Four-rotor aircraft trajectory tracking control method based on improved event triggering mechanism

Abstract

The invention discloses a four-rotor aircraft trajectory tracking control method based on an improved event triggering mechanism. In a four-rotor aircraft trajectory tracking task, an anti-saturation auxiliary system is firstly designed to solve the problem of actuator input saturation of a four-rotor aircraft. The saturation phenomenon is modeled and compensated in advance, so that the influence of the problem on the control performance of the system is reduced. And secondly, through combination of a self-adaptive gain item and a fuzzy controller, a sliding mode reaching law hyperbolic tangent function coefficient is softened, a chattering phenomenon existing in sliding mode control is further inhibited, and the control performance is improved. Finally, an improved event triggering mechanism is designed at an actuator end, a self-adaptive triggering threshold value is introduced, redundant transmission is avoided, dynamic adaptability is enhanced, and communication resources are further saved. According to the method provided by the invention, the requirement of green flight control is met while the control performance of the system is improved.

Description

Technical Field

[0001] The present invention belongs to the field of aircraft control, and more specifically, relates to a quadrotor aircraft trajectory tracking control method based on an improved event triggering mechanism. Background Art

[0002] In recent years, drones have been widely used in military and civilian fields. As a common aircraft, quadcopters are small in size, light in weight, and easy to operate. However, they also have problems such as underactuation, strong coupling, and time-varying. Currently, there is no more comprehensive analysis of many complex situations.

[0003] With the continuous growth of flight mission requirements, quadrotor control faces many challenges. Trajectory tracking control, as a common control task, has attracted the attention of many scholars, and many practical control methods have been proposed, such as PID control, sliding mode control, predictive control, adaptive control, etc. Among them, sliding mode control has been widely used due to its rapid response and strong robustness to external interference. However, current research has failed to effectively suppress the chattering phenomenon and lacks attention to saving communication resources.

[0004] Due to the continuous innovation of communication engineering and control technology, a large amount of data needs to be transmitted in real time through an efficient communication network, which usually brings high energy consumption and heavy communication burden. The traditional time trigger mechanism is stretched when facing complex situations. When the sampling period is small, a large amount of redundant data will be released to the network with limited bandwidth; when the sampling period is large, control lag will occur and system stability will be reduced. The event trigger mechanism can reduce the number of executions of control tasks and further reduce the waste of network resources under the condition of ensuring certain system performance. However, this efficient data transmission mechanism has not been fully applied in the field of quadrotors, and the dynamic adaptability of the mechanism needs to be further improved.

[0005] In summary, in order to ensure the stability and accuracy of trajectory tracking, we should continue to study the trajectory tracking problem in complex scenarios and save communication resources as much as possible. Summary of the invention

[0006] The purpose of the present invention is to propose a quadrotor trajectory tracking control method based on an improved event trigger mechanism. In the actual process of trajectory tracking, it is necessary to face complex situations such as external interference, strong time variability, actuator input saturation, etc. With sliding mode control as the core method, fuzzy control and adaptive gain terms are integrated to weaken the jitter phenomenon and improve the control performance. An anti-saturation auxiliary system is introduced to reduce the impact of saturation on the system through early compensation. The event trigger mechanism is improved to achieve an optimal balance between control performance guarantee and network resource saving.

[0007] To achieve the above object, the present invention provides a quadrotor trajectory tracking control method based on an improved event triggering mechanism, and the specific steps include:

[0008] Step 1: Establish a mathematical model of aircraft dynamics based on Euler equations and Newton's second law;

[0009] Step 2: Build an anti-saturation auxiliary system to model the input saturation phenomenon at the actuator end, feed the compensation term back to the control system, and adjust the control input in advance;

[0010] Step 3: Divide the control system into inner and outer double loop control, which are used to design the attitude control subsystem and the position subsystem respectively. Take sliding mode control as the core method and combine the fuzzy controller with the adaptive gain term;

[0011] Step 4: Introduce an event trigger mechanism and design a new adaptive threshold trigger condition. When the condition is met, the control law is updated. When the condition is not met, the control law at the last triggering moment is maintained.

[0012] Furthermore, a mathematical model of aircraft dynamics is established based on Euler's equations and Newton's second law;

[0013] 1) Define the ground coordinate system [x b ,y b ,z b ] and the body coordinate system [x g ,y g ,z g ], assuming that the angular velocity of the rotation around the center of mass in the body coordinate system is equal to the Euler angular velocity in the ground coordinate system, and deriving the conversion relationship between the two coordinate systems; then, the linear acceleration equation and the attitude angular acceleration dynamics equation of the quadcopter in the inertial coordinate system can be obtained by Newton's law;

[0014] 2) defining four control inputs of the quadrotor aircraft to respectively control the quadrotor aircraft to perform vertical, roll, pitch, and yaw movements.

[0015] Furthermore, an anti-saturation auxiliary system is constructed according to the mathematical model of quadrotor dynamics, the input saturation phenomenon of the actuator end is modeled, the compensation term is fed back to the control system, and the control input is adjusted in advance;

[0016] 1) Construct a saturation constraint function of the following form:

[0017]

[0018] Among them, U i is the controller output, U imax is the actuator input limit; the hyperbolic tangent function is introduced to approximate the limit function, and a is the smoothness coefficient in the hyperbolic tangent function;

[0019] 2) Design and construct the following anti-saturation auxiliary system:

[0020]

[0021] in, ΔU i =sat(U i )-U i , g i >0 is the parameter to be designed, ρ i is the auxiliary variable of the constructed anti-saturation auxiliary system, U i is the controller output, sat(U i ) is the control input after being processed by the anti-saturation auxiliary system.

[0022] Furthermore, the control system is divided into inner and outer double loop control, which are used to design the attitude control subsystem and the position subsystem respectively. The sliding mode control is used as the core method, and the fuzzy controller is combined with the adaptive gain term.

[0023] 1) According to the anti-saturation auxiliary system, a controller based on adaptive sliding mode is designed; first, the tracking error is defined;

[0024] 2) defining a sliding surface according to the tracking error;

[0025] 3) Using the hyperbolic tangent function to replace the sign function in the original exponential reaching law, the design of the new sliding mode reaching law is improved;

[0026] 4) Combining fuzzy control with sliding mode control, the fuzzy controller is designed by fuzzifying the gain coefficient before the hyperbolic tangent function in the sliding mode reaching law of the roll angle and pitch angle;

[0027] The input variables are the sliding surface S and the sliding surface reaching law The output variable is the gain coefficient c before the hyperbolic tangent function of the sliding mode reaching law; the domain of the input variable S is defined as [-6,6], Defined as [-15,15], the domain of the output variable c is defined as [-3,3], and the fuzzy set is divided into seven levels; and the values ​​of the quantization factor and the proportional factor are determined through debugging and verification; then the triangular membership function is selected to construct the membership function distribution; the Mamdani algorithm is applied, and the if Aand B then U statement is used to express the fuzzy implication relationship and establish a fuzzy rule table; finally, the centroid method is used to perform defuzzification operations, and the absolute value of the output variable c is taken;

[0028] 5) Before resolving the expected signals of the roll angle and the pitch angle from the position subsystem, three virtual control quantities are first defined; then the expected signals are transmitted to the attitude subsystem together with the predetermined expected signal of the yaw angle;

[0029] 6) Order The control laws of the attitude subsystem and the position subsystem can be obtained.

[0030] Furthermore, an event trigger mechanism is introduced, and a new adaptive threshold trigger condition is designed. When the condition is met, the control law is updated, and when the condition is not met, the control law at the last triggering moment is maintained.

[0031] 1) First, the control law is transformed as follows:

[0032]

[0033] Among them, m i ,η i is a constant greater than 0;

[0034] 2) Then design the following event trigger:

[0035] e j (t) = w i (t)-W i (t k ),i=1,2,3,4; j=z,φ,θ,ψ (4)

[0036]

[0037] Where k∈N + ,e j (t) represents the control law w at the current moment i (t) and the control law W at the last triggering time i (t k );When the system does not meet the trigger condition, the control law received by the actuator end is always the control law at the last trigger time; and the trigger condition for updating the control law is:

[0038]

[0039] Among them, σ i (t) is the dynamic adaptive trigger threshold, which is based on the following rules:

[0040] σ i (t) = min{max[σ si ,λ i σ i (th)],σ bi},i=1,2,3,4 (7)

[0041]

[0042] Where h is the sampling step size, σ bi >σ si >0,σ si is the lower bound of the trigger threshold, σ bi is the upper limit of the trigger threshold; α i ,β i ,μ i are all non-negative constants.

[0043] Compared with the prior art, the present invention has the following beneficial effects:

[0044] 1. The present invention takes into account the input saturation of the actuator, constructs an anti-saturation auxiliary system, and constructs an auxiliary state vector at the same time, and introduces the auxiliary state vector into the tracking error to compensate for the influence of the input limitation.

[0045] 2. Taking external interference into consideration, the present invention proposes a novel control method for trajectory tracking of quadrotor aircraft. The controller design combines fuzzy control, adaptive gain term and sliding mode control, which not only improves the control effect, but also further reduces the chattering phenomenon in sliding mode control.

[0046] 3. The present invention designs a novel adaptive event trigger mechanism at the actuator end of the quadrotor aircraft, designs an adaptive update condition for the trigger threshold, eliminates unnecessary cyclic operations, thereby reducing resource consumption, helps to improve system performance and improve the overall efficiency of the system, and at the same time meets the needs of green flight control. BRIEF DESCRIPTION OF THE DRAWINGS

[0047] Figure 1 A control structure framework diagram proposed for an embodiment of the present invention;

[0048] Figure 2 A fuzzy controller design flow chart proposed for an embodiment of the present invention;

[0049] Figure 3 A schematic diagram of the input and output variable membership function proposed in the embodiment of the present invention;

[0050] Figure 4 A schematic diagram of trajectory tracking proposed in an embodiment of the present invention;

[0051] Figure 5 A schematic diagram of attitude angle tracking proposed in an embodiment of the present invention;

[0052] Figure 6 A schematic diagram of the triggering time of the traditional algorithm proposed in the embodiment of the present invention;

[0053] Figure 7 This is a schematic diagram of the improved triggering timing proposed in the embodiment of the present invention. DETAILED DESCRIPTION

[0054] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0055] The purpose of the present invention is to study trajectory tracking in the field of quadrotor aircraft control. The specific implementation process is as follows: Figure 1 As shown. First, a dynamic model of a quadrotor is established based on Newton's second law and Euler's equations. Then, considering the saturation of the actuator input, an anti-saturation auxiliary system is established, and an auxiliary state vector is constructed to compensate for the saturated input; the quadrotor is divided into inner and outer loop control subsystems, and adaptive sliding mode controllers are designed for the position subsystem and the attitude angle subsystem respectively; considering that the expected values ​​of the roll angle and the pitch angle are obtained by inverse solution from the position subsystem, in order to further suppress the jitter phenomenon, fuzzy control is combined with adaptive sliding mode control in the attitude subsystem to soften the gain coefficient before the sliding film approach law; finally, considering avoiding the waste of communication resources, an event trigger mechanism is introduced at the actuator end of the quadrotor, and a new adaptive update condition is designed for the trigger threshold to improve the dynamic adaptability of the trigger condition. In order to illustrate the feasibility of the present invention, the following embodiments will be described below.

[0056] Example

[0057] For further information, see Figure 1-7 The specific implementation process of the embodiment of the present application is as follows:

[0058] (1) In the embodiment of the present application, the present invention establishes a mathematical model of aircraft dynamics based on the Euler equation and Newton's second law;

[0059] 1) Define the ground coordinate system [x b ,y b ,z b ] and the body coordinate system [x g ,y g ,z g ], assuming that the angular velocity of the body coordinate system around the center of mass is equal to the Euler angular velocity in the ground coordinate system, and derive the conversion relationship between the two coordinate systems as follows:

[0060]

[0061] 2) Use x, y, and z to represent the position coordinates of the quadrotor in the inertial system; represents the linear velocity of the quadrotor in the inertial system; φ, θ, ψ represent the roll angle, pitch angle and yaw angle respectively; p, q, r represent the angular velocity of rotation in the body coordinate system respectively. According to Newton's law, the linear acceleration equation of the quadrotor in the inertial coordinate system is:

[0062]

[0063] in, is the total lift generated by the four propellers, ω i is the speed of the four motors of the quadrotor aircraft, k t is the propeller lift coefficient; c γ =cosγ,s γ = sinγ, c γ =tanγ, γ=φ, θ, ψ; g is the acceleration due to gravity; m is the mass of the quadrotor;

[0064] 3) The structure of the quadrotor is strictly symmetrical, so the moment of inertia of the body is defined, and the angular motion equation is obtained as follows:

[0065]

[0066] in, ω i is the speed of the four motors of the quadcopter; J is the moment of inertia of a single motor about the rotating shaft; I x ,I y and I z are the body moment of inertia about the x-axis, y-axis and z-axis respectively;

[0067] 4) Define the four control inputs of the quadrotor aircraft to control the quadrotor aircraft to perform vertical, roll, pitch and yaw movements respectively, which are specifically expressed as

[0068]

[0069] Among them, ω i is the speed of the four motors of the quadrotor aircraft, k d is the rotation coefficient, L is the distance from the motor to the center of gravity of the quadrotor aircraft;

[0070] (2) In the embodiment of the present application, the present invention constructs an anti-saturation auxiliary system, models the input saturation phenomenon at the actuator end, feeds back the compensation term to the control system, and adjusts the control input in advance;

[0071] 1) The actuator saturation problem is caused by its own characteristics. A system working in a saturated state is difficult to respond as expected, resulting in reduced control performance. First, define the saturation constraint function:

[0072]

[0073] Among them, U i is the controller output, U imax is the input limit of the actuator; in order to ensure the nonlinear characteristics, the hyperbolic tangent function is introduced to approximate the limit function, and the smoothness of the saturation characteristic curve is adjusted by the parameter a;

[0074] 2) In order to make the actuator input be subject to the saturation constraint function while reducing the impact on the system control effect, the following anti-saturation auxiliary system is designed and constructed

[0075]

[0076] in, ΔU i =sat(U i )-U i , g i >0 is the parameter to be designed, ρ i is the auxiliary variable of the constructed anti-saturation auxiliary system, U i is the controller output, sat(U i ) is the control input after being processed by the anti-saturation auxiliary system;

[0077] (3) In the embodiment of the present application, the present invention divides the control system into inner and outer dual-loop control, which are used to design the attitude control subsystem and the position subsystem respectively. With sliding mode control as the core method, the fuzzy controller is combined with the adaptive gain term to suppress the chattering phenomenon generated in the sliding mode control;

[0078] 1) In order to accurately track the expected signals in the position direction and attitude direction so that the tracking error converges within the effective time, a controller based on adaptive sliding mode is designed according to the aforementioned anti-saturation auxiliary system to meet the control performance; first define the tracking error:

[0079]

[0080] Among them, x d ,y d ,z d ,φ d ,θ d ,ψ dIndicates the expected signal of position direction and attitude direction; x, y, z respectively represent the position direction state information of the quadrotor aircraft, φ, θ, ψ respectively represent the attitude direction state information of the quadrotor aircraft;

[0081] 2) Define the sliding surface based on the tracking error:

[0082]

[0083] Among them, b i are both greater than 0 and are constants, e i is the tracking error described in the position direction and attitude angle direction;

[0084] 3) The hyperbolic tangent function is used to replace the sign function in the original exponential reaching law, and the performance of the controller is enhanced based on the adaptive gain term; it can not only ensure the finite convergence in the approaching stage, but also suppress the chattering phenomenon to a certain extent; the improved new sliding mode reaching law is designed as follows:

[0085]

[0086] Among them, k i are all greater than 0 and are constants. a is the smoothness coefficient in the hyperbolic tangent function to ensure nonlinear characteristics. ε i The adaptive law is as follows:

[0087]

[0088] Among them, ω i >0,c i >0,δ i >0 is the parameter to be designed;

[0089] 4) Since the expected signals of the roll angle and the pitch angle in the attitude angle are solved from the position subsystem, they are greatly affected by the position subsystem itself. The gain before the hyperbolic function term is the main cause of the chattering, which will destroy the control performance of the system. In the embodiment of the present application, fuzzy control and sliding mode control are combined, and the fuzzy controller is designed by fuzzifying the gain coefficient before the hyperbolic tangent function in the sliding mode approaching law of the roll angle and the pitch angle to achieve the purpose of reducing the chattering phenomenon and improving the control accuracy.

[0090] The input variables are the sliding surface S and the sliding surface reaching law The output variable is the gain coefficient c before the hyperbolic tangent function of the sliding mode reaching law; considering the control difficulty and accuracy of the attitude subsystem, the domain of the input variable S is defined as [-6,6], is defined as [-15,15], the domain of the output variable c is defined as [-3,3], and the fuzzy set is divided into seven levels; and after multiple debugging and verification, the values ​​of the quantization factor and the proportional factor are determined; then the triangle membership function with the fastest fuzzification and defuzzification is selected to quickly suppress chattering; the widely used Mamdani algorithm uses the if A and B then U statement to express the fuzzy implication relationship, comprehensively considers the response speed and the suppression of chattering, and establishes a fuzzy rule table; finally, the centroid method is used for defuzzification operation, and the absolute value of the output variable c is taken;

[0091]

[0092] Among them, A(c i ) is the membership function on the output variable domain;

[0093] 5) Before the expected signals of roll angle and pitch angle can be inversely solved from the position subsystem, three virtual control quantities are defined first:

[0094]

[0095] The expected signal is then transmitted to the attitude subsystem together with the predetermined yaw angle expected signal.

[0096]

[0097] 6) Order The sliding mode control law can be obtained as follows:

[0098]

[0099] (4) In the embodiment of the present application, the present invention introduces an event trigger mechanism and designs a new adaptive threshold trigger condition. When the condition is met, the control law is updated, and when the condition is not met, the control law at the last triggering moment is maintained;

[0100] 1) First, the control law is transformed in a certain form:

[0101]

[0102] Among them, m i ,η i is a constant greater than 0.

[0103] 2) Then design the following event trigger:

[0104] e j (t) = w i (t)-W i (t k ),i=1,2,3,4; j=z,φ,θ,ψ (24)

[0105]

[0106] Where k∈N + , e j (t) represents the control law w at the current moment i (t) and the control law W at the last triggering time i (t k ); when the system does not meet the trigger condition, the control law received by the actuator end is always the control law at the last trigger time; and the system control law update trigger condition is:

[0107]

[0108] Among them, σ i (t) is the dynamic adaptive trigger threshold, which is based on the following rules:

[0109] σ i (t) = min{max[σ si ,λ i σ i (th)],σ bi}, i = 1, 2, 3, 4 (27)

[0110]

[0111] Where h is the sampling step size, σ bi >σ si >0,σ si is the lower bound of the trigger threshold, σ bi is the upper limit of the trigger threshold; α i , β i , μ i All of them are non-negative constants. According to the dynamic change of the trigger threshold under this mechanism, an optimal balance between ensuring a certain system performance and saving communication resources is achieved;

[0112] Experimental test:

[0113] The physical parameters of the quadcopter provided by the system platform developed by Professor Quan Quan's team at Beijing University of Aeronautics and Astronautics were used for testing. The entire framework was built in Matlab2022b and Simulink, and the physical parameters are shown in Table 1.

[0114] Physical parameters Numeric m 2 <![CDATA[k t ]]> <![CDATA[1.276×10 -5 ]]> <![CDATA[k d ]]> <![CDATA[1.747×10 -5 ]]> <![CDATA[k x ,k y ,k z ]]> <![CDATA[8.268×10 -2 ]]> L 0.25 <![CDATA[I x ,I y ]]> <![CDATA[3.009×10 -2 ]]> <![CDATA[I z ]]> <![CDATA[5.603×10 -2 ]]> J <![CDATA[1.34×10 -4 ]]>

[0115] Table 1. Physical parameters of quadrotor aircraft.

[0116] The initial position state of the quadrotor is [0, 0, 0], the initial attitude angle state is [0, 0, 0], the initial linear velocity state is [0, 0, 0], the initial angular velocity state is [0, 0, 0], and the simulation duration is 20 seconds. The expected signal of the position direction is [2, 2, 0.1t], and the expected signal of the yaw angle is In addition, considering the complex dynamic environment in reality, external interference is introduced into the position loop and attitude loop respectively. The interference value of the position loop is [0.25sint, 0.25sint, 0.25sint], and the interference value of the attitude loop is [0.2sint, 0.3sint, 0.31sint].

[0117] The red dashed line represents the expected signal of the state, the blue solid line (FASMC+AET+AIS) represents the algorithm proposed in this paper, and the green dotted line (SMC+FET) represents the traditional fixed threshold sliding mode control algorithm. Figures 4 to 7 It can be seen that the convergence speed and response speed of the algorithm proposed by the present invention are significantly faster than those of the traditional algorithm. While further reducing the consumption of communication resources, it can also ensure a certain control accuracy. In addition, the idea of ​​introducing adaptive gain and fuzzy control in the present invention significantly suppresses the jitter phenomenon that occurs in sliding mode control. Based on the improved event trigger mechanism of the present invention, the consumption and waste of communication resources can be further reduced while ensuring a certain control effect, thereby improving the overall efficiency of the system and achieving the purpose of green flight control. In addition, the algorithm that does not adopt the event trigger mechanism transmits communications an average of 4001 times; while the traditional fixed threshold event trigger mechanism is adopted, the average transmission communication is 2411 times, reducing the consumption of communication resources by 39.74%; the adaptive threshold event trigger mechanism of the present invention is adopted, and the average transmission communication is 1207 times, reducing the consumption of communication resources by 69.80%.

[0118] In this patent, an efficient quadcopter trajectory tracking control method is proposed. By constructing an anti-saturation auxiliary strategy, combining fuzzy control with adaptive gain terms and sliding mode control, and improving the event triggering mechanism, an optimal balance between control performance and saving network resources is achieved to meet the needs of green flight control. It is easy for those skilled in the art to understand that the above is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions and improvements made within the spirit and principles of the present invention should be included in the scope of protection of the present invention.

Claims

1. A quadrotor trajectory tracking control method based on an improved event trigger mechanism, characterized in that: include: Step 1: Establish a mathematical model of quadrotor dynamics based on Euler equations and Newton's second law; Step 2: construct an anti-saturation auxiliary system according to the mathematical model of quadrotor dynamics, model the input saturation phenomenon at the actuator end, feed back the compensation term into the control system, and adjust the control input in advance; Step 3: Divide the control system into inner and outer double-loop control, which are used to design the attitude control subsystem and the position subsystem respectively. Take sliding mode control as the core method and combine the fuzzy controller with the adaptive gain term. Step 4: Introduce an event trigger mechanism and design an adaptive threshold trigger condition. When the condition is met, the control law is updated. When the condition is not met, the control law at the last triggering moment is maintained.

2. The quadrotor trajectory tracking control method based on the improved event trigger mechanism according to claim 1 is characterized in that: The implementation process of step (1) is as follows: 1) Define the ground coordinate system [x b ,y b ,z b ] and the body coordinate system [x g ,y g ,z g ], assuming that the angular velocity of the body coordinate system around the center of mass is equal to the Euler angular velocity in the ground coordinate system, and derive the conversion relationship between the two coordinate systems as follows: 2) Use x, y and z to represent the position coordinates of the quadrotor in the inertial system; and represents the linear velocity of the quadrotor in the inertial system; φ, θ and ψ represent the roll angle, pitch angle and yaw angle respectively; p, q and r represent the angular velocity of rotation in the body coordinate system respectively; according to Newton's law, the linear acceleration equation of the quadrotor in the inertial coordinate system is: in, is the total lift generated by the four propellers, ω i is the speed of the four motors of the quadrotor aircraft, k t is the propeller lift coefficient; c γ =cosγ,s γ = sinγ, c γ =tanγ, γ=φ, θ, ψ; g is the acceleration due to gravity; m is the mass of the quadrotor; 3) Establish the dynamic equation of attitude angular acceleration: in, ω i is the speed of the four motors of the quadcopter; J is the moment of inertia of a single motor about the rotating shaft; I x ,I y and I z are the body moment of inertia about the x-axis, y-axis and z-axis respectively; 4) Define the four control inputs of the quadrotor aircraft to control the quadrotor aircraft to perform vertical, roll, pitch and yaw movements respectively, which are specifically expressed as Among them, [U1, U2, U3, U4] is the control input of the quadrotor aircraft, k d is the rotation coefficient, k t is the lift coefficient of the propeller, and L is the distance from the motor of the quadrotor to the center of gravity of the quadrotor.

3. The quadrotor trajectory tracking control method based on the improved event trigger mechanism according to claim 2 is characterized in that: In step (2): 1) Construct a saturation constraint function of the following form: Among them, U i is the controller output, U imax is the actuator input limit; the hyperbolic tangent function is introduced to approximate the limit function, and a is the smoothness coefficient in the hyperbolic tangent function; 2) Design and construct the following anti-saturation auxiliary system: in, ΔU i =sat(U i )-U i , g i >0 is the parameter to be designed, ρ i is the auxiliary variable of the constructed anti-saturation auxiliary system, U i is the controller output, sat(U i ) is the control input after being processed by the anti-saturation auxiliary system.

4. The quadrotor trajectory tracking control method based on the improved event trigger mechanism according to claim 3 is characterized in that: In step (3): 1) According to the anti-saturation auxiliary system, a controller based on adaptive sliding mode is designed; first, the tracking error is defined: Among them, x d ,y d ,z d ,φ d ,θ d ,ψ d Respectively represent the expected signals of position direction and attitude direction, x, y, z respectively represent the position direction state information of the quadrotor aircraft, φ, θ, ψ respectively represent the attitude direction state information of the quadrotor aircraft; 2) Define the sliding surface according to the tracking error: Among them, b i is a constant greater than 0, e i The tracking error in the position direction and attitude angle direction; 3) Using the hyperbolic tangent function to replace the sign function in the original exponential reaching law, the improved sliding mode reaching law is designed as follows: Among them, k i are all greater than 0 and are constants. a is the smoothness coefficient in the hyperbolic tangent function to ensure nonlinear characteristics. ε i The adaptive law is as follows: Among them, ω i >0,c i >0,δ i >0 is the parameter to be designed; 4) Combining fuzzy control with sliding mode control, the fuzzy controller is designed by fuzzifying the gain coefficient before the hyperbolic tangent function in the sliding mode reaching law of the roll angle and pitch angle; The input variables are the sliding surface S and the sliding surface reaching law The output variable is the gain coefficient c before the hyperbolic tangent function of the sliding mode reaching law; the domain of the input variable S is defined as [-6,6], Defined as [-15,15], the domain of the output variable c is defined as [-3,3], and the fuzzy set is divided into seven levels; and the values ​​of the quantization factor and the proportional factor are determined through debugging and verification; then the triangular membership function is selected to construct the membership function distribution; the Mamdani algorithm is applied, and the if Aand Bthen U statement is used to express the fuzzy implication relationship and establish a fuzzy rule table; finally, the centroid method is used to perform defuzzification operations, and the absolute value of the output variable c is taken: Among them, A(c i ) is the membership function on the output variable domain; 5) Before resolving the expected signals of the roll angle and pitch angle from the position subsystem, three virtual control quantities are defined: Then the expected signal and the predetermined yaw angle expected signal are transmitted to the attitude subsystem. 6) Order The control law can be obtained as:

5. The quadrotor trajectory tracking control method based on the improved event trigger mechanism according to claim 4 is characterized in that: The implementation process of step (4) is as follows: 1) First, the control law is transformed as follows: Among them, m i ,η i is a constant greater than 0; 2) Then design the following event trigger: e j (t)=w i (t)-W i (t k ),i=1,2,3,4;j=z,φ,θ,ψ Where k∈N + ,e j (t) represents the control law w at the current moment i (t) and the control law W at the last triggering time i (t k );When the system does not meet the trigger condition, the control law received by the actuator end is always the control law at the last trigger time; and the trigger condition for updating the control law is: Among them, σ i (t) is the dynamic adaptive trigger threshold, which is based on the following rules: s i (t)=min{max[σ si ,l i s i (th)],s bi },i=1,2,3,4 Among them, h is the sampling step size, σ bi >σ si >0,σ si is the lower bound of the trigger threshold, σ bi is the upper limit of the trigger threshold; α i ,β i ,μ i are all non-negative constants.

Images