A method and system for close following control of a spherical airship robot under strong airflow disturbances

Abstract

This invention discloses a method and system for close following control of a spherical airship robot under strong airflow disturbances. The method includes: establishing a three-dimensional kinematic model for close following; establishing an aerodynamic influence model mimicking bird flock close following; establishing the spatial dynamic equations of the spherical airship; establishing collision detection-assisted control based on tactile sensors; and constructing model predictive control equations for close following. This invention addresses the technical shortcomings of traditional control methods by drawing on bird flock formation strategies, constructing a dynamic model integrating aerodynamic characteristics, employing tactile sensor collision detection-assisted control, and using precise model predictive control algorithms. It overcomes the technical deficiencies of traditional control methods in effectively establishing aerodynamic interactions between airships and addressing collision problems caused by missing positioning data during close flight. This achieves stable close following control of the airship, providing technical support for multi-airship collaborative tasks in complex, confined spaces.

Description

Technical Field

[0001] This invention belongs to the field of aircraft control technology, and relates to technologies related to unmanned systems, drones, robots, automatic control, and sensors. In particular, it relates to a close following control method and system for a spherical airship robot under strong airflow disturbance. Background Technology

[0002] Flying robot technology is a cutting-edge research area in the current scientific and technological field. Traditional rotorcraft flying robots, with their advantages of simple mechanical structure, high speed, and high maneuverability, have been widely used in transportation, surveying, rescue, and other fields. In recent years, multi-robot swarm technology has developed rapidly and is playing an important role in scenarios such as logistics distribution, agricultural plant protection, and emergency rescue. This technological concept originates from natural group systems, such as the energy-saving effect of migratory birds flying in formation at specific distances. Closely swarming flying robots not only saves energy but also reduces space consumption.

[0003] Traditional rotorcraft robots, when flying in close formation, are prone to collisions due to their rigid fuselages and high-speed propellers. This not only damages the robots but also potentially endangers the safety of nearby personnel, limiting the application of formation technology in confined or complex spaces and hindering close-range human-robot interaction. In contrast, airship robots employ a unique structure with airbags, generating additional lift by filling with low-density gas. This offers advantages such as low energy consumption and long endurance. Their flexible fuselage structure also reduces the risk of collisions when multiple robots fly close together. Therefore, airship robots have advantages in formation flying. For example, Chinese patent application CN202110245487.X proposes a method for tracking and controlling the flight trajectory of airship formations, enabling airships to track the lead airship and the desired formation; Chinese patent application CN202110924055.1 proposes a method for controlling airship formations, enabling regional coverage control; and Chinese patent application CN202110830757.3 proposes a method for controlling unmanned airship formations, enabling high-precision and stable control of airship formation flight. However, these patents all focus on optimizing formation control strategies, without considering the aerodynamic characteristics of high-density cluster formations of multiple airship robots. They lack in-depth modeling research on the kinematics and dynamics of the airship itself, fail to address the impact of airflow interference between airships on close following motion, and struggle to solve the problems of attitude instability and trajectory deviation caused by aerodynamic coupling when multiple airships are working together at close range.

[0004] The lightweight nature of airships makes them susceptible to airflow variations. Chinese patent application CN202411152511.5 proposes an airship robot and its adjustment method, which adjusts the airship's flight direction and attitude through center-of-mass control, improving the robot's ability to resist environmental airflow disturbances. However, this design primarily focuses on adjusting the airship's structure and lacks research on control schemes, making it unable to handle complex airflow changes. When multiple airships are closely following each other, the interaction of airflow around each airship generates complex aerodynamic interference, making it difficult for the airship robot to achieve stable flight. Furthermore, in close-following multi-airship scenarios, collisions and formation chaos are prone to occur due to inaccurate positioning information. Currently, there is no perfect technical solution to effectively overcome the mutual interference between airships during close flight, failing to meet the requirements of high-precision close-following tasks in confined 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 and close following control. Research on this solution will not only improve the efficiency of multi-airship transport and monitoring tasks and further expand the application areas of airship robots, but also provide a new approach to collaborative control technology for flying robots, possessing significant theoretical and engineering application value. Summary of the Invention

[0006] To address the challenges of unstable control caused by aerodynamic interference between multiple airships during close-following maneuvers in existing technologies, as well as the issues of inaccurate positioning data affecting control precision and formation stability in complex environments, this patent proposes a close-following control method and system for spherical airship robots under strong airflow disturbances. By drawing on bird flock formation strategies, constructing a dynamic model incorporating aerodynamic characteristics, employing tactile sensor collision detection-assisted control, and utilizing precise model predictive control algorithms, this method overcomes the technical shortcomings of traditional control methods, such as the ineffective establishment of aerodynamic interactions between airships and collisions caused by missing positioning data. The goal is to achieve stable close-following control of airships, providing technical support for multi-airship collaborative tasks in complex, confined spaces.

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

[0008] A method for close following control of a spherical airship robot under strong airflow disturbances includes the following steps:

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

[0010] Step 2, establish an aerodynamic influence model for closely following bird flocks: Based on the airflow interference characteristics during the closely following motion of a spherical airship, key influencing factors are selected, and an aerodynamic influence model is established.

[0011] Step 3, Establish the spatial dynamic equations of the spherical airship: Establish the spatial dynamic equations based on the structural characteristics and motion properties of the spherical airship;

[0012] Step 4: Establish collision detection-assisted control based on tactile sensors;

[0013] Step 5: Construct model-predicted close-following control equations: Based on the aforementioned spatial dynamic equations, and according to the close formation motion strategy and control objectives, construct model-predicted close-following control equations.

[0014] Furthermore, 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 closely following the motion as follows:

[0019]

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

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

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

[0023]

[0024]

[0025] Where, x d y d φ is the distance component between the lead airship and the follower airship, d is the gasbag distance, φ is the angle between the lead airship and the follower airship, and u is the distance component between the lead airship and the follower airship. L It's the speed of the pilot airship, u W It follows the speed of the airship, and t is the flight time;

[0026] Step 2.2, Define the force analysis model of the airship airbag.

[0027] The interfering airflow generated by the lead airship acts on the gasbag of the follow airship. The area dS of a certain point of force on the follow airship gasbag is... i for:

[0028]

[0029] Where dl is the width of the annular element containing the force point, r is the radius of the annular element containing the force point, and θ is the angle between the line connecting the annular element containing the force point and the center of the airbag and the vertical direction. c It is the radius of the airship's airbag, and α is the projection of the angle between the line connecting the point of force application and the center of the airbag onto the Oxy plane.

[0030] Step 2.3, the wind load and torque generated by the interfering airflow from the pilot airship at the stress point of the follower airship's gasbag are:

[0031]

[0032]

[0033] Among them, dF i dM i It refers to force and torque, V i It interferes with airflow speed;

[0034] Step 2.4: Select key influencing factor A to characterize the change in the velocity of the interfering airflow on the airbag surface:

[0035]

[0036] Among them, A mn It depends on the surface angle of the gasbag of the following airship, the speed of the lead airship, and the relative deflection angle between the two aircraft, and is independent of the motion state of the following airship;

[0037] Step 2.5, Establish an aerodynamic influence model

[0038] Following the airship's airbag stress point, the disturbance airflow velocity V Wi for:

[0039]

[0040] Where, x Pdi y Pdi The x and y components of the distance between the point of force application and the pilot airship, u L It is the speed component of the pilot airship, u W It follows the airship's velocity component, φ Pi It is the angle between the lead airship and the follower airship;

[0041] The forces and moments generated by the interfering airflow on the surface of the airship's gasbag are:

[0042]

[0043] Among them, F WI The dynamic equation representing the aerodynamic forces surrounding the spherical airbag of the airship is x. di y di z di φ represents the distance between the positions of the airbags subjected to force along the x, y, and z axes in the inertial coordinate system. i The relative deflection angle of the force application location, u L u W These refer to the speeds of the lead airship and the follower airship, respectively.

[0044] Furthermore, step 3 includes the following sub-steps:

[0045] Step 3.1, Establish the airship mathematical model:

[0046]

[0047] Among them, f x f y f z It represents the propulsion force of the electric motor, x, y, z are the position of the airship, ψ is the yaw, and m is the mass of the airship. 11 m 22 m 33 m 66 It is added mass, D u D v D w D p D q D r It is the linear damping coefficient, D u2 D v2 Dw2 D p2 D q2 D r2 This is the second-order damping coefficient, u, v, w are the airship velocities in the body coordinate system, r is the airship yaw rate in the body coordinate system, and F is the second-order damping coefficient. Ix F Iy M Iz It is the component affected by the interfering airflow;

[0048] Step 3.2: During the airship's motion, the yaw angle remains zero. When performing yaw angle control, it is assumed that the x-axis and y-axis velocities are constants u0 and v0, respectively. The airship's spatial state equation is constructed as follows:

[0049]

[0050]

[0051]

[0052]

[0053] Among them, I z It is the moment of inertia along the z-axis, τ z It is the rotational torque about the z-axis.

[0054] Furthermore, step 4 specifically involves distributing several tactile sensors on the surface of the airship's airbag and triggering a control output C(t) when the contact force at any single point exceeds a threshold.

[0055] Furthermore, the tactile sensors are evenly distributed along the equator of the spherical airbag surface, and the tactile sensors are flexible piezoresistive thin-film tactile sensors.

[0056] Furthermore, step 5 includes the following sub-steps:

[0057] Step 5.1, take X = [x, ẋ, y, ẏ, z, ż, ψ, ] T The discretized state-space model of the airship is as follows:

[0058]

[0059] In the formula, X k It is the state vector at time k; u k It is the control input vector at time k; d k Let A be the disturbance vector at time k, and let A, B, and C be the state matrices.

[0060] Step 5.2, obtain the control input variable ∆u k =u k -u k-1The prediction model for the airship robot is as follows:

[0061]

[0062] Among them, X k+1 It is the future N p The predicted state vector at each time step; ∆u k It is the future N c The control input increment vector at each moment; is the future N... p The external disturbance increment vector at each time step; Γ X ,Γ Y and Γ Z It is the prediction coefficient matrix;

[0063] Step 5.3, design the performance index function as follows:

[0064]

[0065] Among them, Y k+i|k It is the predicted output vector at time i in the future; k+i Q is the reference output vector at time i in the future; Q and R are the weight matrices of the output state and the change in the control input, respectively.

[0066] Step 5.4, define the reference output vector as:

[0067]

[0068] Among them, Ŷ k+Np This indicates that the airship robot follows the k+N p The desired state at any given moment;

[0069] Assume that in N p After taking a step, the state of the following airship robot is predictable and constant:

[0070]

[0071] S5.5: Establish the following constraints:

[0072]

[0073]

[0074]

[0075] Among them, u k u k+1 ,…,u k+Nc-1 It is a discrete control input, ∆u k ∆u k+1 ,…,∆u k+Nc-1It is the discrete control input change;

[0076] S5.6: The problem is transformed into a quadratic programming problem as follows:

[0077]

[0078]

[0079] In each sampling time, the optimal solution of the performance index function is obtained by optimizing the 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.

[0080] The present invention also provides a close following control system for a spherical airship robot under strong airflow disturbance, including 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.

[0081] Furthermore, the processor and memory are located on the spherical airship robot, which includes an airbag and a frame located below the airbag, and a thin-film tactile sensor is integrated at the horizontal equator of the airbag.

[0082] Compared with the prior art, the present invention has the following beneficial effects:

[0083] (1) This invention improves the mathematical model of multiple airships following closely by constructing an influence model that includes aerodynamic interference characteristics. Compared with the traditional airship model, it more accurately describes the influence of aerodynamic interference on the airship motion state during the process of multiple airships following closely, and improves the stability of the spherical airship robot in close formation flight control.

[0084] (2) Based on the established airship mathematical model and combined with the model predictive control algorithm, this invention effectively solves the problem of control instability caused by aerodynamic interference during close airship following.

[0085] (3) This invention combines a thin-film tactile sensor to form a prediction-sensing-control solution, enabling adaptive adjustment in complex positioning environments. This allows the airship to achieve stable close following control even when positioning information is missing. 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, thus improving the collaborative operation capability of multiple airships. Attached Figure Description

[0086] Figure 1 This is a schematic diagram of the spherical airship close following control method considering aerodynamic interference in an example of the present invention;

[0087] Figure 2 This is a schematic diagram of the overall structure of a spherical airship in an example of the present invention;

[0088] Figure 3 This is a schematic diagram of an airship coordinate system in an example of the present invention;

[0089] Figure 4 This is a simplified model diagram of an airship in an example of the present invention;

[0090] Figure 5 This is a schematic diagram of the force analysis of an airship airbag in an example of the present invention;

[0091] Figure 6 This is a schematic diagram illustrating the change in gas flow velocity on the surface of an airship's airbag, as described in an example of the present invention.

[0092] Figure 7 This is a schematic diagram of a motion control framework for airship close following in an embodiment of the present invention;

[0093] Figure 8 This is a schematic diagram of the simulation results of a close following motion experiment of an airship in an example of the present invention.

[0094] Explanation of reference numerals in the attached figures:

[0095] 1. Airbag; 2. Frame; 3. Thin-film tactile sensor. Detailed Implementation

[0096] 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 intended to limit the scope of the present invention.

[0097] The present invention provides a close following control method for a spherical airship robot under strong airflow disturbances, the process of which is as follows: Figure 1 As shown, it includes the following steps:

[0098] Step S1: Based on the airship's motion characteristics and the requirement for close following motion, establish a three-dimensional relative motion model for close following motion in the inertial coordinate system, including the following sub-steps:

[0099] 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 geographically east, O n z n The axis is vertically downward, such as Figure 3 As shown.

[0100] S1.2: Define the airship coordinate system: In a close-following motion of multiple airships, the i-th airship and the j-th airship have a lead-follower relationship, and their gasbag centers are the origin O. L O W The x-axis lies within the longitudinal section of the airship, pointing in the forward direction; the y-axis lies within the transverse section of the airship, pointing to the right; the z-axis points downwards, as shown below. Figure 3 As shown. The rotation matrix between the inertial coordinate system and the body coordinate system is:

[0101] (1)

[0102] (2)

[0103] Where φ is the roll angle, θ is the pitch angle, and ψ is the yaw angle.

[0104] S1.3: The transformation relationship between the airship robot and the body coordinate system is as follows:

[0105] (3)

[0106] (4)

[0107] Where, [x, y, z] T Let [u, v, w] be the three-dimensional coordinates of the airship robot. T Let [φ, θ, ψ] be the linear velocity of the airship robot within the machine system. T Let [p, q, r] represent the attitude angles of the airship robot. T Let be the angular velocity of the airship robot within the machine system.

[0108] S1.4: The relative position update equation for the airship closely following the motion is established as follows:

[0109] (5)

[0110] Where, x ijd (t), y ijd (t), z ijd (t) represents the component of the distance between the i-th and j-th airship robots, where the i-th airship is the lead airship and the j-th airship is the follower airship. iL (t), v iL (t), w iL (t) represents the velocity component of the pilot airship, u jW (t), v jW (t), w jW (t) represents the velocity component following the airship, t represents time, and ∆t represents the time interval.

[0111] Step S2: Based on the airflow interference characteristics of the spherical airship closely following the motion, select key influencing factors and establish an aerodynamic influence model, including the following sub-steps:

[0112] S2.1: Define simplified models of the lead airship and follower airship, such as... Figure 4 As shown, with the reference coordinate system being an inertial frame, the positional relationship between the lead airship and the follower airship is as follows:

[0113] (6)

[0114] (7)

[0115] Where, x d y d φ is the distance component between the lead airship and the follower airship, d is the gasbag distance, φ is the angle between the lead airship and the follower airship, and u is the distance component between the lead airship and the follower airship. L It's the speed of the pilot airship, u W It refers to the speed of the airship, and t is the flight time.

[0116] S2.2: Define the airbag force analysis model: The interfering airflow generated by the lead airship acts on the airbag of the follow airship, such as... Figure 5 As shown, a point P on the airship's gasbag is located on a circular element of width dl with radius r. The angle between the line connecting the circular element and the center of the gasbag and the vertical direction is θ. The area of ​​the element containing point P is:

[0117] (8)

[0118] Where, r c It is the radius of the airship's airbag, and α is the projection of the angle between the line connecting the point of force application and the center of the airbag onto the Oxy plane.

[0119] S2.3: The wind load and moment generated at point P by the interfering airflow produced by the pilot airship are:

[0120] (9)

[0121] (10)

[0122] Among them, dF i dM i It refers to force and torque, V i It represents the velocity of the interfering airflow, and ρ is the fluid density.

[0123] S2.4: such as Figure 6 As shown, the velocity of the interfering airflow on the surface of the airship's gasbag is related to the gasbag surface angle, the speed of the lead airship, and the relative deflection angle between the two aircraft. An influencing factor A is introduced to characterize the change in the velocity of the interfering airflow on the gasbag surface:

[0124] (11)

[0125] Among them, A mn (m, n=0, 1, 2, 3, 4, 5) depends on the surface angle of the follower airship's gasbag, the speed of the lead airship, and the relative deflection angle between the two aircraft, and is independent of the follower airship's motion state.

[0126] Based on the above analysis, an aerodynamic influence model can be established:

[0127] S2.5: The velocity of the interfering airflow at the point of impact of the airship's airbag is:

[0128] (12)

[0129] Where, x Pdi y Pdi The x and y components of the distance between the point of force application and the pilot airship, u L It is the speed component of the pilot airship, u W It follows the airship's velocity component, φ Pi It is the angle between the lead airship and the follower airship.

[0130] S2.6: The forces and moments generated by the interfering airflow wind load on the force-bearing surface of the following airship airbag are:

[0131] (13)

[0132] Among them, F WI The dynamic equation representing the aerodynamic forces surrounding the spherical airbag of the airship is x. di y di z di φ represents the distance between the positions of the airbags subjected to force along the x, y, and z axes in the inertial coordinate system. i The relative deflection angle of the force application location, u L u W These refer to the speeds of the lead airship and the follower airship, respectively.

[0133] Step S3: Establish spatial dynamic equations based on the structural characteristics and motion properties of the spherical airship, including the following sub-steps:

[0134] S3.1: The air resistance experienced by an airship during low-speed flight includes linear friction proportional to laminar velocity and turbulent friction proportional to the square of turbulent velocity.

[0135] (14)

[0136] Among them, D u D v Dw D p D q D r It is the linear damping coefficient, D u2 D v2 D w2 D p2 D q2 D r2 It is the secondary damping coefficient.

[0137] S3.2: The fluid inertial forces and torques experienced by the airship during flight are:

[0138] (15)

[0139] Where, m 11 m 22 m 33 m 44 m 55 m 66 It is added mass.

[0140] S3.3: The weight and buoyancy of the airship are:

[0141] (16)

[0142] Where, ρ air V is the gas density, V is the airbag volume, and z is the gas density. G These are the coordinates of the airship's center of gravity.

[0143] S3.4: The motor thrust is:

[0144] (17)

[0145] Among them, f x f y f z τ z These are the forces and torques generated by the motors. f1, f2, f3, f4, f5, and f6 are the thrust generated by the six motors.

[0146] S3.5: From formulas (13), (14), (15), (16) and (17), the mathematical model for the airship can be obtained as follows:

[0147] (18)

[0148] Among them, f x f y f z It is the electric motor propulsion, x, y, z are the airship's position, ψ is the yaw angle, m is the airship's mass, m 11 m 22m 33 m 66 It is added mass, D u D v D w D p D q D r It is the linear damping coefficient, D u2 D v2 D w2 D p2 D q2 D r2 It is the second-order damping coefficient, u, v, w are the airship velocities in the machine system, r is the airship yaw rate in the machine system, and F is the second-order damping coefficient. Ix F Iy M Iz It is the component that affects the airflow.

[0149] S3.6: When the "X"-shaped frame airship is in motion, the yaw angle remains zero. When performing yaw angle control, it is assumed that the velocities along the x-axis and y-axis are constants u0 and v0, respectively. The spatial state equation of the airship is constructed as follows:

[0150] (19)

[0151] (20)

[0152] (twenty one)

[0153] (twenty two)

[0154] Among them, I z It is the moment of inertia along the z-axis, τ z It is the rotational torque about the z-axis.

[0155] S4: Integrated tactile sensor to establish collision detection-assisted control;

[0156] S4.1: A circular flexible piezoresistive thin-film tactile sensor with a radius of 2mm and a thickness of 0.3mm is uniformly attached to the equatorial surface of the spherical airship airbag using silicone adhesive, and the sensor signal is connected to the onboard data acquisition module via a flexible flat cable.

[0157] S4.2: The data acquisition module performs A / D conversion on the analog voltage signal output by the sensor and then 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;

[0158] 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.

[0159] S5: Based on the aforementioned spatial dynamic equations, and according to the close formation motion strategy and control objectives, construct a model to predict the close following control equations.

[0160] S5.1: Take X=[x, ẋ, y, ẏ, z, ż, ψ, ] T The discretized state-space model of the airship is as follows:

[0161] (twenty three)

[0162] In the formula, X k It is the state vector at time k; u k It is the control input vector at time k; d k Let A be the disturbance vector at time k, and let A, B, and C be the state matrices.

[0163] S5.2: Take the control input variable ∆u k =u k -u k-1 The prediction model for the airship robot is as follows:

[0164] (twenty four)

[0165] Among them, X k+1 It is the future N p The predicted state vector at each time step; ∆u k It is the future N c The control input increment vector at each moment; It is the future N p The external disturbance increment vector at each time step; Γ X ,Γ Y and Γ Z It is the prediction coefficient matrix.

[0166] S5.3: The design performance index function is as follows:

[0167] (25)

[0168] Among them, Y k+i|k It is the predicted output vector at time i in the future; k+i Q is the reference output vector at time i in the future; Q and R are the weight matrices of the output state and the change in the control input, respectively.

[0169] S5.4: Define the reference output vector as:

[0170] (26)

[0171] Among them, Ŷ k+NpThis indicates that the airship robot follows the k+N p The desired state at any given moment.

[0172] Assume that in N p After taking a step, the state of the following airship robot is predictable and constant:

[0173] (27)

[0174] S5.5: Establish the following constraints:

[0175] (28)

[0176] (29)

[0177] (30)

[0178] Among them, u k u k+1 ,…,u k+Nc-1 It is a discrete control input, ∆u k ∆u k+1 ,…,∆u k+Nc-1 It is the discrete control input change.

[0179] S5.6: The problem is transformed into a quadratic programming problem as follows:

[0180] (31)

[0181] (32)

[0182] Within each sampling time interval, the optimal solution to the performance index function is obtained through an optimization algorithm, leading to the optimal control sequence and predicted state variables. The optimized state variables are then used as the reference position for the following airship robot, thereby solving the aforementioned optimization problem and obtaining the optimal trajectory.

[0183] The system workflow is as follows:

[0184] (1) The spherical airbag airship completes helium filling, the "X" type six-motor frame performs motor self-test; the thin film tactile sensor array performs zero-point calibration; the positioning and navigation system is selected according to the working environment, GPS is selected for outdoor use, and motion capture system or data fusion mode is selected for indoor use to complete positioning initialization.

[0185] (2) Each sensor collects data in real time and transmits it to the onboard computing unit via serial port or wireless communication. The computing unit preprocesses the data.

[0186] (3) The onboard computing unit runs the control algorithm of the present invention, calculates the control command based on the input data, sends it to the electronic speed controller through the PWM signal, drives the six-axis motor to perform control actions, realizes the airship closely follows the movement, and adjusts the control strategy in real time based on the feedback of the thin film tactile sensor to maintain the stability of close following.

[0187] This invention provides an airship prototype system device, the structure of which is as follows: Figure 2 As shown, it includes:

[0188] The "X"-shaped six-motor frame 2 and the spherical airbag 1 with a diameter of 0.8m are equipped with helium to provide buoyancy. The frame is located below the spherical airbag 1. A thin-film tactile sensor 3 is integrated at the horizontal equator of the airbag. In addition, it is equipped with a laser rangefinder, an airborne IMU and a motion capture positioning system, which can measure and record the flight trajectory information of the two airships in real time and execute processor control commands.

[0189] The airship close-following motion control method of this invention establishes a mathematical model through detailed force analysis, ensuring that the airship's state equations closely match reality at every stage of the close-following control system design, thus avoiding large control errors and formation decoupling issues. Collision detection-assisted control is employed to achieve stable close following among multiple airships in complex scenarios where positioning information is lacking. This invention provides a reference for the dynamics modeling of spherical airship robots. This method not only solves the problem of mutual interference between airship robots leading to unstable formations in existing technologies, but also provides a technical solution for the close formation of airship robots.

[0190] To illustrate the effectiveness of the airship close-following control method provided by this invention, a specific example of a simulation experiment is provided below:

[0191] Taking a spherical airship as the research object and a dual airship close-following system as an example, the airship parameters are: m = 0.1535 kg, V = 0.1436 m. 3 , ρ air =1.205kg / m 3 Z G =0.2582m, I zx , I xz =1×10 −6 kgm 2 I y , I z =0.014677 kgm 2 0.001652 kgm 2 , λ 11 =0.07263 kg, λ 22 , λ 33=0.07886 kg, λ 55 , λ 66 =9.1124×10 −6 kgm 2 D u D v =0.0125 Ns / m, D w =0.048 Ns / m, D q D r =0.000862 Nms / rad.

[0192] like Figure 8 The figure shows the simulation results of the S-curve trajectory closely following the airship when using the airship mathematical model and the airship close-following motion control method of the present invention. As shown in the figure, the scheme of the present invention can achieve stable and close following of the lead airship by the following airship.

[0193] It should be noted that the above content merely illustrates the technical concept of the present invention and should not be construed as limiting the scope of protection of the present invention. For those skilled in the art, various improvements and modifications can be made without departing from the principle of the present invention, and all such improvements and modifications fall within the scope of protection of the claims of the present invention.

Claims

1. A method for close following control of a spherical airship robot under strong airflow disturbance, characterized in that, Includes the following steps: Step 1, establish a three-dimensional kinematic model for close following: Based on the characteristics of airship motion and the requirements for close following motion, establish a three-dimensional relative motion model for close following motion in the inertial coordinate system; Step 2, establish an aerodynamic influence model for closely following bird flocks: Based on the airflow interference characteristics during the closely following motion of a spherical airship, key influencing factors are selected, and an aerodynamic influence model is established. Step 3, Establish the spatial dynamic equations of the spherical airship: Establish the spatial dynamic equations based on the structural characteristics and motion properties of the spherical airship; Step 4: Establish collision detection auxiliary control based on tactile sensors. Specifically, several tactile sensors are distributed on the surface of the airship airbag. When the contact force at any single point exceeds the threshold, the control output C(t) is triggered. Step 5, Construct Model-Predicted Close-Following Control Equations: Based on the aforementioned spatial dynamic equations, and according to the close formation motion strategy and control objective, construct the model-predicted close-following control equations, including the following sub-steps: Step 5.1, take X = [x, ẋ, y, ẏ, z, ż, ψ, ] T The discretized state-space model of the airship is as follows: In the formula, x, y, z are the positions of the airship, ψ is the yaw angle, and X is the position of the airship. k It is the state vector at time k; u k It is the control input vector at time k; d k Let A be the disturbance vector at time k, and let A, B, and C be the state matrices. Step 5.2, obtain the control input variable ∆u k =u k -u k-1 The prediction model for the airship robot is as follows: Among them, X k+1 It is the future N p The predicted state vector at each time step; ∆u k It is the future N c The control input increment vector at each moment; It is the future N p The external disturbance increment vector at each time step; Γ X ,Γ Y and Γ Z It is the prediction coefficient matrix; Step 5.3, design the performance index function as follows: Among them, Y k+i|k It is the predicted output vector at time i in the future; k+i It is the reference output vector at time i in the future; Q and R are the weight matrices of the output state and the change in the control input, respectively; Step 5.4, define the reference output vector as: Among them, Ŷ k+Np This indicates that the airship robot follows the k+N p The desired state at any given moment; Assume that in N p After taking a step, the state of the following airship robot is predictable and constant: in, ; S5.5: Establish the following constraints: Among them, u k u k+1 ,…,u k+Nc-1 It is a discrete control input, ∆u k ∆u k+1 ,…,∆u k+Nc-1 It is the discrete control input change; S5.6: The problem is transformed into a quadratic programming problem as follows: In each sampling time, the optimal solution of the performance index function is obtained by optimizing the 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.

2. The close following control method for a spherical airship robot under strong airflow disturbances according to claim 1, characterized in that, 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 closely following the motion as follows: Where, x ijd (t), y ijd (t), z ijd (t) represents the component of the distance between the i-th and j-th airship robots, where the i-th airship robot is the lead airship and the j-th airship robot is the follower airship. iL (t), v iL (t), w iL (t) represents the velocity component of the pilot airship, u jW (t), v jW (t), w jW (t) represents the velocity component following the airship, t represents time, and ∆t represents the change in time.

3. The close following control method for a spherical airship robot under strong airflow disturbances according to claim 1, characterized in that, Step 2 includes the following sub-steps: Step 2.1, define simplified models of the lead airship and follower airship. The positional relationship between the lead airship and follower airship, with the reference coordinate system being the inertial coordinate system, is as follows: Where, x d y d φ is the distance component between the lead airship and the follower airship, d is the gasbag distance, φ is the angle between the lead airship and the follower airship, and u is the distance component between the lead airship and the follower airship. L It's the speed of the pilot airship, u W It follows the speed of the airship, and t is the flight time; Step 2.2, Define the force analysis model of the airship airbag. The interfering airflow generated by the lead airship acts on the gasbag of the follow airship. The area dS of a certain point of force on the follow airship gasbag is... i for: Where dl is the width of the annular element containing the force point, r is the radius of the annular element containing the force point, and θ is the angle between the line connecting the annular element containing the force point and the center of the airbag and the vertical direction. c It is the radius of the airship's airbag, and α is the projection of the angle between the line connecting the point of force application and the center of the airbag onto the Oxy plane. Step 2.3, the wind load and torque generated by the interfering airflow from the pilot airship at the stress point of the follower airship's gasbag are: Wherein dF i dM i It refers to force and torque, V i It interferes with airflow speed. It is the fluid density; Step 2.4: Select key influencing factor A to characterize the change in the velocity of the interfering airflow on the airbag surface: Among them, A mn It depends on the surface angle of the gasbag of the following airship, the speed of the lead airship, and the relative deflection angle between the two aircraft, and is independent of the motion state of the following airship; Step 2.5: Establish an aerodynamic impact model Following the airship's airbag stress point, the interfering airflow velocity V Wi for: Where, x Pdi y Pdi The x and y components of the distance between the point of force application and the pilot airship, u L It is the speed component of the pilot airship, u W It follows the airship's velocity component, φ Pi It is the angle between the lead airship and the follower airship; The forces and moments generated by the interfering airflow on the surface of the airship's gasbag are: Among them, F WI The dynamic equation representing the aerodynamic forces surrounding the spherical airbag of the airship is x. di y di z di φ represents the distance between the positions of the airbags subjected to force along the x, y, and z axes in the inertial coordinate system. i The relative deflection angle of the force application location, u L u W These refer to the speeds of the lead airship and the follower airship, respectively.

4. The close following control method for a spherical airship robot under strong airflow disturbances according to claim 1, characterized in that, Step 3 includes the following sub-steps: Step 3.1, Establish the airship mathematical model: Among them, f x f y f z It is the electric motor propulsion, x, y, z are the airship's position, ψ is the yaw angle, m is the airship's mass, m 11 m 22 m 33 m 66 It is added mass, D u D v D w D p D q D r It is the linear damping coefficient, D u2 D v2 D w2 D p2 D q2 D r2 This is the second-order damping coefficient, u, v, w are the airship velocities in the body coordinate system, r is the airship yaw rate in the body coordinate system, and F is the second-order damping coefficient. Ix F Iy M Iz It is the component affected by the interfering airflow; Step 3.2: During the airship's motion, the yaw angle remains zero. When performing yaw angle control, it is assumed that the x-axis and y-axis velocities are constants u0 and v0, respectively. The airship's spatial state equation is constructed as follows: Among them, I z It is the moment of inertia along the z-axis, τ z It is the rotational torque about the z-axis.

5. The close following control method for a spherical airship robot under strong airflow disturbances according to claim 1, characterized in that, The tactile sensors are evenly distributed on the equator of the spherical airbag surface, and the tactile sensors are flexible piezoresistive thin-film tactile sensors.

6. A close following control system for a spherical airship robot under strong airflow disturbances, 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 the close following control method for a spherical airship robot under strong airflow disturbance as described in any one of claims 1-5.

7. The close following control system for a spherical airship robot under strong airflow disturbances according to claim 6, characterized in that, The processor and memory are mounted on the spherical airship robot, which includes an airbag and a frame located below the airbag. A thin-film tactile sensor is integrated at the horizontal equator of the airbag.

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