CN116142497A

CN116142497A - Mars unmanned aerial vehicle and control method based on task manifold controller

Info

Publication number: CN116142497A
Application number: CN202310078669.1A
Authority: CN
Inventors: 富立; 王泽宇; 王玲玲; 唐宁
Original assignee: Beihang University
Current assignee: Beihang University
Priority date: 2023-02-08
Filing date: 2023-02-08
Publication date: 2023-05-23

Abstract

The invention relates to a Mars unmanned aerial vehicle and a control method based on a task manifold controller, wherein the Mars unmanned aerial vehicle KPM-VBLA comprises two magnetic control paddles and two rotor paddles, controllable magnetic field force is generated between the two magnetic control paddles, and the magnitude and the direction of the dip angles of an upper rotor and a lower rotor are controlled through magnetic force between the magnetic control paddles and the rotor paddles; the method for controlling the Mars unmanned aerial vehicle based on the task manifold comprises the following steps: s1: defining all coordinate systems of KPM-VBLA of the Mars unmanned aerial vehicle; s2: establishing a six-degree-of-freedom dynamic model of the KPM-VBLA of the Mars unmanned aerial vehicle; s3: and designing a control law of the task manifold controller to obtain the input control force and moment of the KPM-VBLA of the Mars unmanned aerial vehicle so as to realize the control of the Mars unmanned aerial vehicle. Under the virtual simulation environment, three-dimensional track tracking and path tracking with high-order nonlinear curve characteristics are realized, and the maneuver performance of the designed Mars unmanned aerial vehicle KPM-VBLA and the effectiveness of a control algorithm are verified.

Description

Mars unmanned aerial vehicle and control method based on task manifold controller

Technical Field

The invention relates to comprehensive application in the fields of automatic control, aviation and unmanned aerial vehicle design, in particular to a Mars unmanned aerial vehicle and a method for controlling the Mars unmanned aerial vehicle to execute track tracking by using a task manifold-based controller.

Background

Over the decades on the Mars, mars roamers have covered less than 40 miles of relatively flat and open terrain in total. The Mars unmanned aerial vehicle is a planetary aerial robot which can fly on the surface of a Mars and can finish the detection task of a Mars watch in cooperation with a Mars detection vehicle. The method makes up for the gap between the high-position detection of the large area and the low resolution of the Mars survey orbit aircraft and the low-position detection of the small area and the high resolution of the Mars survey vehicle. The Mars unmanned aerial vehicle can strengthen the task of a rover by quickly reconnaissance a safe traversing route or reconnaissance a possible scientific target destination, and can be used for exploring areas which the rover may not reach as an independent system. The use of rotorcraft surveillance will increase the scope and breadth of the mars star-watch detection task and provide easier and safer access to caverns, volcanic vents, ice and any potentially dangerous locations. Advantages of coaxial rotary unmanned aircraft are its compact design, high hover efficiency, relatively high blade reynolds numbers, and weight and volume. Single and multi-main rotors have a large volumetric constraint and cannot achieve the same tip reynolds number for a given volume as for a coaxial rotor.

Since the concept of a Mars unmanned aerial vehicle was proposed in 1970, after several decades of continuous efforts, the first human Mars unmanned aerial vehicle of year 2021, the "smart" of the Mars unmanned aerial vehicle successfully logs on the Mars surface along with the "perseveration" of the Mars detection vehicle, and more than 10 aerial detection flights have been completed so far. Based on the images of the Mars watch photographed by the Mars unmanned aerial vehicle, the efficiency of the Mars watch detection task is effectively improved. With the progress of the planetary aerial robot technology, the future unmanned aerial vehicle cluster is cooperated to finish star detection of sparks, golden stars, soil hexagons and the like.

Mars are quite different from the earth's environment, which places a unique and challenging set of requirements on coaxial rotor unmanned control, e.g., mars watch gravity is about 38% of the earth's gravity; the rarefaction carbon dioxide atmosphere, with a density and acoustic velocity of 1.26% and 67% of the earth, respectively, produces poor aerodynamic performance in a low Reynolds number (Re < 10000) and relatively high tip Mach number (M > 0.2) environment. In addition, the Mars unmanned aerial vehicle control test cannot be performed in a completely duplicated Mars environment on the earth, but the Mars unmanned aerial vehicle control system must ensure smooth work when the Mars detection task is performed for the first time, and thus must rely on detailed modeling, analysis and simulation and perform the test in a partially duplicated environment.

In consideration of the task demands such as vertical lifting and maximum detection distance, the Mars unmanned aerial vehicle should adopt a rotor unmanned aerial vehicle configuration. On the earth's surface, a quadrotor drone has proven to be a successful configuration of a rotorcraft. However, in the case of a Mars meter, there is a problem that the expected lift force cannot be obtained. In order to obtain the largest possible lifting force under the conditions of low Reynolds number and low gravity, the 'intelligent' Mars unmanned aerial vehicle adopts a coaxial double-rotor helicopter structure, and an upper rotor and a lower rotor respectively adopt 1 driving motor to stably control the rotating speed and 3 servo motors to circularly control the rotor inclination angle. Through comprehensively adjusting the rotating speeds and the rotor inclination angles of the upper rotor wing and the lower rotor wing, the moment and the force for changing the gesture and the speed of the unmanned aerial vehicle are obtained, and full-driving control in a six-degree-of-freedom space is realized. In order to realize stable flight control of the Mars unmanned aerial vehicle under the Mars atmospheric condition, the guidance module generates a reference track according to the pre-designed gesture and the navigation point, and the flight control module continuously adjusts the inclination angle of the rotor wing to track the preset flight track. Meanwhile, in a rotor rotation speed control loop, the feedback of a rotor rotation speed observer is increased, and the problem of reduced flight control robustness caused by strong coupling between the rotor rotation speed and course control is effectively solved.

In order to ensure that the flight control system has a sufficiently large stability margin, the "smart" Mars unmanned aerial vehicle guidance module generates specific reference trajectories that can decouple the pitch channel, roll channel, and heading channel. And linearizing the dynamic and kinematic models of the unmanned aerial vehicle according to the balance points provided by the reference track. On the basis, the flight control module realizes single-input single-output control of a pitch channel, a roll channel and a course channel. The elevation and the heading are respectively based on the elevation and the heading estimation output by the navigation module to construct a PID feedback controller, and the pitching channel and the rolling channel adopt a double closed-loop control strategy of PID outer loop position control and PD inner loop attitude control. However, in Mars atmospheric conditions, rotor pitch adjustment will change rotor flap dynamics and upper and lower rotor suction effects, there is pitch/roll channel-to-channel and pitch/vertical channel-to-channel coupling torque. Single input single output flight control schemes present the risk of amplifying these unmodeled coupling moments, reducing the stability domain of the flight control system. On the other hand, the dynamics of coaxial dual rotor unmanned aerial vehicle are related to airspeed. When the ground speed is less than the airspeed, the PID parameters of the controller should be adjusted in real time based on the airspeed measurement. However, due to the limitation of the volume, the weight and the precision of an airspeed sensor, the navigation module of the 'intelligent' Mars unmanned aerial vehicle has no airspeed measurement value, and can only rely on a reference track with large stability margin, and a set of PID parameters are designed to overcome the interference of Mars gust with the strength of less than 3.5 m/s. However, the specific track limits the flexibility of the Mars unmanned aerial vehicle to finish the star-meter detection flight task, and the requirement of the future unmanned aerial vehicle cluster for cooperating with the star-meter detection task cannot be met.

Disclosure of Invention

In order to solve the defects existing in the prior art, the invention firstly designs a novel miniature coaxial double-variable-dip-angle rotor spark unmanned aerial vehicle KPM-VBLA which is oriented to the detection requirement of a future unmanned aerial vehicle cluster cooperative planetary star, and the space geometrical stability effect of the flexible gyroscope is simulated by a magnetic control paddle disc, so that the unmanned aerial vehicle has the maneuverability of completing the required detection task. In order to complete different detection tasks, based on the thought of task manifold design, a unified mixed scheme for KPM-VBLA Mars unmanned aerial vehicle track tracking and path following control is provided, the method reasonably designs a task manifold comprising expected tracks (or paths), speeds and postures, the designed controller centrally (without dividing a ring) ensures that all state variables of the Mars unmanned aerial vehicle are converged on the task manifold asymptotically, and a Lyapunov function is constructed to prove the overall asymptotic stability of a control algorithm. Finally, under the virtual simulation environments of the Mars merle exploration task and the Mars periodic gradient line observation task, three-dimensional track tracking and path tracking with high-order nonlinear curve characteristics are realized by taking KPM-VBLA as a control object, and the maneuver performance of the designed Mars unmanned aerial vehicle KPM-VBLA and the effectiveness of a control algorithm are verified. The specific technical scheme of the invention is as follows:

The utility model provides a spark unmanned aerial vehicle KPM-VBLA which characterized in that adopts miniature coaxial double variable dip rotor structure, and it specifically includes: the device comprises a main body (6), a battery (2), a wireless communication module (1), an upper rotor (7), a lower rotor (8), two magnetic control propeller discs (12), two rotor propeller discs (10), a control module (5), a camera (9), a motor (13), a motor rotating shaft (14) and an elastic hinge (15); wherein, a device bracket is arranged between the upper rotor wing and the lower rotor wing, a visual sensor is arranged at the outer side of the device bracket along the front direction of the main body, and a control module (5) comprises a micro inertial measurement component and a navigation control computer which are arranged in the main body of the center of the device bracket; the method comprises the steps of carrying out a first treatment on the surface of the The two rotor disks (10) are connected with a motor rotating shaft (14) in a split mode through an elastic hinge (15), and the upper rotor and the lower rotor are respectively arranged on the rotor disks (10) at the upper part and the lower part; the two magnetic control propeller discs (12) are respectively positioned on one side coaxial with the two rotor propeller discs (10), electromagnetic materials are embedded in the two magnetic control propeller discs (12) at equal intervals, and the intensity and the direction of a magnetic field generated by the electromagnetic materials are controlled by current; embedding ferromagnetic material on two rotor disks (10) at equal intervals corresponding to the ferromagnetic material of the magnetic control disks (12); under the action of gyro precession effect, the magnetic force between the magnetic control pulp disk (12) and the rotor pulp disk (10) controls the magnitude and the direction of the upper rotor inclination angle and the lower rotor inclination angle, and realizes the variable control of the upper rotor inclination angle and the lower rotor inclination angle.

Further, the solar cell panel (4), the lifting support (3) and the protective cover (11) are also included; a solar panel (4) is arranged above the upper rotor wing (7), and solar energy is utilized to charge a battery; a protective cover (11) is arranged below the lower rotor wing.

The control method of the KPM-VBLA of the Mars unmanned aerial vehicle based on task manifold is characterized by comprising the following steps of:

s1: defining all coordinate systems of KPM-VBLA of the Mars unmanned aerial vehicle;

s2: establishing a six-degree-of-freedom dynamic model of the KPM-VBLA of the Mars unmanned aerial vehicle;

s3: and designing a task manifold controller to obtain the input control force and torque of the KPM-VBLA of the Mars unmanned aerial vehicle so as to realize the control of the Mars unmanned aerial vehicle.

Further, the step S1 specifically includes the following steps:

s1-1: defining a ground coordinate system and a body coordinate system of the KPM-VBLA of the Mars unmanned aerial vehicle: ground coordinate system O _g -X _g Y _g Z _g Origin O of (2) _g Is a fixed point on the Mars ground, wherein O _g X _g The axis points to north, O _g Y _g Axis to the east, O _g Z _g The axis points to the center of the spark; body coordinate system o _b -x _b y _b z _b Origin o of (2) _b Is the center of gravity CG of the Mars unmanned aerial vehicle, wherein o _b x _b Axial-pointing forward vision sensor, o _b z _b The axis being perpendicular to o _b x _b Axis and point downward, o _b y _b The shaft is determined by a right hand rule and points to the right side of the main body of the machine body;

S1-2: the position and attitude kinematics equation in the ground coordinate system in the step S1-1 is obtained by converting the machine body coordinate system into the ground coordinate system:

wherein Y= [ P ] ^T ,Θ ^T ] ^T Is a generalized position vector of the Mars unmanned plane, and P= [ x, y, z ] ^T And Θ=]φ,θ,ψ] ^T Respectively the Mars unmanned aerial vehiclePosition vector and attitude angle vector of machine in ground coordinate system, X= [ V ] ^T ,ω ^T ] ^T Is a generalized velocity vector of the Mars unmanned plane, and V= [ u, V, w ]] ^T And ω= [ p, q, r] ^T The speed vector and the rotation angular velocity vector in the machine body coordinate system are respectively,

is a transformation matrix between a machine body coordinate system and a ground coordinate system>

Mapping a conversion matrix from a machine body coordinate system to a ground coordinate system for the rotation angular velocity of the machine body;

wherein c (·) =cos (·), s (·) =sin (·), t (·) =tan (·);

s1-3: rotor i fixedly connected coordinate system o for defining KPM-VBLA of Mars unmanned aerial vehicle _i -x _i y _i z _i I=1 is the upper rotor, i=2 is the lower rotor, and its origin o _i The rotor i is positioned at the rotation center of the rotor i; o (o) _i x _i The axis is parallel to the plane of the rotation plane of the rotor i and points to the direction of the camera; o (o) _i y _i In-plane perpendicular o with axis parallel to the plane of rotation of rotor i _i x _i A shaft directed to the left; o (o) _i z _i The shaft can be judged to be directed to the normal direction of the rotating plane of the rotor wing i by the right hand rule, and the upward direction is positive.

Further, the step S2 specifically includes the following steps:

s2-1: under the machine body coordinate system in the step S1-1, the speed and angular velocity dynamics equation of KPM-VBLA in the Mars unmanned aerial vehicle can be obtained based on a Newton-Euler equation, wherein the speed and angular velocity dynamics equation are respectively as follows:

wherein ,F^b and M^b Three-axis external force and external moment acting on the center of gravity of the Mars unmanned aerial vehicle under the machine body coordinate system, { I _x ,I _y ,I _z And the Mars unmanned aerial vehicle is wound o _b x _b 、o _b y _b and o_b z _b The rotational inertia of the shaft, m is the mass of the Mars unmanned aerial vehicle;

s2-2: as known from the KPM-VBLA structure of the Mars unmanned aerial vehicle, the external force applied to the main body of the aircraft body comprises a Mars gravity vector F _G Lift vector F generated by rotor rotation _T And a pressing resistance vector F _R The method comprises the steps of carrying out a first treatment on the surface of the The external torque applied by the main body of the machine body comprises a reactive torque vector M generated by the rotation of a rotor wing _Q Gyro moment vector M _G And rotor wing lift force o in machine body coordinate system _b x _b Shaft sum o _b y _b Moment vector M generated by force component of shaft _T The method comprises the steps of carrying out a first treatment on the surface of the Thus, the resultant forces and moments acting on the Mars unmanned KPM-VBLA can be expressed as:

F ^b ＝F _G +F _T +F _R

M ^b ＝M _Q +M _G +M _T

s2-3: based on the step S2-1 and the step S2-2, a complete six-degree-of-freedom dynamic equation model of the KPM-VBLA of the Mars unmanned aerial vehicle can be obtained:

wherein m=diag [ M, M, M, I _x ,I _y ,I _z ]Is a Mars unmanned aerial vehicle quality matrix, N _d For the force and moment related to the generalized velocity vector X of the Mars unmanned plane, N _d ＝[m(vr-wq),m(wp-ur),m(uq-vp),I _y -I _z )rq,(I _z -I _x )pr,(I _x -I _y )pq] ^T ；N _f Is applied to the main body of the machine body by external forceThe moment of force is calculated and the torque,

N _u forces and moments generated for the task manifold controller, i.e. the control law of the task flow controller,/-)>

Further, the step S3 specifically includes the following steps:

s3-1: considering that the flight track or path of the unmanned aerial vehicle KPM-VBLA can be described by the intersection line of a pair of curved surfaces in a three-dimensional space, defining the expected track of the unmanned aerial vehicle KPM-VBLA as a hidden function about the position P, and obtaining:

wherein t is the time of the time, ^j A ₁ (t), ^j A ₂ (t) is a three-dimensional row vector which is designed in advance according to the flight track, b (t) is a one-dimensional vector which is designed in advance according to the flight track, ^j P＝[x ^j ,y ^j ,z ^j ] ^T for vectors composed of j powers of the position coordinate components with respect to the Mars unmanned aerial vehicle, j represents the order describing the desired trajectory or path, e _N1 and e_N2 Is a track tracking error component; when N (p, t) = [ e _N1 e _N2 0] ^T ≠0 _3×1 When there is a track following error component e _N1 and e_N2 The corresponding control law N needs to be designed _u So that the track trace error component e _N1 0 and e _N2 →0；

S3-2: considering that the posture is stable in the flying process of the unmanned aerial vehicle KPM-VBLA, defining a posture error phi (P, Θ, t) as the difference between the posture Θ of the unmanned aerial vehicle KPM-VBLA and the expected posture Θ (P, Θ, t), and obtaining:

Φ(P,Θ,t)＝Θ-Θ*(P,Θ,t)

the corresponding control law N needs to be designed _u So that the attitude error phi (P, theta, t) to 0 _3×1 ；

S3-3: combining step S3-1 and step S3-2, defining a track manifold ψ _tr ＝0 _6×1 The method comprises the following steps of:

the final Mars unmanned aerial vehicle KPM-VBLA generalized position vector Y needs to converge to the track manifold ψ _tr ＝0 _6×1 To ensure that the Mars unmanned aerial vehicle KPM-VBLA flies along the expected track in a stable attitude;

due to psi _tr At least one order of all arguments is conductive, then ψ _tr The full derivative with respect to time t can be expressed as:

wherein ,

s3-4: considering the generalized velocity vector X when the pitman unmanned aerial vehicle KPM-VBLA is constrained to fly along a desired trajectory in order to reduce energy consumption during flight, the velocity manifold is defined as:

wherein ,

is the velocity squared error vector, V _c Is a desired flight speed vector; the generalized velocity vector X of the final Mars unmanned aerial vehicle KPM-VBLA needs to converge to the velocity manifold ψ _v ＝0 _6×1 So that the Mars unmanned aerial vehicle KPM-VBLA takes a desired velocity vector V _c Maintaining the space geometry steady state flight;

s3-5: to ensure the KPM-VBLA of the Mars unmanned aerial vehicle fly along the expected gesture and speed of the detection task, the track manifold ψ is utilized _tr =0 and velocity manifold ψ _v =0 synthesis task manifold ψ=0, resulting in:

Ψ＝Ψ _tr +AΨ _v ＝0

where A is a 6 th order diagonal weighting coefficient matrix, the matrix A is designed such that if and only if ψ _tr→0 and Ψ_v -0, only ψ -0, thus the track following error component e of step 3-1 can also be made _N1 0 and e _N2 0 and the posing error Φ (P, Θ, t) in step 3-2 → 0 _3×1 ；

S3-6: in order to ensure that the generalized position vector Y of the KPM-VBLA of the Mars unmanned aerial vehicle, the generalized velocity vector X and the first derivative thereof converge to the task manifold psi= 0, a 6-order constant coefficient matrix T is designed to meet the following formula:

s3-7: based on the step S2-3, a dynamic equation of KPM-VBLA of the Mars unmanned aerial vehicle is obtained, and the steps S3-5 and S3-6 are combined to obtain a nonlinear task manifold control law N _u The method comprises the following steps:

wherein ,K₀ ＝J ₁ J _∑PX +J _Θ J _∑ΘX ，K ₁ ＝TAK ₁₁ +K ₁₂ ，K ₁₁ ＝[0 _6×3 J ₁ J _∑PΘ +J _Θ J _∑ΘΘ ]，

K ₁₂ ＝(T+A)J _s +TAГ _s ，/>

J ₁ ＝J _P +J _V ，J _V ＝

The nonlinear task manifold control law N _u It can be ensured that all state variables converge asymptotically to the task manifold ψ=0, i.e

Based on the nonlinear task manifold control law N _u The force and moment generated by the task manifold controller can be obtained.

Further, to demonstrate the nonlinear task manifold control law N of steps S3-7 _u Is selected by selecting

Lyapunov function

And deriving time to obtain:

wherein, to make

Only the matrix T in step S3-6 is needed ^-1 Minimum characteristic value T _min When the T is larger than 0, considering that the T is a diagonal matrix, all diagonal elements of the T are positive.

The simulation method for carrying out track tracking and path following control on the KPM-VBL of the Mars unmanned aerial vehicle by adopting the control method constructs a 3D virtual scene of the Mars meteorite crater and the Mars periodic gradient line based on the Unity 3D in a virtual simulation environment, and is based on a task manifold control law N designed in the step S3 _u The control simulation of the Mars unmanned aerial vehicle KPM-VBLA realizes the Mars merle exploration task and the Mars periodic gradient line observation task.

Further, for the Mary Mars meteorite crater exploration task, the expected track is designed to descend into the meteorite crater along the meteorite crater wall, then fly around the meteorite crater wall along the spiral line, finally fly out of the meteorite crater and fly to the expected end point along a straight line, and track tracking control is carried out by the task manifold controller in the step 3 and the existing sliding mode controller respectively.

Further, for the Mars periodic gradient line observation task, designing a desired track as a higher-order curve conforming to the gradient line pattern characteristics, and performing path following control by using the task manifold controller in the step 3.

Compared with the prior art, the invention has the following beneficial effects:

1. the invention designs an innovative miniature coaxial double-variable-dip-angle rotor unmanned aerial vehicle KPM-VBLA based on the detection requirements of non-linear geometric feature landforms such as a spark meteorite pit, a spark periodic gradient line and the like of a spark unmanned aerial vehicle, and also considers the mechanical multiple challenges of the unmanned aerial vehicle for executing tasks in a spark environment. And a Newton-Euler vector mechanics method is used for establishing a six-degree-of-freedom nonlinear dynamics model of the Mars unmanned aerial vehicle KPM-VBLA.

2. The invention provides a task manifold controller inspired by a cooperative synthesis control method to finish a nonlinear geometric landform proximity detection task. The task manifold is weighted by a track manifold and a velocity popularity, wherein the track manifold is a desired track and attitude error represented by a high-order nonlinear hidden function. The velocity manifold is designed to give a velocity limit when the mars drone is flying. And the convergence of all state variables of the closed loop system is ensured by designing a weighting coefficient matrix and a cooperative gain matrix of the task manifold controller. The stability analysis of the controller is demonstrated by the constructed Lyapunov function.

3. In the 3D virtual simulation environment of two tasks of Mars merle exploration and Mars periodic gradient line observation, the Mars unmanned aerial vehicle KPM-VBLA realizes rapid tracking of exploration tracks similar to high-order nonlinear geometric features with less energy, and the effectiveness of a task manifold control algorithm is verified.

Drawings

For a clearer description of an embodiment of the invention or of the solutions of the prior art, reference will be made to the accompanying drawings, which are used in the embodiments and which are intended to illustrate, but not to limit the invention in any way, the features and advantages of which can be obtained according to these drawings without inventive labour for a person skilled in the art. Wherein:

FIG. 1 is a block diagram of a KPM-VBLA of a miniature coaxial dual-variable-tilt rotor spark unmanned aerial vehicle of the present invention;

FIG. 2 is a cross-sectional view of a KPM-VBLA magnetic control paddle structure of the Mars unmanned aerial vehicle of the invention;

FIG. 3 is a schematic diagram of the definition of the coordinate systems of KPM-VBLA of the Mars unmanned aerial vehicle of the present invention;

FIG. 4 is a diagram of the san Maria Mare merle taken in a high resolution imaging science experiment of an embodiment of the present invention;

FIG. 5 (a) is a 3D virtual model diagram of the Mary Mars meteorite crater of an embodiment of the invention;

FIG. 5 (b) is a trace diagram of a Mars unmanned aerial vehicle in a 3D virtual model diagram of the Mars meteorite crater of san Maria in an embodiment of the present invention;

FIG. 6 is a graph of airspeed tracking for a Mars merle exploration mission by the Mars unmanned KPM-VBLA of an embodiment of the present invention;

FIGS. 7 (a) and (b) are graphs of the velocity and attitude response of the Mars unmanned KPM-VBLA performing Mars merle exploration tasks, respectively, of an embodiment of the present invention;

FIG. 8 is a graph of position error for a Mars unmanned KPM-VBLA performing a Mars merle exploration task according to an embodiment of the present invention;

FIGS. 9 (a) and (b) are graphs of feedback control force and moment for performing a Mars merle exploration task by the Mars unmanned aerial vehicle KPM-VBLA, respectively, in accordance with an embodiment of the present invention;

FIG. 10 is a diagram of a periodic ramp of Mars taken from a high resolution imaging science experiment of an embodiment of the present invention;

FIG. 11 (a) is a 3D virtual model diagram of a Mars periodic ramp line in accordance with an embodiment of the present invention;

FIG. 11 (b) is a trace diagram of a Mars unmanned aerial vehicle in a 3D virtual model diagram of a Mars periodic ramp line in accordance with an embodiment of the present invention;

FIG. 12 is a plot of airspeed tracking for a Mars unmanned KPM-VBLA performing a Mars periodic ramp line observation task in accordance with an embodiment of the present invention;

FIGS. 13 (a) and (b) are graphs of the velocity and attitude response of the Mars unmanned aerial vehicle KPM-VBLA performing a Mars periodic slope line observation task, respectively, in accordance with an embodiment of the present invention;

FIG. 14 is a graph of position error for a Mars unmanned KPM-VBLA performing a Mars periodic slope line observation task according to an embodiment of the present invention;

fig. 15 (a) and (b) are graphs of feedback control force and moment for performing a task of observing a spark periodic ramp line by a KPM-VBLA of a spark unmanned aerial vehicle according to an embodiment of the present invention, respectively.

Reference numerals illustrate:

the device comprises a 1-wireless communication module, a 2-battery, a 3-lifting support, a 4-solar panel, a 5-control module, a 6-fuselage main body, a 7-upper rotor, a 8-lower rotor, a 9-camera, a 10-rotor paddle, a 11-protection cover, a 12-magnetic control paddle, a 13-motor, a 14-motor rotating shaft and a 15-flexible hinge.

Detailed Description

In order that the above-recited objects, features and advantages of the present invention will be more clearly understood, a more particular description of the invention will be rendered by reference to the appended drawings and appended detailed description. It should be noted that, without conflict, the embodiments of the present invention and features in the embodiments may be combined with each other. In the following description, numerous specific details are set forth in order to provide a thorough understanding of the present invention, however, the present invention may be practiced in other ways than those described herein, and therefore the scope of the present invention is not limited to the specific embodiments disclosed below.

The invention provides a nonlinear task manifold controller based on the tracking problem of the track (path) of the Mars unmanned aerial vehicle, so that the Mars unmanned aerial vehicle can stably fly with less energy consumption while finishing the track (path) tracking task. First, a desired trajectory and pose composition trajectory manifold with nonlinear geometric features is defined for a Mars unmanned aerial vehicle. To reduce the energy consumption of the control system, a generalized speed constraint is defined in which the speed manifold describes the Mars unmanned aerial vehicle. On this basis, six-dimensional task manifolds are weighted and synthesized. Then, the feedback control force and control moment of the KPM-VBLA of the Mars unmanned aerial vehicle are designed by utilizing the task manifold, namely the task manifold control law N _u So that the generalized position and generalized velocity converge to the trajectory manifold and velocity manifold, respectively. And the stability of the nonlinear task manifold controller was analyzed. This approach avoids the decomposition of the controller's "internal" and "external" feedback loops, without the need to handle 12 state variables (6 generalized positions and 6 generalized velocities) in a cascaded fashion. But directly utilizes six-dimensional task manifold to obtain control force and control moment of KPM-VBLA of the Mars unmanned aerial vehicle, ensures stable speed and angular speed, and simultaneously enables track tracking error to converge to zero.

Specifically, as shown in fig. 1, the structure of the KPM-VBLA of the miniature coaxial double-variable-tilt rotor unmanned aerial vehicle designed by the present invention is shown, and the KPM-VBLA of the miniature coaxial double-variable-tilt rotor unmanned aerial vehicle adopts a miniature coaxial double-variable-tilt rotor structure, which specifically includes: solar cell panel 4, landing gear 3, fuselage main part 6, battery 2 and wireless communication module 1, upper rotor 7, lower rotor 8, two magnetic control oar dish 12, two rotor oar dish 10, control module 5 and camera 9, safety cover 11, motor 13, motor shaft 14. The camera 9 is arranged on the control module 5, a visual sensor is arranged on the outer sides of the equipment supports in the center of the upper rotor wing and the lower rotor wing along the front direction of the main body, and a micro inertial measurement assembly and a navigation control computer are arranged in the main body of the center of the equipment support as the control module. The small-size solar cell panel 4 of upper rotor top utilizes solar energy to charge for the battery, is provided with safety cover 11 below the lower rotor for stopping the spark sand grain that the rotor was rotatory to raise when taking off and landing, reduce the rotation axis damage that the spark sand grain probably caused, rotor oar dish 10 is connected by elastic hinge 15 with motor shaft 14. As shown in fig. 2, the upper and lower magnetic control paddles 12 are respectively located at coaxial positions of the two rotor paddles 10 fixedly connected with the upper and lower rotor wings, so long as the upper and lower magnetic control paddles are coaxially adjacent to each other, no matter whether the magnetic control paddles 12 are located above or below the rotor paddles 10, electromagnetic materials are embedded in the magnetic control paddles 12 at equal intervals, and the intensity and direction of a magnetic field generated by the electromagnetic materials are controlled by current; ferromagnetic material is embedded at equal intervals in rotor disk 10 fixedly connected to motor shaft 14 of main body 6, corresponding to electromagnetic material of magnetron disk 12. Under the action of gyro precession effect, because rotor disk and motor shaft are elastic hinged connection, through the magnetic field on the control magnetic control oar disk, can control rotor disk's slope size and direction, that is the magnetic force between magnetic control oar disk 12 and rotor disk 10 will control the size and the direction of upper and lower rotor inclination, realizes the variable control to upper and lower twin-rotor inclination.

A Mars unmanned aerial vehicle and a control method based on a task manifold controller thereof comprise the following steps:

s1: defining all coordinate systems of KPM-VBLA of miniature coaxial double-variable-dip-angle rotor spark unmanned aerial vehicle, wherein the coordinate system is defined as shown in figure 3, o _i -x _i y _i z _i A coordinate system is fixedly connected for the rotor wing i, o _b (CG)-x _b y _b z _b Is the body coordinate system, O _g -X _g Y _g Z _g Is a ground coordinate system.

Preferably, the specific steps of the step S1 are as follows:

s1-1: definition of Mars nothingGround coordinate system and organism coordinate system of man-machine KPM-VBLA: ground coordinate system O _g -X _g Y _g Z _g Origin O of (2) _g Is a fixed point on the Mars ground, wherein O _g X _g The axis points to north, O _g Y _g Axis to the east, O _g Z _g The axis points to the center of the spark; body coordinate system o _b -x _b y _b z _b Origin o of (2) _b Is the center of gravity CG of the Mars unmanned aerial vehicle, wherein o _b x _b Axial-pointing forward vision sensor, o _b z _b The axis being perpendicular to o _b x _b Axis and point downward, o _b y _b The shaft is determined by a right hand rule and points to the right side of the main body of the machine body;

wherein Y= [ P ] ^T ,Θ ^T ] ^T Is a generalized position vector of the Mars unmanned plane, and P= [ x, y, z] ^T And Θ= [ phi, θ, ψ ]] ^T Respectively a position vector and an attitude angle vector of the Mars unmanned aerial vehicle in a ground coordinate system, wherein X= [ V ] ^T ,ω ^T ] ^T Is a generalized velocity vector of the Mars unmanned plane, and V= [ u, V, w ]] ^T And ω= [ p, q, r] ^T The speed vector and the rotation angular velocity vector in the machine body coordinate system are respectively,

wherein c (·) =cos (·), s (·) =sin (·), t (·) =tan (·);

S2: and establishing a six-degree-of-freedom dynamic model of the KPM-VBLA of the Mars unmanned aerial vehicle.

Preferably, S2-1: under the machine body coordinate system in the step S1-1, the speed and angular velocity dynamics equation of KPM-VBLA in the Mars unmanned aerial vehicle can be obtained based on a Newton-Euler equation, wherein the speed and angular velocity dynamics equation are respectively as follows:

s2-2: as known from the KPM-VBLA structure of the Mars unmanned aerial vehicle, the external force applied to the main body of the aircraft body comprises a Mars gravity vector F _G The method comprises the steps of carrying out a first treatment on the surface of the Lift force vector F generated by rotation of upper rotor and lower rotor _T And a pressing resistance vector F _R Machine for makingThe external torque applied to the main body comprises a reactive torque vector M generated by the rotation of the upper rotor wing and the lower rotor wing _Q Gyro moment vector M _G And the lift force of the upper rotor wing and the lower rotor wing are lower than that of the machine body coordinate system _b x _b Shaft sum o _b y _b Moment vector M generated by force component of shaft _T The method comprises the steps of carrying out a first treatment on the surface of the The force and moment vectors related to the upper rotor wing and the lower rotor wing can be obtained by fixedly connecting a coordinate system with a rotor wing i at present and then are converted into a machine body coordinate system; thus, the resultant forces and moments acting on the Mars unmanned KPM-VBLA can be expressed as:

F ^b ＝F _G +F _T +F _R

M ^b ＝M _Q +M _G +M _T

wherein m=diag [ M, M, M, I _x ,I _y ,I _z ]Is a Mars unmanned aerial vehicle quality matrix, N _d For the force and moment related to the generalized velocity vector X of the Mars unmanned plane, N _d ＝[m(vr-wq),m(wp-ur),m(uq-vp),I _y -I _z )rq,(I _z -I _x )pr,(I _x -I _y )pq] ^T ；N _f Is the force and moment of the external force acting on the main body of the machine body,

N _u forces and moments generated for the task manifold controller, i.e. the control law of the task flow controller,/-) >

S3: nonlinear task manifold control law N for designing task manifold controller _u Namely, the input control force and moment of the KPM-VBLA of the Mars unmanned aerial vehicle in the step S2 are obtained, so that the Mars unmanned aerial vehicle is controlled.

Preferably, the specific steps of the step S3 are as follows:

wherein t is the time of the time, ^j A ₁ (t), ^j A ₂ (t) is a three-dimensional row vector which is designed in advance according to the flight track, b (t) is a one-dimensional vector which is designed in advance according to the flight track, wherein the flight track can be changed with time or can be kept unchanged, ^j P＝[x ^j ,y ^j ,z ^j ] ^T for vectors composed of j powers of the position coordinate components with respect to the Mars unmanned aerial vehicle, j represents the order describing the desired trajectory or path, e _N1 and e_N2 Is a track tracking error component; when N (P, t) = [ e _N1 e _N2 0] ^T ≠0 _3×1 When there is a track following error component e _N1 and e_N2 The corresponding control law N is designed in the following steps _u So that the track trace error component e _N1 0 and e _N2 →0；

Φ(P,Θ,t)＝Θ-Θ*(P,Θ,t)

The corresponding control law N is designed in the following steps _u So that the attitude error phi (P, theta, t) to 0 _3×1 ；

/>

wherein ,

wherein ,

is the velocity squared error vector, V _c Is a desired flight speed vector; the generalized velocity vector X of KPM-VBLA of the final Mars unmanned aerial vehicle needs to converge to velocityDegree manifold ψ _v ＝0 _6×1 So that the Mars unmanned aerial vehicle KPM-VBLA takes a desired velocity vector V _c Maintaining the space geometry steady state flight;

Ψ＝Ψ _tr +AΨ _v ＝0

where A is a 6 th order diagonal weighting coefficient matrix, the matrix A is designed such that if and only if ψ _tr→0 and Ψ_v -0, only ψ -0, thus the track following error component e of step 3-1 can also be made _N1 0 and e _N2 0 and the posing error Φ (P, Θ, t) in step 3-2 → 0 _3×1 The method comprises the steps of carrying out a first treatment on the surface of the The synthesis of the task manifold psi= 0 can ensure that the controller only needs to process the 6-dimensional problem, and can unify the flight control task and the track tracking task with stable gesture and speed;

s3-6: in order to ensure that the generalized position vector Y of the Mars unmanned aerial vehicle KPM-VBLA, the generalized velocity vector X and the first derivative thereof converge to the task manifold ψ=0, a 6 th-order constant coefficient matrix T, that is, a cooperative gain matrix, is designed so as to satisfy the following formula:

and the convergence of all state variables of the closed loop system is ensured by designing a weighting coefficient matrix and a cooperative gain matrix of the task manifold controller.

K ₁₂ ＝(T+A)J _s +TAГ _s ，/>

J ₁ ＝J _P +J _V ，/>

/>

Based on the nonlinear task manifold control law N _u The matrix of the task manifold controller can be correspondingly obtained after being split.

To prove the nonlinear task manifold control law N of step S3-7 _u Selecting Lyapunov function

And deriving time to obtain:

wherein, to make

Based on the control simulation, the control simulation of the Marble pit exploration task and the Marble periodic gradient line observation task is performed by utilizing the 3D virtual scene based on the Unity 3D to construct the Marble pit and the Marble periodic gradient line of the san Maria, so that the control effect and the control precision of the task manifold controller and the controlled performance of the designed miniature coaxial double-variable-inclination rotor unmanned aerial vehicle KPM-VBLA are further verified. The specific method adopted is as follows: for the Mary Mars meteorite crater exploration task, the expected track is designed to descend into the meteorite crater along the meteorite crater wall, then fly along the spiral line around the meteorite crater wall, finally fly out of the meteorite crater and fly along a straight line to the expected end point, and track tracking control is carried out by the task manifold controller and the sliding mode controller with better track tracking control effect at present. For a Mars periodic gradient line observation task, designing a desired track as a high-order curve conforming to gradient line characteristics, and carrying out path following control by using the task manifold controller.

The control effect and accuracy verification of the task manifold controller of the invention for controlling the spark unmanned aerial vehicle KPM-VBLA to execute the spark exploration task are specifically described below by a specific embodiment. Fig. 5 and 11 are 3D virtual model diagrams of the san malaya Mare meteorite crater and Mars periodic ramp lines constructed in accordance with the present invention.

Taking the exploration requirement of fully and detailed imaging of the internal landform of the Marble pit into consideration, the KPM-VBLA flight task of the Marble unmanned aerial vehicle is designed to fly above the edge of the Marble pit, gradually descend to be close to the bottom of the Marble pit, then spirally ascend to above the Marble pit along the wall of the Marble pit so as to scan the wall of the Marble pit, and finally gradually fly to the pit edge. The descending depth is set to be 6m, the spiral spool is positioned at the center of the Mars merle pit, the radius of the bottom surface and the radius of the top surface of the spiral line are both 40m, and the ascending speed in the vertical direction is 001m/s. Set a desired speed V _c =1 m/s, initial position P ₀ ＝[-8,-40,0] ^T m, initial linear velocity v ₀ ＝[0.1,0.2,0] ^T m/s, initial pose Θ ₀ ＝[0,0,0] ^T rad, the other state is 0. The designed exploration track is a splice of 3 continuous curves, which are respectively described by the following three manifolds

/>

Wherein r=40m, t ₁ 10s is the time when the Mars switches from the diagonal path to the spiral path, t ₂ = (10+200 pi) s is the time for the spark unmanned KPM-VBLA to switch from the spiral trajectory to the straight path.

As shown in FIG. 8, under the task manifold controller and the sliding mode controller, the track tracking is performed within the track tracking task time of 700s, and the steady-state error is not more than 0.3m, which indicates that the Mars unmanned aerial vehicle can accurately track the secondary task track under the two controllers so as to complete the Mars merle exploration task. During the first 10s ramp down, the slip-form controller was started with a position error overshoot of 0.09m, 4 times the task manifold controller, and a steady state error of 0.013m was present. At 10s, the KPM-VBLA is finished by the ramping process and is spirally increased, at the moment, the initial position error of the task manifold controller is 0.275m, which is higher than 0.1m of the sliding mode controller, the convergence time is 2s, which is lower than 5s of the sliding mode controller, and the steady state error is 0.0011m which is slightly smaller than 0.0013m of the sliding mode controller. At 63s, KPM-VBLA spiral rise ends, beginning to ramp to pit edge. At this time, the task manifold controller and the sliding mode controller have good transition, and the position error of the task manifold controller returns to 0, because the oblique line is exactly the tangent line of the spiral line, and the two tracks are smoothly connected. As can be seen from FIG. 8, there is a large speed overshoot of the slipform controller at the beginning of the KPM-VBLA drop and at the 10s KPM-VBLA track switch, with overshoot rates as high as 28% and 10%, while the task manifold controller is not overshooting in speed. In comparison with the velocity component of fig. 7 (a), the x-direction and z-direction velocity changes appear to be dramatic, which explains that the task manifold controller track error is higher than the slipform controller when track switching is performed at 10s KPM-VBLA. Task manifold controllers perform well in speed tracking because speed constraints are considered in the synthesis of task manifolds. From the convergence time, the task manifold controller is equivalent to or even lower than the sliding mode controller, because the task manifold controller unifies the tracking errors of the traditional 'inner' and 'outer' loop instructions in the task manifold synthesis process, and the reaction speed of the Mars unmanned aerial vehicle to the control instructions is accelerated. Fig. 7 (b) shows that the three-axis attitude remains at all times at 0, illustrating that the designed spark unmanned aerial vehicle KPM-VBLA has a spatially-geometrically stable capability.

In the extreme environment of a Mars, the limited power of the unmanned aerial vehicle needs to be distributed for functions such as flight control, imaging, communication, survival heating and the like. Therefore, it is required to optimize the flight control function module, and reduce power consumption as much as possible while satisfying control accuracy. As shown in fig. 9 (a), the maximum feedback control force of the three axial directions under the task manifold controller is not more than 1.5N, wherein the feedback control force in the x-axis direction is 0.3N at 10s, that is, the x-axis acceleration is generated to track along the spiral track, and the feedback control force in the z-axis direction is-1.4N at 10s, which indicates that the Mars unmanned aerial vehicle decelerates and descends with the z-axis reverse acceleration at 10 s. From the fact that the attitude angle of the Mars unmanned aerial vehicle in fig. 8 is always kept to be 0 and the triaxial feedback control moment of the Mars unmanned aerial vehicle in fig. 9 (b) is always kept to be 0, it is known that the attitude of the Mars unmanned aerial vehicle is always kept stable and unchanged in the track tracking task process, and the camera shooting picture is ensured to be stable in the imaging process so as to acquire image data. Although stable track tracking can be realized under the sliding mode controller, when track switching is performed in 10 seconds, the feedback control force in the x-axis direction is 0.5N, the feedback control force in the z-axis direction is-1.7N, which is 1.67 times and 1.21 times that under the task manifold controller, and the energy supply requirement is higher.

Simulation results show that the designed Mars unmanned aerial vehicle KPM-VBLA has satisfactory flight performance and space geometric stability, can finish Mars meteorite pit entry search tasks with high quality, and simultaneously proves the effectiveness of the design method of the task manifold controller. Meanwhile, aiming at the unique challenge of track tracking precision and energy consumption saving in the spark environment, the task manifold controller provided by the invention has certain advantages for the KPM-VBLA of the spark unmanned aerial vehicle to execute the track tracking task in the spark detection task.

Although advanced nonlinear controllers such as sliding mode controllers can solve the problem of controlling secondary task trajectories, they do not meet the control requirements of higher order task trajectories. Set a desired speed V _c =1 m/s, initial position P ₀ ＝

[-35,-120,-5] ^T m, initial linear velocity v ₀ ＝[0.1,-0.2,0] ^T m/s, initial pose Θ ₀ ＝[0,0,0] ^T rad, the other state is 0. In view of the task need for observation of the Mars periodic slope line along its characteristic shape in fig. 14, a higher-order curve conforming to the shape characteristics of the Mars periodic slope line is fitted as the desired path for the Mars periodic slope line observation task, described by the following manifold

As can be seen from fig. 14, the initial point of the KPM-VBLA of the mars unmanned aerial vehicle is not located on the expected path, and the mars unmanned aerial vehicle converges to the expected path after about 10s of flight, and in the subsequent path tracking process, the tracking error always approaches to 0, which shows the good performance of the KPM-VBLA of the mars unmanned aerial vehicle under the task manifold controller in tracking the 4-step curve as shown in the manifold. As shown in FIG. 12, the Mars unmanned KPM-VBLA speed converged to the desired speed of 1m/s over 3.5s and remained well in steady state until 400s ended, although the x and y axis direction speed components were varied as shown in FIG. 13 (a). As in fig. 13 (B), the attitude remains spatially geometrically stable throughout the course of 400s, although there are three turning points a, B and C for the flight path as in fig. 11 (a). This demonstrates the role of taking into account kinematic constraints in the velocity manifold, and the ability of the designed Mars unmanned aerial vehicle KPM-VBLA to remain geometrically stable while maneuver.

Fig. 15 (a) and (B) show that there is a force change of 0.1N and 0.2N in the x and y axis directions at the start time, respectively, based on the feedback control force and moment obtained by the control law of the task manifold, in order to allow the mars unmanned aerial vehicle to quickly converge to the desired path, and then a change of not more than 0.2N in amplitude is produced at 140s,175s and 250s, corresponding to the forces required for the a, B and C3 turning points in fig. 11 (a), to change the speed direction of the mars unmanned aerial vehicle. While the control force in z direction remains always-1N because the mars drone is already at the desired altitude of-5 m at the initial moment and remains at this altitude throughout the flight, the x and y direction motion changes do not cause additional motion in z direction. The constant zero 3-axis moment corresponds to the geometric steady state of the Mars unmanned aerial vehicle KPM-VBLA. The change in feedback force and torque again shows the low demand for power consumption by the task manifold controller.

Simulation results show that the designed Mars unmanned aerial vehicle KPM-VBLA still has space geometric stability when the speed direction changes, does not generate coupling between shafts, and can be used for high-order path tracking tasks. Meanwhile, the validity of maneuver of the KPM-VBLA of the Mars unmanned aerial vehicle along the high-order expected path under the task manifold controller is verified, namely the task manifold controller ensures that the path tracking error and the speed tracking error are converged to 0 rapidly.

It is apparent that the above examples are given by way of illustration only and are not limiting of the embodiments. Other variations or modifications of the above teachings will be apparent to those of ordinary skill in the art. It is not necessary here nor is it exhaustive of all embodiments. While still being apparent from variations or modifications that may be made by those skilled in the art are within the scope of the invention.

Claims

1. The utility model provides a spark unmanned aerial vehicle KPM-VBLA which characterized in that adopts miniature coaxial double variable dip rotor structure, and it specifically includes: the device comprises a main body (6), a battery (2), a wireless communication module (1), an upper rotor (7), a lower rotor (8), two magnetic control propeller discs (12), two rotor propeller discs (10), a control module (5), a camera (9), a motor (13), a motor rotating shaft (14) and an elastic hinge (15); wherein, a device bracket is arranged between the upper rotor wing and the lower rotor wing, a visual sensor is arranged at the outer side of the device bracket along the front direction of the main body, and a control module (5) comprises a micro inertial measurement component and a navigation control computer which are arranged in the main body of the center of the device bracket; the method comprises the steps of carrying out a first treatment on the surface of the The two rotor disks (10) are connected with a motor rotating shaft (14) in a split mode through an elastic hinge (15), and the upper rotor and the lower rotor are respectively arranged on the rotor disks (10) at the upper part and the lower part; the two magnetic control propeller discs (12) are respectively positioned on one side coaxial with the two rotor propeller discs (10), electromagnetic materials are embedded in the two magnetic control propeller discs (12) at equal intervals, and the intensity and the direction of a magnetic field generated by the electromagnetic materials are controlled by current; embedding ferromagnetic material on two rotor disks (10) at equal intervals corresponding to the electromagnetic material of the magnetic control disks (12); under the action of gyro precession effect, the magnetic force between the magnetic control pulp disk (12) and the rotor pulp disk (10) controls the magnitude and the direction of the dip angles of the upper rotor and the lower rotor, so as to realize variable control of the dip angles of the upper rotor and the lower rotor.

2. The Mars unmanned aerial vehicle KPM-VBLA according to claim 1, further comprising a solar panel (4), a landing bracket (3) and a protective cover (11); a solar panel (4) is arranged above the upper rotor wing (7), and solar energy is utilized to charge a battery; a protective cover (11) is arranged below the lower rotor wing.

3. A control method of a KPM-VBLA of a mars unmanned aerial vehicle according to claim 1 or 2 based on task manifold, comprising the steps of:

s3: nonlinear task manifold control law N for designing task manifold controller _u And obtaining the input control force and moment of the KPM-VBLA of the Mars unmanned aerial vehicle so as to realize the control of the Mars unmanned aerial vehicle.

4. A control method according to claim 3, wherein said step S1 specifically comprises the steps of:

s1-1: defining a ground coordinate system and a body coordinate system of the KPM-VBLA of the Mars unmanned aerial vehicle: ground coordinate system O _g -X _g Y _g Z _g Origin O of (2) _g Is a fixed point on the Mars ground, wherein O _g X _g The axis points to north, O _g Y _g The axis is directed to the east,

O _g Z _g the axis points to the center of the spark; body coordinate system o _b -x _b y _b z _b Origin o of (2) _b Is the center of gravity CG of the Mars unmanned aerial vehicle, wherein,

o _b x _b axial-pointing forward vision sensor, o _b z _b The axis being perpendicular to o _b x _b Axis and point downward, o _b y _b The shaft is determined by a right hand rule and points to the right side of the main body of the machine body;

wherein Y= [ P ] ^T ,Θ ^T ] ^T Is a generalized position vector of the Mars unmanned plane, and P= [ x, y, z] ^T And Θ= [ phi, θ, ψ ]] ^T Respectively a position vector and an attitude angle vector of the Mars unmanned aerial vehicle in a ground coordinate system, wherein X= [ V ] ^T ,ω ^T ] ^T Is a generalized velocity vector of the Mars unmanned plane, and V= [ u, V, w ]] ^T And ω= [ p, q, r] ^T Speed vector and rotation angular speed in the machine body coordinate system respectivelyThe degree vector of the degree vector is used to determine,

Mapping a conversion matrix from a machine body coordinate system to a ground coordinate system for the rotation angular velocity of the machine body; />

Wherein c (·) =cos (·), s (·) =sin (·), t (·) =tan (·);

5. The control method according to claim 4, wherein the step S2 specifically includes the steps of:

s2-2: as known from the KPM-VBLA structure of the Mars unmanned aerial vehicle, the external force applied to the main body of the aircraft body comprises a Mars gravity vector F _G Lift force vector F generated by rotation of upper rotor wing and lower rotor wing _T And a pressing resistance vector F _R The method comprises the steps of carrying out a first treatment on the surface of the The external torque applied by the main body of the machine body comprises a reactive torque vector M generated by the rotation of the upper rotor wing and the lower rotor wing _Q Gyro moment vector M _G And the lift force of the upper rotor wing and the lower rotor wing are lower than that of the machine body coordinate system _b x _b Shaft sum o _b y _b Moment vector M generated by force component of shaft _T The method comprises the steps of carrying out a first treatment on the surface of the Thus, the resultant forces and moments acting on the Mars unmanned KPM-VBLA can be expressed as:

F ^b ＝F _G +F _T +F _R

M ^b ＝M _Q +M _G +M _T

S2-3: based on the step S2-1 and the step S2-2, a complete six-degree-of-freedom kinetic equation model of the KPM-VBLA of the Mars unmanned aerial vehicle can be obtained under the machine body coordinate system:

wherein m=diagm, M, M, I _x ,I _y ,I _z ]Is a Mars unmanned aerial vehicle quality matrix, N _d For the force and moment related to the generalized velocity vector X of the Mars unmanned plane, N _d ＝[m(vr-wq),m(wp-ur),m(uq-vp),I _y -I _z )rq,(I _z -I _x )pr,(I _x -I _y )pq] ^T ；N _f Is the force and moment of the external force acting on the main body of the machine body,

6. The control method according to claim 5, wherein the step S3 specifically includes the steps of:

wherein t is the time of the time, ^j A ₁ (t), ^j A ₂ (t) is a three-dimensional row vector which is designed in advance according to the flight track, b (t) is a one-dimensional vector which is designed in advance according to the flight track, ^j P＝[x ^j ,y ^j ,z ^j ] ^T for vectors composed of j powers of the position coordinate components with respect to the Mars unmanned aerial vehicle, j represents the order describing the desired trajectory or path, e _N1 and e_N2 Is a track tracking error component; when N (P, t) = [ e _N1 e _N2 0] ^T ≠0 _3×1 When there is a track following error component e _N1 and e_N2 The control law N is designed correspondingly _u So that the track trace error component e _N1 0 and e _N2 →0；

S3-2: considering stable posture in the flying process of the KPM-VBLA of the Mars unmanned aerial vehicle, defining a posture error phi (P, theta, t) as the KPM of the Mars unmanned aerial vehicleVBLA pose Θ and desired pose Θ ^* The difference of (P, Θ, t) gives:

Φ(P,Θ,t)＝Θ-Θ ^* (P,Θ,t)

the control law N is designed correspondingly _u So that the attitude error phi (P, theta, t) to 0 _3×1 ；

wherein ,

wherein ,

Ψ＝Ψ _tr +AΨ _v ＝0

K ₁₂ ＝(T+A)J _s +TAГ _s ，/>

J ₁ ＝J _P +J _V ，/>

m＝{P,Θ},n＝{X,Θ}；

7. The control method according to claim 6, wherein for proving step S3-7, the nonlinear task manifold control law N _u Selecting Lyapunov function

And deriving time to obtain:

wherein, to make

8. Simulation method for trajectory tracking and path following control of KPM-VBL of said Mars unmanned aerial vehicle employing the control method according to any of the claims 3-7, characterized in that in a virtual simulation environment, 3D virtual scenes of san maria Mars merle and Mars periodic gradient lines are constructed based on Unity3D, and task flow control law N designed based on the preceding step S3 _u The control simulation of the Mars unmanned aerial vehicle KPM-VBLA realizes the Mars merle exploration task and the Mars periodic gradient line observation task.

9. The simulation method according to claim 8, wherein for the st-mar Mars merle exploration task, the desired trajectory is designed to descend into the merle along the merle wall, then fly around the merle wall along the spiral line, finally fly out of the merle and fly straight to the desired destination, and trajectory tracking control is performed by the task manifold controller and the existing slipform controller in step 3, respectively.

10. The simulation method according to claim 9, wherein for a Mars periodic slope line observation task, a desired track is designed to be a higher-order curve conforming to the slope line pattern feature, and the task manifold controller in step 3 is used for path following control.