Unmanned aerial vehicle energy-saving anti-wind disturbance flight control method based on wind energy utilization

Abstract

The invention relates to the technical field of unmanned aerial vehicle flight control, and relates to an unmanned aerial vehicle energy-saving anti-wind disturbance flight control method based on wind energy utilization. Firstly, a wind field is subjected to partial modeling, partial dynamic characteristics of the environment wind field are fused into an unmanned aerial vehicle kinetic model, and quantitative analysis of the influence of the wind field on flight is achieved; secondly, a sliding mode control strategy is adopted, and the anti-interference capability of the unmanned aerial vehicle in a wind field is improved; meanwhile, a disturbance observer is designed, wind field disturbance characteristics are estimated in real time, wind energy utilization judgment conditions are provided based on mechanical analysis, and an unmanned aerial vehicle control strategy is dynamically adjusted. Wind field energy is effectively utilized by combining wind field modeling, a disturbance observer and a sliding mode control strategy and analyzing the influence of wind energy on the flight of the quad-rotor unmanned aerial vehicle, so that the flight energy efficiency is improved, the wind disturbance resistance is enhanced, and the method can be widely applied to unmanned aerial vehicle inspection, environment monitoring, emergency rescue and other tasks and has wide application prospects. The method is especially suitable for flight scenes with complex wind fields and limited energy supply.

Description

Technical Field

[0001] The present invention relates to the technical field of unmanned aerial vehicle flight control, and in particular to an unmanned aerial vehicle energy-saving and wind-disturbance-resistant flight control method based on wind energy utilization. Background Art

[0002] Quad-rotor drones are widely used in environmental monitoring, logistics, disaster relief, and inspection due to their simple structure, strong maneuverability, and flexible control. However, since they rely on the rotors to generate lift and control torque, they are easily disturbed by external wind fields during actual flight, especially in complex environments such as low-altitude wind shear and gusts. They are prone to problems such as unstable attitude, trajectory deviation, and increased energy consumption. The current UAV flight control system mainly focuses on improving the ability to resist wind disturbance, but there is little research on wind energy utilization, and the potential boost of environmental wind energy to UAV flight has not been effectively explored. Therefore, how to reasonably utilize wind energy to achieve energy-saving flight of UAVs while resisting wind disturbance is still a problem that needs to be solved urgently.

[0003] At present, the anti-wind disturbance control of UAVs mainly relies on methods such as robust control, adaptive control and predictive control. Among them, robust control improves the stability of UAVs in wind fields by enhancing the anti-interference ability of the system, but it is usually conservative and difficult to take into account energy efficiency; adaptive control can adjust the control strategy according to the changes in the wind field, but it has high real-time requirements and is easily affected by sensor noise; predictive control relies on the estimation of future wind fields to optimize control inputs, but in complex wind fields, the prediction accuracy is difficult to guarantee and the computational cost is also high. In addition, the existing control methods mainly focus on weakening the impact of wind field disturbances on UAVs, but less on how to reasonably utilize wind field energy to assist flight and reduce energy consumption. This means that current UAVs still face large energy consumption and endurance bottlenecks when flying in complex environments. Summary of the invention

[0004] The purpose of the present invention is to provide an energy-saving and wind-resistant flight control method for UAVs based on wind energy utilization, so as to solve the problems of high energy consumption, limited wind resistance and inability to effectively utilize wind energy when flying in a wind field environment proposed in the above-mentioned background technology.

[0005] To achieve the above object, the present invention provides an energy-saving and wind-disturbance-resistant flight control method for a UAV based on wind energy utilization, comprising the following steps:

[0006] S1. Establish a wind field dynamics model suitable for quad-rotor UAVs and integrate it into the UAV dynamics equation to quantitatively analyze the impact of wind field on UAV flight;

[0007] S2. Design a sliding mode controller to control the UAV flying under wind field disturbance through sliding mode control strategy;

[0008] S3. Construct a disturbance observer to estimate the residual wind disturbance and lumped disturbance in real time, and propose wind energy utilization judgment conditions based on the analysis of wind field mechanical characteristics;

[0009] S4. When the conditions for wind energy utilization are met, adjust the UAV control strategy and use the wind field energy to partially replace the UAV's own power requirements.

[0010] As a further improvement of the technical solution, the wind field dynamics model in step S1 includes the integration of the following components:

[0011] Average wind component , obtained by measuring the environmental reference wind speed;

[0012] Wind shear component , according to the flight altitude and wind shear formula Calculate, where is the height at which the mean wind component is measured, is the wind shear index.

[0013] As a further improvement of the technical solution, the sliding mode controller design in step S2 includes:

[0014] Terminal sliding mode function ,in , , are the designed parameters;

[0015] By controlling the amount, the accessibility of the sliding surface is ensured.

[0016] As a further improvement of the technical solution, the disturbance observer in step S3 is designed as follows:

[0017]

[0018] As a further improvement of the technical solution, the wind energy utilization judgment condition in step S4 includes:

[0019] Wind field disturbance utilization conditions ;

[0020] Residual disturbance utilization conditions ;

[0021] when =0 or =0, the corresponding disturbance is retained to assist flight.

[0022] As a further improvement of the technical solution, the dynamic adjustment of the control strategy is achieved by updating the control amount:

[0023]

[0024] in, The value is determined according to the judgment condition of step S4.

[0025] As a further improvement of the technical solution, when the energy-saving flight is realized by utilizing the disturbance in the operating environment in step S4, the effectiveness of the energy-saving flight needs to be further judged by the following steps:

[0026] Select the Lyapunov function as , combined with the sliding mode function and control algorithms right The derivative is:

[0027]

[0028] When the disturbance characteristics meet the utilization conditions, and Take 0 to retain the influence of disturbance, thereby improving The speed tends to 0 to achieve energy-saving and anti-interference flight.

[0029] Compared with the prior art, the present invention has the following beneficial effects:

[0030] 1. Improve the ability to resist wind disturbance: The sliding mode control strategy enhances the system's robustness to wind field disturbances and improves the stability of the UAV in strong wind environments.

[0031] 2. Reduce flight energy consumption: Through wind energy utilization strategies, reduce the energy consumption of the drone's own power system and improve endurance.

[0032] 3. Enhance environmental adaptability: Use wind field modeling and disturbance observers to perform real-time wind field disturbance estimation, so that the UAV can adapt to different wind field conditions and improve flight flexibility and reliability.

[0033] 4. Optimize flight control strategy: Combine anti-wind disturbance control and wind energy utilization to achieve intelligent control of UAVs in wind fields and improve the execution efficiency of flight missions. BRIEF DESCRIPTION OF THE DRAWINGS

[0034] Figure 1 This is an overall control block diagram of the energy-saving and wind-disturbance-resistant flight control method for UAV based on wind energy utilization of the present invention.

[0035] Figure 2 The present invention is a flowchart of modeling the wind disturbance part of the UAV operating environment according to an embodiment of the present invention.

[0036] Figure 3 The present invention is a flowchart of an anti-disturbance control algorithm for a quadrotor drone based on sliding mode control according to an embodiment of the present invention.

[0037] Figure 4 This is a flow chart of an energy-saving and anti-interference flight method for a quad-rotor drone based on wind disturbance analysis according to an embodiment of the present invention. DETAILED DESCRIPTION

[0038] 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.

[0039] The present invention provides an energy-saving and wind-disturbance-resistant flight control method for a UAV based on wind energy utilization, comprising the following steps:

[0040] S1. Establish a wind field dynamics model suitable for quad-rotor UAVs and integrate it into the UAV dynamics equation to quantitatively analyze the impact of wind field on UAV flight;

[0041] S2. Design a sliding mode controller to control the UAV flying under wind field disturbance through sliding mode control strategy;

[0042] S3. Construct a disturbance observer to estimate the residual wind disturbance and lumped disturbance in real time, and propose wind energy utilization judgment conditions based on the analysis of wind field mechanical characteristics;

[0043] S4. When the conditions for wind energy utilization are met, adjust the UAV control strategy and use the wind field energy to partially replace the UAV's own power requirements.

[0044] Embodiment 1:

[0045] like Figure 1 As shown, the present invention provides an energy-saving anti-disturbance control method for a quad-rotor drone, the method comprising a user layer 10, an algorithm layer 20 and a device layer 30, and the functions of each layer are as follows:

[0046] User layer 10: The user observes the operating environment of the quadrotor drone in real time and sends control instructions through the control device 101. The instructions include information such as the desired position or posture. The function of the control device is limited to sending the desired state instruction without limiting the specific type of control device.

[0047] Algorithm layer 20: This layer includes a state error generation module 201, an anti-interference algorithm module 202 and an energy-saving algorithm module 203; wherein the anti-interference algorithm and the energy-saving algorithm are designed based on the state error respectively, and finally generate a control algorithm 204, which is formed by the synergistic effect of the anti-interference algorithm and the energy-saving algorithm to achieve stable control and energy optimization of the UAV.

[0048] Equipment layer 30: This layer corresponds to the quad-rotor drone and its operating environment. The wind energy in the environment is analyzed and utilized by the energy-saving algorithm 203 in the algorithm layer 20, so as to achieve energy-saving flight of the drone while ensuring flight stability.

[0049] Embodiment 2:

[0050] like Figure 2 As shown in the figure, in order to achieve energy-saving flight of a quad-rotor drone, the present invention constructs a state error model of the drone and a partial wind field model of the operating environment. The model can partially reflect the wind field characteristics in the environment where the drone is located and provide wind field disturbance information for the control algorithm. The specific steps are as follows:

[0051] Step S2-1: After the user layer issues a control instruction, the expected position given by the instruction is generated through the expected state , The UAV is in the spatial coordinate system. The desired position on the three axes is the given position that the quadcopter needs to track; the current position of the quadcopter obtained by GPS is set to , The UAV is in the spatial coordinate system. The actual position on the three axes, the final state error is set to , The UAV is in the spatial coordinate system The position error on the three axes is obtained by subtracting the desired position from the current position of the drone.

[0052] Step S2-2: Splitting the wind field into average wind components in wind field modeling , In the spatial coordinate system Average wind components on the three axes, as well as wind shear components , In the spatial coordinate system Wind shear components on the three axes: the average wind component is the baseline value of wind speed in the environment, which is the average wind speed at a certain height; the wind shear component is the increase in wind speed as the altitude of the drone increases. , the wind shear component of the drone is obtained by the wind shear formula, which is:

[0053]

[0054] in is the height at which the mean wind component is measured, is the wind shear index;

[0055] Step S2-3: Integrate the average wind component and the wind shear component to obtain some wind disturbances in the UAV operating environment , the magnitude and direction of the wind disturbance force of the drone are constructed according to the wind force formula. The wind force formula is:

[0056]

[0057] in , The UAV is in the spatial coordinate system The magnitude of the wind force on the three axes, is the drag coefficient of the drone, is the air density, is the windward area of ​​the UAV, is the speed difference between the drone and the wind speed, Used to determine whether the speed direction of the drone is consistent with the wind speed direction. Indicates that the speed direction is consistent. Indicates that the speed direction is inconsistent.

[0058] Embodiment three:

[0059] To achieve energy-saving flight control algorithms in the UAV operating environment, it is first necessary to ensure the stability of the UAV, that is, to ensure anti-interference capabilities. Traditional control algorithms are difficult to strike a balance between anti-interference performance and energy-saving performance, and usually require a trade-off between control accuracy and energy consumption.

[0060] The present invention firstly adopts a sliding mode control algorithm to realize the anti-disturbance control of the UAV, and then introduces an energy-saving algorithm on this basis, so that the UAV can use wind energy more efficiently and reduce energy consumption. Therefore, the present invention adopts a control strategy combining a sliding mode control algorithm with an energy-saving algorithm to improve the anti-wind disturbance capability of the UAV and realize energy-saving flight.

[0061] The specific control process of the UAV sliding mode control algorithm is as follows: Figure 3 As shown, the specific steps are as follows: Step S3-1: First, a mathematical model for controlling the position of the UAV is established by combining the wind field model:

[0062]

[0063] in For the quality of the drone, are the accelerations on the three axes, are the control quantities on the three axes respectively, are the drag coefficient, are the speeds on the three axes, are the wind disturbances on the three axes, are the residual lumped disturbances on the three axes respectively. According to the desired state, the controlled model is converted into an error model. Due to the symmetry of the quadrotor drone, only the control algorithm design on one axis is introduced here. In the present invention, the same control method is used on each axis, and the error model is:

[0064]

[0065] in They are Velocity error and acceleration error on the axis, for Desired acceleration on the axis;

[0066] Step S3-2: To achieve more effective tracking based on anti-disturbance, a terminal sliding mode control algorithm is used to achieve faster tracking and a sliding mode function is designed. for:

[0067]

[0068] in , are the design parameters, , are position error and velocity error respectively.

[0069] Step S3-3: Design a control algorithm to ensure the accessibility of the sliding surface and the anti-disturbance performance of the control algorithm for:

[0070] ,

[0071] in, It’s the quality of the drone. is the design parameter of the sliding mode function, is the upper bound of the remaining unknown disturbance About The symbolic function of

[0072] in Ensure the stability of the system.

[0073] Embodiment 4:

[0074] On the basis of realizing anti-disturbance control in step three, the energy-saving algorithm is further combined to realize the energy-saving flight of the quadcopter. The key to energy-saving flight lies in the accurate estimation of the external environment. Therefore, on the basis of partial modeling of the external wind field, it is also necessary to accurately estimate the residual wind disturbance and the lumped disturbance in the modeling. To this end, the present invention designs a disturbance observer to observe and estimate the influence of the residual wind disturbance and the lumped disturbance. In the stability analysis of sliding mode control, the Lyapunov analysis method is usually used, and the same method can also be used in the energy-saving effect analysis.

[0075] Based on the above analysis, the present invention first designs a disturbance observer based on the control algorithm in step 3, and analyzes the disturbance characteristics based on the observed values ​​and the wind field model to determine whether the disturbance is conducive to the energy-saving flight of the quadcopter. According to the judgment result, it is decided whether to use wind disturbance and the remaining concentrated disturbance to optimize the energy-saving flight of the drone. The specific energy-saving flight control process is as follows: Figure 4 As shown, the specific implementation steps are as follows:

[0076] Step S4-1: The mechanical characteristics of the wind field can be directly determined by the positive and negative characteristics of the wind force formula, while the determination of the characteristics of the remaining disturbance first requires accurate disturbance estimation. In the present invention, the disturbance observer is designed as:

[0077]

[0078] in are auxiliary variables, It is the observation gain. Based on the designed disturbance observer, the residual wind disturbance of the quadrotor UAV and the concentrated disturbance in the modeling can be accurately estimated. Combined with the partial wind disturbance information in the wind field model, the detailed characteristics of all disturbances to which the quadrotor UAV is subjected can be fully known.

[0079] Step S4-2: After knowing the characteristics of all disturbances, the energy-saving algorithm in the control algorithm can be designed according to the characteristics. The energy-saving algorithm is realized by utilizing the disturbances that are beneficial to the operation of the system, so it is necessary to design the utilization judgment conditions for each disturbance. First, design the wind disturbance utilization conditions in the wind field model:

[0080]

[0081] The judgment conditions It is used to ensure that the wind disturbance is retained when the force characteristics of the wind field disturbance are conducive to the stability of the system. Then the disturbance characteristics are judged, and the observation results are The characteristic design disturbance utilization conditions are:

[0082]

[0083] The judgment conditions It is used to ensure that disturbances are retained when the residual wind disturbances and the lumped disturbance characteristics in the modeling are conducive to the stability of the system.

[0084] Step S4-3: Based on the designed disturbance utilization characteristics and Figure 3 Combined with the control algorithm shown in the figure, the control algorithm is updated as follows:

[0085]

[0086] When the characteristics of the disturbance meet the utilization conditions in step S4-3, and will be eliminated to ensure that the control algorithm does not suppress disturbances in the operating environment of the quadcopter, thereby achieving effective utilization of these disturbances. When these disturbances can be utilized, the drone can use part of the energy in the environment to assist flight, thereby achieving energy-saving flight control.

[0087] Step S4-4: When using the disturbance in the operating environment to achieve energy-saving flight, it is necessary to further judge the effectiveness of energy-saving flight. In the control effect analysis of sliding mode control, the accessibility and stability of the system are usually judged by using the Lyapunov analysis method. Therefore, the present invention also uses the same method for analysis. The Lyapunov function is selected as , combined with the sliding mode function and control algorithms right The derivative is:

[0088]

[0089] When the disturbance characteristics meet the utilization conditions, and Take 0 to retain the influence of disturbance, thereby improving The speed tends to 0 to achieve energy-saving and anti-interference flight.

[0090] To sum up, the present invention uses a comprehensive control method of wind field modeling, sliding mode control, disturbance observation and wind energy utilization to enable the quadrotor UAV to fly stably, efficiently and energy-savingly in a wind field environment. It is suitable for various application scenarios such as inspection, logistics, emergency rescue, etc., and has broad application prospects and industrial value.

[0091] The above shows and describes the basic principles, main features and advantages of the present invention. Those skilled in the art should understand that the present invention is not limited by the above embodiments. The above embodiments and descriptions are only preferred examples of the present invention and are not intended to limit the present invention. Without departing from the spirit and scope of the present invention, the present invention may have various changes and improvements, which fall within the scope of the present invention. The scope of protection of the present invention is defined by the attached claims and their equivalents.

Claims

1. A wind energy-saving and wind-disturbance-resistant flight control method for a UAV, characterized in that: The following steps are involved: S1. Establish a wind field dynamics model suitable for quad-rotor UAVs and integrate it into the UAV dynamics equation to quantitatively analyze the impact of wind field on UAV flight; S2. Design a sliding mode controller to control the UAV flying under wind field disturbance through sliding mode control strategy; S3. Construct a disturbance observer to estimate the residual wind disturbance and lumped disturbance in real time, and propose wind energy utilization judgment conditions based on the analysis of wind field mechanical characteristics; S4. When the conditions for wind energy utilization are met, adjust the UAV control strategy and use the wind field energy to partially replace the UAV's own power requirements.

2. The energy-saving and wind-disturbance-resistant flight control method for unmanned aerial vehicles based on wind energy utilization according to claim 1 is characterized in that: The wind farm dynamics model in step S1 includes the integration of the following components: Average wind component , obtained by measuring the environmental reference wind speed; Wind shear component , according to the flight altitude and wind shear formula Calculate, where is the height at which the mean wind component is measured, is the wind shear index.

3. The energy-saving and wind-disturbance-resistant flight control method for unmanned aerial vehicles based on wind energy utilization according to claim 2 is characterized in that: The sliding mode controller design in step S2 includes: Construct an error model based on the mathematical model of the UAV position control; Terminal sliding mode function ,in , For the design parameters, , They are Position tracking error and velocity tracking error on the axis, The design can improve the convergence speed of sliding variables. ensure Tracking error ; By controlling the amount, the accessibility of the sliding surface is ensured.

4. The energy-saving and wind-disturbance-resistant flight control method for unmanned aerial vehicles based on wind energy utilization according to claim 3 is characterized in that: The disturbance observer in step S3 is designed as: ， in, are the auxiliary variables bypassing that observer, is the observation gain used to adjust the observation speed of the observer, For drones The output of the controller on the axis, is the drag coefficient of the drone, For no one The speed of the axis, For drones The wind disturbance force on the shaft is For drones The expected acceleration on the axis, for Velocity tracking error on the axis, is the perturbation observation result.

5. The energy-saving and wind-disturbance-resistant flight control method for unmanned aerial vehicles based on wind energy utilization according to claim 4 is characterized in that: The wind energy utilization judgment conditions in step S4 include: Wind field disturbance utilization conditions ; Residual disturbance utilization conditions ; When the disturbance characteristics satisfy or When the disturbance is judged to be beneficial to the stability of the system, the utilization condition is set to =0 or =0, retain the corresponding disturbance to assist flight.

6. The energy-saving and wind-disturbance-resistant flight control method for unmanned aerial vehicles based on wind energy utilization according to claim 5 is characterized in that: The dynamic adjustment of the control strategy is achieved by updating the control quantity: ； in, It’s the quality of the drone. is the sliding mode function design parameter, is the upper bound of the remaining unknown disturbance About The symbol function of It is to take a value according to the judgment condition of step S4.

7. The energy-saving and wind-disturbance-resistant flight control method for unmanned aerial vehicles based on wind energy utilization according to claim 6 is characterized in that: When the energy-saving flight is realized by utilizing the disturbance in the operating environment in step S4, the effectiveness of the energy-saving flight needs to be further judged through the following steps: Select the Lyapunov function as , combined with the sliding mode function and control algorithms right The derivative is: ； in is the upper bound of the remaining unknown disturbance, It is the wind disturbance power. is the observed value of the disturbance To take a value according to the judgment condition of step S4; When the disturbance characteristics meet the utilization conditions, and Take 0 to retain the influence of disturbance, thereby improving The speed tends to 0 to achieve energy-saving and anti-interference flight.

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