Helicopter rotation landing safety trajectory rapid planning method and device

Abstract

The invention provides a helicopter rotation landing safety trajectory rapid planning method and device, and the method comprises the steps: 1, obtaining a non-linear rotation kinetic model of a rotation state according to the stress change caused by the stopping of an engine; 2, determining a state quantity and a control quantity according to the nonlinear autorotation dynamical model, setting a key objective function, and determining a flight constraint condition to obtain an autorotation landing optimization model; and 3, solving the autorotation landing optimization model to obtain a safe landing trajectory.

Description

Technical Field

[0001] The invention belongs to the field of helicopter flight control and relates to a method and a device for quickly planning a safe trajectory for helicopter autorotation landing. Background Art

[0002] When the helicopter engine stops during flight, it needs to enter autorotation flight to achieve a safe landing. Autorotation landing is the process of landing at a safe landing point under a series of complex constraints such as rotor speed, flight attitude, flight speed, and control amount. It requires the pilot to make continuous and accurate controls in sequence in a short period of time, and the flight load is extremely high. At this time, it is particularly important to quickly plan a safe autorotation landing trajectory, which can serve as a reference target for pilots to carry out autorotation flight control and improve the safety of autorotation landing.

[0003] At present, relevant universities have carried out research, combining the autorotation dynamics model to establish the optimal control problem of autorotation landing, set the objective function and constraints, and solve the safe autorotation landing trajectory.

[0004] The solution efficiency of the optimal control problem in the above research method is not high, and it takes a long time to solve the complex six-degree-of-freedom autorotation dynamics model, which can be used to analyze the autorotation landing characteristics. After the helicopter engine stops, it needs to perform autorotation control in a short time. Therefore, the above method cannot provide a safe trajectory for the pilot's reference in time, which does not meet the needs of on-board use. Summary of the invention

[0005] The present invention proposes a method for planning a safe trajectory for helicopter autorotation landing, which can quickly plan a safe landing trajectory according to the current flight state and landing point position after the engine is stopped, and serve as a reference target for the pilot's autorotation control.

[0006] In a first aspect, the present application provides a method for quickly planning a safe trajectory for autorotation landing of a helicopter, the method comprising:

[0007] Step 1: According to the force change caused by engine shutdown, the nonlinear autorotation dynamics model of the autorotation state is obtained;

[0008] Step 2: According to the nonlinear autorotation dynamics model, determine the state quantity and control quantity, set the key objective function, and determine the flight constraints to obtain the autorotation landing optimization model;

[0009] Step 3: Optimize the autorotation landing optimization model to obtain a safe landing trajectory.

[0010] Specifically, step 1 includes:

[0011] Step 11: Calculate the rotor anti-torque coefficient m according to the following formula k ;

[0012]

[0013] Where σ is the rotor solidity, C x is the blade airfoil drag coefficient, μ is the advance ratio, κ is the blade tip loss coefficient, a ∞ is the slope of the lift line of the airfoil, θ0 is the installation angle of the blade root, θ1 is the blade twist, v0 is the average induced speed of the rotor, λ0 is the inflow ratio, a0 is the rotor taper angle, and a 1s The chamfer after the rotor flaps, b 1s is the rotor flapping side chamfer, A1 is the lateral cyclic pitch change, and B1 is the longitudinal cyclic pitch change;

[0014] Step 12: According to the rotor anti-torque coefficient m k , determine the resultant moment M in the z direction of the body axis coordinate system Z ;

[0015] Step 13: According to the resultant moment M in the z direction of the body axis coordinate system Z Establish the nonlinear autorotation dynamics model of helicopter.

[0016] Specifically, step 12 includes:

[0017] According to the formula M k =m k ρ(ΩR) 2 πR 3 / 2 determines the rotor torque after power failure, where ρ is the atmospheric density, Ω is the rotor speed after power failure, and R is the rotor radius.

[0018] Rotor torque M k By summing the moments of the fuselage, horizontal tail, vertical tail and tail rotor, the resultant moment M in the z direction of the body axis coordinate system can be determined. Z .

[0019] Specifically, step 2 includes:

[0020] Step 21: Determine the state quantity X = [x, y, z, u, v, w, φ, θ, ψ, p, q, r, Ω] T , control quantity U=[δ b ,δ a ,δ c ,δ r ] T , where x is the longitudinal position, y is the lateral position, z is the vertical position, u is the longitudinal velocity, v is the lateral velocity, w is the vertical velocity, φ is the tilt angle, θ is the pitch angle, ψ is the heading angle, p is the tilt angular velocity, q is the pitch angular velocity, r is the heading angular velocity, δ b is the longitudinal periodic pitch, δ a is the lateral periodic variation, δ cis the total distance, δ r is the tail rotor pitch;

[0021] Step 22: Set the flight time objective function J1 = t f , and the manipulated variable objective function Among them, t f is the end time of rotation;

[0022] Step 23: Separate process constraints, terminal constraints and control constraints.

[0023] Specifically, the process constraints are flight constraints for determining the position, velocity, attitude, angular velocity, and rotor speed states during the autorotation landing process;

[0024] The terminal constraints are the constraints on landing position, landing speed and landing attitude;

[0025] Control constraints are the range of control quantities determined based on the manipulation range and authority.

[0026] Specifically, step 3 includes:

[0027] Step 31: Using the formula The time range t∈[t0,t f ], converted to the time domain τ∈[-1,1];

[0028] Step 32: Discretize the state quantity and control quantity to obtain the discretized autorotation landing optimization model:

[0029]

[0030] Among them, n is the number of discrete points, D is the differential coefficient matrix, f is the nonlinear autodynamic model, and w is the Gaussian weight coefficient matrix.

[0031] Step 33: Solve the discretized autorotation landing optimization model, select the preset number of Gaussian nodes, and use the SNOPT solver to obtain a safe landing trajectory.

[0032] Among them, the preset number of Gaussian nodes is 8.

[0033] In a second aspect, the present application provides a device for quickly planning a safe trajectory of a helicopter autorotation landing, the device comprising a nonlinear autorotation dynamics model building unit, an autorotation landing optimization model building unit and a solving unit, wherein:

[0034] A nonlinear autorotation dynamics model building unit is used to obtain a nonlinear autorotation dynamics model of the autorotation state according to the force change caused by the engine shutdown;

[0035] An autorotation landing optimization model building unit is used to determine the state quantity and control quantity, set the key objective function, and determine the flight constraint conditions according to the nonlinear autorotation dynamics model to obtain the autorotation landing optimization model;

[0036] The solving unit is used to optimize the autorotation landing optimization model to obtain a safe landing trajectory.

[0037] Specifically, the nonlinear rotation dynamics model building unit is specifically used for:

[0038] According to the following formula, calculate the rotor anti-torque coefficient m k ;

[0039]

[0040] Where σ is the rotor solidity, C x is the blade airfoil drag coefficient, μ is the advance ratio, κ is the blade tip loss coefficient, a ∞ is the slope of the lift line of the airfoil, θ0 is the installation angle of the blade root, θ1 is the blade twist, v0 is the average induced speed of the rotor, λ0 is the inflow ratio, a0 is the rotor taper angle, and a 1s The chamfer after the rotor flaps, b 1s is the rotor flapping side chamfer, A1 is the lateral cyclic pitch change, and B1 is the longitudinal cyclic pitch change;

[0041] According to the rotor anti-torque coefficient m k , determine the resultant moment M in the z direction of the body axis coordinate system Z ;

[0042] According to the body axis coordinate system z direction the resultant moment M Z Establish the nonlinear autorotation dynamics model of helicopter.

[0043] In summary, the present invention provides a method and device for quickly planning a safe trajectory for autorotation landing of a helicopter. The flight constraints, optimal control process, safe trajectory planning, and other issues in the process of autorotation landing after the helicopter engine is stopped are analyzed, and a method for quickly planning a landing trajectory suitable for multiple constraints is designed. Simulation results show that the method for planning a safe trajectory for autorotation landing flight designed by the present invention can quickly plan an autorotation flight trajectory that meets the constraint conditions after the engine is stopped, and achieve a safe landing at a designated landing point. BRIEF DESCRIPTION OF THE DRAWINGS

[0044] Figure 1 A schematic diagram of a method for quickly planning a safe trajectory for autorotation landing of a helicopter provided in this application;

[0045] Figure 2 Planning trajectory for safe autorotation landing provided for this application;

[0046] Figure 3 The rotor speed curve provided for this application;

[0047] Figure 4 Longitudinal velocity profile provided for this application;

[0048] Figure 5 The descent rate curve provided for this application;

[0049] Figure 6 The tilt angle curve provided for this application;

[0050] Figure 7 The pitch angle curve provided for this application;

[0051] Figure 8 The heading angle curve provided for this application. DETAILED DESCRIPTION

[0052] Embodiment 1

[0053] The present application provides a method for quickly planning a safe trajectory for autorotation landing of a helicopter, the method comprising:

[0054] Step 1: According to the force change caused by engine shutdown, the nonlinear autorotation dynamics model of the autorotation state is obtained;

[0055] Specifically, step 1 includes:

[0056] Step 11: Calculate the rotor anti-torque coefficient m according to the following formula k ;

[0057]

[0058] Where σ is the rotor solidity, C x is the blade airfoil drag coefficient, μ is the advance ratio, κ is the blade tip loss coefficient, a ∞ is the slope of the lift line of the airfoil, θ0 is the installation angle of the blade root, θ1 is the blade twist, v0 is the average induced speed of the rotor, λ0 is the inflow ratio, a0 is the rotor taper angle, and a 1s The chamfer after the rotor flaps, b 1s is the rotor flapping side chamfer, A1 is the lateral cyclic pitch change, and B1 is the longitudinal cyclic pitch change.

[0059] Step 12: According to the rotor anti-torque coefficient m k , determine the resultant moment M in the z direction of the body axis coordinate system Z ;

[0060] Specifically, step 12 includes:

[0061] According to the formula M k =m k ρ(ΩR) 2πR 3 / 2 determines the rotor torque after power failure, where ρ is the atmospheric density, Ω is the rotor speed after power failure, and R is the rotor radius.

[0062] Rotor torque M k By summing the moments of the fuselage, horizontal tail, vertical tail and tail rotor, the resultant moment M in the z direction of the body axis coordinate system can be determined. Z .

[0063] Step 13: According to the resultant moment M in the z direction of the body axis coordinate system Z Establish the nonlinear autorotation dynamics model of helicopter.

[0064] Step 2: According to the nonlinear autorotation dynamics model, determine the state quantity and control quantity, set the key objective function, and determine the flight constraints to obtain the autorotation landing optimization model;

[0065] Specifically, step 2 includes:

[0066] Step 21: Determine the state quantity X = [x, y, z, u, v, w, φ, θ, ψ, p, q, r, Ω] T , control quantity U=[δ b ,δ a ,δ c ,δ r ] T , where x is the longitudinal position, y is the lateral position, z is the vertical position, u is the longitudinal velocity, v is the lateral velocity, w is the vertical velocity, φ is the tilt angle, θ is the pitch angle, ψ is the heading angle, p is the tilt angular velocity, q is the pitch angular velocity, r is the heading angular velocity, δ b is the longitudinal periodic pitch, δ a is the lateral periodic variation, δ c is the total distance, δ r is the tail rotor pitch;

[0067] Step 22: Set the flight time objective function J1 = t f , and the manipulated variable objective function Among them, t f is the end time of rotation;

[0068] Step 23: Separate process constraints, terminal constraints and control constraints.

[0069] Specifically, the process constraints are flight constraints that determine the position, speed, attitude, angular velocity and rotor speed status during the autorotation landing process; the terminal constraints are constraints on the landing position, landing speed and landing attitude; and the control constraints are the control quantity range determined according to the control range and authority.

[0070] Step 3: Optimize the autorotation landing optimization model to obtain a safe landing trajectory.

[0071] Specifically, step 3 includes:

[0072] Step 31: Using the formula The time range t∈[t0,t f ], converted to the time domain τ∈[-1,1];

[0073] Step 32: Discretize the state quantity and control quantity to obtain the discretized autorotation landing optimization model:

[0074]

[0075] Among them, n is the number of discrete points, D is the differential coefficient matrix, f is the nonlinear autodynamic model, and w is the Gaussian weight coefficient matrix.

[0076] Step 33: Solve the discretized autorotation landing optimization model, select the preset number of Gaussian nodes, and use the SNOPT solver to obtain a safe landing trajectory.

[0077] Among them, the preset number of Gaussian nodes is 8.

[0078] Embodiment 2

[0079] The present invention mainly solves the problem of quickly planning a safe landing trajectory after the helicopter engine stops. Based on the simplified nonlinear autorotation dynamics model, the optimal control problem of autorotation landing is constructed, key objective functions and flight constraints are set, and the safe landing trajectory is obtained by solving the Gaussian pseudo-spectral optimization method to achieve high-efficiency trajectory planning. The overall solution framework is as follows Figure 1 shown.

[0080] (1) Nonlinear rotational dynamics model

[0081] The helicopter autorotation landing process includes entering autorotation, stable descent, and pulling up to land. The flight characteristics of each stage are significantly different, and the linear model cannot accurately reflect the dynamic change characteristics. The present invention adopts a simplified nonlinear autorotation dynamics model to carry out analysis and design, ensuring the accuracy of the model while maximizing the calculation efficiency.

[0082] a. First, establish a six-degree-of-freedom nonlinear model of the helicopter in normal state. In the body axis coordinate system, it can be expressed as:

[0083]

[0084] Where m is the mass of the helicopter, g is the gravitational acceleration. u, v and w are the velocity components of the body axis system. p, q and r are the angular velocities around the three axes of the body axis system. φ, θ and ψ are the tilt angle, pitch angle and yaw angle. F x 、Fy 、F z is the resultant external force on the three channels. x 、M y 、M z is the resultant torque of the external force.

[0085] The external force received by the helicopter during autorotation is composed of the aerodynamic forces and moments of the rotor, fuselage, horizontal tail, vertical tail and tail rotor. The aerodynamic forces of the fuselage, horizontal tail and vertical tail are calculated by aerodynamic parameters obtained from wind tunnel data.

[0086] The rotor and tail rotor are calculated using the blade element theory. To improve the computational efficiency of the optimization algorithm, the pull coefficient, lateral force coefficient, and moment coefficient are all calculated in analytical form using simplified integrals based on the blade element theory.

[0087] The control variables are the rotor longitudinal cyclic pitch, lateral cyclic pitch, collective pitch and tail rotor pitch. The helicopter flight is controlled by changing the components of the aerodynamic force on the three body axes.

[0088] b. By introducing the force changes caused by engine shutdown into the normal state nonlinear model, a nonlinear dynamic model of the rotation state can be obtained.

[0089] After the engine stops, the reverse torque of the rotor rotation on the fuselage will also disappear. Without the effect of engine output power, the rotor speed change equation is:

[0090]

[0091] Where, Ω is the rotor speed, M k is the aerodynamic torque on the rotor, J MR is the rotor moment of inertia. The aerodynamic torque coefficient is:

[0092]

[0093] Among them, σ is the rotor solidity, Cx is the blade airfoil drag coefficient, μ is the advance ratio, κ is the blade tip loss coefficient, and a ∞ is the slope of the lift line of the airfoil, θ0 is the installation angle of the blade root, θ1 is the blade twist, v0 is the average induced speed of the rotor, λ0 is the inflow ratio, a0 is the rotor taper angle, and a 1s The chamfer after the rotor flaps, b 1s is the rotor flapping side chamfer, A1 is the lateral cyclic pitch change, and B1 is the longitudinal cyclic pitch change.

[0094] (2) Autorotation landing optimization model

[0095] The helicopter autorotation landing process needs to land in a safe position under a series of flight restrictions, which can be transformed into a nonlinear autorotation landing optimization model with constraints. The specific steps are as follows:

[0096] a. Determine the optimized state quantity and control quantity

[0097] The nonlinear dynamic model of rotation can be expressed as

[0098]

[0099] The state quantity X=[x,y,z,u,v,w,φ,θ,ψ,p,q,r,Ω] T , control quantity U=[δ b ,δ a ,δ c ,δ r ] T .

[0100] The autorotation landing process can be described as follows: the helicopter starts from the state X0 when the engine fails, and by adjusting the control quantity U, it finally reaches the state Xf and achieves a safe landing under certain flight constraints and control conditions.

[0101] b. Set the key objective function

[0102] The objective function is the control effect that needs to be achieved in the optimal control problem, which will directly affect the optimization result. The usual practice is to select a weighted combination of flight time, control amount, landing attitude, landing speed, etc. as the objective function, but this will affect the solution efficiency.

[0103] Based on actual engineering needs, the present invention only selects the most concerned flight time and control amount as the objective function. Specifically:

[0104] min J1=t f

[0105]

[0106] Among them, tf is the end time of autorotation. The optimization index is to minimize the autorotation time or minimize the total amount of operation. When the helicopter is autorotating, the rotor transmission mechanism is disconnected from the engine, and the power available for various equipment on the aircraft is limited. In this case, it is necessary to optimize the autorotation time and complete the landing as soon as possible. Minimizing the total amount of operation can reduce the pilot's operating load.

[0107] In the present invention, the landing attitude and speed are used as constraints, and they only need to be within a certain range without optimization, thereby improving the efficiency of solving the optimal control problem and meeting the actual needs to the greatest extent.

[0108] c. Determine flight constraints

[0109] The constraints of the optimal control problem of autorotation landing mainly include initial value constraints, process constraints, terminal constraints and control constraints.

[0110] The initial value constraint is the flight state of the helicopter when the engine stops and enters autorotation, that is, X(τ0)=X0.

[0111] The process constraints are mainly the limits of the position, speed, attitude, angular velocity and rotor speed during the autorotation landing process, which can be expressed in the following form:

[0112] x min ≤x(t)≤x max ,y min ≤y(t)≤y max ,z min ≤z(t)≤z max

[0113] u min ≤u(t)≤u max ,v min ≤v(t)≤v max ,w min ≤w(t)≤w max

[0114] φ min ≤φ(t)≤φ max ,θ min ≤θ(t)≤θ max ,ψ min ≤ψ(t)≤ψ max ,

[0115] p min ≤p(t)≤p max ,q min ≤q(t)≤q max ,r min ≤r(t)≤r max

[0116] Ω min ≤Ω(t)≤Ω max

[0117] The terminal constraints are the landing position, landing speed and landing attitude limits, which are expressed in the following form:

[0118] x fmin ≤x(t f )≤x fmax ,y fmin ≤y(t f )≤y fmax ,z fmin ≤z(t f )≤z fmax

[0119] u fmin ≤u(t f)≤u fmax ,v fmin ≤v(t f )≤v fmax ,w fmin ≤w(t f )≤w fmax

[0120] φ fmin ≤φ(t f )≤φ fmax ,θ fmin ≤θ(t f )≤θ fmax ,ψ fmin ≤ψ(t f )≤ψ fmax ,

[0121] The control constraint is the control range determined by the manipulation range and authority, expressed as:

[0122] δ bmin ≤δ b (t)≤δ bmax ,δ amin ≤δ a (t)≤δ amax

[0123] δ cmin ≤δ c (t)≤δ cmax ,δ rmin ≤δ r (t)≤δ rmax

[0124] According to the above steps, the helicopter autorotation landing process is converted into an autorotation landing optimization model in mathematical form.

[0125] (3) Gaussian pseudo-spectral method to solve the autorotation landing optimization model

[0126] The above problem is a continuous autorotation landing optimization model. The present invention uses the Gaussian pseudo-spectral method to optimize and solve it, which can have good solution accuracy and high calculation efficiency.

[0127] The control quantity and state quantity are approximated by selecting a series of Gaussian points to construct Lagrange interpolation polynomials, so that the autorotation landing optimization model in the continuous time domain is rewritten as a discretized nonlinear programming problem, which is convenient for numerical solution. The specific steps are as follows:

[0128] a. Time domain conversion

[0129] The time range of the autorotation landing process is t∈[t0,t f], the Gaussian pseudospectral method stipulates that the problem is solved in the time domain τ∈[-1,1], and the optimal control problem needs to be transformed into the following time domain:

[0130]

[0131] b. Discretization of state and control quantities

[0132] Select the number of Gaussian nodes as n, then we can get each node τ1,τ2,...τ n Combined with the Lagrange interpolation polynomial, the state and control quantities at any time in the autorotation landing problem are approximated by Gaussian nodes:

[0133]

[0134] Among them, L l is the Lagrange interpolation basis function, l=1,2,…n.

[0135] c. Discretized autorotation landing optimization model

[0136] The discretized state quantity is differentiated and then substituted into the rotational dynamics equation to obtain the discretized equation algebraic constraint equation of the rotational dynamics:

[0137]

[0138] Where D il is the differential coefficient, which can be obtained by differentiating the Lagrange interpolation basis function, and its matrix is ​​represented by D.

[0139] The above discretization process parametrically approximates the dynamic equation at the Gaussian point. The state at the two endpoints needs to be constrained by the Gaussian integral formula, which is:

[0140]

[0141] Where w i is the Gaussian weight coefficient, which can be expressed as w in matrix form.

[0142] In summary, the discretized autorotation landing optimization model can be obtained:

[0143]

[0144] stDX(τ)-(t f -t0)f(X(τ),U(τ)) / 2=0

[0145] X(τ f )-X(τ0)-w(t f -t0)f(X(τ),U(τ)) / 2=0

[0146] X(τ0)=X0

[0147] d. Solve for a safe landing trajectory

[0148] The SNOPT solver is used to numerically solve the above discrete form of optimization problem to obtain a safe autorotation landing trajectory that meets the landing point and flight constraints.

[0149] The key points of the present invention are:

[0150] a) Based on the nonlinear dynamic model of the normal flight state of the helicopter, the equations of rotor force and speed change after the engine is shut down are introduced. The aerodynamic force calculation adopts the analytical form obtained by simplifying the integral based on the blade element theory to form a simplified nonlinear autorotation dynamic model, which can improve the calculation efficiency of the subsequent optimal control problem.

[0151] b) Simplify the setting of the objective function of the optimal control problem, and select the flight time and control amount that are of most concern in engineering as the objective function. Taking the landing speed, attitude, etc. as constraints and not performing optimization processing can reduce the complexity of the optimization calculation. While meeting engineering requirements, it can also maximize the optimization solution speed.

[0152] c) The Gaussian pseudo-spectral method is used to solve the nonlinear autorotation landing trajectory optimization problem. The appropriate number of Gaussian nodes is selected to ensure high solution efficiency while ensuring calculation accuracy.

[0153] A certain type of manned helicopter is selected to carry out the simulation of autorotation landing safe flight trajectory planning. The initial state of the helicopter entering autorotation flight is: altitude 450m, speed 100km / h, pitch angle 7°, roll angle 0.8°, heading angle 0°. The selected landing point position is 900m longitudinally and 180m laterally relative to the initial position. The terminal constraint condition is 0≤u(t f )≤15,-3≤v(t f )≤3,0≤w(t f )≤4,-10≤φ(t f )≤10,-5≤θ(t f )≤10,-40≤ψ(t f )≤40. The trajectory planning solution takes 2.6s, and the optimization results are as follows Figure 2 As shown in the figure, the autorotation landing flight process takes 37.2 seconds. Figure 3 As shown in the figure, the rotor speed gradually decreases after the engine stops, gradually increases as the collective pitch is rapidly lowered, and is in a stable state during the stable descent. Figure 4 and Figure 5 As shown, the maximum descent rate is 14.1m / s; Figure 6 , Figure 7 and Figure 8As shown, the flight attitude angle satisfies the terminal constraint, and the helicopter can achieve a safe autorotation landing at the designated landing point.

[0154] The present invention analyzes the flight constraints, optimal control process, and safe trajectory planning during the autorotation landing process after the helicopter engine is shut down, and designs a fast landing trajectory planning method suitable for multiple constraints. Simulation results show that the autorotation landing flight safety trajectory planning method designed by the present invention can quickly plan an autorotation flight trajectory that meets the constraint conditions after the engine is shut down, and achieve a safe landing at a designated landing point.

Claims

1. A method for quickly planning a safe trajectory for helicopter autorotation landing, characterized in that: The method comprises: Step 1: According to the force change caused by engine shutdown, the nonlinear autorotation dynamics model of the autorotation state is obtained; Step 2: According to the nonlinear autorotation dynamics model, determine the state quantity and control quantity, set the key objective function, and determine the flight constraints to obtain the autorotation landing optimization model; Step 3: Solve the autorotation landing optimization model to obtain a safe landing trajectory.

2. The method according to claim 1, characterized in that: Step 1 includes: Step 11: Calculate the rotor anti-torque coefficient m according to the following formula k ; Where σ is the rotor solidity, C x is the blade airfoil drag coefficient, μ is the advance ratio, κ is the blade tip loss coefficient, a ∞ is the slope of the lift line of the airfoil, θ0 is the installation angle of the blade root, θ1 is the blade twist, v0 is the average induced speed of the rotor, λ0 is the inflow ratio, a0 is the rotor taper angle, and a 1s The chamfer after the rotor flaps, b 1s is the rotor flapping side chamfer, A1 is the lateral cyclic pitch change, and B1 is the longitudinal cyclic pitch change; Step 12: According to the rotor anti-torque coefficient m k , determine the resultant moment M in the z direction of the body axis coordinate system Z ; Step 13: According to the resultant moment M in the z direction of the body axis coordinate system Z Establish a nonlinear autorotation dynamics model of helicopter.

3. The method according to claim 2, characterized in that Step 12 includes: According to the formula M k =m k ρ(ΩR) 2 πR 3 / 2 determines the rotor torque after power failure, where ρ is the atmospheric density, Ω is the rotor speed after power failure, and R is the rotor radius. Rotor torque M k By summing the moments of the fuselage, horizontal tail, vertical tail and tail rotor, the resultant moment M in the z direction of the body axis coordinate system can be determined. Z .

4. The method according to claim 1, characterized in that: Step 2 includes: Step 21: Determine the state quantity X = [x, y, z, u, v, w, φ, θ, ψ, p, q, r, Ω] T , control quantity U=[δ b ,δ a ,δ c ,δ r ] T , where x is the longitudinal position, y is the lateral position, z is the vertical position, u is the longitudinal velocity, v is the lateral velocity, w is the vertical velocity, φ is the tilt angle, θ is the pitch angle, ψ is the heading angle, p is the tilt angular velocity, q is the pitch angular velocity, r is the heading angular velocity, δ b is the longitudinal periodic pitch, δ a is the lateral periodic variation, δ c is the total distance, δ r is the tail rotor pitch. Step 22: Set the flight time objective function J1 = t f , and the manipulated variable objective function Among them, t f The rotation end time. Step 23: Separate process constraints, terminal constraints and control constraints.

5. The method according to claim 4, characterized in that The process constraints are flight constraints that determine the position, velocity, attitude, angular velocity and rotor speed during the autorotation landing process; The terminal constraints are the constraints on landing position, landing speed and landing attitude; Control constraints are the range of control quantities determined based on the manipulation range and authority.

6. The method according to claim 1, characterized in that Step 3 includes: Step 31: Using the formula The time range t∈[t0,t f ], converted to the time domain τ∈[-1,1]; Step 32: Discretize the state quantity and control quantity to obtain the discretized autorotation landing optimization model: Among them, n is the number of discrete points, D is the differential coefficient matrix, f is the nonlinear autodynamic model, and w is the Gaussian weight coefficient matrix. Step 33: Solve the discretized autorotation landing optimization model, select the preset number of Gaussian nodes, and use the SNOPT solver to obtain a safe landing trajectory. Among them, the preset number of Gaussian nodes is 8.

7. A device for quickly planning a safe trajectory for helicopter autorotation landing, characterized in that: The device comprises a nonlinear autorotation dynamics model building unit, an autorotation landing optimization model building unit and a solving unit, wherein: A nonlinear autorotation dynamics model building unit is used to obtain a nonlinear autorotation dynamics model of the autorotation state according to the force change caused by the engine shutdown; An autorotation landing optimization model building unit is used to determine the state quantity and control quantity, set the key objective function, and determine the flight constraint conditions according to the nonlinear autorotation dynamics model to obtain the autorotation landing optimization model; The solving unit is used to solve the autorotation landing optimization model to obtain a safe landing trajectory.

8. The device according to claim 7, characterized in that The nonlinear rotation dynamics model building unit is specifically used for: According to the following formula, calculate the rotor anti-torque coefficient m k ; Where σ is the rotor solidity, C x is the blade airfoil drag coefficient, μ is the advance ratio, κ is the blade tip loss coefficient, a ∞ is the slope of the lift line of the airfoil, θ0 is the installation angle of the blade root, θ1 is the blade twist, v0 is the average induced speed of the rotor, λ0 is the inflow ratio, a0 is the rotor taper angle, and a 1s The chamfer after the rotor flaps, b 1s is the rotor flapping side chamfer, A1 is the lateral cyclic pitch change, and B1 is the longitudinal cyclic pitch change; According to the rotor anti-torque coefficient m k , determine the resultant moment M in the z direction of the body axis coordinate system Z ; According to the body axis coordinate system z direction the resultant moment M Z Establish a nonlinear autorotation dynamics model of helicopter.

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