Dynamic modeling and optimizing method for unmanned aerial vehicle driving mechanism

Abstract

The invention belongs to a dynamic modeling and optimizing method for an unmanned aerial vehicle driving mechanism. The method comprises the following specific steps: establishing an unmanned aerial vehicle driving mechanism model; establishing a coordinate system, a fuselage fixed connection coordinate system and an executing mechanism angle; analyzing kinematics of the driving mechanism: taking the length of each rod as a variable, analyzing the change condition of related performance parameters of the driving mechanism, and providing a qualitative rule for design; establishing a dynamic model of the driving mechanism; establishing a dynamic equation set and verifying the correctness of the dynamic equation set; and the peak torque of the driving mechanism is optimized. Compared with the prior art, the driving performance of the unmanned aerial vehicle is optimized, the peak value of the driving torque is reduced, and the motion law of the driving mechanism is improved, so that the jamming problem of the driving mechanism is solved, the load of the brushless motor is reduced, and the overall performance and stability of the unmanned aerial vehicle are improved.

Description

Technical Field

[0001] The present invention relates to the technical field of unmanned aerial vehicles, and in particular to a dynamic modeling and optimization method for a driving mechanism of an unmanned aerial vehicle. Background Art

[0002] As a highly integrated aviation device, the dynamic characteristics of the driving mechanism of a UAV are crucial to its flight performance and stability. The driving mechanism of a UAV is usually composed of a series of connecting rods, driving components, etc. The performance of these components directly affects the flight efficiency, range and control accuracy of the UAV.

[0003] The dynamic characteristics of the UAV drive mechanism not only affect the operating range of the actuator, but also affect the output torque of equipment such as servos / motors.

[0004] The existing drive mechanism only considers the kinematics law, and there are problems: the input and output torques are not considered, which will cause the drive motor to jam. In addition, the existing dynamics methods are mainly based on the Newton-Euler equation or the Lagrange equation. Due to the simple way of constructing the equation, it is not convenient to carry out optimization design. In the existing optimization methods of UAV drive mechanisms, only kinematics is optimized, and dynamics optimization is not designed, and even the influence of UAV aerodynamics is not considered. Summary of the invention

[0005] In view of the above problems, the purpose of the present invention is to provide a dynamic modeling and optimization method for a UAV drive mechanism, optimize the driving performance of the UAV, reduce the peak driving torque, improve the motion law of the driving mechanism, thereby solving the problem of driving mechanism jamming, reducing the load of the brushless motor, and improving the overall performance and stability of the UAV.

[0006] The technical solution to achieve the purpose of the present invention is: a dynamic modeling and optimization method for the driving mechanism of an unmanned aerial vehicle, the specific steps are as follows:

[0007] Establish the UAV drive mechanism model: establish the coordinate system, the fuselage fixed coordinate system and the actuator angle;

[0008] Analyze the kinematics of the drive mechanism: Take the length of each rod as a variable, analyze the changes in the performance parameters related to the drive mechanism, and provide qualitative rules for the design;

[0009] Furthermore, a dynamic model of the driving mechanism is established: a group of dynamic equations is established to verify the correctness of the dynamic equations;

[0010] Establish the objective function and optimize the peak torque of the driving mechanism.

[0011] In the establishment of the UAV drive mechanism model, the UAV drive mechanism is a crank rocker mechanism; the coordinate system AXY is defined as the fuselage fixed coordinate system. Looking at the fuselage from the nose perspective, the X-axis points to the left side of the fuselage, the Y-axis is perpendicular to the X-axis and upward, and the coordinate system AXY is located in the cross section perpendicular to the longitudinal axis of the fuselage, where Axy is the mechanism fixed coordinate system, the x-axis points from the crank fixed point A along the base to the rocker fixed point D, and the y-axis is perpendicular to the x-axis; θ is defined as the actuator angle, θ0 is the base installation angle, θ3 is the rocker angle, and θ4 is the actuator installation angle.

[0012] Furthermore, the kinematics of the driving mechanism is analyzed and the constraints are established:

[0013] In addition to satisfying the conditions for the crank rocker mechanism to be established, the constraints that must be met are:

[0014] Geometric constraints:

[0015]

[0016] Where l1 is the crank length, l2 is the connecting rod length, l3 is the rocker length, l4 is the base length, θ1 is the crank angle, θ2 is the connecting rod angle, and θ3 is the rocker angle.

[0017] Furthermore, in establishing the dynamic model of the driving mechanism, the dynamic equations of the driving mechanism are:

[0018]

[0019] Where M is the mass inertia matrix, L is the centrifugal moment matrix, Q is the sum of the external moment matrix W and the gravity moment matrix G, B is the constraint coefficient matrix, λ is the Lagrange multiplier matrix, θ1 is the crank angle, θ2 is the connecting rod angle, and θ3 is the rocker angle;

[0020] The external moment matrix W is:

[0021] W=[M1 0 M3] T

[0022] Where M1 is the crank drive torque, that is, the torque required to drive the motor to operate the mechanism; M3 is the rocker input torque, that is, when the mechanism drives the actuator to move, the torque of the drone's aerodynamic load reacting to the drive mechanism. The actuator is connected to the rocker, so it is called the rocker input torque.

[0023] Furthermore, in order to verify the correctness of the dynamic equations and results of the driving mechanism, the crank rocker model was established using Adams software. The crank frequency, i.e., crank speed, was given, and the rocker input torque was given as a constant value and a sinusoidal law, respectively. The crank driving torque was solved and the results were compared.

[0024] Furthermore, in optimizing the peak torque of the driving mechanism, the specific steps are as follows:

[0025] (1) Select peak torque as the optimal target and establish the objective function;

[0026] (2) Select the length of each rod and the position angle of the actuator as the decision variables;

[0027] (3) Establish a nonlinear programming mathematical model;

[0028] (4) Establish inequality linear constraints based on the crank rocker establishment conditions;

[0029] (5) Establish nonlinear constraints based on aerodynamic requirements;

[0030] (6) Combine aerodynamics to find the optimal solution.

[0031] Furthermore, the peak value of the crank drive torque is selected as the optimization target, and the established objective function is: min|M1| max , where M1 is the crank drive torque.

[0032] Furthermore, the nonlinear programming model of the optimization problem is:

[0033] min|M1| max

[0034]

[0035] Where M1 is the crank driving torque, which can be obtained according to the dynamic equation; A′ is the inequality linear constraint matrix, X is the decision variable, c is the inequality nonlinear constraint matrix, and c eq is the equality nonlinear constraint matrix.

[0036] Furthermore, the aerodynamic results are combined to optimize the mechanism. The specific process is as follows:

[0037] Given the initial values ​​of the lengths of the connecting rods and the position angles of the actuators;

[0038] Substitute the kinematic and dynamic models of the drive mechanism; then obtain the aerodynamic force, rocker input torque and crank drive torque;

[0039] Iterative optimization is performed with the peak torque as the optimization target, and then the optimization results of the length dimensions of each rod of the mechanism and the position angle of the actuator are obtained;

[0040] Aerodynamic force judgment: Substitute the optimized parameter results into the kinematic model of the drive mechanism to obtain the aerodynamic force, and verify whether the aerodynamic force is reduced. If it is reduced, re-enter the optimization process to carry out optimization. If it is not reduced, the aerodynamic conditions are met and the optimization is terminated.

[0041] Dynamic modeling and optimization method: The present invention provides a dynamic modeling and optimization method for the UAV drive mechanism, especially for the crank rocker mechanism. This method optimizes the performance of the drive mechanism through kinematic analysis and dynamic modeling, combined with the joint optimization of aerodynamics and dynamics.

[0042] 2. During the optimization process, the peak value of the crank drive torque was selected as the optimization target, which reduced the peak value of the drive torque of the UAV drive mechanism to improve the drive peak torque, solve the problem of drive mechanism jamming, reduce the load of the brushless motor, and improve the stability and reliability of the drive mechanism.

[0043] 3. By combining the aerodynamic force to search for the best, it is possible to ensure that the peak value of the crank drive torque is minimized without losing the aerodynamic force, thus meeting the requirements of the UAV. The implementation of the present invention not only optimizes the performance of the drive mechanism, but also indirectly improves the flight performance and endurance of the UAV, providing strong support for the widespread application of UAVs. BRIEF DESCRIPTION OF THE DRAWINGS

[0044] Figure 1 This is a flow chart of the dynamic modeling and optimization method of a UAV drive mechanism;

[0045] Figure 2 It is a schematic diagram of a four-bar linkage;

[0046] Figure 3 This is a schematic diagram of the UAV driving mechanism;

[0047] Figure 4 is the law of angular motion of the actuator;

[0048] Figure 5 This is the crank rocker Adams model diagram;

[0049] Figure 6 The verification diagram of the crank drive torque calculation results under different rocker input torque conditions, where (a) is the constant rocker input torque and (b) is the sinusoidal rocker input torque;

[0050] Figure 7 To optimize the peak torque flow chart of the drive mechanism;

[0051] Figure 8 To develop an optimization flow chart in combination with aerodynamics;

[0052] Fig. 9 To optimize the iterative process diagram;

[0053] Fig.10 This is the peak torque optimization result diagram. DETAILED DESCRIPTION

[0054] In order to make the technical means and creative features of the present invention easy to understand, the following is a brief description of the present invention in conjunction with the attached Figure 1-10 The technical scheme of the present invention is further illustrated with embodiments.

[0055] The crank-rocker mechanism is an extended deformation based on the planar four-bar linkage. It is a classic single-degree-of-freedom planar motion mechanical mechanism. It is widely used in the driving mechanisms of UAVs such as flapping-wing aircraft and coaxial twin-rotor UAVs. This paper takes the crank-rocker mechanism as a typical case to introduce the dynamic modeling and optimization method of the UAV driving mechanism.

[0056] like Figure 1 As shown, the following steps are included:

[0057] S1: Building a UAV drive mechanism model

[0058] S1.1: Define crank-rocker mechanism

[0059] According to the definition in the planar four-bar linkage, if a revolute pair can become a full revolute pair, then one of the two components it connects must be the shortest rod, and the length relationship of the four components satisfies the sum of the rod lengths. In this case, if the shortest rod is taken as the frame, a double crank mechanism is obtained; if any of the connected components of the shortest rod is taken as the frame, a crank rocker mechanism is obtained; if the component opposite the shortest rod is taken as the frame, a double rocker mechanism is obtained. If the four-bar linkage does not meet the sum of the rod lengths, no matter which component is selected as the frame, the resulting mechanism is a double rocker mechanism.

[0060] Therefore, the conditions for the crank-rocker mechanism to be established are:

[0061] a) The crank is the shortest rod;

[0062] b) The sum of the shortest and longest rods must be less than or equal to the sum of the lengths of the remaining rods.

[0063] like Figure 2 As shown, the rod AB that rotates a whole circle is a crank, the rod CD that reciprocates is a rocker, the rod AD fixed to the fuselage is a base, and the rod BC opposite to the base is a connecting rod. Usually, the crank AB serves as the active part, and the rocker CD serves as the driven part. The driving mechanism is organically formed by the four rods.

[0064] S1.2: Establish a simplified model of the drive mechanism

[0065] The driving mechanism on the drone is not necessarily parallel to the horizontal plane, and the joystick is not necessarily a straight rod. Therefore, it is necessary to combine the schematic diagram of the four-bar linkage to simplify it for the convenience of kinematic and dynamic modeling and analysis of the driving mechanism.

[0066] exist Figure 2On the basis of the four-bar linkage, the relative position of the installation angle adjustment mechanism and the fuselage is introduced, and the actuator DE is fixedly connected to the rocker CD to form a driving mechanism. Figure 3 As shown, each connecting rod is connected with a column hinge (hinged), and the rocker CD of the four-bar linkage is fixedly connected to the actuator DE. The crank AB is driven by the motor and the reducer to produce a full rotation, and the rocker CD is transmitted through the connecting rod BC to produce reciprocating motion. The rocker CD is fixedly connected to the actuator DE, thereby generating a suitable motion amplitude and motion law.

[0067] S1.3: Establish the drive mechanism coordinate system

[0068] In order to conveniently express and solve the relevant motion angles and coordinates of the driving mechanism, the following is established: Figure 3 The coordinate system shown in the figure, where the coordinate system AXY is the fixed coordinate system of the fuselage, looking at the fuselage from the nose, the X-axis points to the left side of the fuselage, the Y-axis is perpendicular to the X-axis and upward, and the coordinate system AXY is located in the cross section perpendicular to the longitudinal axis of the fuselage. Where Axy is the fixed coordinate system of the mechanism, the x-axis points from the crank fixed point A along the base to the rocker fixed point D, and the y-axis is perpendicular to the x-axis.

[0069] in:

[0070] θ0 is the angle between the mechanism fixed coordinate system Axy and the fuselage fixed coordinate system AXY, that is, the angle between the base (x-axis) and the horizontal direction of the entire fuselage (X-axis), which is hereinafter referred to as the base installation angle.

[0071] θ1 is the angle between the crank (AB) and the base (x-axis), which will be referred to as the crank angle hereinafter.

[0072] θ2 is the angle between the connecting rod (BC) and the base direction (x-axis direction), which will be referred to as the connecting rod angle hereinafter.

[0073] θ3 is the angle between the joystick (CD) and the base direction (x-axis direction), which will be referred to as the joystick angle hereinafter.

[0074] θ4 is the fixed angle between the rocker (CD) and the actuator (DE), which is referred to as the actuator installation angle hereinafter.

[0075] θ is the angle between the actuator DE and the horizontal plane X-axis, which is positive when it is upward and negative when it is downward. It is referred to as the actuator angle in the following. It can be expressed as the following formula:

[0076] θ=θ0+θ3+θ4(1)

[0077] Where θ is the actuator angle, θ0 is the base mounting angle, θ3 is the rocker angle, and θ4 is the actuator mounting angle.

[0078] When the drive mechanism design is completed, θ0 and θ4 are fixed values, and the sum of the two θ04 It is the key parameter of the flapping wing drive mechanism kinematics, which mainly determines the position of the actuator amplitude range, θ 04 Referred to as actuator position angle.

[0079] θ 04 =θ0+θ4 (2)

[0080] Where θ 04 is the actuator position angle, θ0 is the base installation angle, and θ4 is the actuator installation angle.

[0081] Substituting formula (2) into formula (1), we can obtain:

[0082] θ=θ3+θ 04 (3)

[0083] Where θ is the actuator angle, θ3 is the rocker angle, and θ 04 is the actuator position angle.

[0084] θ 04 The position of the actuator angle relative to the fuselage fixed coordinate system AXY can be adjusted without changing the actuator amplitude, that is, the upper and lower actuator angle distribution, for example, by changing θ 04 , the actuator movement of 40° upward and 30° downward can be modified to the actuator movement of 30° upward and 40° downward, which affects the torque of the aerodynamic force caused by the actuator acting on the rocker, θ 04 It will be used as one of the optimization parameters in the subsequent optimization process for minimizing the crank drive torque.

[0085] S2: Analyze drive mechanism kinematics

[0086] In mechanical principles, the design of a crank-rocker mechanism usually uses a drawing method to obtain the position of each column hinge according to the working stroke position of the rocker, and then connects the lines to obtain the length of each rod. However, in the design of the drive mechanism of a UAV, it is often necessary to adjust the length of each connecting rod according to the size of the frame, while meeting the requirements of the overall design for the actuator amplitude. Therefore, through the kinematic analysis of the crank-rocker mechanism, the length of each rod is taken as a variable, and the changes in the performance parameters related to the drive mechanism are analyzed, which can provide qualitative rules for the design.

[0087] The length of the crank, connecting rod, rocker and base is defined as: l i (i=1,2,3,4).

[0088] According to the establishment conditions of the crank rocker mechanism, the following constraints can be given:

[0089]

[0090] Where l1 is the crank length, l2 is the connecting rod length, l3 is the rocker length, l4 is the base length, l max It is the longest rod among l1, l2, l3, and l4. Since the longest rod can appear in any of the above four rods, its position cannot be determined. max replace.

[0091] At the same time, the UAV drive mechanism also has the following geometric constraints:

[0092]

[0093] Where l1 is the crank length, l2 is the connecting rod length, l3 is the rocker length, l4 is the base length, θ1 is the crank angle, θ2 is the connecting rod angle, and θ3 is the rocker angle.

[0094] When the crank motion law is given, that is, the motion law of θ1 is given, substituting into equation (5), θ2 and θ3 can be obtained. Combined with the constant θ 04 , substituting into formula (3), the motion law of the actuator angle θ can be obtained.

[0095] According to the above description and definition, the θ actuator angle is the angle that changes with the time period. To facilitate subsequent solution and optimization, the angle between the upper and lower limits of the θ actuator angle movement is defined as θ A Actuator range.

[0096] According to the definition of formula (3), θ 04 The actuator position angle is a fixed value, so the upper and lower limit angles of the actuator angle θ are equal to the upper and lower limit angles of the rocker angle θ3. A It can be obtained according to the motion law of the θ3 rocker angle, and the calculation formula is as follows:

[0097] θ A ={θ3} max -{θ3} min (6)

[0098] In the formula, θ A is the actuator amplitude, {θ3} max is the maximum value (upper limit) of the θ3 rocker angle movement,

[0099] {θ3} min It is the minimum value (lower limit) of the θ3 rocker angle movement.

[0100] Assume that the actuator amplitude requirement θ A =70°, the design parameters mainly include the length of each rod l i (i=1,2,3,4) and actuator position angle θ 04 .

[0101] Combined with the crank rocker mechanism establishment conditions, according to θ A =70° and formula (3), combined with experience, the preliminary proposed mechanism size parameters are shown in Table 1.

[0102] Table 1 Mechanism size parameters

[0103]

[0104] When the crank rotation speed is 7Hz, the θ actuator angle motion law is as follows: Figure 4 As shown, the law of motion is close to the cosine curve with the same phase.

[0105] S3: Establishing the dynamic model of the driving mechanism

[0106] S3.1 Establishment of the kinetic equations

[0107] In order to solve the driving torque and establish the relationship between the crank driving torque and the rocker input torque, it is necessary to perform a dynamic analysis of the driving mechanism.

[0108] Figure 3 The dynamic system shown in the figure includes three rigid bodies (crank, connecting rod, rocker), which can be expressed by three generalized coordinates θ i (i=1,2,3) indicates that equation (5) is the constraint equation of the system. The degree of freedom of the system is 1. Therefore, the system belongs to the complete constraint with redundant coordinates, and the Routh equation can be used to establish the dynamic equation group.

[0109]

[0110] Where T is the kinetic energy of the system, q j is the generalized coordinate, λ k is the Lagrange multiplier, Q j is a generalized force, B kj is a nonholonomic constraint, and s is the number of nonholonomic constraint equations.

[0111] The dynamic equations of the driving mechanism are obtained as follows:

[0112]

[0113] Where M is the mass inertia matrix, L is the centrifugal moment matrix, Q is the sum of the external moment matrix W and the gravity moment matrix G, B is the constraint coefficient matrix, λ is the Lagrange multiplier matrix, θ1 is the crank angle, θ2 is the connecting rod angle, and θ3 is the rocker angle.

[0114] The external moment matrix W is:

[0115] W=[M10 M3] T (9)

[0116] Where M1 is the crank drive torque, that is, the torque required to drive the motor to operate the mechanism; M3 is the rocker input torque, that is, when the mechanism drives the actuator to move, the torque of the drone's aerodynamic load reacting to the drive mechanism. The actuator is connected to the rocker, so it is called the rocker input torque.

[0117] Combination Figure 3 Analysis shows that the coordinate system established by the above dynamic equations is Axy, which is the fixed coordinate system of the mechanism. There is an installation angle θ0 with the fixed coordinate system AXY of the fuselage. Therefore, the gravity moment matrix G is:

[0118]

[0119] Where m1 is the crank mass, m2 is the connecting rod mass, m3 is the rocker mass, l1 is the crank length, l2 is the connecting rod length, l3 is the rocker length, θ0 is the base mounting angle, θ1 is the crank angle, θ2 is the connecting rod angle, θ3 is the rocker angle, and g is the acceleration due to gravity.

[0120] The constraint equation of formula (5) is written in variational form:

[0121]

[0122] According to the above formula, the constraint coefficient matrix B can be obtained:

[0123]

[0124] Where l1 is the crank length, l2 is the connecting rod length, l3 is the rocker length, θ1 is the crank angle, θ2 is the connecting rod angle, and θ3 is the rocker angle.

[0125] Define the Lagrange multiplier matrix λ as:

[0126] λ=[λ1 λ2] T (13)

[0127] Where λ1 is the first Lagrange multiplier and λ2 is the second Lagrange multiplier.

[0128] According to the previous text, when the crank motion law is given, that is, the motion law of θ1 is given, substituting it into equation (5), θ2 and θ3 can be obtained, and then performing differential operations, we can get: Given the rocker input torque M3, the crank drive torque M1 can be obtained according to equation group (8).

[0129] S3.2 Verify the correctness of the kinetic equation

[0130] To verify the correctness of the equations and results, Adams software was used to establish Figure 5 The crank rocker model is shown, and the rod length and mass are shown in Table 2.

[0131] Table 2 Verification model length and quality parameters

[0132]

[0133] Given a crank frequency of 7 Hz, i.e. a crank speed of 420 rpm, and a rocker input torque of a constant value M3 = 5 N·m and a sinusoidal value M3 = 5sin(2πft)N·m, calculate the crank drive torque M1. Figure 6 As shown, the two agree well, which verifies the correctness of the equation.

[0134] S4: Optimize the peak torque of the driving mechanism;

[0135] Optimize processes and implementation plans such as Figure 7 The specific optimization method is as follows:

[0136] S4.1 selects the peak torque as the optimal target and establishes the objective function;

[0137] The driving mechanism of a UAV is generally driven by a brushless motor, etc. The brushless motor is most sensitive to the size of the crank drive torque M1. In order to reduce the drive load of the brushless motor and solve the problem of drive mechanism jamming, it is necessary to use the peak value of the crank drive torque M1 as the optimization target and perform iterative optimization.

[0138] This optimization problem is a nonlinear programming problem with linear and nonlinear constraints, multiple variables, and nonlinear objective function. The objective function is:

[0139] min|M1| max (14)

[0140] S4.2 selects the length of each rod and the position angle of the actuator as decision variables;

[0141] The decision variables are:

[0142] X=[l1 l2 l3 l4θ 04 ] T (15)

[0143] Among them l i (i=1,2,3,4) is the length of crank, connecting rod, rocker and base (unit: mm), θ 04 is the actuator position angle (unit: deg).

[0144] S4.3 Establish a nonlinear programming mathematical model;

[0145] The mathematical expression of the nonlinear programming model of this optimization problem is shown in the following formula (16):

[0146] min|M1| max

[0147]

[0148] Where M1 is the crank driving torque, which can be obtained according to the dynamic equation; A′ is the inequality linear constraint matrix, X is the decision variable, c is the inequality nonlinear constraint matrix, and c eq is the equality nonlinear constraint matrix.

[0149] S4.4 Establish inequality linear constraints based on the crank rocker establishment conditions;

[0150] According to the formation conditions of the crank-rocker mechanism, the crank length is specified to be minimum, the base length is maximum, and the sum of the crank and base lengths is less than the sum of the connecting rod and rocker lengths. The inequality linear constraint matrix is:

[0151]

[0152] S4.5 Establish nonlinear constraints based on aerodynamic requirements

[0153] In order to meet the aerodynamic requirements, it is necessary to ensure that the actuator amplitude is equal to 70°, the median value of the actuator angle θ is limited to within ±5° of the horizontal plane, and the stroke speed ratio coefficient K is limited to between 0.9 and 1.1.

[0154] According to the actuator amplitude of 70°, the nonlinear constraint is:

[0155] c eq =θ max -θ min -70 (18)

[0156] In the formula, θ max is the maximum actuator angle, θ min is the minimum actuator angle.

[0157] The inequality nonlinear constraints are:

[0158]

[0159] In the formula, θ max is the maximum actuator angle, θ min is the minimum value of the actuator angle, and K is the travel speed ratio coefficient. In order to establish an intuitive connection with the mechanism angle, the angle unit here is described in degrees.

[0160] θ max ,θ min It can be determined based on the angular kinematics of the actuator.

[0161] Formula (19) limits the median value of the actuator angle θ to within ±5° of the horizontal plane, and at the same time limits the stroke speed ratio coefficient K to between 0.9 and 1.1.

[0162] S4.6 Optimization is performed in combination with aerodynamics;

[0163] The rocker is fixed to the actuator, and the movement of the drive mechanism is closely related to the movement of the actuator. The change of the drive mechanism movement will inevitably affect the aerodynamic force of the drone. The optimization of the dynamics of a single mechanism is easy to obtain a better peak torque result, but it may have an adverse effect on the aerodynamic force. Therefore, from the perspective of the entire drone, the mechanism is optimized in combination with the aerodynamic results to ensure that the peak torque is effectively reduced without much loss of aerodynamic force. The optimization process is carried out in combination with the aerodynamic force. Figure 8 shown.

[0164] The specific steps are:

[0165] S4.6.1 Given the initial values ​​of the lengths of the connecting rods and the position angles of the actuators

[0166] As shown in formula (15), given the initial values ​​of decision variables, including l i (i=1,2,3,4) Dimensions of crank, connecting rod, rocker, base, length (unit: mm) and θ 04 Actuator position angle (unit: deg).

[0167] S4.6.2 Substitute the kinematic model of the drive mechanism

[0168] Given a crank frequency of 7 Hz, that is, a crank speed of 420 rpm, substituting into equation (5), we can obtain θ2 and θ3. 04 , substituting into formula (3), the motion law of the actuator angle θ can be obtained.

[0169] S4.6.3 Determining the aerodynamic forces

[0170] According to the motion law of the θ actuator angle, the aerodynamic force can be obtained using the pneumatic calculation method (this method is a mature method and will not be described in detail in this article). The aerodynamic force is the force acting on the rocker.

[0171] S4.6.4 Obtain the rocker input torque M3

[0172] When the aerodynamic force of the drone reacts to the joystick, the input torque of the joystick can be obtained by multiplying the force and the lever arm. This solution is a basic mechanics method and will not be elaborated in this article.

[0173] Substitute S4.6.5 into the dynamic model of the drive mechanism and obtain the crank drive torque M1

[0174] According to the rocker input torque M3, substitute it into the dynamic equation group (8) to obtain the crank drive torque M1.

[0175] S4.6.6 Iterative optimization with peak torque as optimization target

[0176] The peak value of the crank drive torque M1 is taken as the optimization target, and iterative optimization is performed in combination with formula (16).

[0177] S4.6.7 obtains the optimization result (length of each connecting rod and position angle of the actuator)

[0178] According to formula (16), the optimization results are obtained by iterative optimization, including l i (i=1,2,3,4) Dimensions of crank, connecting rod, rocker, base, length (unit: mm) and θ 04 Actuator position angle (unit: deg).

[0179] S4.6.8 Verify that aerodynamic forces are reduced

[0180] Substitute the optimization results (lengths of each connecting rod and position angle of the actuator) into the kinematic model of the drive mechanism (S4.6.2) and obtain the aerodynamic force (S4.6.3) to verify whether the aerodynamic force is reduced. If it is reduced, re-enter the optimization process to carry out optimization. If it is not reduced and the aerodynamic conditions are met, the optimization is terminated.

[0181] In summary, by combining aerodynamics to conduct optimization, it is possible to ensure that the peak value of the crank drive torque is minimized without losing aerodynamics, thus meeting the needs of UAVs.

[0182] S4.7 Get the optimization results and analyze the optimization results

[0183] This paper uses the mature MATLAB nonlinear programming toolbox fmincon, which is suitable for solving nonlinear programming problems with nonlinear constraints. In the fmincon toolbox, the interior-point method is used for optimization. This algorithm is a local optimal algorithm. Byrd and Waltz proved the convergence and local optimality of this algorithm. This paper directly uses this algorithm to solve the problem.

[0184] The initial value of the iteration is:

[0185] X0 = [722122466.4] T (20)

[0186] The optimization iteration process is as follows Fig. 9 As shown:

[0187] The optimization results are:

[0188] X opt =[7.725.313.725.380.9] T(twenty one)

[0189] like Fig.10 As shown in the figure, after optimization, the peak torque of the drive has been greatly improved, the peak difference between the two peaks has been reduced, and the peak torque of the drive has been reduced from 2.47N·m to 1.59N·m, a reduction of nearly 36%. This makes the crank drive torque curve smoother, which is of great significance for solving the problem of drive mechanism jamming and reducing the load of brushless motors.

[0190] The above is only an implementation mode of the present invention. It should be pointed out that for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the technical principles of the present invention. These improvements and modifications should also be regarded as the scope of protection of the present invention.

Claims

1. A method for dynamic modeling and optimization of a UAV drive mechanism, characterized in that: The specific steps are as follows: Establish the UAV drive mechanism model: establish the coordinate system, the fuselage fixed coordinate system and the actuator angle; Analyze the kinematics of the drive mechanism: Take the length of each rod as a variable, analyze the changes in the performance parameters related to the drive mechanism, and provide qualitative rules for the design; Establish the dynamic model of the driving mechanism: establish the dynamic equation group and verify the correctness of the dynamic equation; Establish the objective function and optimize the peak torque of the driving mechanism.

2. The method for dynamic modeling and optimization of a UAV driving mechanism according to claim 1, characterized in that: In the establishment of the UAV drive mechanism model, the UAV drive mechanism is a crank rocker mechanism; the coordinate system AXY is defined as the fuselage fixed coordinate system. Looking at the fuselage from the nose perspective, the X-axis points to the left side of the fuselage, the Y-axis is perpendicular to the X-axis and upward, and the coordinate system AXY is located in the cross section perpendicular to the longitudinal axis of the fuselage, where Axy is the mechanism fixed coordinate system, the x-axis points from the crank fixed point A along the base to the rocker fixed point D, and the y-axis is perpendicular to the x-axis; θ is defined as the actuator angle, θ0 is the base installation angle, θ3 is the rocker angle, and θ4 is the actuator installation angle.

3. The method for dynamic modeling and optimization of the UAV driving mechanism according to claim 2, characterized in that: Analyze the kinematics of the drive mechanism and establish constraints: In addition to satisfying the conditions for the crank rocker mechanism to be established, the constraints that must be met are: Geometric constraints: Where l1 is the crank length, l2 is the connecting rod length, l3 is the rocker length, l4 is the base length, θ1 is the crank angle, θ2 is the connecting rod angle, and θ3 is the rocker angle.

4. The method for dynamic modeling and optimization of a UAV driving mechanism according to claim 2, characterized in that: In establishing the dynamic model of the driving mechanism, the dynamic equations of the driving mechanism are: Where M is the mass inertia matrix, L is the centrifugal moment matrix, Q is the sum of the external moment matrix W and the gravity moment matrix G, B is the constraint coefficient matrix, λ is the Lagrange multiplier matrix, θ1 is the crank angle, θ2 is the connecting rod angle, and θ3 is the rocker angle; The external moment matrix W is: In=[M1 0M3] T Where M1 is the crank drive torque, that is, the torque required to drive the motor to operate the mechanism; M3 is the rocker input torque, that is, when the mechanism drives the actuator to move, the torque of the drone's aerodynamic load reacting to the drive mechanism. The actuator is connected to the rocker, so it is called the rocker input torque.

5. The method for dynamic modeling and optimization of a UAV driving mechanism according to claim 4, characterized in that: In order to verify the correctness of the dynamic equations and results of the driving mechanism, the crank rocker model was established using Adams software. The crank frequency, i.e., crank speed, was given, and the rocker input torque was given as a constant value and a sinusoidal law, respectively. The crank driving torque was solved and the results were compared.

6. The method for dynamic modeling and optimization of a UAV driving mechanism according to claim 2, characterized in that: In optimizing the peak torque of the drive mechanism, the specific steps are: (1) Select peak torque as the optimal target and establish the objective function; (2) Select the length of each rod and the position angle of the actuator as the decision variables; (3) Establish a nonlinear programming mathematical model; (4) Establish inequality linear constraints based on the crank rocker establishment conditions; (5) Establish nonlinear constraints based on aerodynamic requirements; (6) Combine aerodynamics to find the optimal solution.

7. The method for dynamic modeling and optimization of a UAV driving mechanism according to claim 6, characterized in that: The peak value of the crank drive torque is selected as the optimization target, and the established objective function is: min|M1| max , where M1 is the crank drive torque.

8. The method for dynamic modeling and optimization of a UAV driving mechanism according to claim 7, characterized in that: The nonlinear programming model for the optimization problem is: my|M1| max Where M1 is the crank driving torque, which can be obtained according to the dynamic equation; A′ is the inequality linear constraint matrix, X is the decision variable, c is the inequality nonlinear constraint matrix, and c eq is the equality nonlinear constraint matrix.

9. The method for dynamic modeling and optimization of a UAV driving mechanism according to claim 8, characterized in that: Combined with the aerodynamic results, the mechanism is optimized. The specific process is as follows: Given the initial values ​​of the lengths of the connecting rods and the position angles of the actuators; Substitute the kinematic and dynamic models of the drive mechanism; then obtain the aerodynamic force, rocker input torque and crank drive torque; Iterative optimization is performed with the peak torque as the optimization target, and then the optimization results of the length dimensions of each rod of the mechanism and the position angle of the actuator are obtained; Aerodynamic force judgment: Substitute the optimized parameter results into the kinematic model of the drive mechanism to obtain the aerodynamic force, and verify whether the aerodynamic force is reduced. If it is reduced, re-enter the optimization process to carry out optimization. If it is not reduced, the aerodynamic conditions are met and the optimization is terminated.

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