle of the flying car, where Q and R are both weight matrices;

[0029] use The computational equations and loss function are used to solve for u. k→k+1 The optimal vector is the optimal total lift and the optimal torque in three directions from the current moment to the next moment.

[0030] Furthermore, when the flying car's behavior is to ascend or descend;

[0031] When the flying car's behavior is a level flight turn, the flying car's state equation in the air is:

[0032]

[0033] Where A, B, and C are all matrices; x k Let t be the current time. k Flying car state parameters: x k =[p k,x ;p k,y ;p k,z ;v k,x ;v k,y ;v k,z ;w k,x ;w k,y ;w k,z ;q k,w ;q k,x ;q k,y ;qk,z ] T Among them, (p k,x ;p k,y ;p k,z (t) represents the current time. k The three components of the flying car's position, (v k,x ;v k,y ;v k,z (t) represents the current time. k The three components of the speed of the flying car, w k,x w k,y and w k,z They are the current time t. k The roll angle, pitch angle, and yaw angle of the flying car; [q k,w ;q k,x ;q k,y ;q k,z ] T Let t be the current time. k The quaternion of flying cars;

[0034] x k+1 For the predicted next time t k+1 The flying car's status parameters;

[0035] u k→k+1 Let t be the current time. k At the next moment t k+1 Control input:

[0036] u k→k+1 =pThrust;M x M y M z ] T

[0037] Where Thrust is the total lift from the current moment to the next moment, M x M y and M z These represent the torques in three directions of the flying car from the current moment to the next moment;

[0038] y k+1 For the next moment t k+1 Output:

[0039] y k+1 =[p k+1,x ;p k+1,y ;p k+1,z yaw k+1 ] T

[0040] Among them, (p k+1,x ;p k+1,y;p k+1,z ) represents the next time step t k+1 The three components of the flying car's position, yaw k+1 For the next moment t k+1 The yaw angle of the flying car;

[0041]

[0042] Where p is the position vector of the flying car. Let p be the first derivative of p, and v be the velocity vector of the flying car. Let v be the first derivative of v, and w be the angular velocity component of the flying car. Let w be the first differential of w, and q be the quaternion of the flying car. The first differential of q; The derivative of the flying car's state parameters;

[0043] The system of equations for calculation is as follows:

[0044]

[0045] Where c is the lift vector: c = [0; 0; Thrust] T g is the gravity vector: g = [0; 0; 9.8] T M is the torque vector: M = [M x M y M z ] T J is the moment of inertia vector: J = [J xx J yy J zz ] T J xx J yy and J zz These represent the moments of inertia of the flying car in three directions; T represents the transpose.

[0046] Define the loss function minJ as:

[0047] minJ=(y k+1 -y ref ) T ·Q·(y k+1 -y ref )+u k→k+1 T ·R·u k→k+1

[0048] Among them, y ref For the next moment t k+1 The expected value of the output:

[0049] yref =[p ref,x ;p ref,y ;p ref,z yaw ref ] T

[0050] (p ref,x ;p ref,y ;p ref,z ) represents the next time step t k+1 The desired positions of the flying car in three directions, yaw ref For the next moment t k+1 The expected yaw angle of the flying car, where Q and R are both weight matrices;

[0051] use The computational equations and loss function are used to solve for u. k→k+1 The optimal vector is the optimal total lift and the optimal torque in three directions from the current moment to the next moment.

[0052] Furthermore, the dynamic model of the aerial flight is as follows:

[0053]

[0054] Where F1, F2, F3, and F4 represent the lift of the four rotors, M1, M2, M3, and M4 represent the torque of the four rotors, l1, l2, l3, and l4 represent the distances from the center of mass of the four rotors to the center of mass of the flying car, θ is the servo deflection angle, and m is the mass of the flying car. The optimal total lift from the current moment to the next moment. and This represents the optimal torque in the three directions from the current moment to the next moment.

[0055] Furthermore, the control chip also includes a ground mode control module, and the mode switching module is further configured to: in response to a mode switching command, use a state machine to switch the flying car to ground mode and start the ground mode control module;

[0056] The ground modal control module is used to determine whether the flying car is moving or stationary based on the relative positions of the starting point and the target point. Based on the motion state parameters at the current moment, it uses the first PID controller and the second PID controller to calculate the output of the position loop and the output of the attitude loop at the next moment, thereby obtaining the second derivatives of the velocity and steering angle at the next moment. Based on the second derivatives of the velocity and steering angle at the next moment, it uses the dynamic model of ground motion to calculate the velocity of the four rotors of the cycloidal rotor aircraft at the next moment, and sends the velocity of the four rotors at the next moment to the cycloidal rotor aircraft.

[0057] Furthermore, based on the state parameters at the current moment, the output of the position loop and the output of the attitude loop at the next moment are calculated using the first PID controller and the second PID controller, thereby obtaining the second derivatives of the velocity and steering angle at the next moment; including:

[0058] The differential equation of the first PID controller is:

[0059]

[0060] Among them, K 1p K 1i and K 1d These represent the proportional coefficient, integral coefficient, and derivative coefficient of the first PID controller, respectively; e x e y and e z The three components of the flying car's positional deviation:

[0061] [e x ,e y ,e z ] T =[p x -p x_ref ,p y -p y_ref ,p z -p z_ref ] T

[0062] [p x ;p y ;p z ] T These are the three components representing the current position of the flying car;

[0063] [p x_ref ,p y_ref ,p z_ref ] T The three components represent the target position of the flying car;

[0064] [δ x ,δ y ,δ z ] T The output of the position loop; δ x The first differential of the position in the x-direction; δ y The first differential of the position in the y-direction; δ z The first-order differential of the position in the z-direction;

[0065] The differential equation for the second PID controller is:

[0066]

[0067] Among them, K 2p K 2i and K 2d These represent the proportional coefficient, integral coefficient, and derivative coefficient of the second PID controller, respectively. For the deviation of the steering angle of the flying car:

[0068] yaw is the current turning angle of the flying car. ref The target turning angle of the flying car;

[0069] This is the output of the attitude loop at the next moment; The first derivative of the flying car's steering angle;

[0070] Calculate the speed v of the left wheel based on the output of the position ring at the next moment. l And the speed v of the right wheel r To obtain the velocity at the next moment.

[0071] Based on the output of the attitude loop at the next moment, the second derivative of the steering angle at the next moment is obtained.

[0072] Furthermore, the dynamic model of the ground motion is as follows:

[0073]

[0074] Where v1, v2, v3, and v4 represent the speeds of the four rotors, R is the rotor radius, and l l and l r These are the radii of the left and right wheels.

[0075] Furthermore, the control chip also includes a water surface mode control module, and the mode switching module is further configured to: in response to a mode switching command, use a state machine to switch the flying car to water surface mode and activate the water surface mode control module;

[0076] The water surface modal control module is used to determine whether the flying car is moving or stationary based on the relative positions of the starting point and the target point. Based on the state parameters at the current moment, it uses the third PID controller and the fourth PID controller to calculate the output of the position loop and the output of the attitude loop at the next moment, thereby obtaining the optimal total lift and the optimal torque in the Z direction from the current moment to the next moment. Based on the optimal total lift and the optimal torque in the Z direction from the current moment to the next moment, it uses the dynamic model of water surface motion to calculate the lift of the four rotors of the cycloidal rotor aircraft from the current moment to the next moment. The lift of the four rotors is then sent to the cycloidal rotor aircraft.

[0077] Furthermore, based on the state parameters at the current moment, the position loop and attitude loop for the next moment are calculated using the third and fourth PID controllers, thereby obtaining the optimal total lift and optimal torque in the Z direction from the current moment to the next moment; including:

[0078] The differential equation for the third PID controller is:

[0079]

[0080] Among them, K 3p K 3i and K 3d These represent the proportional, integral, and derivative coefficients of the third PID controller, respectively; e x e y and e z The three components of the flying car's positional deviation:

[0081] [e x ,e y ,e z ] T =[p x -p x_ref ,p y -p y_ref ,p z -p z_ref ] T

[0082] [p x ;p y ;p z ] T These are the three components representing the current position of the flying car;

[0083] [p x_ref ,p y_ref ,p z_ref ] T The three components represent the target position of the flying car;

[0084] [δ x ,δ y ,δ z ] T The output of the position loop at the next moment; [δ x ,δ y ,δ z ] T The output of the position loop; δ x The first differential of the position in the x-direction; δ y The first differential of the position in the y-direction; δ z The first-order differential of the position in the z-direction;

[0085] The differential equation for the fourth PID controller is:

[0086]

[0087] Among them, K 4p K 4i and K 4d These represent the proportional coefficient, integral coefficient, and derivative coefficient of the fourth PID controller, respectively; e Φ ,e Θ and For the roll angle deviation, pitch angle deviation, and steering angle deviation of the flying car:

[0088]

[0089] roll is the current roll angle of the flying car. ref The target roll angle of the flying car; pitch is the current pitch angle of the flying car. ref The target pitch angle of the flying car; yaw is the current steering angle of the flying car. ref The target turning angle for the flying car;

[0090] The output of the attitude loop at the next moment; δ Φ The first derivative of the roll angle; δ Θ The first derivative of the pitch angle; The first derivative of the deflection angle;

[0091] The optimal total lift from the current moment to the next moment is obtained based on the output of the position loop. The optimal torque in the Z direction from the current moment to the next moment is obtained based on the output of the attitude loop.

[0092] Furthermore, the dynamic model of the water surface motion is as follows:

[0093]

[0094] Where F1, F2, F3, and F4 represent the lift of the four rotors, M1, M2, M3, and M4 represent the torque of the four rotors, l1, l2, l3, and l4 represent the distances from the center of mass of the four rotors to the center of mass of the flying car, and θ represents the servo deflection angle.

[0095] This application enables level flight turning behavior by changing the yaw angle of the flying car, and there will be no drop in altitude when reaching the desired position. Attached Figure Description

[0096] To more clearly illustrate the technical solutions in the specific embodiments of this application or the prior art, the drawings used in the description of the specific embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of this application. For those skilled in the art, other drawings can be obtained from these drawings without creative effort.

[0097] Figure 1 This is a functional structure diagram of an agile configuration intelligent flying car according to an embodiment of this application;

[0098] Figure 2 This is a schematic diagram of a cycloidal rotor aircraft according to an embodiment of this application. Detailed Implementation

[0099] To make the objectives, technical solutions, and advantages of the embodiments of this application clearer, the technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. The components of the embodiments of this application described and shown in the accompanying drawings can generally be arranged and designed in various different configurations.

[0100] Therefore, the following detailed description of the embodiments of this application provided in the accompanying drawings is not intended to limit the scope of the claimed application, but merely to illustrate selected embodiments of the application. All other embodiments obtained by those skilled in the art based on the embodiments of this application without inventive effort are within the scope of protection of this application.

[0101] First, a brief introduction to the design concept of the embodiments of this application will be given.

[0102] While a flying car is in flight, the yaw angle cannot be changed directly. The yaw angle is usually changed by changing the roll and pitch angles. This method may result in a drop in altitude when reaching the desired position, making it impossible to achieve level flight and turning behavior.

[0103] To address the aforementioned issues, this application solves the problem of insufficient degrees of freedom in traditional UAVs by incorporating a variable-pitch servo in a cycloidal rotor aircraft and then setting the corresponding control program in the control chip. During flight, the yaw angle of the flying vehicle can be easily adjusted, preventing altitude loss upon reaching the desired position and enabling level flight and turning. It can autonomously analyze the desired position and attitude and determine whether to adjust the yaw angle based on the desired values.

[0104] If the yaw angle does not need to be changed, and the servo angles at the two rear rotors are set to 0°, the platform is similar to a traditional UAV platform, with controlled degrees of freedom of x, y, z, roll, and pitch. The actual position and attitude are adjusted only by changing the roll and pitch angles.

[0105] If the yaw angle needs to be changed, the servo angle will be set to 10° and -10° respectively, depending on whether the desired yaw angle is positive or negative. Since the goal of this multimodal simulation platform is to change the yaw angle, it will suppress changes in roll and pitch angles to prevent altitude loss and impact on yaw angle calculation. The degrees of freedom for control at this time are x, y, and yaw. When the multimodal simulation platform reaches the desired position and attitude, the servo angle will return to 0° to achieve dynamic stability.

[0106] After introducing the application scenarios and design concepts of the embodiments of this application, the technical solutions provided by the embodiments of this application will be described below.

[0107] like Figure 1 As shown, this application provides an agile configuration intelligent flying car, including: a cycloidal rotor aircraft and a control chip; the cycloidal rotor aircraft is equipped with a servo motor for achieving level flight turning behavior in the air by changing the yaw angle of the flying car; the control chip is equipped with a mode switching module and an air mode control module;

[0108] The mode switching module is used to respond to the mode switching command, use a state machine to switch the flying car mode to the air mode, and start the air mode control module.

[0109] The aerial modal control module is used to determine whether the flying car's behavior is ascent, descent, or level flight turn based on the starting point and target point of the pre-set flight path. Based on the flying car's state parameters at the current moment, it uses the aerial state equation to calculate the optimal total lift and the optimal torque in three directions from the current moment to the next moment. Based on the optimal total lift and the optimal torque in three directions from the current moment to the next moment, it uses the dynamic model of aerial flight to calculate the lift of the four rotors of the cycloidal rotor aircraft from the current moment to the next moment, and sends the lift of the four rotors to the cycloidal rotor aircraft.

[0110] The cycloidal rotor aircraft has four rotors: MOTOR1, MOTOR2, MOTOR3, and MOTOR4, each connected to an electronic speed controller (ESC), corresponding to ESC1, ESC2, ESC3, and ESC4. A detailed structural diagram of the cycloidal rotor aircraft is shown below. Figure 2 As shown.

[0111] The mode switching command can come from an external controller or be generated autonomously based on environmental perception.

[0112] For example, the aerial mode is when the flying car is in the air, and in this mode, it can perform behaviors such as ascending, descending, hovering, and level flight turning.

[0113] When the altitude of the starting point of the flight path is less than the altitude of the target point, the flying car will ascend; when the altitude of the starting point of the flight path is greater than the altitude of the target point, the flying car will descend. The control strategies for ascent and descent include:

[0114] 1. Based on the desired behavior or position, the flying car sets the servo angle to 0 to suppress the influence of yaw on the flying car's attitude, and prepares to adjust the speed of each rotor to achieve the desired behavior or position.

[0115] 2. Real-time feedback of the current position, and calculation of the optimal lift and torque based on the set desired position, loss function and upper and lower limits of state variables.

[0116] 3. Based on the calculated lift and torque, the required rotational speeds of each rotor are determined using the dynamic model and transmitted to the flying car.

[0117] 4. The flying car adjusts its displacement and attitude according to the required rotation speed at the current moment to achieve the desired behavior or position, and finally the flying car becomes hovering.

[0118] When the altitude of the starting point of the flight path equals the altitude of the target point, and the starting point and the target point are not the same point, the flying car's behavior is a level flight turn. The control strategy for a level flight turn includes:

[0119] 1. Based on the desired behavior or position, the flying car suppresses the influence of roll and pitch on the flying car in the controller, sets the servo angle to 10° or -10° to change the attitude of the flying car through yaw, and prepares to adjust the speed of each rotor to achieve the desired behavior or position.

[0120] 2. Real-time feedback of the current position, and calculation of the optimal lift and torque based on the set desired position, loss function and upper and lower limits of state variables.

[0121] 3. Based on the calculated lift and torque, the required rotational speeds of each rotor are determined using the dynamic model and transmitted to the flying car.

[0122] 4. The flying car adjusts its displacement and attitude according to the required rotation speed at the current moment to achieve the desired behavior or position, and finally the flying car becomes hovering.

[0123] When the starting point and the target point are the same point, the flying car behaves as hovering. The hovering control strategy includes:

[0124] The sum of the lift generated by the rotational speeds of each rotor of the flying car is equal to the weight of the flying car itself, and each attitude angle is 0.

[0125] In this embodiment, the flying car's behavior is a level flight turn;

[0126] Based on the flying car's state parameters from the previous moment, the optimal lift and optimal torque in three directions from the current moment to the next moment are calculated using the air state equations, including:

[0127] When the flying car's behavior is a level flight turn, the flying car's state equation in the air is:

[0128]

[0129] Where A, B, and C are all matrices; x k Let t be the current time. k Flying car state parameters: x k =[p k,x ;p k,y ;p k,z ;v k,x ;v k,y ;v k,z ;w k,x ;w k,y ;w k,z ;q k,w ;q k,x ;q k,y ;q k,z ] T Among them, (p k,x ;p k,y ;p k,z (t) represents the current time. k The three components of the flying car's position, (v k,x ;v k,y ;v k,z (t) represents the current time. k The three components of the speed of the flying car, w k,x w k,y and w k,z They are the current time t. k The roll angle, pitch angle, and yaw angle of the flying car; [q k,w ;q k,x ;q k,y ;q k,z ] T Let t be the current time. k The quaternion of flying cars;

[0130] x k+1 For the predicted next time t k+1 The flying car's status parameters;

[0131] u k→k+1 Let t be the current time. k At the next moment t k+1 System input:

[0132] u k→k+1 =[Thrust;M x M y M z ] T

[0133] Where Thrust is the total lift from the current moment to the next moment, M x M y and M z These represent the torques in three directions of the flying car from the current moment to the next moment;

[0134] y k+1 For the next moment t k+1 Output:

[0135] y k+1 =[p k+1,x ;p k+1,y ;p k+1,z yaw k+1 ] T

[0136] Among them, (p k+1,x ;p k+1,y ;p k+1,z ) represents the next time step t k+1 The three components of the flying car's position, yaw k+1 For the next moment t k+1 The yaw angle of the flying car;

[0137]

[0138] Where p is the position vector of the flying car. Let p be the first derivative of p, and v be the velocity vector of the flying car. Let v be the first derivative of v, and w be the angular velocity component of the flying car. Let w be the first differential of w, and q be the quaternion of the flying car. The first differential of q; The derivative of the flying car's state parameters;

[0139] The system of equations for calculation is as follows:

[0140]

[0141] Where c is the lift vector: c = [0; 0; Thrust] T g is the gravity vector: g = [0; 0; 9.8] T M is the torque vector: M = [M x M y M z ] T J is the moment of inertia vector: J = [J xx J yy J zz ] T J xx J yy and J zz These represent the moments of inertia of the flying car in three directions; T represents the transpose.

[0142] Define the loss function minJ as:

[0143] minJ=(y k+1 -u ref ) T ·Q·(u k+1 -y ref )+u k→k+1 T ·R·u k→k+1

[0144] Among them, y ref For the next moment t k+1 The expected value of the output:

[0145] y ref =[p ref,x ;p ref,y ;p ref,z yaw ref ] T

[0146] (p ref,x ;p ref,y ;p ref,z ) represents the next time step t k+1 The desired positions of the flying car in three directions, yaw ref For the next moment t k+1 The expected yaw angle of the flying car, where Q and R are both weight matrices;

[0147] use The computational equations and loss function are used to solve for u. k→k+1 The optimal vector is the optimal total lift and the optimal torque in three directions from the current moment to the next moment.

[0148] The specific solution method is as follows:

[0149] Based on the state equation and the loss function, the following inequality can be obtained.

[0150]

[0151] Since all the unknowns are related to the system input u, it can be simplified to the following inequality.

[0152]

[0153] A(u) and f(u) are functions of u;

[0154] The solution method is the Lagrange multiplier method, which mainly includes the following steps:

[0155] Define the function L(u,λ) as follows:

[0156] L(u,λ)=f(u) T ·Q·f(u)+u T ·R·u+λ T (A(u)-b)

[0157] λ is a parameter vector; setting the derivative of L(u,λ) with respect to u and λ to 0, we obtain the system of linear equations:

[0158]

[0159] The optimal solution for u can then be obtained using the above equation.

[0160] In this embodiment, when the flying car's behavior is ascending or descending, the flying car's air state equation is the same as when it is flying and turning, the difference is... The system of equations for calculation is as follows:

[0161]

[0162] In this embodiment, the dynamic model of the flight in the air is as follows:

[0163]

[0164] Where F1, F2, F3, and F4 represent the lift of the four rotors, M1, M2, M3, and M4 represent the torque of the four rotors, l1, l2, l3, and l4 represent the distances from the center of mass of the four rotors to the center of mass of the flying car, θ is the servo deflection angle (pre-set, 10° or -10°), and m is the mass of the flying car. The optimal total lift from the current moment to the next moment. and This represents the optimal torque in the three directions from the current moment to the next moment.

[0165] Preferably, the control chip further includes a ground mode control module, and the mode switching module is further configured to: in response to a mode switching command, use a state machine to switch the flying car to ground mode and start the ground mode control module;

[0166] The ground modal control module is used to determine whether the flying car is moving or stationary based on the relative positions of the starting point and the target point. Based on the motion state parameters at the current moment, it uses the first PID controller and the second PID controller to calculate the output of the position loop and the output of the attitude loop at the next moment, thereby obtaining the second derivatives of the velocity and steering angle at the next moment. Based on the second derivatives of the velocity and steering angle at the next moment, it uses the dynamic model of ground motion to calculate the velocity of the four rotors of the cycloidal rotor aircraft at the next moment, and sends the velocity of the four rotors at the next moment to the cycloidal rotor aircraft.

[0167] The ground mode is when the flying car is on the ground, and in this mode it can perform behaviors such as going straight, turning, and staying still.

[0168] Control strategies for motion and stillness include:

[0169] 1. The flying car prepares to adjust the speed of each rotor to achieve the desired behavior or position based on the desired behavior or position.

[0170] 2. Real-time feedback of the current position, setting displacement loop and attitude loop to calculate the required linear velocity of each rotor according to the desired position.

[0171] 3. The calculated linear velocity is used to inversely solve the required rotational speed of each rotor based on the dynamic model and then transmitted to the flying car.

[0172] 4. The flying car adjusts its displacement and attitude according to the required rotation speed at the current moment to achieve the desired behavior or position, and eventually the flying car comes to a standstill.

[0173] Specifically, based on the state parameters at the current moment, the output of the position loop and the output of the attitude loop at the next moment are calculated using the first PID controller and the second PID controller, thereby obtaining the second derivatives of the velocity and steering angle at the next moment; including:

[0174] The differential equation of the first PID controller is:

[0175]

[0176] Among them, K 1p K 1i and K 1d These represent the proportional coefficient, integral coefficient, and derivative coefficient of the first PID controller, respectively; e x ey and e z The three components of the flying car's positional deviation:

[0177] [e x ,e y ,e z ] T =[p x -p x_ref ,p y -p y_ref ,p z -p z_ref ] T

[0178] [p x ;p y ;p z ] T These are the three components representing the current position of the flying car;

[0179] [p x_ref ,p y_ref ,p z_ref ] T The three components represent the target position of the flying car;

[0180] [δ x ,δ y ,δ z ] T The output of the position loop; δ x The first differential of the position in the x-direction; δ y The first differential of the position in the y-direction; δ z The first-order differential of the position in the z-direction;

[0181] The differential equation for the second PID controller is:

[0182]

[0183] Among them, K 2p K 2i and K 2d These represent the proportional coefficient, integral coefficient, and derivative coefficient of the second PID controller, respectively. For the deviation of the steering angle of the flying car:

[0184] yaw is the current turning angle of the flying car. ref The target turning angle of the flying car;

[0185] This is the output of the attitude loop at the next moment; The first derivative of the flying car's steering angle;

[0186] Calculate the speed v of the left wheel based on the output of the position ring at the next moment. l And the speed v of the right wheel r To obtain the velocity at the next moment.

[0187] Based on the output of the attitude loop at the next moment, the second derivative of the steering angle at the next moment is obtained.

[0188] For example, the dynamic model of the ground motion is as follows:

[0189]

[0190] Where v1, v2, v3, and v4 represent the speeds of the four rotors, R is the rotor radius, and l l and l r These are the radii of the left and right wheels.

[0191] Preferably, the control chip further includes a water surface mode control module, and the mode switching module is further configured to: in response to a mode switching command, use a state machine to switch the flying car to water surface mode and start the water surface mode control module;

[0192] The water surface modal control module is used to determine whether the flying car is moving or stationary based on the relative positions of the starting point and the target point. Based on the state parameters at the current moment, it uses the third PID controller and the fourth PID controller to calculate the output of the position loop and the output of the attitude loop at the next moment, thereby obtaining the optimal total lift and the optimal torque in the Z direction from the current moment to the next moment. Based on the optimal total lift and the optimal torque in the Z direction from the current moment to the next moment, it uses the dynamic model of water surface motion to calculate the lift of the four rotors of the cycloidal rotor aircraft from the current moment to the next moment. The lift of the four rotors is then sent to the cycloidal rotor aircraft.

[0193] The water surface mode refers to the flying car being on the water surface, and in this mode, it can perform behaviors such as going straight, turning, and staying still.

[0194] Control strategies for motion and stillness include:

[0195] 1. Based on the desired behavior or position, the flying car sets the speed of the two front rotors to 0, and prepares to adjust the speed of the two rear rotors to achieve the desired behavior or position.

[0196] 2. Provide real-time feedback on the current position, and set up displacement and attitude loops to calculate the required thrust and torque based on the desired position.

[0197] 3. Based on the calculated lift and torque, the required speeds of the last two rotors are determined by inverse solving of the dynamic model and transmitted to the flying car.

[0198] 4. The flying car adjusts its displacement and attitude according to the required rotational speed of the two rotors at the current moment to achieve the desired behavior or position, and eventually the flying car comes to a standstill.

[0199] In this embodiment, based on the state parameters at the current moment, the position loop and attitude loop for the next moment are calculated using the third PID controller and the fourth PID controller, thereby obtaining the total lift and torque in the Z direction from the current moment to the next moment; including:

[0200] The differential equation for the third PID controller is:

[0201]

[0202] Among them, K 3p K 3i and K 3d These represent the proportional, integral, and derivative coefficients of the third PID controller, respectively; e x e y and e z The three components of the flying car's positional deviation:

[0203] [e x ,e y ,e z ] T =[p x -p x_ref ,p y -p y_ref ,p z -p z_ref ] T

[0204] [p x ;p y ;p z ] T These are the three components representing the current position of the flying car;

[0205] [p x_ref ,p y_ref ,p z_ref ] T The three components represent the target position of the flying car;

[0206] [δ x ,δ y ,δ z ] T The output of the position loop at the next moment; [δ x ,δ y ,δ z ] T The output of the position loop; δ xThe first differential of the position in the x-direction; δ y The first differential of the position in the y-direction; δ z The first-order differential of the position in the z-direction;

[0207] The differential equation for the fourth PID controller is:

[0208]

[0209] Among them, K 4p K 4i and K 4d These represent the proportional coefficient, integral coefficient, and derivative coefficient of the fourth PID controller, respectively; e Φ ,e Θ and For the roll angle deviation, pitch angle deviation, and steering angle deviation of the flying car:

[0210]

[0211] roll is the current roll angle of the flying car. ref The target roll angle of the flying car; pitch is the current pitch angle of the flying car. ref The target pitch angle of the flying car; yaw is the current steering angle of the flying car. ref The target turning angle for the flying car;

[0212] The output of the attitude loop at the next moment; δ Φ The first derivative of the roll angle; δ Θ The first derivative of the pitch angle; The first derivative of the deflection angle;

[0213] The optimal total lift from the current moment to the next moment is obtained based on the output of the position loop. The optimal torque in the Z direction from the current moment to the next moment is obtained based on the output of the attitude loop.

[0214] In this embodiment, the dynamic model of the water surface motion is as follows:

[0215]

[0216] Where F1, F2, F3 and F4 represent the lift of the four rotors, M1, M2, M3 and M4 represent the torque of the four rotors, l1, l2, l3 and l4 represent the distances from the center of mass of the four rotors to the center of mass of the flying car, and θ represents the servo deflection angle.

[0217] It should be noted that although several units or sub-units of the device have been mentioned in the detailed description above, this division is merely exemplary and not mandatory. In fact, according to embodiments of this application, the features and functions of two or more units described above can be embodied in one unit. Conversely, the features and functions of one unit described above can be further divided and embodied by multiple units.

[0218] Furthermore, although the operations of the method of this application are described in a specific order in the accompanying drawings, this does not require or imply that these operations must be performed in that specific order, or that all the operations shown must be performed to achieve the desired result. Additionally or alternatively, certain steps may be omitted, multiple steps may be combined into one step, and / or one step may be broken down into multiple steps.

[0219] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of this application and are not intended to limit it. Although this application has been described in detail with reference to the embodiments, those skilled in the art should understand that modifications or equivalent substitutions to the technical solutions of this application do not depart from the spirit and scope of the technical solutions of this application, and should all be covered within the scope of the claims of this application.

Claims

1. An agile configuration intelligent flying car, characterized in that, include: A cycloidal rotor aircraft and a control chip; the cycloidal rotor aircraft is equipped with a servo motor. This is used to achieve level flight and turning behavior in the air by changing the yaw angle of the flying car; the control chip is equipped with a mode switching module and an air mode control module; The mode switching module is used to respond to the mode switching command, use a state machine to switch the flying car mode to the air mode, and start the air mode control module. The airborne modal control module is used to determine whether the flying car is ascending, descending, or turning in level flight based on the starting point and target point of the pre-set flight path. Based on the current state parameters of the flying car, it uses the airborne state equation to calculate the optimal total lift and the optimal torque in three directions from the current time to the next time. Based on the optimal total lift and the optimal torque in three directions from the current time to the next time, it uses the dynamic model of airborne flight to calculate the lift of the four rotors of the cycloidal rotor aircraft from the current time to the next time, and sends the lift of the four rotors to the cycloidal rotor aircraft. The control chip also includes a ground mode control module, and the mode switching module is further configured to: in response to a mode switching command, use a state machine to switch the flying car to ground mode and start the ground mode control module; The ground modal control module is used to determine whether the flying car is moving or stationary based on the relative positions of the starting point and the target point. Based on the motion state parameters at the current moment, it uses the first PID controller and the second PID controller to calculate the output of the position loop and the output of the attitude loop at the next moment, thereby obtaining the second derivatives of the velocity and steering angle at the next moment. Based on the second derivatives of the velocity and steering angle at the next moment, it uses the dynamic model of ground motion to calculate the velocity of the four rotors of the cycloidal rotor aircraft at the next moment, and sends the velocity of the four rotors at the next moment to the cycloidal rotor aircraft.

2. The agile configuration intelligent flying car according to claim 1, characterized in that, When the flying car behaves as a level flight turn; Based on the flying car's state parameters from the previous moment, the optimal total lift and optimal torque in three directions from the current moment to the next moment are calculated using the air state equations, including: The state equation for the flying car in the air is: Where A, B, and C are all matrices; x k Let t be the current time. k Flying car state parameters: x k =[p k,x ;p k,y ;p k,z ;v k,x ;v k,y ;v k,z ;w k,x ;w k,y ;w k,z ;q k,w ;q k,x ;q k,y ;q k,z ] T Among them, (p k,x ;p k,y ;p k,z (t) represents the current time. k The three components of the flying car's position, (v k,x ;v k,y ;v k,z (t) represents the current time. k The three components of the speed of the flying car, w k,x 、w k,y and w k,z They are the current time t. k The roll angle, pitch angle, and yaw angle of the flying car; [q k,w ;q k,x ;q k,y ;q k,z ] T Let t be the current time. k The quaternion of flying cars; x k+1 For the predicted next time t k+1 The flying car's status parameters; u k→k+1 Let t be the current time. k At the next moment t k+1 Control input: u k→k+1 =[Thrust;M x ;M y ;M z ] T Where Thrust is the total lift from the current moment to the next moment, M x M y and M z These represent the torques in three directions of the flying car from the current moment to the next moment; y k+1 For the next moment t k+1 Output: y k+1 =[p k+1,x ;p k+1,y ;p k+1,z ;yaw k+1 ] T Among them, (p k+1,x ;p k+1,y ;p k+1,z ) represents the next time step t k+1 The three components of the flying car's position, yaw k+1 For the next moment t k+1 The yaw angle of the flying car; Where p is the position vector of the flying car. Let p be the first derivative of p, and v be the velocity vector of the flying car. Let v be the first derivative of v, and w be the angular velocity component of the flying car. Let w be the first differential of w, and q be the quaternion of the flying car. The first differential of q; The derivative of the flying car's state parameters; The system of equations for calculation is as follows: Where c is the lift vector: c = [0; 0; Thrust] T g is the gravity vector: g = [0; 0; 9.8] T M is the torque vector: M = [M x M y M z ] T J is the moment of inertia vector: J = [J xx J yy J zz ] T J xx J yy and J zz The moment of inertia of the flying car in three directions; Tt represents the transpose; Define the loss function minJ as: minJ=(and k+1 -and ref ) T ·Q·(and k+1 -and ref )+u k→k+1 T ·R·u k→k+1 Among them, y ref For the next moment t k+1 The expected value of the output: y ref =[p ref,x ;p ref,y ;p ref,z ;yaw ref ] T (p ref,x ;p ref,y ;p ref,z ) represents the next time step t k+1 The desired positions of the flying car in three directions, yaw ref For the next moment t k+1 The expected yaw angle of the flying car, where Q and R are both weight matrices; use The computational equations and loss function are used to solve for u. k→k+1 The optimal vector is the optimal total lift and the optimal torque in three directions from the current moment to the next moment.

3. The agile configuration intelligent flying car according to claim 1, characterized in that, When the flying car's behavior is to ascend or descend; Based on the flying car's state parameters from the previous moment, the optimal total lift and optimal torque in three directions from the current moment to the next moment are calculated using the air state equations, including: The state equation for the flying car in the air is: Where A, B, and C are all matrices; x k Let t be the current time. k Flying car state parameters: x k =[p k,x ;p k,y ;p k,z ;v k,x ;v k,y ;v k,z ;w k,x ;w k,y ;w k,z ;q k,w ;q k,x ;q k,y ;q k,z ] T Among them, (p k,x ;p k,y ;p k,z (t) represents the current time. k The three components of the flying car's position, (v k,x ;v k,y ;v k,z (t) represents the current time. k The three components of the speed of the flying car, w k,x 、w k,y and w k,z They are the current time t. k The roll angle, pitch angle, and yaw angle of the flying car; [q k,w ;q k,x ;q k,y ;q k,z ] T Let t be the current time. k The quaternion of flying cars; x k+1 For the predicted next time t k+1 The flying car's status parameters; u k→k+1 Let t be the current time. k At the next moment t k+1 Control input: u k→k+1 =[Thrust;M x ;M y ;M z ] T Where Thrust is the total lift from the current moment to the next moment, M x M y and M z These represent the torques in three directions of the flying car from the current moment to the next moment; y k+1 For the next moment t k+1 Output: y k+1 =[p k+1,x ;p k+1,y ;p k+1,z ;yaw k+1 ] T Among them, (p k+1,x ;p k+1,y ;p k+1,z ) represents the next time step t k+1 The three components of the flying car's position, yaw k+1 For the next moment t k+1 The yaw angle of the flying car; Where p is the position vector of the flying car. Let p be the first derivative of p, and v be the velocity vector of the flying car. Let v be the first derivative of v, and w be the angular velocity component of the flying car. Let w be the first differential of w, and q be the quaternion of the flying car. The first differential of q; The derivative of the flying car's state parameters; The system of equations for calculation is as follows: Where c is the lift vector: c = [0; 0; Thrust] T g is the gravity vector: g = [0; 0; 9.8] T M is the torque vector: M = [M x M y M z ] T J is the moment of inertia vector: J = [J xx J yy J zz ] T J xx J yy and J zz These represent the moments of inertia of the flying car in three directions; T represents the transpose. Define the loss function minJ as: minJ=(and k+1 -and ref ) T ·Q·(and k+1 -and ref )+u k→k+1 T ·R·u k→k+1 Among them, y ref For the next moment t k+1 The expected value of the output: y ref =[p ref,x ;p ref,y ;p ref,z ;yaw ref ] T (p ref,x ;p ref,y ;p ref,z ) represents the next time step t k+1 The desired positions of the flying car in three directions, yaw ref For the next moment t k+1 The expected yaw angle of the flying car, where Q and R are both weight matrices; use The computational equations and loss function are used to solve for u. k→k+1 The optimal vector is the optimal total lift and the optimal torque in three directions from the current moment to the next moment.

4. The intelligent flying car with an agile configuration according to claim 2 or 3, characterized in that, The dynamic model of the flight in the air is as follows: Where F1, F2, F3, and F4 represent the lift of the four rotors, M1, M2, M3, and M4 represent the torque of the four rotors, l1, l2, l3, and l4 represent the distances from the center of mass of the four rotors to the center of mass of the flying car, θ is the servo deflection angle, and m is the mass of the flying car. The optimal total lift from the current moment to the next moment. and This represents the optimal torque in the three directions from the current moment to the next moment.

5. The agile configuration intelligent flying car according to claim 1, characterized in that, Based on the current state parameters, the outputs of the position loop and attitude loop at the next moment are calculated using the first and second PID controllers, thereby obtaining the second derivatives of the velocity and steering angle at the next moment; including: The differential equation of the first PID controller is: Among them, K 1p , K 1i and K 1d These represent the proportional coefficient, integral coefficient, and derivative coefficient of the first PID controller, respectively; e x e y and e z The three components of the flying car's positional deviation: [e x ,e y ,e z ] T =[p x -p x_ref ,p y -p y_ref ,p z -p z_ref ] T [p x ;p y ;p z ] T These are the three components representing the current position of the flying car; [p x_ref ,p y_ref ,p z_ref ] T The three components represent the target position of the flying car; [δ x ,δ y ,δ z ] T The output of the position loop; δ x The first differential of the position in the x-direction; δ y The first differential of the position in the y-direction; δ z The first-order differential of the position in the z-direction; The differential equation for the second PID controller is: Among them, K 2p K 2i and K 2d These represent the proportional coefficient, integral coefficient, and derivative coefficient of the second PID controller, respectively. For the deviation of the steering angle of the flying car: yaw is the current turning angle of the flying car. ref The target turning angle of the flying car; This is the output of the attitude loop at the next moment; The first derivative of the flying car's steering angle; Calculate the speed v of the left wheel based on the output of the position ring at the next moment. l And the speed v of the right wheel r To obtain the velocity at the next moment. Based on the output of the attitude loop at the next moment, the second derivative of the steering angle at the next moment is obtained.

6. The agile configuration intelligent flying car according to claim 5, characterized in that, The dynamic model of the ground motion is as follows: Where v1, v2, v3, and v4 represent the speeds of the four rotors, R is the rotor radius, and l l and l r These are the radii of the left and right wheels.

7. The agile configuration intelligent flying car according to claim 1, characterized in that, The control chip also includes a water surface mode control module, and the mode switching module is further configured to: in response to a mode switching command, use a state machine to switch the flying car to water surface mode and start the water surface mode control module; The water surface modal control module is used to determine whether the flying car is moving or stationary based on the relative positions of the starting point and the target point. Based on the state parameters at the current moment, it uses the third PID controller and the fourth PID controller to calculate the output of the position loop and the output of the attitude loop at the next moment, thereby obtaining the optimal total lift and the optimal torque in the Z direction from the current moment to the next moment. Based on the optimal total lift and the optimal torque in the Z direction from the current moment to the next moment, it uses the dynamic model of water surface motion to calculate the lift of the four rotors of the cycloidal rotor aircraft from the current moment to the next moment. The lift of the four rotors is then sent to the cycloidal rotor aircraft.

8. The agile configuration intelligent flying car according to claim 7, characterized in that, Based on the current state parameters, the position loop and attitude loop for the next moment are calculated using the third and fourth PID controllers, thereby obtaining the optimal total lift and optimal torque in the Z direction from the current moment to the next moment; including: The differential equation for the third PID controller is: Among them, K 3p K 3i and K 3d These represent the proportional, integral, and derivative coefficients of the third PID controller, respectively; e x e y and e z The three components of the flying car's positional deviation: [e x ,e y ,e z ] T =[p x -p x_ref ,p y -p y_ref ,p z -p z_ref ] T [p x ;p y ;p z ] T These are the three components representing the current position of the flying car; [p x_ref ,p y_ref ,p z_ref ] T The three components represent the target position of the flying car; [δ x ,δ y ,δ z ] T The output of the position loop at the next moment; [δ x ,δ y ,δ z ] T The output of the position loop; δ x The first differential of the position in the x-direction; δ y The first differential of the position in the y-direction; δ z The first-order differential of the position in the z-direction; The differential equation for the fourth PID controller is: Among them, K 4p , K 4i and K 4d These represent the proportional coefficient, integral coefficient, and derivative coefficient of the fourth PID controller, respectively; e Φ ,e Θ and For the roll angle deviation, pitch angle deviation, and steering angle deviation of the flying car: roll is the current roll angle of the flying car. ref The target roll angle of the flying car; pitch is the current pitch angle of the flying car. ref The target pitch angle of the flying car; yaw is the current steering angle of the flying car. ref The target turning angle for the flying car; The output of the attitude loop at the next moment; δ Φ The first derivative of the roll angle; δ Θ The first derivative of the pitch angle; The first derivative of the deflection angle; The optimal total lift from the current moment to the next moment is obtained based on the output of the position loop. The optimal torque in the Z direction from the current moment to the next moment is obtained based on the output of the attitude loop.

9. The agile configuration intelligent flying car according to claim 8, characterized in that, The dynamic model of the water surface motion is as follows: Where F1, F2, F3, and F4 represent the lift of the four rotors, M1, M2, M3, and M4 represent the torque of the four rotors, l1, l2, l3, and l4 represent the distances from the center of mass of the four rotors to the center of mass of the flying car, and θ represents the servo deflection angle.

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