Terminal Sliding Mode Control Method for Fixed-Wing UAV Position Tracking with Deviation Constraints

Abstract

The invention discloses a terminal sliding mode control method under the constraint of the position tracking deviation of a fixed-wing unmanned aerial vehicle, which is used to solve the problem that the flight control system of the fixed-wing unmanned aerial vehicle is affected by nonlinear and uncertain disturbances, resulting in a decrease in the flight position tracking accuracy and even the instability of the overall system of the fixed-wing unmanned aerial vehicle. The control method first establishes an outer-loop position tracking control model of the fixed-wing unmanned aerial vehicle for the kinematic and three-degree-of-freedom dynamic models of the fixed-wing unmanned aerial vehicle in the inertial coordinate system, considering the uncertain disturbances. Secondly, a finite-time constraint controller is designed based on a preset performance function and a fast non-singular terminal sliding mode surface, and an adaptive disturbance observer is used to estimate the uncertain disturbances in the model to improve the outer-loop constraint control accuracy of the fixed-wing unmanned aerial vehicle. Finally, the stability of the overall closed-loop system is proved. The invention is used for the terminal sliding mode constraint control under the position tracking deviation of the fixed-wing unmanned aerial vehicle.

Description

Technical Field

[0001] The present invention relates to a terminal sliding mode control method for position tracking deviation constraint of a fixed-wing unmanned aerial vehicle, belonging to the field of aircraft constraint control. Technical Background

[0002] The intelligent unmanned system is the product of the combination of artificial intelligence and unmanned systems, and has developed rapidly in the past decade. As the terminal of artificial intelligence, the unmanned system will play a more and more extensive role. Among them, the unmanned aerial vehicle (UAV) is a typical autonomous unmanned system, which plays a very important role in both military and civilian fields. At present, UAVs are widely used in aerial photography, plant protection, environmental monitoring, map surveying and mapping, as well as surveillance and reconnaissance, ground strike and electronic countermeasure, etc. However, most of the current UAV technologies stay in the stage of stable flight, and can only fly under limited roll and pitch attitudes, unable to exert the maneuverability of UAVs. With the expansion of the application scope and the competition in the military field, maneuverable flight has become the key point of the future development of UAV technology. With the improvement of the mission requirements of aircraft and the complexity of the aircraft's own design, higher requirements are put forward for the entire control system. In recent years, the research on the software and hardware of unmanned systems has developed rapidly. The development of flight control has experienced classical control and modern control, and many breakthroughs have been made, but it still cannot meet the complex mission requirements. The improvement of sensors and the development of intelligent control bring new possibilities, and breakthroughs are expected to be made in autonomous maneuverable flight and the control of complex systems. McGill University in Canada has achieved vertical hovering and blade stunt simulation flight through precise wind tunnel modeling, attitude control (considering the force model), position control, and thrust control.

[0003] Due to the high aerodynamic efficiency of fixed-wing aircraft, they have long endurance and a large range of activities. They are particularly outstanding in large-scale monitoring, especially in forest fire prevention. At the same time, in some special tasks, some fixed-wing UAVs need to fly in complex environments such as urban buildings and woods. Maneuvering flight enables UAVs to quickly change their posture and position in complex environments, which can greatly improve the survivability of UAVs. However, factors such as complex and changing mission environments, uncertain parameter disturbances, and multi-state constraints bring a series of control problems that need to be solved for autonomous flight of UAVs. Due to the physical limitations of mechanical manufacturing and actuators, if the relevant physical constraints are not considered in the control design of the UAV flight system, the violation of constraints during the execution of the flight mission based on the unconstrained control scheme may have an adverse effect on the system performance. The position tracking control of fixed-wing UAVs requires the UAV to track any specified flight route as much as possible to complete the flight mission. Completing the convergence of tracking deviation within a limited time is a necessary means to ensure the safe and stable control of drones. Constraining the tracking deviation within a pre-set range can ensure the accuracy of the drone's outer loop control, its dynamic performance and overall stability, and enable drones to fully demonstrate their original maneuverable and flexible performance advantages while completing complex tasks. This has important practical significance for the safe flight of fixed-wing drones. Existing nonlinear system constraint control schemes have achieved many results, but there are still the following shortcomings:

[0004] 1. Most of the existing constraint control schemes require the steady-state performance of nonlinear systems to meet certain indicators. There are few technical means for the rapid dynamic convergence of constrained nonlinear systems. At the same time, most of them are robust forms of control, which are very conservative. There are relatively few constraint controls for the outer loop position tracking deviation of fixed-wing UAVs.

[0005] 2. Currently, most fixed-wing UAV outer loop position tracking deviation constraint control laws rarely perform bounded estimation of disturbances and modeling uncertainties at the same time, which may lead to unsatisfactory control accuracy and constraint performance, and cannot guarantee the boundedness and engineering feasibility of the control signal. Summary of the invention

[0006] Purpose of the Invention

[0007] In order to solve the above technical problems, the purpose of the present invention is to provide a terminal sliding mode control method for a fixed-wing UAV under position tracking deviation constraints, so as to ensure that the fixed-wing UAV tracks the expected position signal under the influence of external disturbances while constraining the tracking deviation within a predetermined constraint range within a limited time.

[0008] Technical Solution

[0009] In order to achieve the above object, the present invention adopts the following technical solutions:

[0010] The present invention is a terminal sliding mode control method for a fixed-wing unmanned aerial vehicle (UAV) under the constraint of position tracking deviation, and the method includes the following steps:

[0011] Step 1: Establish a three-degree-of-freedom dynamic model of the fixed-wing UAV;

[0012] Step 2: Design a finite-time constraint controller based on a preset performance function and a fast non-singular terminal sliding mode surface, and use an adaptive disturbance observer to estimate the uncertain disturbances in the model to improve the outer-loop constraint control accuracy of the fixed-wing UAV;

[0013] Step 3: Use the output result of the finite-time constraint controller as a control input signal to achieve terminal sliding mode control of the fixed-wing UAV under the constraint of position tracking deviation.

[0014] Furthermore, the specific process of Step 1 includes the following:

[0015] Step 1.1: Define the position of the UAV in the three directions of the X-axis, Y-axis, and H-axis of the inertial coordinate system as P = [x, y, h], and establish a three-degree-of-freedom kinematic model of the fixed-wing UAV T ,

[0016]

[0017] where V is the flight airspeed of the UAV, γ and χ are the flight path inclination angle and flight path azimuth angle of the UAV, and establish a three-degree-of-freedom particle model of the UAV:

[0018]

[0019] where m is the mass of the UAV, g is the acceleration due to gravity, T e and Df are the engine thrust and drag, φ is the roll angle, n is the load factor, i.e., the ratio of lift to weight, and gncosφ and gnsinφ respectively represent the pitch acceleration and yaw acceleration of the fixed-wing UAV; D = [d t , d y , d p T , d t , d y , d p are respectively the uncertain disturbances existing in the three parameters V, χ, and γ in the model; introduce the pseudo-control quantity

[0020] U = [u t , u y , u p T (3) where each element u t , u​​y and u p The relationships with n, φ, and T are respectively u y = gnsinφ and u p = gncosφ;

[0021] By differentiating Equation (1), we obtain

[0022]

[0023] where the rotation matrix R is

[0024]

[0025] By substituting Equation (2) into Equation (4), we get

[0026]

[0027] Rewrite the UAV dynamics model as

[0028]

[0029] where G = [0, 0, -g] T .

[0030] Furthermore, Step 2 specifically includes the following process:

[0031] Step 2.1 Define the position tracking deviation P of the fixed-wing UAV e = P - P d , where P d = [x d , y d , z d T are the desired position commands of the UAV in the three directions of the X-axis, Y-axis, and H-axis respectively. Then the position tracking deviation constraint is expressed as

[0032]

[0033] where i represents each element in the above 3D vector respectively, k i and are positive constants, ε i (t) is a smooth decreasing function

[0034]

[0035] where the initial value of the function The final value satisfies and ω > 0 is the convergence rate of the ε i (t) function. Select relevant parameters k i ​and such that the tracking deviation P ei is constrained within ;

[0036] Then the position tracking deviation constraint inequality (8) is converted to

[0037] P ei = ε i Ω(E i ) (10) where Ω(·) is a smooth increasing function and has the following properties:

[0038] ◆ Ω(E i ) is a bounded function that makes hold;

[0039] ◆ and

[0040] ◆

[0041] where the position tracking deviation constraint function is expressed as

[0042]

[0043] where

[0044] is obtained by differentiating equation (11)

[0045]

[0046] where then

[0047]

[0048] is obtained by differentiating (12)

[0049]

[0050] Step 2.2 Select the fast non-singular terminal sliding mode surface according to the conversion function of the position tracking error constraint as

[0051]

[0052] where C 1 and C 2 are positive definite diagonal matrices, and σ(E) = [σ(E 1 ), σ(E 2 ), σ(E 3 )] is expressed as

[0053]

[0054] Among them 0 < α = α 1 / α 2 <1 and α 1 and α 2 are positive odd numbers, and where e s is an arbitrarily small positive constant.

[0055] Deriving (16) gives

[0056]

[0057] Then, the derivative of equation (15), which is the fast non - singular terminal sliding mode surface, is

[0058]

[0059] Since assuming that the external uncertainty disturbance D is bounded and continuously differentiable, and satisfies ||D|| 2 ≤ d 1 、 where d 1 and d 2 are unknown upper bounds.

[0060] Furthermore, the specific process of step three includes the following:

[0061] Design the pseudo - control quantity of the position tracking deviation constraint controller based on the fast non - singular terminal sliding mode as

[0062]

[0063] where m 1 , n 1 are positive definite diagonal matrices to be designed, 0 < τ < 1, h > 0 is a positive constant, and is the estimated value of the disturbance upper bound d1, and its adaptation law is

[0064]

[0065] The beneficial effects of the present invention are as follows:

[0066] (1) The present invention considers the position tracking deviation constraint control problem of a fixed - wing UAV in the presence of uncertainty disturbances and modeling uncertainties. Based on the preset performance control theory and adaptive disturbance estimation technology, the designed finite - time constraint control scheme not only ensures the stable flight of the fixed - wing UAV under uncertainty disturbances, but also enables the outer - loop position tracking deviation of the fixed - wing UAV to be limited within a pre - specified constraint range in finite time;

[0067] (2) In the control design, a fast non-singular terminal sliding mode control technology with finite-time convergence characteristics is adopted, that is, a non-linear function is introduced in the design of the sliding hyperplane, so that the position tracking deviation on the sliding surface can converge within a finite time, ensuring the dynamic performance, i.e., rapidity, of the overall outer-loop control system;

[0068] (3) It has good practical significance and application prospects in the outer-loop constraint control of fixed-wing UAVs.

[0069] Explanation of attached figures

[0070] Figure 1 It is the flow chart of the terminal sliding mode control method under the position tracking deviation constraint of the fixed-wing UAV;

[0071] Figure 2 It is the block diagram of the terminal sliding mode control system under the position tracking deviation constraint of the fixed-wing UAV;

[0072] Figure 3 It is the curve graph of the flight trajectory of the fixed-wing UAV;

[0073] Figure 4 It is the curve graph of the position tracking deviation of the fixed-wing UAV in the X-axis direction;

[0074] Figure 5 It is the curve graph of the position tracking deviation of the fixed-wing UAV in the Y-axis direction;

[0075] Figure 6 It is the curve graph of the position tracking deviation of the fixed-wing UAV in the H-axis direction;

[0076] Figure 7 It is the curve graph of the adaptive disturbance estimation value;

[0077] Figure 8 It is the curve graph of the actual control input quantity of the designed fixed-wing UAV. Specific implementation manners

[0078] Combined with the attached figures, the control method of the present invention will be further explained.

[0079] (a) Establish a three-degree-of-freedom dynamic model of the fixed-wing UAV:

[0080] Define the position P = [x, y, h] of the UAV in the three directions of the X-axis, Y-axis and H-axis in the inertial coordinate system T , and establish a three-degree-of-freedom kinematic model of the fixed-wing UAV

[0081]

[0082] Among them, V is the flight airspeed of the UAV, γ and χ are the track inclination angle and track azimuth angle of the UAV, and a three-degree-of-freedom particle model of the UAV is established:

[0083]

[0084] Among them, m is the mass of the UAV, g is the acceleration due to gravity, T c and Df are the engine thrust and drag, φ is the roll angle, n is the load factor, that is, the ratio of lift to weight, and gncosφ and gnsinφ respectively represent the pitch acceleration and yaw acceleration of the fixed-wing UAV; D = [d t , d y , d p T , d t , d y , d p are the uncertain disturbances existing in the V, χ 和γ channels in the model respectively; The pseudo-control quantity of the UAV is introduced

[0085] U = [u t , u y , u p T (3)

[0086] Among them, the elements u t , u y and u p in the pseudo-control quantity have the following relationships with n, φ and T respectively u y = gnsinφ and u p = gncosφ;

[0087] By taking the derivative of equation (1), we get

[0088]

[0089] Among them, the rotation matrix R is

[0090]

[0091] By substituting equation (2) into equation (4), we get

[0092]

[0093] Rewrite the UAV dynamics as

[0094]

[0095] Among them, G = [0, 0, -g] T . ​​

[0096] (b) Design of preset constraint performance function:

[0097] Define the position tracking deviation \(P\) of the fixed-wing UAV e \(= P - P_d\) d , where \(P_d\) d \(= [x_d\) d , \(y_d\) d , \(z_d\) d \(^T\) T are the desired position commands of the UAV in the three directions of the X-axis, Y-axis, and Z-axis, respectively. Then the position tracking deviation constraint is expressed as

[0098]

[0099] where \(i\) represents each element in the above 3D vector, k i and are positive constants, and \(\epsilon(t)\) i is a smooth decreasing function

[0100]

[0101] where the initial value of the function and the final value satisfy and \(w>0\) is the convergence rate of the \(\epsilon(t)\) i function. Appropriately select the relevant parameters k i and in the function so that the tracking deviation \(P\) ei can be constrained within .

[0102] Then the position tracking deviation constraint inequality (8) is converted to

[0103] \(P\) ei \(= \epsilon\) i \(\Omega(E\) i ) (10)

[0104] where \(\Omega(\cdot)\) is a smooth increasing function and has the following properties:

[0105] ◆ \(\Omega(E\) i ) is a bounded function that makes hold;

[0106] ◆ item

[0107] ◆

[0108] Then the position tracking deviation constraint function is expressed as

[0109]

[0110] Among them,

[0111] By taking the derivative of Equation (11), we get

[0112]

[0113] Among them, Then

[0114]

[0115] By taking the derivative of (12), we get

[0116]

[0117] (c) Design based on deviation constraints of the fast terminal sliding surface:

[0118] According to the conversion function of the position tracking error constraint, select the fast non-singular terminal sliding surface as

[0119]

[0120] Among them, C 1 and C 2 are positive definite diagonal matrices, and σ(E) = [σ(E 1 ), σ(E 2 ), σ(E 3 )] is expressed as

[0121]

[0122] Among them 0 < α = α 1 / α 2 < 1 and α 1 and α 2 are positive odd numbers, and Among them, e s is an arbitrarily small positive constant.

[0123] After taking the derivative of (16), we get

[0124]

[0125] Then, Equation (15), which is the derivative of the fast non-singular terminal sliding surface, is

[0126]

[0127] Since Assume that the external uncertainty disturbance D is bounded and continuously differentiable, and satisfies ||D|| 2 ≤ d1 , where d 1 and d 2 have unknown upper bounds.

[0128] (d) Design of position tracking deviation constraint controller and adaptive disturbance estimation:

[0129] Design the pseudo-control quantity of the position tracking deviation constraint controller based on fast non-singular terminal sliding mode as

[0130]

[0131] where m 1 , n 1 are positive definite diagonal matrices to be designed, 0 < τ < 1, h > 0 are positive constants, and is the estimated value of the disturbance upper bound d 1 , and its adaptive law is

[0132]

[0133] (e) Stability analysis of the position tracking deviation constraint control scheme

[0134] Select the Lyapunov function as

[0135]

[0136] Taking the derivative of (21) gives

[0137]

[0138] where ζ = min{2λ min (m 1 ), l 1 l 2},

[0139] From this, the terminal sliding mode surface S and the disturbance estimation error are finally uniformly asymptotically stable, and there exists an unknown constant such that holds.

[0140] Subsequently, select a new Lyapunov function as

[0141]

[0142] Taking the derivative of (23) gives

[0143]

[0144] where If the parameter matrix m1 Satisfy Then equation (24) is rewritten as where 0 < θ 1 < 1 and holds when

[0145] According to the above analysis, the fast terminal sliding mode variable S will converge to a finite domain within a finite time within the domain.

[0146] When the sliding mode variable S reaches the sliding mode surface S = Ω 1 , assume there exists a diagonal matrix and a positive constant such that holds, then the following equation is obtained

[0147]

[0148] The following will discuss three cases for the fast terminal sliding mode:

[0149] Case 1: When holds, there is

[0150]

[0151] Select the Lyapunov function as

[0152]

[0153] According to the Young's inequality, combined with equation (16) and taking the derivative of the above equation, we get

[0154]

[0155] where According to the finite time theorem, the position tracking error E converges to a bounded domain Ω within a finite time 2 = {E: V 2 ≤ Δ 2 / (1 - θ 2 )μ 3}.

[0156] Case 2: When S ≠ 0 and the position tracking deviation satisfies |E i | ≤ e s , according to the fast terminal sliding mode in and we get

[0157]

[0158] Assume there exists a positive definite matrix Ψ = diag{ψ 1 , ψ 2 , ψ 3} > 0 such that when i = 1, 2, 3 holds, we have That is, the position tracking error E will converge to Ω c2 within a finite time T 3 = {E: ||E|| 1 ≤ 3||Ψ|| 1}.

[0159] Case 3: When and the position tracking deviation satisfies |E i | > e s , we have

[0160]

[0161] The above equation is rewritten in the following two forms

[0162]

[0163]

[0164] According to Equation (31), when holds, it can be obtained that the position tracking error will converge within a finite time T c31 in the domain . And according to Equation (32), when holds, it can be obtained that the position tracking error will converge within a finite time T c32 in the domain . That is, it is obtained that the position tracking deviation E will converge in a finite time T c3 = max{T c31 , T c32} to Ω 4 = {E: ||E|| 1 ≤ 3||Ω 5 || 1}, where

[0165]

[0166] According to the above analysis, it can be obtained that under the design of this terminal sliding mode control, the position tracking deviation E will converge within a finite time T c = max{T c1 , T c2 , T c3} to the bounded domain Ω = min{Ω 2 , Ω 3 , Ω 4}. According to the preset performance function, the position tracking deviation Pe It will eventually be uniformly bounded stable and converge within the preset constraint range of Equation (8).

[0167] (f) According to the obtained control input U, return to the outer loop model of the fixed-wing UAV, and perform finite-time position tracking deviation constraint control on the fixed-wing UAV with uncertain disturbances.

[0168] The effectiveness of the present invention is verified by the following simulation:

[0169] The dynamic model and various definitions of the fixed-wing UAV are shown in (1)-(6). The structural parameter values are m = 25 kg, g = 9.8 m·s, and the desired position signal is set such that the X-axis, Y-axis, and H-axis respectively follow the trajectories of x d = 28cos(0.45t) + 80 m, y d = 28sin(0.45t) + 80 m, and h d = 3t + 1024 m, climbing in a spiral shape. Assume that the resistance D f = 0 during the flight of the UAV, and the uncertain disturbances in the model are respectively set as D = [0.2sin(0.3t); 0.4sin(0.35t); 0.3sin(0.4t)] from 0 s to 10 s, D = [0.2; 0.2; 0.25] from 18 s to 21 s, and D = [0.015; 0.02; 0.015] after 32 s; the initial state of the system is set as V(0) = 12.9 m / s, χ(0) = 0.01°, γ(0) = 0.015°.

[0170] Select the relevant parameters of the position tracking deviation preset function as k 1 = 0.9, η = 0.8, k 2 = 0.9, k 3 = 0.9, The parameters of the fast non-singular terminal sliding mode are selected as α = 5 / 7, e s = 0.001, C 1 = diag{8, 11.2, 8}, C 2 = diag{0.2, 0.28, 0.2}, the controller parameters are selected as m 1 = diag{5, 5, 5}, n 1 = diag{0.25, 0.25, 0.25}, τ = 0.6, and the adaptive disturbance estimation parameters are selected as l 1 = 0.2, l 2 = 0.5, h 1，2 = 0.9.

[0171] The simulation results show that the terminal sliding mode control method designed for the fixed-wing UAV under the position tracking deviation constraint can better control the position tracking of the UAV and has a good deviation constraint effect. Figure 3 It is a schematic diagram of the fixed-wing UAV tracking a given desired position under the designed control law. The curve in the figure shows that the actual flight trajectory of the UAV tends to be consistent with the desired signal. Figure 4 , Figure 5 and Figure 6 are the curve graphs of the tracking deviation constraints of the fixed-wing UAV on the X, Y, and H axes respectively. It can be clearly seen that the position state E1 of the UAV can converge within a finite time, which means that the position deviation P e can be and is strictly constrained within the preset constraint deviation range ; Figure 7 is a schematic diagram of the designed adaptive disturbance estimation value. According to the figure, it can be obtained that the adaptive disturbance estimation is a bounded value, which can prove the stability of the designed adaptive disturbance. Figure 8 The curve in shows the actual control signal quantities T e , φ, and n in the present invention. The actual control input signals obtained by designing the control law are finally stable and bounded.

[0172] In summary, for the case of the fixed-wing UAV with uncertain disturbances considering the position tracking deviation constraint, the method of the present invention can achieve the disturbance estimation and position tracking deviation constraint control of the fixed-wing UAV within a finite time.

[0173] The above is only the preferred implementation manner of the present invention. It should be noted that for those of ordinary skill in the art, without departing from the principle of the present invention, several improvements and adjustments can be made, and these improvements and adjustments should also be regarded as the protection scope of the present invention.

Claims

1. Terminal sliding mode control method for a fixed-wing unmanned aerial vehicle (UAV) under position tracking deviation constraints, characterized in that, the method comprises the following steps: Step 1, establish a three-degree-of-freedom dynamic model of the fixed-wing UAV; the three-degree-of-freedom dynamic model is: where G = [0, 0, -g] T , g is the gravitational acceleration, U is the pseudo-control quantity matrix of the UAV, R is the general rotation matrix of the three-degree-of-freedom dynamic model, and D is the disturbance matrix; Step 2, design a finite-time constraint controller based on a preset performance function and a fast non-singular terminal sliding mode surface, and use an adaptive disturbance observer to estimate the uncertain disturbances in the model to improve the outer-loop constraint control accuracy of the fixed-wing UAV; the specific process of Step 2 is as follows: Step 2.1 Define the position tracking deviation \(P\) of the fixed-wing UAV e \(= P - P_{ref}\) d , where \(P_{ref}\) d \(= [x_{ref}\) d , y_{ref}\) d , z_{ref}\) d \ T are the desired position commands of the UAV in the three directions of the X-axis, Y-axis and H-axis respectively. Then the position tracking deviation constraint is expressed as where \(i\) represents each element in the above three-dimensional vector respectively, k i and are positive constants, and \(\varepsilon\) i (t) is a smooth decreasing function Among them, the initial value of the function The final value satisfies And ω > 0 is the convergence rate of the ε i (t) function. Select relevant parameters k i And Make the tracking deviation P ei Constrained within ; Then the position tracking deviation constraint inequality (8) is converted to P ei = ε i Ω(E i ) (10) where, Ω(·) is a smooth increasing function and has the following properties: ◆Ω(E i ) is a bounded function that makes hold; ◆ and ◆ where, the position tracking deviation constraint function is expressed as Among them, By taking the derivative of equation (11), we get Among them, then By taking the derivative of (12), we get Step 2.2, according to the conversion function of the position tracking error constraint, select the fast non-singular terminal sliding mode surface as Among them, C 1 and C 2 are positive definite diagonal matrices, and σ(E) = [σ(E 1 ), σ(E 2 ), σ(E 3 )] is expressed as Among them 0 < α = α 1 / α 2 < 1 and α 1 and α 2 is a positive odd number, and where e s is an arbitrarily small positive constant; Taking the derivative of (16), we get Then, the derivative of equation (15), i.e., the fast non-singular terminal sliding mode surface, is Since assuming that the external uncertainty disturbance D is bounded and continuously differentiable and satisfies ||D|| 2 ≤d 1 、 where d 1 and d 2 are unknown upper bounds; Step 3, use the output result of the finite-time constraint controller as the control input signal to achieve terminal sliding mode control for the fixed-wing UAV under position tracking deviation constraints; the specific process of Step 3 is as follows: Design the pseudo-control quantity of the position tracking deviation constraint controller based on the fast non-singular terminal sliding mode as where m 1 , n 1 are positive definite diagonal matrices to be designed, 0 < τ < 1, h > 0 is a positive constant, and is the estimated value of the upper bound d 1 of the perturbation, and its adaptation law is 2. The terminal sliding mode control method for a fixed-wing UAV under position tracking deviation constraints according to claim 1, characterized in that, the specific process of Step 1 is as follows: Step 1.1 Define the position of the UAV in three directions of the inertial coordinate system X-axis, Y-axis and H-axis as P = [x, y, h] T , and establish a three-degree-of-freedom kinematic model of the fixed-wing UAV where, V is the flight airspeed of the UAV, γ and χ are the flight path inclination angle and flight path azimuth angle of the UAV, and establish a three-degree-of-freedom particle model of the UAV: where m is the mass of the UAV, g is the acceleration due to gravity, T e and D f are the engine thrust and drag, φ is the roll angle, n is the load factor which is the ratio of lift to weight, and gncosφ and gnsinφ represent the pitch acceleration and yaw acceleration of the fixed-wing UAV respectively; D = [d t , d y , d p T , d t , d y , d p are the uncertainty disturbances existing in the three parameters V, χ, and γ in the model respectively; the pseudo-control quantity of the UAV is introduced​ U = [u t , u y , u p T (3)​ Among them, each element u in the pseudo-control quantity t , u y and u p The relationships with n, φ, and T are respectively u y = gnsinφ and u p = gncosφ; By taking the derivative of equation (1), we get where, the rotation matrix R is By substituting equation (2) into equation (4), we get Rewrite the UAV dynamic model as where G = [0, 0, -g] T .

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