Close following control method and system for spherical airship robot under strong airflow disturbance

Abstract

The invention discloses a close following control method and system for a spherical airship robot under strong airflow disturbance. The method comprises the steps that a close following three-dimensional kinematics model is established; establishing a bird flock-imitating close following aerodynamic influence model; establishing a spherical airship space dynamic equation; establishing collision detection auxiliary control based on a touch sensor; and constructing a model prediction close following control equation. According to the method, a bird flock formation strategy is used for reference, a dynamic model fused with aerodynamic characteristics, touch sensor collision detection auxiliary control and an accurate model prediction control algorithm are constructed, and the technical defects that a traditional control method cannot effectively establish aerodynamic interaction between airships and the problem of tight flight collision is caused by missing positioning data are overcome; stable airship close following control is achieved, and technical support is provided for a multi-airship cooperative task in a small-space complex scene.

Description

Technical Field

[0001] The present invention belongs to the field of aircraft control technology, and involves related technologies in the technical fields of unmanned systems, drones, robots, automatic control, sensors, etc., and in particular, relates to a close following control method and system for a spherical airship robot under strong airflow disturbance. Background Art

[0002] Flying robot technology is a cutting-edge research area in current science and technology. Traditional rotary-wing flying robots, with their advantages such as simple mechanical structure, high speed, and high maneuverability, have been widely used in transportation, mapping, and rescue operations. In recent years, multi-robot formation technology has developed rapidly, playing a vital role in logistics distribution, agricultural plant protection, and emergency rescue. This technology is based on the concept of natural flocking systems, such as migratory birds that save energy by flying in formation at specific distances. Flying robots in close formation not only save energy but also reduce space consumption.

[0003] When traditional rotorcraft fly in close formation, their rigid fuselages and high-speed propellers can easily collide, causing damage and potentially endangering nearby personnel. This limits the application of formation technology in confined or complex spaces, making close-range human-robot interaction difficult. In contrast, airship robots utilize a unique structure containing airbags, which generate additional lift through low-density gas filling. This offers advantages such as low energy consumption and extended flight time. Their flexible fuselage reduces the risk of collisions during close-range flight. Therefore, airship robots offer advantages in formation operations. For example, the Chinese patent application with application number CN202110245487.X proposes a method for tracking and controlling the trajectory of airship formation flight, which can enable the airship to track the lead airship and the desired formation formation; the Chinese patent application with application number CN202110924055.1 proposes a method for controlling the flight of airship formation, which can achieve regional coverage control; the Chinese patent application with application number CN202110830757.3 proposes a method for controlling the flight of unmanned airship formation, which can achieve high-precision and stable control of the flight of airship formation. However, the above patents all focus on the optimization of formation control strategies, without considering the aerodynamic characteristics of multiple airship robots under high-density cluster formations, lack in-depth modeling research on the kinematics and dynamic characteristics of the airship itself, and fail to solve the impact of airflow interference between airships on close-following motion. It is difficult to solve the problems of attitude instability and trajectory deviation caused by aerodynamic coupling when multiple airships work together in close proximity.

[0004] The light weight of airships makes them susceptible to interference from changes in airflow. Chinese patent application number CN202411152511.5 proposes an airship robot and adjustment method. By controlling the center of mass, the airship's flight direction and attitude can be adjusted, enhancing the robot's ability to withstand environmental airflow disturbances. This design primarily focuses on adjusting the airship's structure, lacks research on control schemes, and is unable to cope with complex airflow changes. When multiple airships are closely following each other, the interaction of airflow around each body creates complex aerodynamic interference, making it difficult for the airship robot to achieve stable flight. Furthermore, when multiple airships are closely following each other, collisions and formation disruptions can easily occur due to inaccurate positioning information. The existing technology lacks a comprehensive technical solution that can effectively overcome the mutual interference between airship bodies during close flight, and cannot meet the requirements of high-precision, close-following missions in small spaces and complex scenarios.

[0005] Therefore, there is an urgent need to develop a new technical solution that can accurately model aerodynamic interference between airships and achieve stable, close-following control. This solution will not only improve the efficiency of multi-airship transport and monitoring tasks, further expanding the application areas of airship robots, but also provide new insights into collaborative control technology for flying robots, thus possessing important theoretical significance and engineering application value. Summary of the Invention

[0006] In response to the existing problems in the prior art of unstable control caused by aerodynamic interference between airships during close following motion, and the problem of data inaccuracy of the positioning system in complex environments affecting control accuracy and formation stability, this patent proposes a close following control method and system for a spherical airship robot under strong airflow disturbances. The method aims to solve the technical defects of traditional control methods in that they fail to effectively establish aerodynamic interactions between airships and close flight collisions caused by missing positioning data by drawing on bird flock formation strategies, constructing a dynamic model that integrates aerodynamic characteristics, tactile sensor collision detection auxiliary control, and precise model predictive control algorithms, thereby achieving stable close following control of airships and providing technical support for multi-airship collaborative tasks in complex scenarios in small spaces.

[0007] To achieve the above object, the technical solution adopted by the present invention is as follows:

[0008] A close following control method for a spherical airship robot under strong airflow disturbance comprises the following steps:

[0009] Step 1: Establish a close-following three-dimensional kinematic model: Based on the airship's motion characteristics and the close-following motion requirements, establish a three-dimensional relative motion model of close-following motion in an inertial coordinate system.

[0010] Step 2: Establish an aerodynamic impact model for closely following a flock of birds: Based on the airflow interference characteristics during the closely following motion of the spherical airship, select key influencing factors and establish an aerodynamic impact model;

[0011] Step 3: Establishing the spatial dynamic equation of the spherical airship: Establishing the spatial dynamic equation based on the structural characteristics and motion characteristics of the spherical airship;

[0012] Step 4: Establishing collision detection auxiliary control based on tactile sensors;

[0013] Step 5: Constructing a model to predict the close following control equation: Based on the spatial dynamic equations, according to the close formation motion strategy and control objectives, constructing a model to predict the close following control equation.

[0014] Furthermore, the step 1 includes the following sub-steps:

[0015] Step 1.1, define the inertial coordinate system O n x n y n z n ;

[0016] Step 1.2, define the airship body coordinate system and establish the rotation matrix between the inertial coordinate system and the airship body coordinate system;

[0017] Step 1.3: Establish the transformation relationship between the airship robot in the inertial coordinate system and the body coordinate system;

[0018] Step 1.4, establish the relative position update equation for the airship to closely follow the motion:

[0019]

[0020] Among them, x ijd (t), y ijd (t), z ijd (t) is the component of the distance between the i-th and j-th airship robots, the i-th airship robot is the pilot airship, the j-th airship robot is the follower airship, u iL (t), v iL (t), w iL (t) is the velocity component of the pilot airship, u jW (t), v jW (t), w jW (t) is the velocity component of the following airship, t is time, and Δt is the time change.

[0021] Furthermore, step 2 includes the following sub-steps:

[0022] Step 2.1: Define the simplified models of the pilot airship and the follower airship. The positional relationship between the pilot airship and the follower airship, with the reference coordinate system being the inertial coordinate system, is as follows:

[0023]

[0024] Among them, x d 、y d is the distance component between the pilot airship and the following airship, d is the airbag distance, is the angle between the lead airship and the follower airship, u L is the pilot airship speed, u W is the speed of the following airship, t is the flight time;

[0025] Step 2.2: Define the airship airbag force analysis model

[0026] The interference airflow generated by the pilot airship acts on the airbag of the following airship. The microelement area dS of a certain force point on the airbag of the following airship is i for:

[0027]

[0028] Among them, dl is the width of the infinitesimal element of the circular ring where the force point is located, r is the radius of the circular ring where the force point is located, θ is the angle between the line connecting the circular ring where the force point is located and the center of the airbag and the vertical direction, r c is the radius of the airbag following the airship, α is the projection of the angle between the force point and the center of the airbag on the Oxy plane;

[0029] Step 2.3: The wind load and moment generated by the interference airflow generated by the pilot airship at the force point of the airbag of the follower airship are:

[0030]

[0031] dM i =dF i ×r c sinθ

[0032] Among them, dF i 、dM i is the force and torque, V i is the speed of the disturbed air flow;

[0033] Step 2.4: Select the key influencing factor A to characterize the change in the velocity of the disturbed airflow on the airbag surface:

[0034]

[0035] Among them, A mn It depends on the opening angle of the airbag surface of the following airship, the speed of the leading airship and the relative deflection angle between the two aircraft, and has nothing to do with the motion state of the following airship;

[0036] Step 2.5: Establish aerodynamic impact model

[0037] The velocity of the disturbed airflow at the force point of the following airship airbag V Wi for:

[0038]

[0039] Among them, x Pdi 、y Pdi are the y-axis and y-axis components of the distance between the force point and the pilot airship, u L is the velocity component of the pilot airship, u W is the velocity component following the airship, is the deflection angle between the lead airship and the following airship;

[0040] The force and torque generated by the interfering airflow on the force-bearing surface of the airbag following the airship are:

[0041]

[0042] Among them, F WI The dynamic equation representing the aerodynamic force around the spherical airbag following the airship is x di 、y di 、z di are the distances between the airbag force position in the x, y, and z axes in the inertial coordinate system, is the relative deflection angle of the force position, u L 、u W are the speeds of the lead airship and the following airship respectively.

[0043] Furthermore, step 3 includes the following sub-steps:

[0044] Step 3.1, establish the mathematical model of the airship:

[0045]

[0046] Among them, f x 、f y 、f z is the motor propulsion force, x, y, z are the position of the airship, ψ is the yaw, m is the mass of the airship, m 11 、m 22 、m 33 、m 66 is the additional mass, D u 、D v 、D w 、D p 、D q 、D r is the linear damping coefficient, D u2 、Dv2 、D w2 、D p2 、D q2 、D r2 is the secondary damping coefficient, u, v, w are the airship velocities in the body coordinate system, r is the yaw angular velocity of the airship in the body coordinate system, F Ix 、F Iy 、M Iz It is the component affected by the interfering airflow;

[0047] Step 3.2: The yaw angle of the airship is kept at zero degrees during the motion. When performing yaw angle control, it is assumed that the x-axis and y-axis velocities are constants u0 and v0. The spatial state equation of the airship is constructed as follows:

[0048]

[0049] Among them, I z is the z-axis moment of inertia, τ z is the rotational torque about the z-axis.

[0050] Furthermore, the step 4 is specifically as follows: a plurality of tactile sensors are distributed on the surface of the airship airbag, and a control output C(t) is triggered when it is determined that any single point contact force exceeds a threshold.

[0051] Furthermore, the tactile sensors are evenly distributed on the equator of the surface of the spherical airbag, and the tactile sensors are flexible piezoresistive thin film tactile sensors.

[0052] Furthermore, the step 5 includes the following sub-steps:

[0053] Step 5.1, take The discretized state space model of the airship is:

[0054] X k+1 =AX k +Bu k +Cd k

[0055] Where, X k is the state vector at time k; u k is the control input vector at time k; d k is the interference vector at time k, A, B, C are the state matrices;

[0056] Step 5.2, take the control input variable Δu k =u k -u k-1 , the prediction model of the following airship robot is:

[0057] X k+1|k =Γ X ΔX k +Γu Δu k +Γ D ΔD k

[0058] Among them, X k+1 It is the future N p The predicted state vector at the moment; Δu k It is the future N c The control input increment vector at the moment is the future N p The external interference increment vector at the moment; Γ X , Γ Y and Γ Z is the prediction coefficient matrix;

[0059] Step 5.3, design the performance index function as:

[0060]

[0061] Among them, Y k+i|k is the predicted output vector at time i in the future; is the reference output vector at time i in the future; Q and R are the weight matrices of the output state and the control input change, respectively.

[0062] Step 5.4, define the reference output vector as:

[0063]

[0064] in, Indicates that the following airship robot is at k+N p The desired state at the moment;

[0065] Assume that in N p After the step, the state of the follower airship robot is predictable and constant:

[0066]

[0067] S5.5: Establish constraints as follows:

[0068]

[0069] ΔU min ≤ΔU≤ΔU max

[0070] Among them, u k ,u k+1 ,…,u k+Nc-1 is the discrete control input, Δu k , Δu k+1 ,…,Δu k+Nc-1 is the discrete control input variation;

[0071] S5.6: Convert the problem into a quadratic programming problem:

[0072]

[0073] In each sampling time, the optimal solution of the performance index function is solved by the optimization algorithm to obtain the optimal control sequence and predicted state variables; the optimized state variables are taken as the reference position of the following airship robot to obtain the optimal trajectory.

[0074] The present invention also provides a close following control system for a spherical airship robot under strong airflow disturbance, comprising a memory, a processor and a computer program stored in the memory, wherein the processor executes the computer program to implement the steps of a close following control method for a spherical airship robot under strong airflow disturbance.

[0075] Furthermore, the processor and memory are arranged on a spherical airship robot, and the spherical airship robot includes an airbag and a frame arranged below the airbag, and a thin film tactile sensor is integrated at the horizontal equator line of the airbag.

[0076] Compared with the prior art, the present invention has the following beneficial effects:

[0077] (1) The present invention improves the mathematical model of close following of multiple airships by constructing an influence model that includes the characteristics of aerodynamic interference. Compared with the traditional airship model, it more accurately describes the influence of aerodynamic interference on the motion state of airships during the close following of multiple airships, thereby improving the stability of spherical airship robots in close formation flight control.

[0078] (2) The present invention is based on the established mathematical model of the airship and combines it with the model predictive control algorithm to effectively solve the control instability problem caused by aerodynamic interference during the close following of the airship.

[0079] (3) The present invention combines thin film tactile sensors to form a prediction-perception-control solution, which realizes adaptive adjustment in complex positioning environments, so that the airship can achieve stable close following control in the absence of positioning information. At the same time, in scenarios such as indoor precision operations and small space collaborative transportation, it can complete close following tasks with higher safety and stability, thereby improving the collaborative operation capabilities of multiple airships. BRIEF DESCRIPTION OF THE DRAWINGS

[0080] Figure 1 1 is a flow chart of a spherical airship close following control method considering aerodynamic interference in an embodiment of the present invention;

[0081] Figure 2 This is a schematic diagram of the overall structure of a spherical airship in an example of the present invention;

[0082] Figure 3 This is a schematic diagram of an airship coordinate system in an example of the present invention;

[0083] Figure 4 This is a simplified model diagram of an airship in an example of the present invention;

[0084] Figure 5 This is a schematic diagram of force analysis of an airship airbag in an example of the present invention;

[0085] Figure 6 This is a schematic diagram of a method of following the change of gas flow velocity on the surface of an airship airbag in an example of the present invention;

[0086] Figure 7 is a schematic diagram of an airship closely following a motion control framework in an example of the present invention;

[0087] Figure 8 It is a schematic diagram of the results of a simulation experiment of an airship closely following motion in an example of the present invention.

[0088] Description of reference numerals:

[0089] 1. Airbag; 2. Frame; 3. Thin film tactile sensor. DETAILED DESCRIPTION

[0090] The technical solutions provided by the present invention will be described in detail below with reference to specific embodiments. It should be understood that the following embodiments are only used to illustrate the present invention and are not used to limit the scope of the present invention.

[0091] The present invention provides a close following control method for a spherical airship robot under strong airflow disturbance, the process of which is as follows: Figure 1 As shown, the following steps are included:

[0092] Step S1: Based on the airship motion characteristics and the requirement of closely following the motion, a three-dimensional relative motion model of closely following the motion is established in an inertial coordinate system, including the following sub-steps:

[0093] S1.1: Define the inertial coordinate system O n x n y n z n :O n x n The axis points to the geographic North Pole, O n y n The axis points to geographic east, O n z n The axis is vertically downward, such as Figure 3 shown.

[0094] S1.2: Define the airship coordinate system: In a multi-airship close following motion, the i-th airship and the j-th airship are in a leading and following relationship, and the center of their airbags is the origin O.L , O W , the x-axis is in the longitudinal section of the airship and points to the forward direction; the y-axis is in the transverse section of the airship and points to the right; the z-axis points to the bottom, as shown in Figure 3 As shown. The rotation matrix between the inertial coordinate system and the body coordinate system is:

[0095]

[0096] in, is the roll angle, θ is the pitch angle, and ψ is the yaw angle.

[0097] S1.3: The transformation relationship between the inertial coordinate system and the body coordinate system of the airship robot is:

[0098]

[0099] where [x, y, z] T is the three-dimensional coordinate of the airship robot, [u, v, w] T is the linear velocity of the airship robot in the machine system, is the attitude angle of the airship robot, [p, q, r] T is the angular velocity of the airship robot in the machine system.

[0100] S1.4: The relative position update equation for the airship to closely follow the motion is established as:

[0101]

[0102] Among them, x ijd (t), y ijd (t), z ijd (t) is the component of the distance between the i-th and j-th airship robots, the i-th airship is the pilot airship, the j-th airship is the follower airship, u iL (t), v iL (t), w iL (t) is the velocity component of the pilot airship, u jW (t), v jW (t), w jW (t) is the velocity component of the following airship, t is time, and Δt is the time interval.

[0103] Step S2: Based on the airflow interference characteristics during the close following motion of the spherical airship, key influencing factors are selected and an aerodynamic influence model is established, which includes the following sub-steps:

[0104] S2.1: Define the simplified model of the pilot airship and the follower airship, such as Figure 4 As shown, the reference coordinate system is the inertial system. The position relationship between the pilot airship and the follower airship is:

[0105]

[0106] Among them, x d 、y d is the distance component between the pilot airship and the following airship, d is the airbag distance, is the angle between the lead airship and the follower airship, u L is the pilot airship speed, u W is the speed of the following airship, and t is the flight time.

[0107] S2.2: Define the airbag force analysis model: The interference airflow generated by the pilot airship acts on the airbag of the following airship, such as Figure 5 As shown, a force point P on the follower airship airbag is located on a circular ring element with a width of dl. The radius of the ring is r, and the angle between the line connecting the ring and the airbag center and the vertical direction is θ. The area of ​​the element where point P is located is:

[0108]

[0109] Among them, r c is the radius of the airbag following the airship, and α is the projection of the angle between the force point and the center of the airbag on the Oxy plane.

[0110] S2.3: The wind load and moment generated by the interference airflow generated by the pilot airship at point P are:

[0111]

[0112] dM i =dF i ×r c sinθ (10)

[0113] Among them, dF i 、dM i is the force and torque, V i is the disturbing air velocity and ρ is the fluid density.

[0114] S2.4: If Figure 6 As shown in the figure, the velocity of the interfering airflow on the airbag surface of the following airship is related to the opening angle of the airbag surface, the speed of the pilot airship, and the relative angle between the two aircraft. The influencing factor A is introduced to characterize the change of the interfering airflow velocity on the airbag surface:

[0115]

[0116] Among them, A mn (m, n = 0, 1, 2, 3, 4, 5) depends on the opening angle of the airbag surface of the following airship, the speed of the leading airship and the relative deflection angle between the two aircraft, and has nothing to do with the motion state of the following airship.

[0117] Based on the above analysis, an aerodynamic impact model can be established:

[0118] S2.5: The velocity of the interfering airflow at the force point of the following airbag is:

[0119]

[0120] Among them, x Pdi 、y Pdi are the y-axis and y-axis components of the distance between the force point and the pilot airship, u L is the velocity component of the pilot airship, u W is the velocity component following the airship, is the deflection angle between the lead airship and the following airship.

[0121] S2.6: The force and moment generated by the interfering airflow wind load on the load-bearing surface of the follower airbag are:

[0122]

[0123] Among them, F WI The dynamic equation representing the aerodynamic force around the spherical airbag following the airship is x di 、y di 、z di are the distances between the airbag force position in the x, y, and z axes in the inertial coordinate system, is the relative deflection angle of the force position, u L 、u W are the speeds of the lead airship and the following airship respectively.

[0124] Step S3: Establishing a spatial dynamic equation based on the structural characteristics and motion characteristics of the spherical airship, including the following sub-steps:

[0125] S3.1: The air resistance experienced by an airship flying at low speed consists of linear friction proportional to the laminar velocity and turbulent friction proportional to the square of the turbulent velocity:

[0126]

[0127] Among them, D u 、D v 、D w 、D p 、D q 、D r is the linear damping coefficient, D u2 、D v2 、D w2 、D p2 、D q2 、D r2 is the secondary damping coefficient.

[0128] S3.2: The fluid inertial forces and moments acting on the airship during flight are:

[0129]

[0130] Among them, m 11 、m 22 、m 33 、m 44 、m 55 、m 66 is the added mass.

[0131] S3.3: The gravity and buoyancy of the airship are:

[0132]

[0133] Among them, ρ air is the gas density, V is the volume of the airbag, z G are the coordinates of the airship's center of gravity.

[0134] S3.4: The motor propulsion force is:

[0135]

[0136] Among them, f x 、f y 、f z , τ z are the forces and torques generated by the motors, and f1, f2, f3, f4, f5, and f6 are the thrusts generated by the six motors.

[0137] S3.5: From equations (13), (14), (15), (16), and (17), the mathematical model of the following airship is:

[0138]

[0139] Among them, f x 、f y 、f z is the motor propulsion force, x, y, z are the position of the airship, ψ is the yaw angle, m is the mass of the airship, m 11 、m 22 、m 33 、m 66 is the additional mass, D u 、D v 、D w 、D p 、D q 、D r is the linear damping coefficient, D u2 、D v2 、D w2 、D p2 、D q2、D r2 is the secondary damping coefficient, u, v, w are the airship velocities in the machine system, r is the yaw angular velocity of the airship in the machine system, F Ix 、F Iy 、M Iz It is the component affected by the interfering airflow.

[0140] S3.6: The yaw angle of the "X"-shaped airship is maintained at zero degrees during motion. When performing yaw angle control, the x-axis and y-axis velocities are assumed to be constant values ​​u0 and v0, respectively. The spatial state equation of the airship is constructed as follows:

[0141]

[0142]

[0143] Among them, I z is the z-axis moment of inertia, τ z is the rotational torque about the z-axis.

[0144] S4: Integrate tactile sensors to establish collision detection auxiliary control;

[0145] S4.1: A circular flexible piezoresistive thin film tactile sensor with a radius of 2 mm and a thickness of 0.3 mm is evenly attached to the equatorial surface of the spherical airship airbag using a silicone adhesive. The sensor signal is connected to the onboard data acquisition module via a flexible flat cable.

[0146] S4.2: The data acquisition module performs A / D conversion on the analog voltage signal output by the sensor and transmits it to the onboard computing unit. The computing unit determines the single-point contact force using a preset contact force threshold Fth = 0.5N.

[0147] S4.3: The onboard computing unit processes the above results and controls the output of the collision signal C(t), that is, when the single-point contact force exceeds the threshold, the control output C(t) is triggered.

[0148] S5: Based on the spatial dynamic equations, according to the close formation motion strategy and control objectives, a model is constructed to predict the close following control equations.

[0149] S5.1: Take The discretized state space model of the airship is:

[0150] X k+1 =AX k +Bu k +Cd k (twenty three)

[0151] Where, X k is the state vector at time k; u k is the control input vector at time k; dk is the interference vector at time k, and A, B, and C are state matrices.

[0152] S5.2: Take the control input variable Δu k =u k -u k-1 , the prediction model of the following airship robot is:

[0153] X k+1|k =Γ X ΔX k +Γ u Δu k +Γ D ΔD k (twenty four)

[0154] Among them, X k+1 It is the future N p The predicted state vector at the moment; Δu k It is the future N c The control input increment vector at the moment is the future N p The external interference increment vector at the moment; Γ X , Γ Y and Γ Z is the prediction coefficient matrix.

[0155] S5.3: Design the performance indicator function as follows:

[0156]

[0157] Among them, Y k+i|k is the predicted output vector at time i in the future; is the reference output vector at time i in the future; Q and R are the weight matrices of the output state and the control input change, respectively.

[0158] S5.4: Define the reference output vector as:

[0159]

[0160] in, Indicates that the following airship robot is at k+N p The desired state at the moment.

[0161] Assume that in N p After the step, the state of the follower airship robot is predictable and constant:

[0162]

[0163] S5.5: Establish constraints as follows:

[0164]

[0165] ΔU min ≤ΔU≤ΔU max (30)

[0166] Among them, u k ,u k+1 ,…,u k+Nc-1 is the discrete control input, Δu k , Δu k+1 ,…,Δu k+Nc-1 is the discrete control input change.

[0167] S5.6: Convert the problem into a quadratic programming problem:

[0168]

[0169] At each sampling time, an optimization algorithm is used to find the optimal solution to the performance indicator function, resulting in the optimal control sequence and predicted state variables. The optimized state variables are used as the reference position of the following airship robot, further solving the aforementioned optimization problem and obtaining the optimal trajectory.

[0170] The system workflow is as follows:

[0171] (1) The spherical airbag airship is filled with helium, and the "X"-shaped six-motor rack performs motor self-test; the thin film tactile sensor array is zero-point calibrated; the positioning and navigation system is selected according to the operating environment, and GPS is selected outdoors, and the motion capture system or data fusion mode is selected indoors to complete positioning initialization.

[0172] (2) Each sensor collects data in real time and transmits it to the onboard computing unit through serial port or wireless communication, which pre-processes the data.

[0173] (3) The onboard computing unit runs the control algorithm of the present invention, calculates the control instructions based on the input data, sends them to the electronic speed regulator through PWM signals, drives the six-axis motor to execute the control action, realizes the close following movement of the airship, and adjusts the control strategy in real time according to the feedback from the thin film tactile sensor to maintain the stability of close following.

[0174] The present invention provides an airship prototype system device, the structure of which is as follows: Figure 2 Shown, including:

[0175] The "X"-shaped six-motor frame 2 and the spherical airbag 1 with a diameter of 0.8m are equipped with a built-in helium to provide buoyancy. The frame is set below the spherical airbag 1, and a thin film tactile sensor 3 is integrated at the horizontal equator of the airbag. In addition, it is also equipped with a laser ranging sensor, an airborne IMU and a motion capture positioning system, which can measure and record the flight trajectory information of the dual airships in real time and execute processor control instructions.

[0176] The present invention's close-following motion control method for airships establishes a mathematical model through detailed force analysis. This ensures that the airship state equations are realistic at every stage of the close-following control system design, avoiding problems such as large control errors and formation decoupling. Collision detection-assisted control is employed, and in complex scenarios where positioning information is missing, collision detection-assisted adjustment is used to achieve stable close-following of multiple airships. This invention provides a reference for dynamic modeling of spherical airship robots. This method not only resolves the prior art issue of mutual interference between airship robots, which leads to unstable formations, but also provides a technical solution for close formations of airship robots.

[0177] In order to illustrate the effectiveness of the airship close following control method provided by the present invention, the present invention provides a specific example of a simulation experiment, which is as follows:

[0178] Taking the spherical airship as the research object and the double airship close following system as an example, the airship parameters are: m = 0.1535kg, V = 0.1436m 3 , ρ air =1.205kg / m 3 , Z G =0.2582m, I zx ,I xz =1×10 -6 kgm 2 , I y ,I z =0.014677kgm 2 ,0.001652kgm 2 ,λ 11 =0.07263kg, λ 22 ,λ 33 =0.07886kg,λ 55 ,λ 66 =9.1124×10 - 6 kgm 2 , D u ,D v =0.0125Ns / m, D w =0.048Ns / m, D q ,D r =0.000862Nms / rad.

[0179] like Figure 8 The figure shows the simulation results of an S-curve trajectory closely following the motion of an airship using the mathematical model and control method of the airship closely following motion of the present invention. As shown in the figure, the scheme of the present invention can achieve a stable and close following of the pilot airship by the following airship.

[0180] It should be noted that the above content merely illustrates the technical idea of ​​the present invention and cannot be used to limit the scope of protection of the present invention. For ordinary technicians in this technical field, several improvements and modifications can be made without departing from the principles of the present invention. These improvements and modifications all fall within the scope of protection of the claims of the present invention.

Claims

1. A close following control method for a spherical airship robot under strong airflow disturbance, characterized in that: The steps include: Step 1: Establish a close-following three-dimensional kinematic model: Based on the airship's motion characteristics and the close-following motion requirements, establish a three-dimensional relative motion model of close-following motion in an inertial coordinate system. Step 2: Establish an aerodynamic impact model for closely following a flock of birds: Based on the airflow interference characteristics during the closely following motion of the spherical airship, select key influencing factors and establish an aerodynamic impact model; Step 3: Establishing the spatial dynamic equation of the spherical airship: Establishing the spatial dynamic equation based on the structural characteristics and motion characteristics of the spherical airship; Step 4: Establishing collision detection auxiliary control based on tactile sensors; Step 5: Constructing a model to predict the close following control equation: Based on the spatial dynamic equations, according to the close formation motion strategy and control objectives, constructing a model to predict the close following control equation.

2. The close following control method of a spherical airship robot under strong airflow disturbance according to claim 1 is characterized in that: The step 1 includes the following sub-steps: Step 1.1, define the inertial coordinate system O n x n y n z n ; Step 1.2, define the airship body coordinate system and establish the rotation matrix between the inertial coordinate system and the airship body coordinate system; Step 1.3: Establish the transformation relationship between the airship robot in the inertial coordinate system and the body coordinate system; Step 1.4, establish the relative position update equation for the airship to closely follow the motion: Among them, x ijd (t), y ijd (t), z ijd (t) is the component of the distance between the i-th and j-th airship robots, the i-th airship robot is the pilot airship, the j-th airship robot is the follower airship, u iL (t), v iL (t), w iL (t) is the velocity component of the pilot airship, u jW (t), v jW (t), w jW (t) is the velocity component of the following airship, t is time, and Δt is the time change.

3. The close following control method of a spherical airship robot under strong airflow disturbance according to claim 1 is characterized in that: The step 2 includes the following sub-steps: Step 2.1: Define the simplified models of the pilot airship and the follower airship. The positional relationship between the pilot airship and the follower airship, with the reference coordinate system being the inertial coordinate system, is as follows: Among them, x d 、y d is the distance component between the pilot airship and the following airship, d is the airbag distance, is the angle between the lead airship and the follower airship, u L is the pilot airship speed, u W is the speed of the following airship, t is the flight time; Step 2.2: Define the airship airbag force analysis model The interference airflow generated by the pilot airship acts on the airbag of the following airship. The microelement area dS of a certain force point on the airbag of the following airship is i for: Among them, dl is the width of the infinitesimal element of the circular ring where the force point is located, r is the radius of the circular ring where the force point is located, θ is the angle between the line connecting the circular ring where the force point is located and the center of the airbag and the vertical direction, r c is the radius of the airbag following the airship, α is the projection of the angle between the force point and the center of the airbag on the Oxy plane; Step 2.3: The wind load and moment generated by the interference airflow generated by the pilot airship at the force point of the airbag of the follower airship are: dM i =dF i ×r c sinθ Among them, dF i 、dM i is the force and torque, V i is the speed of the disturbed air flow; Step 2.4: Select the key influencing factor A to characterize the change in the velocity of the disturbed airflow on the airbag surface: Among them, A mn It depends on the opening angle of the airbag surface of the following airship, the speed of the leading airship and the relative deflection angle between the two aircraft, and has nothing to do with the motion state of the following airship; Step 2.5: Establish aerodynamic impact model The velocity of the disturbed airflow at the force point of the following airship airbag V Wi for: Among them, x Pdi 、y Pdi are the y-axis and y-axis components of the distance between the force point and the pilot airship, u L is the velocity component of the pilot airship, u W is the velocity component following the airship, is the deflection angle between the lead airship and the following airship; The force and torque generated by the interfering airflow on the force-bearing surface of the airbag following the airship are: Among them, F WI The dynamic equation representing the aerodynamic force around the spherical airbag following the airship is x di 、y di 、z di are the distances between the airbag force position in the x, y, and z axes in the inertial coordinate system, is the relative deflection angle of the force position, u L 、u W are the speeds of the lead airship and the following airship respectively.

4. The close following control method of a spherical airship robot under strong airflow disturbance according to claim 1 is characterized in that: The step 3 includes the following sub-steps: Step 3.1, establish the mathematical model of the airship: Among them, f x 、f y 、f z is the motor propulsion force, x, y, z are the position of the airship, ψ is the yaw, m is the mass of the airship, m 11 、m 22 、m 33 、m 66 is the additional mass, D u 、D v 、D w 、D p 、D q 、D r is the linear damping coefficient, D u2 、D v2 、D w2 、D p2 、D q2 、D r2 is the secondary damping coefficient, u, v, w are the airship velocities in the body coordinate system, r is the yaw angular velocity of the airship in the body coordinate system, F Ix 、F Iy 、M Iz It is the component affected by the interfering airflow; Step 3.2: The yaw angle of the airship is kept at zero degrees during the motion. When performing yaw angle control, it is assumed that the x-axis and y-axis velocities are constants u0 and v0. The spatial state equation of the airship is constructed as follows: Among them, I z is the z-axis moment of inertia, τ z is the rotational torque about the z-axis.

5. The close following control method of the spherical airship robot under strong airflow disturbance according to claim 1 is characterized in that: The step 4 specifically includes: distributing a number of tactile sensors on the surface of the airship airbag, and triggering the control output C(t) when it is determined that any single point contact force exceeds a threshold.

6. The close following control method of the spherical airship robot under strong airflow disturbance according to claim 5 is characterized in that: The tactile sensors are evenly distributed on the equator of the surface of the spherical airbag, and the tactile sensors are flexible piezoresistive thin film tactile sensors.

7. The close following control method of a spherical airship robot under strong airflow disturbance according to claim 1 is characterized in that: The step 5 includes the following sub-steps: Step 5.1, take The discretized state space model of the airship is: X k+1 =AX k +Bu k +Cd k Where, X k is the state vector at time k; u k is the control input vector at time k; d k is the interference vector at time k, A, B, C are the state matrices; Step 5.2, take the control input variable Δu k =u k -u k-1 , the prediction model of the following airship robot is: X k+1|k =C X ΔX k +C u Thu k +C D ΔD k Among them, X k+1 It is the future N p The predicted state vector at the moment; Δu k It is the future N c The control input increment vector at the moment is the future N p The external interference increment vector at the moment; Γ X , Γ Y and Γ Z is the prediction coefficient matrix; Step 5.3, design the performance index function as: Among them, Y k+i|k is the predicted output vector at time i in the future; is the reference output vector at time i in the future; Q and R are the weight matrices of the output state and the control input change, respectively. Step 5.4, define the reference output vector as: in, Indicates that the following airship robot is at k+N p The desired state at the moment; Assume that in N p After the step, the state of the follower airship robot is predictable and constant: S5.5: Establish constraints as follows: ΔU min ≤ΔU≤ΔU max Among them, u k ,u k+1 ,…,u k+Nc-1 is the discrete control input, Δu k , Δu k+1 ,…,Δu k+Nc-1 is the discrete control input variation; S5.6: Convert the problem into a quadratic programming problem: In each sampling time, the optimal solution of the performance index function is solved by the optimization algorithm to obtain the optimal control sequence and predicted state variables; the optimized state variables are taken as the reference position of the following airship robot to obtain the optimal trajectory.

8. A close following control system for a spherical airship robot under strong airflow disturbance, comprising a memory, a processor, and a computer program stored in the memory, characterized in that: The processor executes the computer program to implement the steps of a close following control method for a spherical airship robot under strong airflow disturbance.

9. The close following control system for a spherical airship robot under strong airflow disturbance according to claim 8, characterized in that: The processor and the memory are arranged on a spherical airship robot. The spherical airship robot comprises an airbag and a frame arranged below the airbag. A thin film tactile sensor is integrated at the horizontal equator line of the airbag.

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