Four-rotor unmanned aerial vehicle air transportation control method

Abstract

The invention discloses a four-rotor unmanned aerial vehicle air transportation control method. The method comprises the following steps: step 1, constructing a two-dimensional interference dynamic model of a four-rotor unmanned aerial vehicle air transportation system; 2, constructing two interference observers for estimating equivalent external interference; and step 3, constructing an adaptive sliding mode controller, a y-axis motion control signal for controlling the motion of the quadrotor unmanned aerial vehicle in the y-axis direction and counteracting the swing angle, and a z-axis motion control signal for controlling the motion of the quadrotor unmanned aerial vehicle in the z-axis direction, and calculating the motion of the quadrotor unmanned aerial vehicle according to a control feedback signal of the quadrotor unmanned aerial vehicle and the equivalent external interference estimated in the step 2. A z-axis motion control signal is obtained through a sliding mode controller; acquiring a y-axis motion control signal through a self-adaptive sliding mode controller; and 4, converting the control signal of the quad-rotor unmanned aerial vehicle obtained in the step 3 into the control force of the quad-rotor unmanned aerial vehicle. According to the invention, the nonlinear interference observer is designed and is used for estimating and compensating unknown interference in real time, so that the anti-interference capability is improved.

Description

Technical Field

[0001] The invention relates to the technical field of aerial transport control of unmanned aerial vehicles, and in particular to an aerial transport control method of a quad-rotor unmanned aerial vehicle. Background Art

[0002] Quad-rotor drones have been widely used in military, agriculture, logistics, environmental monitoring and other fields due to their high maneuverability, low cost and small size. Among them, quad-rotor drones have shown special advantages in air transportation, especially suitable for transportation tasks with suspended loads. In recent years, air transportation systems based on quad-rotor drones have become a research hotspot and have received more and more attention and development.

[0003] At present, there are two main design methods for the air transport system of quadcopters. One is the rigid connection method, that is, the load is directly connected to the drone through a rigid mechanical structure. Although this method simplifies the control design, the addition of the mechanical structure significantly increases the system inertia, thereby reducing the flexibility and overall load capacity of the system. The other is the flexible connection method, that is, the load is connected to the quadcopter through a rope. Flexible connection can significantly increase the load capacity while maintaining the flexibility of the system, but the challenge that comes with it is that the entire system is more susceptible to external environmental interference. In addition, due to the flexible connection, the swing angle of the load cannot be directly controlled by the driving force, and the swing of the load can only be indirectly adjusted by the control force applied to the drone body. This underpowered characteristic greatly increases the difficulty of control.

[0004] In actual flight, when a quadcopter is disturbed by the external environment or performs complex maneuvering tasks, the suspended load often swings uncontrollably. This swing has a slow natural convergence speed and may be further amplified by the movement of the drone, increasing the instability of the system and even threatening the safety and reliability of the entire transportation task. Therefore, how to effectively suppress the load swing and achieve coordinated control of the drone and the load has become a research focus in this field. In response to the above problems, researchers have proposed a variety of control strategies to achieve anti-swing control and position control, thereby reducing the risks brought by load swing. The most commonly used control methods currently include: PID control directly suppresses the load swing angle, but the effect is poor and it is difficult to meet the control requirements of complex transportation tasks; the input shaping controller is mainly used to eliminate the internal swing problem of the system, but its ability to suppress external interference is limited; LQR is usually combined with the backstepping method of known trajectories for control, but its adaptability to external interference is weak; although adaptive control can better cope with complex systems, its design process is complicated, parameter adjustment is difficult, and the control effect is easy to fluctuate with changes in the control rate. Summary of the invention

[0005] In view of the deficiencies in the prior art, the present invention provides a quad-rotor UAV aerial transport control method to solve the technical problem that the prior art lacks effective control for objects with unknown parameters.

[0006] The present invention provides a quad-rotor UAV air transport control method, comprising the following steps:

[0007] Step 1: Construct a two-dimensional interference dynamics model of the quadrotor UAV air transport system;

[0008] Step 2: Construct two disturbance observers to estimate the equivalent external disturbances of the y-axis and z-axis in the disturbance observer state model respectively;

[0009] Step 3: Construct an adaptive sliding mode controller, a y-axis motion control signal that controls the y-axis motion of the quadrotor drone and offsets the swing angle, and a z-axis motion control signal that controls the z-axis motion of the quadrotor drone.

[0010] According to the control feedback signal of the quadrotor drone and the equivalent external disturbance estimated by step 2, the z-axis motion control signal is obtained by the sliding mode controller; the y-axis motion control signal is obtained by the adaptive sliding mode controller, wherein the control target of the sliding mode controller is: the position of the quadrotor drone on the z-axis of the inertial coordinate system tends to the desired position; the control target of the adaptive sliding mode controller is: the position of the quadrotor drone on the y-axis of the inertial coordinate system tends to the desired position, and the swing angle tends to zero;

[0011] Step 4: Convert the control signal of the quadrotor drone obtained in step 3 into the control force of the quadrotor drone to control the quadrotor drone.

[0012] Furthermore, in step 2, the state model of the disturbance observer constructed for the y-axis equivalent external disturbance is:

[0013]

[0014] The state model of the disturbance observer constructed for the equivalent external disturbance of the z-axis is:

[0015]

[0016] Where, d y is the equivalent external disturbance on the y-axis, d y =-d γ m p cosγ-f 1 m q ;d z is the equivalent external disturbance on the z-axis, d z =-d γ m psinγ-m q f 2 ;d γ =f 1 cosγ+f 2 sinγ;

[0017] Furthermore, the estimation formula of the y-axis equivalent external interference is:

[0018]

[0019] In the formula, v 1 is the auxiliary variable of the disturbance observer, l 1 is the state estimation error,

[0020] Furthermore, the estimation formula of the z-axis equivalent external interference is:

[0021]

[0022] In the formula, v 2 is the auxiliary variable of the disturbance observer, is the state estimation error,

[0023] Furthermore, in step 3, the z-axis motion control signal is:

[0024]

[0025] In the formula, e z is the position tracking error signal of the quadrotor drone in the z direction, e z =zz d ; S z is the sliding surface,

[0026]

[0027] Furthermore, in step 3, the y-axis motion control signal is:

[0028]

[0029] In the formula, e y is the position tracking error signal of the quadrotor drone in the y direction, e y =yy f ; S y is the sliding surface, y f It is the adaptive control target of the y-axis motion control signal.

[0030] Furthermore, in step 3, the adaptive control variable y of the y-axis motion control signal f The specific formula for (t) is:

[0031] In the formula, h n,0 =y f (nT);

[0032]

[0033] Furthermore, the control force of the quadrotor drone in step 4 is:

[0034]

[0035] Beneficial effects of the present invention:

[0036] The present invention designs a new type of nonlinear disturbance observer for real-time estimation and compensation of unknown disturbances in a quad-rotor suspension transport system. The disturbance observer of the present invention has nonlinear system characteristics. By modeling and analyzing the dynamic relationship between the input and output of the system, it can accurately capture the characteristics of different types of disturbances, including external environmental disturbances, such as wind force, airflow fluctuations, and system internal uncertainties, such as parameter changes and structural coupling effects. By introducing an disturbance observer, the present invention can achieve efficient estimation of disturbances without adding additional sensors, ensure accurate modeling and compensation of various complex disturbances, not only improve the estimation accuracy of the disturbance observer itself, but also effectively enhance the controller's adaptability and robustness to dynamic changes in the system. The real-time disturbance estimation output of the disturbance observer is used to correct the input signal of the controller, thereby significantly reducing the control error caused by unknown disturbances and improving the overall performance of the system.

[0037] When designing the control strategy, the present invention constructs an adaptive controller and an adaptive control target, so that the controller can dynamically adjust its own parameters to adapt to different operating states and task requirements. The adaptive control target combines position control and load swing angle constraints, and optimizes the control input to ensure that the system meets the strict constraints on the load swing angle while achieving the position control target. Compared with traditional methods, the present invention not only has higher response speed and control accuracy, but also can maintain system stability in complex dynamic environments.

[0038] The present invention provides an efficient and universal solution to the disturbance compensation and constraint control problems in underactuated systems, and can be widely used in quadrotor air transportation and other complex nonlinear control systems. BRIEF DESCRIPTION OF THE DRAWINGS

[0039] The features and advantages of the present invention will be more clearly understood by referring to the accompanying drawings, which are schematic and should not be construed as limiting the present invention in any way. In the accompanying drawings:

[0040] Figure 1 is a schematic diagram of signal flow in a specific embodiment of the present invention;

[0041] Figure 2 Schematic diagram of a quad-rotor drone power model according to a specific embodiment of the present invention;

[0042] Figure 3 It is a block diagram of an interference observer in a specific embodiment of the present invention. DETAILED DESCRIPTION

[0043] In order to make the purpose, technical solution and advantages of the embodiments of the present invention clearer, the technical solution in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative work are within the scope of protection of the present invention.

[0044] The present invention is further illustrated below in conjunction with specific embodiments. Those skilled in the art should understand that these embodiments are only used to illustrate the present invention and are not used to limit the scope of the present invention, and modifications to various equivalent forms of the present invention fall within the scope defined by the appended claims of this application.

[0045] like Figure 1 As shown, the present invention provides a method for controlling air transportation of a quad-rotor UAV, comprising the following steps:

[0046] Step 1: If Figure 2 As shown in the figure, a two-dimensional interference dynamics model of the quadrotor UAV air transport system is constructed:

[0047]

[0048] In the formula, m q 、m p are the masses of the quadcopter and the load, respectively; l is the length of the hanging rope; γ is the swing angle of the load; g is the acceleration of gravity; b is the air resistance coefficient; d 1 ,d 2 All are unknown external interferences; y and z are the positions of the quadrotor drone relative to the inertial coordinate system; u y 、u z The control input is I ,z I Directional control;

[0049] Rewrite the dynamic model into Euler-Poincare form:

[0050]

[0051] In the formula, q is the state vector of the system, that is, the drone is in y I ,z I The position and load in two directions and the angle between them and the vertical direction of the machine body, q = [y zγ] T ∈R 3 ;M c (q), G(q)∈R 3 They represent the inertial matrix, centripetal-Coriolis matrix, and gravity vector of the quadrotor air transport system respectively; U∈R 3 They represent the unknown external disturbance vector of the quadrotor and the lift vector of the propeller, respectively. The unknown external disturbance vector includes the air resistance vector, which is specifically defined as follows:

[0052]

[0053] G(q)=[0(m p +m q )gm p glsinγ] T

[0054]

[0055]

[0056] Step 2: Construct two disturbance observers to estimate the equivalent external disturbances of the y-axis and z-axis in the disturbance observer state model respectively;

[0057] The kinetic model is rewritten as:

[0058]

[0059] in,

[0060] According to Cramer's law, the state model of the disturbance observer constructed for the equivalent external disturbance on the y-axis is:

[0061]

[0062] The state model of the disturbance observer constructed for the equivalent external disturbance of the z-axis is:

[0063]

[0064] Where, d yis the equivalent external disturbance on the y-axis, d y =-d γ m p cosγ-f 1 m q ;d z is the equivalent external disturbance on the z-axis, d z =-d γ m p sinγ-m q f 2 ;d γ =f 1 cosγ+f 2 sinγ.

[0065] like Figure 3 As shown, take the disturbance observer constructed for the equivalent external disturbance on the y-axis as an example:

[0066] The state estimation model of the disturbance observer is:

[0067]

[0068] In the formula, x 1 represents the estimated state variables of the system; k 1 =(m q +m p cos 2 γ)u y ; k 3 =u z m p sinγcosγ; D=m q (m p +m q ); c is the disturbance observer gain, which is used to adjust the dynamic response speed of the disturbance observer.

[0069] The state estimation error of the disturbance observer is l 1 Set to actual output With the state estimate x 1 The difference between:

[0070]

[0071] By l 1 and its derivatives and the second derivative Construct the auxiliary variable v of the disturbance observer 1 (t), auxiliary variable v 1 The satisfied relationship is as follows:

[0072]

[0073] By combining the auxiliary variables and the state estimation error, we can get the estimated value of the equivalent external disturbance on the y-axis:

[0074]

[0075] The disturbance observer continuously corrects the state estimation error l 1 and its first and second order derivatives, estimate the disturbance in the system in real time and feed it back to the control input to effectively compensate for the disturbance.

[0076] Similarly, the estimated value of the equivalent external disturbance on the y-axis by the disturbance observer constructed for the equivalent external disturbance on the z-axis is:

[0077]

[0078] in, k 4 =(m q +m p sin 2 γ)u z ; k 6 =u y m p sinγcosγ;k 7 =-(m q +m p )m q g.

[0079] In both disturbance observers, the value of D depends on the system parameters. c is a positive constant and can be fine-tuned through experiments. The disturbance observer can use known information about the controlled object, such as system state, control input or output, to estimate the external disturbance. In addition, the output of the disturbance observer can also be used to design the control law. According to the designed disturbance observer, by properly selecting the control parameter c, the intermediate variable v can be obtained. i .therefore, We can use the known variable l i and v i to achieve.

[0080] Step 3: Construct an adaptive sliding mode controller, a y-axis motion control signal that controls the y-axis motion of the quadrotor drone and offsets the swing angle, and a z-axis motion control signal that controls the z-axis motion of the quadrotor drone.

[0081] According to the control feedback signal of the quadrotor UAV and the equivalent external disturbance estimated by step 2, the z-axis motion control signal is obtained through the sliding mode controller; the y-axis motion control signal is obtained through the adaptive sliding mode controller, wherein the control target of the sliding mode controller is: the position of the quadrotor UAV on the z-axis of the inertial coordinate system tends to the desired position; the control target of the adaptive sliding mode controller is: the position of the quadrotor UAV on the y-axis of the inertial coordinate system tends to the desired position, and the swing angle tends to zero.

[0082] For the control of the motion in the z-axis direction, a common sliding mode controller is used.

[0083] Sliding surface S of sliding mode control z for:

[0084]

[0085] Among them, α 1 Is a positive number, used to adjust the convergence speed of the system. Sliding surface S z The design purpose of =0 is to hope that when the system moves on the sliding surface, the error can gradually tend to zero, thereby achieving the control goal of the system.

[0086] Reaching Law of Sliding Mode Control z for:

[0087] Among them, β 1 Is a positive number.

[0088] z-axis motion control signal w 1 The construction process is:

[0089] Let w 1 =k 4 +k 6 , after adding the sliding mode controller:

[0090]

[0091] Adding the estimated value of the disturbance observer to the disturbance can effectively reduce the jitter by reducing the switching gain, and the z-axis motion control signal w 1 The final build is:

[0092]

[0093] In the formula, e z is the position tracking error signal of the quadrotor drone in the z direction, e z =zz d ; S z is the sliding surface,

[0094] For the control of the motion in the y-axis direction, the constructed adaptive sliding mode controller is used for control, and a control signal is required to realize the control of the motion in the y-direction and the control of the swing angle γ.

[0095] In order to realize the simultaneous control of the y-direction motion and the swing angle γ, the present invention introduces the adaptive control variable y f (t), and adjust y by adaptive sliding mode controller f (t) makes the swing angle approach zero, while y f (t) tends to the desired position y d .y f The specific formula of (t) is as follows:

[0096]

[0097] Where, t is the time variable; T is the sampling period; h,h n,0 ,h n,1 The calculation formula is as follows:

[0098]

[0099] h n,0 =y f (nT)

[0100]

[0101] in, The kinetic model can be: Transformed into: get.

[0102] Y-axis motion control signal w 1 The construction process is:

[0103] Let w 2 =k 1 +k 3 , after adding the adaptive sliding mode controller and the estimated disturbance value:

[0104]

[0105] In the formula, e y is the position tracking error signal of the quadrotor drone in the y direction, e y =yy f ; S y is the sliding surface, y f It is the adaptive control target of the y-axis motion control signal.

[0106] Step 4: Convert the control signal of the quadrotor drone obtained in step 3 into the control force of the quadrotor drone to control the quadrotor drone.

[0107] By 1 and w 2 The design can get the control input u y and u z for:

[0108]

[0109] Although the embodiments of the present invention have been described in conjunction with the accompanying drawings, those skilled in the art may make various modifications and variations without departing from the spirit and scope of the present invention, and such modifications and variations are all within the scope defined by the appended claims.

Claims

1. A quad-rotor drone air transport control method, characterized in that: The steps include: Step 1: Construct a two-dimensional interference dynamics model of the quadrotor UAV air transport system; Step 2: Construct two disturbance observers to estimate the equivalent external disturbances of the y-axis and z-axis in the disturbance observer state model respectively; Step 3: Construct an adaptive sliding mode controller, a y-axis motion control signal that controls the y-axis motion of the quadrotor drone and offsets the swing angle, and a z-axis motion control signal that controls the z-axis motion of the quadrotor drone. According to the control feedback signal of the quadrotor drone and the equivalent external disturbance estimated by step 2, the z-axis motion control signal is obtained by the sliding mode controller; the y-axis motion control signal is obtained by the adaptive sliding mode controller, wherein the control target of the sliding mode controller is: the position of the quadrotor drone on the z-axis of the inertial coordinate system tends to the desired position; the control target of the adaptive sliding mode controller is: the position of the quadrotor drone on the y-axis of the inertial coordinate system tends to the desired position, and the swing angle tends to zero; Step 4: Convert the control signal of the quadrotor drone obtained in step 3 into the control force of the quadrotor drone to control the quadrotor drone.

2. The quad-rotor drone air transport control method according to claim 1, characterized in that: In step 2, the state model of the disturbance observer constructed for the equivalent external disturbance on the y-axis is: The state model of the disturbance observer constructed for the equivalent external disturbance of the z-axis is: Where, d y is the equivalent external disturbance on the y-axis, d y =-d γ m p cosγ-f1m q ;d z is the equivalent external disturbance on the z-axis, d z =-d γ m p sinγ-m q f2;d γ =f1cosγ+f2sinγ; 3. The quad-rotor drone air transport control method according to claim 2, characterized in that: The estimation formula of the y-axis equivalent external interference is: Where v1 is the auxiliary variable of the disturbance observer, l1 is the state estimation error, 4. The quad-rotor drone air transport control method according to claim 2, characterized in that: The estimation formula of the equivalent external interference of the z-axis is: Where v2 is the auxiliary variable of the disturbance observer, l3 is the state estimation error, 5. The quad-rotor UAV air transport control method according to claim 3, characterized in that: In step 3, the y-axis motion control signal is: In the formula, e y is the position tracking error signal of the quadrotor drone in the y direction, e y =yy f ; S y is the sliding surface, y f It is the adaptive control target of the y-axis motion control signal.

6. The quad-rotor drone air transport control method according to claim 4, characterized in that: In step 3, the z-axis motion control signal is: In the formula, e z is the position tracking error signal of the quadrotor drone in the z direction, e z =zz d ; S z is the sliding surface, 7. The quad-rotor drone air transport control method according to claim 5, characterized in that: In step 3, the adaptive control variable y of the y-axis motion control signal f The specific formula for (t) is: In the formula, h n,0 =y f (nT); 8. The quad-rotor drone air transport control method as described in any one of claims 5 to 7, characterized in that: The control force of the quadrotor drone in step 4 is:

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