Explicit model tracking flight control method based on EFDT-ESO

Abstract

The invention relates to the technical field of helicopter control, and discloses an EFDT-ESO-based explicit model tracking flight control method, which comprises the following steps: step 1, constructing a helicopter six-degree-of-freedom kinematics equation; step 2, based on a helicopter six-degree-of-freedom kinematical equation, constructing a model tracking control system; step 3, designing an indifference disturbance tracking state observer, suppressing system vibration caused by harmonic disturbance, and improving system control precision; and step 4, designing a tracking control law of the helicopter based on the explicit model tracking control system and the indifference disturbance tracking state observer. The helicopter nonlinear dynamic model is constructed, the indifference disturbance tracking state observer is designed, the influence of a state tracking error of a traditional expansion state observer on the system is eliminated, system vibration caused by harmonic disturbance is remarkably restrained, the precision of the whole control system is effectively improved, the control system is tracked through the display model, and the control precision is improved. The flight process is ensured to be more stable, and the target attitude trajectory is tracked accurately.

Description

Technical Field

[0001] The present invention relates to the technical field of helicopter control, in particular to an explicit model tracking flight control method based on EFDT-ESO. Background Art

[0002] Helicopters, as specialized aircraft capable of vertical takeoff and landing, hovering, and omnidirectional maneuverability, play an irreplaceable role in emergency rescue, forest fire prevention, and aerial photography. As demand for helicopter performance continues to increase, there is a need to expand the helicopter's flight envelope, reduce engine fuel consumption, improve system control stability, and enhance overall reliability in harsh environments.

[0003] Helicopter flight control system is the basis for helicopters to perform upper-level tasks. In helicopter flight control systems, linear control methods play an important role. The main idea is to linearize the helicopter nonlinear model and then use linear control methods to control the helicopter flight system. Currently, the commonly used linear control methods mainly include PID, LQR, and explicit model tracking control. Addressing aircraft control performance issues, especially for helicopters, which have more complex aerodynamic characteristics and strong inter-axis coupling, the cross-coupling between pitch and roll, and the cross-coupling between collective pitch and pitch, as well as collective pitch and heading, are major factors affecting helicopter flight performance. Compared to fixed-wing and other configurations, the coupling between helicopter control channels is more prominent, posing a challenge to controller design. The explicit model tracking control system achieves a decoupling effect by designing an explicit model that forces the helicopter to track the explicit model, thereby improving flight performance and reducing the piloting burden.

[0004] In recent years, helicopter control technology has garnered widespread attention from scholars both domestically and internationally, and considerable theoretical research has been achieved. However, existing composite control methods, primarily including adaptive control, optimal control, and active disturbance rejection control, offer good control over nonlinear controlled objects but suffer from poor robustness. Therefore, an integral is introduced to suppress steady-state errors, maintaining automatic helicopter trim throughout the flight envelope. Furthermore, a zero-disturbance tracking state observer is introduced to suppress control system vibrations caused by harmonic disturbances, effectively improving the accuracy of the entire control system. Summary of the Invention

[0005] The present invention aims to provide an explicit model tracking flight control method based on EFDT-ESO. This method introduces an error-free disturbance tracking state observer (EFDT-ESO) to suppress system vibrations caused by harmonic disturbances in the control system, effectively improving the accuracy and stability of the explicit model tracking control system. Furthermore, the EFDT-ESO is an improvement over the traditional extended state observer (ESO). It features high tracking accuracy, strong anti-interference capability, good frequency stability, and strong robustness against error disturbances.

[0006] The present invention is achieved by adopting the following technical solutions:

[0007] An explicit model tracking flight control method based on EFDT-ESO includes the following steps:

[0008] Step 1: Construct the helicopter's six-degree-of-freedom kinematic equations based on the aerodynamic models of the helicopter's rotor, fuselage, tail rotor, vertical tail, and horizontal tail;

[0009] Step 2: Based on the helicopter's six-degree-of-freedom kinematic equations, construct an explicit model tracking control system;

[0010] Step 3: Design a zero-difference disturbance tracking state observer to suppress system vibration caused by harmonic disturbances and improve system control accuracy;

[0011] Step 4: Design the tracking control law of the helicopter based on the explicit model tracking control system and the zero-disturbance tracking state observer.

[0012] Further preferably, in step 1, the helicopter six-degree-of-freedom kinematic equation includes a linear motion equation of the center of mass translation and an angular rotation equation about the center of mass, and the helicopter six-degree-of-freedom kinematic equation is constructed as follows:

[0013] ;

[0014] ;

[0015] Helicopter attitude angle , , With body axis 、 、 Three-axis angular velocity , , The relationship is:

[0016] ;

[0017] in, is the mass of the helicopter; 、 、 Represent the longitudinal axis of the helicopter under the body axis system , horizontal axis , vertical axis The velocity component of , , Respectively expressed in the body axis system 、 、 Angular velocity of three axes; , , Represent the pitch angle, roll angle and yaw angle of the helicopter respectively; 、 、 Respectively expressed in the body axis system 、 、 Three-axis forces; 、 、 Respectively expressed in the body axis system 、 、 The acting moments on the three axes; 、 、 They represent the roll angular velocity, yaw angular velocity, and pitch angular velocity respectively; 、 、 Represents the helicopter orbiting 、 、 Moment of inertia of the three axes; 、 、 Respectively 、 、 The derivative of 、 、 Respectively 、 、 The derivative of For objects in Product of inertia in the plane; Represents the acceleration due to gravity.

[0018] Further preferably, in step 2, the explicit model tracking control system specifically includes:

[0019] Horizontal channel:

[0020] ;

[0021] Longitudinal channel:

[0022] ;

[0023] Heading channel:

[0024] ;

[0025] Total channel:

[0026] ;

[0027] in, 、 、 、 Represent the model bandwidth of the lateral, longitudinal, heading and collective channels respectively; is the damping coefficient; 、 、 、 Respectively represent the roll angle command output, pitch angle command output, yaw rate command output, and vertical velocity command output; 、 、 、 Respectively represent the roll angle command input, pitch angle command input, yaw rate command input, and vertical speed command input; represents the complex frequency variable in the Laplace transform.

[0028] Further preferably, in step 3, the dynamic equation of the zero-disturbance tracking state observer system is:

[0029] ;

[0030] in, is the system status; is the output of the system; is the gain of the input system; represents the nominal gain of the input system; System status , expansion state Tracking estimates; are the parameters of the extended state observer ESO; is the total disturbance estimate of the system; 、 They are The derivative of .

[0031] Further preferably, step 4 is specifically as follows: the linear state equation of the dynamic helicopter is:

[0032] ;

[0033] Where, , is a 9×9 state matrix, It is a 9×4 control matrix; , respectively representing the control input signals for the actuators of the four channels: lateral, longitudinal, heading, and altitude;

[0034] Step 4.1: Discretize the state equation using the backward difference method, and obtain the helicopter discretized dynamic equation as follows:

[0035] ;

[0036] in, In discrete time The state vector at the moment; represents the discrete state matrix; represents the discrete control matrix; represents a discrete time step; Indicates The amount of state change at a moment; Indicates The change in control input at each moment;

[0037] Step 4.2: After one sampling period, the system enters a new balancing state. Substituting the state and control vector of the balancing point into the new state, we can obtain:

[0038] ;

[0039] in, represents the target control input; represents the control input vector; represents the state vector;

[0040] Step 4.3 The output of the controller consists of a proportional part and an integral part, which can be expressed as:

[0041] ;

[0042] in, Indicates proportional control input; represents the integral control input;

[0043] According to the assumption , we can get: ,

[0044] ;

[0045] Step 4.4: Set the desired posture , we can get:

[0046] ;

[0047] in, Expressing an expectation posture; Indicates state error;

[0048] exist time, The proportional output of the (proportional-integral) controller is:

[0049] ;

[0050] in, That is The solution of the (proportional) controller is:

[0051] ;

[0052] Step 4.5: Control matrix Divided into the control matrix of the controlled quantity , and the control matrix of the uncontrolled quantity , and obtain the control matrix ;

[0053] ;

[0054] Finally, the tracking control law is:

[0055] .

[0056] Compared with the prior art, the present invention has the following advantages:

[0057] First, the explicit model tracking control system can effectively reduce the inter-axis coupling and improve the flight control quality.

[0058] Second, the difference-free disturbance tracking state observer eliminates the influence of the state tracking error of the traditional extended state observer on the system, significantly suppresses the system vibration caused by harmonic disturbances, and improves the system control accuracy. It has the advantages of high tracking accuracy, strong anti-interference ability, good frequency stability, and good control performance.

[0059] Third, the present invention adopts the explicit model tracking control method to design the flight control system, which improves the flight control quality and reduces the burden on the pilot. On this basis, the present invention introduces the zero-difference disturbance tracking state observer to suppress the system vibration caused by harmonic disturbances, effectively improving the accuracy and stability of the control system. Compared with the existing technology, this method has outstanding anti-interference ability and the advantages of comprehensive state estimation and control.

[0060] The method of the present invention is reasonably designed. Aiming at the attitude tracking control problem of a helicopter, a nonlinear dynamic model of the helicopter is constructed, and a zero-disturbance tracking state observer is designed. The influence of the state tracking error of the traditional extended state observer on the system is eliminated, the system vibration caused by harmonic disturbance is significantly suppressed, and the accuracy of the entire control system is effectively improved. The method also ensures that the flight process is more stable and the target attitude trajectory is tracked accurately through the explicit model tracking control system, and has good practical application value. BRIEF DESCRIPTION OF THE DRAWINGS

[0061] Figure 1 It is a flow chart of the method of the present invention.

[0062] Figure 2 A diagram showing the simulation results of the pitch angle tracking response under the control method designed by the present invention.

[0063] Figure 3 A diagram showing the simulation results of the roll angle tracking response under the control method designed by the present invention.

[0064] Figure 4 A diagram showing the simulation results of the yaw rate tracking response under the control method designed by the present invention.

[0065] Figure 5 A diagram showing the simulation results of the vertical velocity tracking response under the control method designed by the present invention. DETAILED DESCRIPTION

[0066] The present invention will be further described in detail below with reference to the accompanying drawings and specific embodiments.

[0067] The present invention proposes an explicit model tracking flight control method based on EFDT-ESO, the process is as follows: Figure 1 As shown, the following steps are included:

[0068] Step 1: Construct the six-degree-of-freedom kinematic equations of the helicopter based on the aerodynamic models of the helicopter's rotor, fuselage, tail rotor, vertical tail, and horizontal tail.

[0069] The six-degree-of-freedom kinematic equations of a helicopter include the linear motion equations of the center of mass translation and the angular rotation equations around the center of mass. The original equations are:

[0070] ;

[0071] in, is the mass of the helicopter; , represents the angular velocity of the three axes under the body axis system; is the rate of change of the helicopter's angular velocity; , represents the body axis system 、 、 Linear speed of three axes; is the rate of change of velocity; represents the net external force acting on the helicopter; is the moment of inertia matrix of the helicopter; Expressed as the net external torque.

[0072] Helicopter's moment of inertia matrix The specific form is:

[0073] ;

[0074] in, For the object to orbit moment of inertia about axis rotation; For the object to orbit moment of inertia about axis rotation; For the object to orbit moment of inertia about axis rotation; For objects in The product of inertia in a plane represents the distribution of the mass of an object relative to and Asymmetry of the axis; For objects in The product of inertia in a plane represents the distribution of the mass of an object relative to and Asymmetry of the axis; For objects in The product of inertia in a plane represents the distribution of the mass of an object relative to and Axis asymmetry; since the moment of inertia matrix is symmetric, .

[0075] Gravity on the helicopter The specific form in the body axis system is:

[0076] ;

[0077] represents the pitch angle of the helicopter, the net external force Expressed as: ,in, represents the acceleration due to gravity; Expressed as:

[0078] ;

[0079] in, Include 、 、 Three components, expressed in the body axis system 、 、 The resultant force of the three axes; 、 、 Represents the helicopter rotor 、 、 The forces generated in three axes; 、 、 Respectively represent the helicopter fuselage 、 、 The forces generated in three axes; 、 、 Respectively represent the helicopter tail rotor 、 、 The forces generated in three axes; 、 、 Represents the vertical tail of the helicopter 、 、 The forces generated in three axes; 、 、 Represents the horizontal tail of the helicopter 、 、 Force generated in three axes.

[0080] It represents the net external torque, and its specific form is:

[0081] ;

[0082] in 、 、 Represents the helicopter rotor 、 、 The torque generated by the three axes; 、 、 Respectively represent the helicopter fuselage 、 、 The torque generated by the three axes; 、 、 Respectively represent the helicopter tail rotor 、 、 The torque generated by the three axes; 、 、 Represents the vertical tail of the helicopter 、 、 The torque generated by the three axes; 、 、 Represents the horizontal tail of the helicopter 、 、 The torque generated on three axes.

[0083] The six-degree-of-freedom kinematic equations of the helicopter are constructed as follows:

[0084] ;

[0085] ;

[0086] Helicopter attitude angle , , With body axis , , Three-axis angular velocity , , The relationship is:

[0087] ;

[0088] in, is the mass of the helicopter; 、 、 They represent the velocity components of the helicopter's longitudinal axis, transverse axis, and vertical axis in the body axis system respectively; , , Respectively expressed in the body axis system 、 、 Angular velocity of three axes; , , Represent the pitch angle, roll angle and yaw angle of the helicopter respectively; 、 、 Respectively expressed in the body axis system 、 、 Three-axis forces; 、 、 Respectively expressed in the body axis system 、 、 The acting moments on the three axes; 、 、 They represent the roll angular velocity, yaw angular velocity, and pitch angular velocity respectively; 、 、 Represents the helicopter orbiting 、 、 Moment of inertia of the three axes; 、 、 Respectively 、 、 The derivative of 、 、 Respectively 、 、 The derivative of For objects in Product of inertia in the plane; Represents the acceleration due to gravity.

[0089] Step 2: Based on the helicopter's six-degree-of-freedom kinematic equations, construct an explicit model tracking control system as follows:

[0090] The explicit model tracking control system specifically includes:

[0091] Horizontal channel:

[0092] ;

[0093] Longitudinal channel:

[0094] ;

[0095] Heading channel:

[0096] ;

[0097] Total channel:

[0098] ;

[0099] in, 、 、 、 Represent the model bandwidth of the lateral, longitudinal, heading and collective channels respectively; is the damping coefficient; 、 、 、 Respectively represent the roll angle command output, pitch angle command output, yaw rate command output, and vertical velocity command output; 、 、 、 Respectively represent the roll angle command input, pitch angle command input, yaw rate command input, and vertical speed command input; represents the complex frequency variable in the Laplace transform.

[0100] In specific applications, according to the bandwidth and damping coefficient of the real dynamic model of the helicopter, refer to the requirements of the relevant specifications (ADS-33C), 、 、 、 All set to , Set to 0.7.

[0101] Step 3: Design a zero-difference disturbance tracking state observer to suppress system vibration caused by harmonic disturbances and improve system control accuracy.

[0102] Step 3.1, the first-order linear system is expressed as:

[0103] ;

[0104] in, is the system status; is the output of the system; is the gain of the input system; is the total disturbance of the system.

[0105] Step 3.2: The expansion state formula corresponding to the first-order system is:

[0106] ;

[0107] Among them, the expansion state ; is the nominal gain of the input system.

[0108] Step 3.3: The ESO corresponding to the first-order system is expressed as:

[0109] ;

[0110] in, Is the system status Tracking estimates; It is in expansion state Tracking estimates; Parameters of the Extended State Observer (ESO); 、 They are The derivative of .

[0111] Step 3.4, let , from steps 3.2 and 3.3 we can get:

[0112] ;

[0113] in, represents the system disturbance error, Indicates the rate of change of the system disturbance error.

[0114] Step 3.5: Based on the above, we can get:

[0115] ;

[0116] Finally, the dynamic equation of the zero-disturbance tracking state observer system is:

[0117] ;

[0118] in, is the total disturbance estimate of the system.

[0119] Step 4: Design the tracking control law of the helicopter based on the explicit model tracking control system and the zero-disturbance tracking state observer.

[0120] The linear state equation of the helicopter dynamics is

[0121] ;

[0122] Where, , is a 9×9 state matrix, It is a 9×4 control matrix; , representing the control input signals of the four channel actuators of lateral, longitudinal, heading and altitude respectively.

[0123] Step 4.1: Discretize the state equation using the backward difference method and set the sampling time to ;

[0124] ;

[0125] Convert the above formula into:

[0126] ;

[0127] Left multiplication We can get:

[0128] ;

[0129] make , , the discretized dynamic equation of the helicopter is:

[0130] ;

[0131] in, In discrete time The state vector at the moment; Represents a discrete state matrix, which mainly describes the dynamic relationship between states; Represents the discrete control matrix, which mainly describes the influence of control input on state change; represents a discrete time step; Indicates The amount of state change at a moment; Indicates The change in control input at time.

[0132] Step 4.2: Since the above formula is derived by linearization near the balancing point, substituting the state and control vector of the balancing point into the equation, we can get the result:

[0133] ;

[0134] Based on the assumption that tracking is achieved in one beat, the system enters a new balancing state after one sampling period, and we can get:

[0135] ;

[0136] Substituting the above equation into the state and control vector of the trim point, we can get:

[0137] ;

[0138] in, represents the target control input; represents the control input vector; Represents the state vector.

[0139] Step 4.3 The output of the controller consists of a proportional part and an integral part, which can be expressed as:

[0140] ;

[0141] in, Indicates proportional control input; Represents the integral control input.

[0142] According to the above important assumptions , we can get: ,

[0143] .

[0144] Step 4.4: Set the desired posture , we can get:

[0145] ;

[0146] in, Expressing an expectation posture; Indicates state error;

[0147] exist time, The controller proportional output is:

[0148] ;

[0149] in, That is The solution of the controller is:

[0150] .

[0151] Step 4.5: Due to It is a 9×4 matrix and cannot be directly inverted. Divided into the control matrix of the controlled quantity , and the control matrix of the uncontrolled quantity , and obtain the control matrix ;

[0152] ;

[0153] Finally, the tracking control law is:

[0154] .

[0155] According to the method of the present invention, the simulation results are as follows:

[0156] The control method designed by the present invention is simulated to input the ideal pitch angle As an example, the single-channel tracking effects of pitch angle, roll angle, yaw angle rate and vertical rate are tested respectively, and the results are as follows Figures 2 to 5 The simulation results are shown in Figure 2. Figure 2 As shown, the simulation time is set to 70s, and the ideal pitch angle is input After that, the actual pitch angle converges to the command value in about 20s. , the steady-state error is less than 1.8°, the dynamic process is smooth without obvious oscillation, and it meets the requirements of helicopter pitch control. Figure 3 As shown in Figure 2, the maximum instantaneous offset of the roll angle caused by the pitch maneuver is about 0.2°, but the controller can suppress it within only 12 seconds, indicating that the pitch angle tracking effect is good and the system can track stably. Figure 4As shown in Figure 1, the maximum deviation of the yaw rate is 0.25° / s, because the change in the fuselage attitude caused by pitching leads to aerodynamic side force, but by coordinating the tail rotor action through control distribution, no significant yaw oscillation is caused. Figure 5 As shown, the vertical velocity fluctuation is less than 0.2 m / s, indicating that the control module effectively balances the lift disturbance caused by the pitch maneuver. The system can quickly respond to and stably track the command values for pitch angle, roll angle, yaw rate, and vertical velocity within a short period of time, demonstrating the good performance of the control system, with strong stability and rapidity.

[0157] In summary, the EFDT-ESO-based explicit model tracking flight control method has demonstrated significant advantages in the field of helicopter flight control. This method not only effectively improves the helicopter's flight control quality, enabling more precise and stable flight attitude adjustments, but also significantly reduces the pilot's workload. In actual flight, it suppresses system vibrations caused by harmonic disturbances in the control system, which is crucial for ensuring flight safety and extending the helicopter's service life. This significantly improves the control system's accuracy and stability, enabling the helicopter to maintain excellent flight performance even in complex flight environments. This has significantly promoted the development of helicopter flight control technology and provided pilots with a safer and more reliable flight experience.

[0158] The above description is merely a specific embodiment of the present invention, which enables those skilled in the art to understand or implement the present invention. Although detailed descriptions have been made with reference to the aforementioned embodiments, those skilled in the art should understand that they may still modify the technical solutions described in the aforementioned embodiments, or replace some or all of the technical features therein with equivalents; and such modifications or replacements do not deviate from the essence of the corresponding technical solutions within the scope of the technical solutions of the embodiments, and they should all be included in the scope of protection of the claims.

Claims

1. An explicit model tracking flight control method based on EFDT-ESO, characterized by: The steps include: Step 1: Construct the helicopter's six-degree-of-freedom kinematic equations based on the aerodynamic models of the helicopter's rotor, fuselage, tail rotor, vertical tail, and horizontal tail; Step 2: Based on the helicopter's six-degree-of-freedom kinematic equations, construct an explicit model tracking control system; Step 3: Design a zero-difference disturbance tracking state observer to suppress system vibration caused by harmonic disturbances and improve system control accuracy; Step 4: Design the tracking control law of the helicopter based on the explicit model tracking control system and the zero-disturbance tracking state observer.

2. The EFDT-ESO-based explicit model tracking flight control method according to claim 1, characterized in that: In step 1, the six-degree-of-freedom kinematic equations of the helicopter include the linear motion equations of the center of mass translation and the angular rotation equations around the center of mass. The original equations are: ； in, is the mass of the helicopter; , represents the body axis system 、 、 Angular velocity of three axes; is the rate of change of the helicopter's angular velocity; , represents the body axis system 、 、 Linear speed of three axes; is the rate of change of velocity; represents the net external force acting on the helicopter; is the moment of inertia matrix of the helicopter; Expressed as the net external torque.

3. The EFDT-ESO based explicit model tracking flight control method according to claim 2, characterized in that: Helicopter's moment of inertia matrix The specific form is: ； in, For the object to orbit moment of inertia about axis rotation; For the object to orbit moment of inertia about axis rotation; For the object to orbit moment of inertia about axis rotation; For objects in Product of inertia in the plane; For objects in Product of inertia in the plane; For objects in Product of inertia in the plane; ; Gravity on the helicopter The specific form in the body axis system is: ； represents the pitch angle of the helicopter, the net external force Expressed as: ,in, represents the acceleration due to gravity; Expressed as: ； in, Include 、 、 Three components, expressed in the body axis system 、 、 The resultant force of the three axes; 、 、 Represents the helicopter rotor 、 、 The forces generated in three axes; 、 、 Respectively represent the helicopter fuselage 、 、 The forces generated in three axes; 、 、 Respectively represent the helicopter tail rotor 、 、 The forces generated in three axes; 、 、 Represents the vertical tail of the helicopter 、 、 The forces generated in three axes; 、 、 Represents the horizontal tail of the helicopter 、 、 The forces generated in three axes; It represents the net external torque, and its specific form is: ； in 、 、 Represents the helicopter rotor 、 、 The torque generated by the three axes; 、 、 Respectively represent the helicopter fuselage 、 、 The torque generated by the three axes; 、 、 Respectively represent the helicopter tail rotor 、 、 The torque generated by the three axes; 、 、 Represents the vertical tail of the helicopter 、 、 The torque generated by the three axes; 、 、 Represents the horizontal tail of the helicopter 、 、 The torque generated on three axes.

4. The EFDT-ESO based explicit model tracking flight control method according to claim 3, characterized in that: The six-degree-of-freedom kinematic equations of the helicopter are constructed as follows: ； ； Helicopter attitude angle , , With body axis 、 、 Three-axis angular velocity , , The relationship is: ； in, is the mass of the helicopter; 、 、 They represent the velocity components of the helicopter's longitudinal axis, transverse axis, and vertical axis in the body axis system respectively; , , Respectively expressed in the body axis system 、 、 Angular velocity of three axes; , , Represent the pitch angle, roll angle and yaw angle of the helicopter respectively; 、 、 Respectively expressed in the body axis system 、 、 Three-axis forces; 、 、 Respectively expressed in the body axis system 、 、 The acting moments on the three axes; 、 、 They represent the roll angular velocity, yaw angular velocity, and pitch angular velocity respectively; 、 、 Represents the helicopter orbiting 、 、 Moment of inertia of the three axes; 、 、 Respectively 、 、 The derivative of 、 、 Respectively 、 、 The derivative of For objects in Product of inertia in the plane; Represents the acceleration due to gravity.

5. The EFDT-ESO based explicit model tracking flight control method according to claim 1, characterized in that: In step 2, the explicit model tracking control system specifically includes: Horizontal channel: ； Longitudinal channel: ； Heading channel: ； Total channel: ； in, 、 、 、 Represent the model bandwidth of the lateral, longitudinal, heading and collective channels respectively; is the damping coefficient; 、 、 、 Respectively represent the roll angle command output, pitch angle command output, yaw rate command output, and vertical velocity command output; 、 、 、 Respectively represent the roll angle command input, pitch angle command input, yaw rate command input, and vertical speed command input; represents the complex frequency variable in the Laplace transform.

6. The EFDT-ESO based explicit model tracking flight control method according to claim 5, characterized in that: 、 、 、 All set to , Set to 0.

7.

7. The EFDT-ESO based explicit model tracking flight control method according to claim 1, characterized in that: In step 3, the dynamic equation of the zero-disturbance tracking state observer system is: ； in, is the system status; is the output of the system; is the gain of the input system; represents the nominal gain of the input system; Is the system status Tracking estimates; It is in expansion state Tracking estimates; are the parameters of the extended state observer ESO; is the total disturbance estimate of the system; 、 They are The derivative of .

8. The EFDT-ESO based explicit model tracking flight control method according to claim 7, characterized in that: Step 3 is as follows: Step 3.1: The first-order linear system is expressed as: ； in, is the gain of the input system; is the total disturbance of the system; Step 3.2: The expansion state formula corresponding to the first-order system is: ； Among them, the expansion state ; is the nominal gain of the input system; Step 3.3: The ESO corresponding to the first-order system is expressed as: ； Step 3.4: Make , from steps 3.2 and 3.3: ； in, represents the system disturbance error, Indicates the rate of change of system disturbance error; Step 3.5: Based on the above, we can get: ； Finally, the dynamic equation of the zero-disturbance tracking state observer system is: 。 9. The EFDT-ESO based explicit model tracking flight control method according to claim 1, characterized in that: Step 4 is as follows: The linear state equation of the helicopter dynamics is ； Where, , is a 9×9 state matrix, It is a 9×4 control matrix; , respectively representing the control input signals for the actuators of the four channels: lateral, longitudinal, heading, and altitude; Step 4.1: Discretize the state equation using the backward difference method, and obtain the helicopter discretized dynamic equation as follows: ； in, In discrete time The state vector at the moment; represents the discrete state matrix; represents the discrete control matrix; represents a discrete time step; Indicates The amount of state change at a moment; Indicates The change in control input at each moment; Step 4.2: After one sampling period, the system enters a new trim state. Substituting the trim point state and control vector, we get: ； in, represents the target control input; represents the control input vector; represents the state vector; Step 4.3 The output of the controller consists of a proportional part and an integral part, which can be expressed as: ； in, Indicates proportional control input; represents the integral control input; According to the assumption ,have to: , ； Step 4.4: Set the desired posture ,have to: ； in, Expressing an expectation posture; Indicates state error; exist time, The controller proportional output is: ； in, That is The solution of the controller is: ； Step 4.5: Control matrix Divided into the control matrix of the controlled quantity , and the control matrix of the uncontrolled quantity , and obtain the control matrix ; ； Finally, the tracking control law is: 。

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