Unmanned aerial vehicle feedforward control law design method based on nonlinear interference observer

Abstract

The invention discloses an unmanned aerial vehicle feedforward control law design method based on a non-linear interference observer, and relates to the technical field of unmanned aerial vehicle control laws, and the technical scheme is characterized in that the method comprises the steps: building an interference observer-oriented kinetic equation of an unmanned aerial vehicle; designing a disturbance observer equation; calculating to obtain an interference estimation value according to the interference observer equation; and enabling the interference estimation value to pass through a feed-forward controller to obtain a feed-forward control part based on the interference observer, and adding the feed-forward control part with a PID feedback control part to obtain a PID controller based on the interference observer. According to the method, strong external interference in an extreme wind field is estimated, interference characteristics are extracted, interference data processing is performed, a feedforward control law is designed by using an interference estimated value, active anti-interference control of interference is realized, adverse effects of the interference on large-maneuvering flight of an aircraft are offset, and stable flight of the unmanned aerial vehicle in strong wind is assisted.

Description

Technical Field

[0001] The present invention relates to the technical field of unmanned aerial vehicle control law, and more specifically, to a design method of unmanned aerial vehicle feedforward control law based on nonlinear disturbance observer. Background Art

[0002] Unmanned aerial vehicle (UAV) refers to an unmanned aircraft controlled by radio remote control equipment and self-contained program control devices, including unmanned fixed-wing aircraft, unmanned vertical take-off and landing aircraft, unmanned airships, unmanned helicopters, unmanned multi-rotor aircraft, etc.

[0003] With the rapid development of UAV technology, UAV technology has made significant progress in flight control, navigation and positioning, payload carrying, communication transmission, etc. The improvement of these technologies has made the flight of UAVs in complex environments more stable and accurate, and can achieve centimeter-level or even millimeter-level positioning accuracy. It can carry more diverse mission equipment and can transmit high-definition images, videos and other data in real time to provide support for remote monitoring and command, so that it can meet the needs of different fields. The application scenarios are constantly expanding, from the initial military applications to the civilian field, such as power inspection, agricultural monitoring, environmental monitoring, logistics and transportation, etc. The UAV industry will continue to maintain a good development momentum.

[0004] At present, UAVs usually encounter the problem of strong wind interference when performing flight missions, which makes the UAV face the situation of reduced flight stability, reduced track tracking performance, and possible structural damage. Some improvements on the structure of UAVs have also been proposed in the prior art, such as forming a windproof enclosure when the UAV lands to reduce the interference of strong winds on the UAV and improve the accuracy and safety of landing, and installing a windshield on the outside of the UAV wing and cooperating with a wind vane to detect the wind direction to achieve automatic and accurate wind resistance; however, the UAV windproof device is only an improvement on its physical structure, and the effect is not significant during the actual flight process. In addition, the environment in which the UAV is located when performing flight missions is dynamically changing, and the UAV needs to achieve rapid response and adapt to the control requirements of multiple types of UAVs and multiple mission scenarios. This is crucial for the UAV to make rapid adjustments and maneuverable flights in a dynamically changing environment.

[0005] Therefore, the present invention aims to provide a UAV feedforward control law design method based on nonlinear disturbance observer to solve the above problems. Summary of the invention

[0006] The purpose of the present invention is to provide a method for designing a feedforward control law for a UAV based on a nonlinear disturbance observer. The present invention estimates the strong external disturbance under extreme wind fields, extracts disturbance characteristics, processes disturbance data, and designs a feedforward control law using the disturbance estimation value, thereby realizing active anti-disturbance control of the disturbance and offsetting its adverse effects on the large maneuvering flight of the aircraft. The method has the advantages that both feedback control and feedforward design satisfy the corresponding separation principles, that is, tracking control performance and disturbance suppression performance can be achieved by respectively adjusting the feedback controller and the feedforward controller, thereby solving the instability problem of the UAV when facing strong wind disturbance and helping the UAV to fly stably in strong winds.

[0007] The above technical objectives of the present invention are achieved through the following technical solutions: A method for designing a feedforward control law for an unmanned aerial vehicle based on a nonlinear disturbance observer, comprising the following steps:

[0008] S1. Establish the dynamic equation of the UAV facing the disturbance observer;

[0009] S2, design disturbance observer equation;

[0010] S3, calculating the interference estimation value according to the interference observer equation;

[0011] S4. The disturbance estimation value is passed through a feedforward controller to obtain a feedforward control part based on a disturbance observer, and is added to the PID feedback control part to obtain a PID controller based on a disturbance observer.

[0012] The present invention is further configured as follows: when there is wind disturbance, the dynamic equation for the disturbance observer is expressed as follows:

[0013]

[0014] Among them, φ, θ, ψ represent the roll angle, pitch angle and yaw angle respectively, M xplane , M yplane , M zplane They represent the moments of the aircraft body about the x, y, and z axes of the body axis system, respectively. xx ,I yy ,I zz They represent the inertia moment of the aircraft, L δa ,L δe ,L δr They represent the control effectiveness of aileron, elevator and rudder respectively, δ a ,δ e ,δ r Indicates the control amount of aileron, elevator and rudder, d x ,d y ,d z Respectively represent interference.

[0015] The present invention is further configured as follows: the disturbance observer equation is expressed in the form of:

[0016]

[0017] Where z is the internal state of the disturbance observer, p(x) is the nonlinear function to be designed, and l(x) is the gain of the nonlinear disturbance observer, which is determined by the following formula:

[0018]

[0019] For the disturbance observer of the three postures of the UAV, p(x) is designed as:

[0020] p(x)=λx2

[0021] in, Then l(x) = λ, f(x), g1(x), g2(x) are the corresponding parameters in the aircraft dynamics equation, and the estimated value of the interference is calculated from this

[0022] The present invention is further configured as follows: the process of obtaining the PID controller based on the disturbance observer in step S4 is as follows: the disturbance estimation value passes through the feedforward controller, and is divided by the control efficiency of each actuator to calculate the fault loss of the actuator, thereby obtaining the feedforward control part u based on the disturbance observer. ff , through the cascade PID feedback control part u fb Add together and then get the feedforward feedback comprehensive robust control based on disturbance observer.

[0023] In summary, the present invention has the following beneficial effects:

[0024] 1. Faster response to disturbance processing: The present invention provides a feedforward compensation term for the disturbance observer to directly offset the disturbance in the control system, while the passive anti-interference method only suppresses the disturbance through passive feedback regulation, so that the disturbance observer control method of the present invention can always obtain a faster dynamic response when processing disturbances;

[0025] 2. It has a "patch" feature: the disturbance feedforward compensation term in the present invention can be regarded as a patch to the existing feedback control. The advantage of this is that there is no need to change the PID feedback control. In the absence of disturbance, the disturbance observer only outputs a zero disturbance estimate. The PID control law based on the disturbance observer can be simplified to a basic PID controller to maintain the nominal tracking performance. Therefore, in this case, the present invention does not require poor transient performance and excessive control energy to suppress disturbances.

[0026] 3. Low conservatism: The interference observer in the present invention is not designed based on the worst case scenario, and can estimate and compensate for interference online. Therefore, it has outstanding adaptability and low conservatism, avoiding the fact that most existing robust control methods are designed based on the worst case scenario. The cost of good robustness is to reduce the nominal performance, so they are too conservative. The interference observer in the present invention can be regarded as a "refined" robust control method, so that the technical solution of the present invention can solve the instability problem of drones facing strong wind interference and help drones to fly stably in strong winds. BRIEF DESCRIPTION OF THE DRAWINGS

[0027] Figure 1 This is a basic framework diagram of a method for designing a feedforward control law for a UAV based on a nonlinear disturbance observer in an embodiment of the present invention;

[0028] Figure 2 1 is a control framework diagram of a nonlinear disturbance observer in an embodiment of the present invention. DETAILED DESCRIPTION

[0029] The following is combined with Figure 1-2 The present invention is described in further detail.

[0030] Embodiment: A method for designing a feedforward control law for a UAV based on a nonlinear disturbance observer comprises the following steps:

[0031] S1. Establish the dynamic equations of the UAV facing the disturbance observer.

[0032] The basic framework of the interference observer used in this embodiment is as follows: Figure 1 As shown, a nonlinear disturbance observer module is introduced into the attitude loop to estimate the disturbance, so that the pitch angle controller can achieve better tracking effect under strong interference environment.

[0033] In this embodiment, the composite controller of the disturbance observer consists of two parts:

[0034] u=u fb +u ff

[0035] Among them, u fb It is the feedback control part, which is usually used for tracking and stabilizing the nominal dynamics of the controlled object. In this part, disturbances and uncertainties do not need to be considered. ff For the feedforward control part based on disturbance observer, the uncertainty of the controlled object is estimated by disturbance observer and then compensated by feedforward control.

[0036] For a nonlinear affine system with the following characteristics:

[0037]

[0038] Among them, x, u, d, and y represent the state quantity, control input, interference, and output vector respectively. For the aircraft under study, taking pitch control as an example, its dynamic equation is written in the above form, which can be expressed as:

[0039]

[0040] Among them, φ, θ, ψ represent the roll angle, pitch angle and yaw angle respectively, M xplane , M yplane , M zplane They represent the moments of the aircraft body about the x, y, and z axes of the body axis system, respectively. xx ,I yy ,I zz They represent the inertia moment of the aircraft, L δa ,L δe ,L δr They represent the control effectiveness of aileron, elevator and rudder respectively, δ a ,δ e ,δ r Indicates the control amount of aileron, elevator and rudder.

[0041] When there is strong interference, the dynamic equation of the aircraft can be expressed as:

[0042]

[0043] Among them, d x ,d y ,d z is the disturbance value that the disturbance observer needs to estimate.

[0044] S2. After obtaining the dynamic equation of the aircraft facing the disturbance observer, we can Figure 2 The disturbance observer equation is designed in the structural form.

[0045] The disturbance observer equation in this embodiment is expressed as:

[0046]

[0047] Where z is the internal state of the disturbance observer, p(x) is the nonlinear function to be designed, and l(x) is the gain of the nonlinear disturbance observer, which is determined by the following formula:

[0048]

[0049] For the disturbance observer of the three postures of the UAV, p(x) is designed as:

[0050] p(x)=λx2

[0051] in, Then l(x)=λ, f(x), g1(x), g2(x) are the corresponding parameters in the aircraft dynamics equations.

[0052] S3. Calculate the interference estimate according to the interference observer equation

[0053] S4. The calculated disturbance estimate is passed through the feedforward controller and divided by the control efficiency of each actuator to calculate the actuator failure loss, thereby obtaining the feedforward control part u based on the disturbance device. ff , through the cascade PID feedback control part u fb Add together and then get the feedforward feedback comprehensive robust control based on disturbance observer.

[0054] This specific embodiment is merely an explanation of the present invention and is not a limitation of the present invention. After reading this specification, those skilled in the art may make non-creative modifications to the present embodiment as needed. However, as long as they are within the scope of the claims of the present invention, they are protected by the patent law.

Claims

1. A method for designing a feedforward control law for an unmanned aerial vehicle based on a nonlinear disturbance observer, characterized by: The following steps are involved: S1. Establish the dynamic equation of the UAV facing the disturbance observer; S2, design disturbance observer equation; S3, calculating the interference estimation value according to the interference observer equation; S4. The disturbance estimation value is passed through a feedforward controller to obtain a feedforward control part based on a disturbance observer, and is added to the PID feedback control part to obtain a PID controller based on a disturbance observer.

2. The method for designing a feedforward control law for an unmanned aerial vehicle based on a nonlinear disturbance observer according to claim 1 is characterized by: The dynamic equation for the disturbance observer in the presence of wind disturbance is expressed as: Among them, φ, θ, ψ represent the roll angle, pitch angle and yaw angle respectively, M xplane , M yplane , M zplane They represent the moments of the aircraft body about the x, y, and z axes of the body axis system, respectively. xx ,I yy ,I zz They represent the inertia moment of the aircraft, L δa ,L δe ,L δr They represent the control effectiveness of aileron, elevator and rudder respectively, δ a ,δ e ,δ r Indicates the control amount of aileron, elevator and rudder, d x ,d y ,d z Respectively represent interference.

3. The method for designing a feedforward control law for an unmanned aerial vehicle based on a nonlinear disturbance observer according to claim 1 is characterized by: The disturbance observer equation is expressed as: Where z is the internal state of the disturbance observer, p(x) is the nonlinear function to be designed, and l(x) is the gain of the nonlinear disturbance observer, which is determined by the following formula: For the disturbance observer of the three postures of the UAV, p(x) is designed as: p(x)=λx2 in, Then l(x) = λ, f(x), g1(x), g2(x) are the corresponding parameters in the aircraft dynamics equation, and the estimated value of the interference is calculated from this 4. The method for designing a feedforward control law for an unmanned aerial vehicle based on a nonlinear disturbance observer according to claim 1 is characterized by: The process of obtaining the PID controller based on the disturbance observer in step S4 is as follows: the disturbance estimate passes through the feedforward controller, and is divided by the control efficiency of each actuator to calculate the fault loss of the actuator, thereby obtaining the feedforward control part u based on the disturbance observer. ff , through the cascade PID feedback control part u fb Add together and then get the feedforward feedback comprehensive robust control based on disturbance observer.

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