CN114217632B - Self-adaptive fault-tolerant unmanned aerial vehicle tracking cruise system and method - Google Patents
Self-adaptive fault-tolerant unmanned aerial vehicle tracking cruise system and method Download PDFInfo
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Abstract
The invention provides a self-adaptive fault-tolerant unmanned aerial vehicle tracking cruise system and a self-adaptive fault-tolerant unmanned aerial vehicle tracking cruise method, wherein the self-adaptive fault-tolerant unmanned aerial vehicle tracking cruise system comprises an unmanned aerial vehicle flight parameter acquisition module, a self-adaptive alignment calculation module, an early warning obstacle avoidance control module and a wireless power supply module; the self-adaptive alignment calculation module comprises an upper control module and a bottom control module, wherein the bottom control module comprises a position control module, a tension and gesture distribution module, a gesture control module and an accelerator control module, and the tension and gesture distribution module controls the position control module, the gesture control module and the accelerator control module to achieve the purpose of reaching a desired cruising route with minimum inclination angle and power. According to the invention, the three-dimensional attitude speed, position coordinates and three-dimensional stress condition of the unmanned aerial vehicle in the flight process can be monitored in real time, the random forest method is adopted for optimization iteration, deviation in the calculation process is avoided, and the active fault-tolerant control is carried out through the early warning obstacle avoidance control module, so that the unmanned aerial vehicle can be corrected in real time to deviate from the route, and cruising is carried out in the preset target cruising route.
Description
Technical Field
The invention belongs to the technical field of unmanned aerial vehicles, and particularly relates to a self-adaptive fault-tolerant unmanned aerial vehicle tracking cruise system and method.
Background
With the development of unmanned aerial vehicle technology, unmanned aerial vehicles are increasingly used for performing the task of cruising in the air. Meanwhile, the task environment of the unmanned aerial vehicle is more and more complex, so that the unmanned aerial vehicle is time-consuming and labor-consuming by means of the traditional manual track planning method, and task requirements are difficult to meet. The four-rotor unmanned aerial vehicle is a robot system which collects external information in real time through an airborne sensor and uploads the state of the four-rotor unmanned aerial vehicle, and completes work tasks in an autonomous or manual remote control mode. Compared with the traditional wheel type unmanned system, the four-rotor unmanned aerial vehicle can vertically take off and land, hover at fixed points, carry different operation tools in different landforms and areas, and has wide application prospects in the fields of disaster search and rescue, life service and the like.
In the prior art, as disclosed in chinese patent application 202010801338.2, an unmanned aerial vehicle cruises and tracking system and method based on deep learning technology, its main technical scheme is to adopt image real-time acquisition module to monitor whether there is dangerous article, dangerous action and dangerous personnel to get into unmanned aerial vehicle real-time monitoring's field, guarantee unmanned aerial vehicle's automatic tracking flight through video acquisition module, personnel tracking module, laser ranger module, flight control module etc. and make dangerous personnel be located the very center of picture, ground command post still can send control command (stop tracking, switch tracking target etc.) to unmanned aerial vehicle simultaneously, its control mode is more nimble, further promote tracking efficiency. However, the unmanned aerial vehicle may deviate from a target area to be monitored in real time in the monitoring process, so that the real-time monitoring result is missed or dangerous objects, dangerous behaviors, dangerous personnel entering and the like cannot be found. Therefore, there is an urgent need for a control system and method that can correct the deviation of the unmanned aerial vehicle from the course in real time so that it can cruise within a predetermined target cruise route.
Disclosure of Invention
Aiming at the defects, the invention provides the method for monitoring the three-dimensional attitude speed, the position coordinates and the three-dimensional stress condition of the unmanned aerial vehicle in the flying process in real time, and the method adopts the random forest optimization algorithm to iterate continuously, so that the pitch angle speed of the unmanned aerial vehicle at the time t+delta t obtained in the calculating process is avoidedCourse angular velocity->And roll angular velocity>The phenomenon of deviation occurs, and the nonlinear of the system is processed by adopting a Takagi-Sugeno model through an early warning obstacle avoidance control module to perform active fault-tolerant control, so that the unmanned aerial vehicle can be corrected in real time from the route, and the adaptive fault-tolerant unmanned aerial vehicle tracking cruise system and method for cruising in a preset target cruise route are ensured.
The invention provides the following technical scheme: the self-adaptive fault-tolerant unmanned aerial vehicle tracking cruise system is used for monitoring the flight route of the unmanned aerial vehicle in real time and carrying out self-fault-tolerant early warning and flight control on the unmanned aerial vehicle, and is characterized by comprising an unmanned aerial vehicle flight parameter acquisition module, a self-adaptive alignment calculation module, an early warning obstacle avoidance control module and a wireless power supply module; the self-adaptive alignment calculation module comprises an upper layer control module and a bottom layer control module, wherein the bottom layer control module comprises a position control module, a tension and gesture distribution module, a gesture control module and an accelerator control module, and the tension and gesture distribution module is used for controlling the position control module, the gesture control module and the accelerator control module to achieve the purpose of reaching a desired cruising route with the minimum inclination angle and power;
the unmanned aerial vehicle flight parameter acquisition module acquires parameters of relevant gestures of the unmanned aerial vehicle at the moment t: unmanned aerial vehicle pitch angle speedCourse angular velocity->Roll angular velocity +.>Pitch angle acceleration->Course angular acceleration->Roll angular acceleration->And mechanical parameters of the unmanned aerial vehicle at time t: the throttle gives a first power moment A (t) in the x-axis direction, a second power moment B (t) in the y-axis direction, a third power moment C (t) in the z-axis direction parallel to the north pole of the earth and a resistance moment M (t) to be received to the unmanned aerial vehicle;
the upper control module adopts a random forest algorithm to train and optimize the data acquired by the unmanned aerial vehicle flight parameter acquisition module for route planning, mission planning and path planning;
the wireless power supply module is used for wirelessly supplying power for tracking and cruising of the unmanned aerial vehicle.
Further, the early warning obstacle avoidance control module adopts a Takagi-Sugeno model to process the nonlinearity of the system so as to perform active fault tolerance control.
Further, the gesture controller is a sliding mode controller.
Further, the flight parameter acquisition module comprises an unmanned aerial vehicle flight three-dimensional speed acquisition module, an unmanned aerial vehicle flight three-dimensional gesture acquisition module, an unmanned aerial vehicle three-dimensional position acquisition module and an unmanned aerial vehicle flight three-dimensional moment acquisition module.
Further, the wireless power supply module is used for supplying power to the battery in an induction type wireless mode.
Further, the wireless power supply module comprises a direct-current voltage source, a transmitting circuit module, a transmitting coil, a receiving coil, an AC-DC converter and a DC-DC converter, wherein the direct-current voltage source, the transmitting circuit module and the transmitting coil are arranged at a transmitting end, and the receiving coil, the AC-DC converter and the DC-DC converter are arranged on the unmanned aerial vehicle.
Further, the output power of the direct-current voltage source is 25W.
The invention also provides a self-adaptive fault-tolerant unmanned aerial vehicle tracking cruising method of the system, which comprises the following steps:
s1: the unmanned aerial vehicle flight parameter acquisition module acquires parameters of relevant gestures of the unmanned aerial vehicle at the moment t: unmanned aerial vehicle is proneElevation velocityCourse angular velocity->Roll angular velocity +.>Pitch angle acceleration->Course angular acceleration->Roll angular accelerationAnd mechanical parameters of the unmanned aerial vehicle at time t: the throttle gives a first power moment A (t) in the x-axis direction, a second power moment B (t) in the y-axis direction, a third power moment C (t) in the z-axis direction parallel to the north pole of the earth and a resistance moment M (t) to be received to the unmanned aerial vehicle;
s2: transmitting the acquired data to an upper control module, wherein the upper control module adopts a random forest algorithm to train and optimize the data acquired by the unmanned aerial vehicle flight parameter acquisition module for route planning, mission planning and path planning;
s3: the upper control module sends planned route, task and path diameter to the bottom control module, the tension and gesture distribution module distributes a tension instruction to be executed after planning to the accelerator control module, and gesture instructions are respectively distributed to the gesture control module and the position control module and are used for controlling the unmanned aerial vehicle to reach a desired cruising route with minimum inclination angle and power;
s4: the early warning obstacle avoidance control module adopts a Takagi-Sugeno model to process nonlinearity of the system, active fault tolerance control is carried out, if the tension and gesture command threshold value is exceeded, an alarm is given to the upper control module, the upper control module carries out route planning, task planning and path planning in the S2-S4 steps again, and if the tension and gesture command threshold value is not exceeded, self-adaptive fault tolerance is completed.
Further, the step S2 includes the steps of:
s21: the upper control module constructs the flight arrival position [ x 'y' z 'of the unmanned aerial vehicle in the delta t time interval'] T And (3) calculating a model:
wherein x is the flight coordinate value of the unmanned aerial vehicle at the time t in the x-axis direction, y is the flight coordinate value of the unmanned aerial vehicle at the time t in the y-axis direction, and z is the flight coordinate value of the unmanned aerial vehicle at the time t in the z-axis direction;roll angular velocity of unmanned aerial vehicle at time t+Δt +.>Pitch angle rate of unmanned aerial vehicle at time t+Δt +.>The course angular velocity of the unmanned aerial vehicle at the time t+delta t is set; the flight coordinate value of the unmanned aerial vehicle at the time t+delta t in the x-axis direction, the flight coordinate value of the unmanned aerial vehicle at the time t+delta t in the y-axis direction and the flight coordinate value of the unmanned aerial vehicle at the time t+delta t in the z-axis direction are calculated;
s22: the upper control module acquires pitch angle acceleration according to the moment tCourse angular acceleration->Roll angular acceleration->Calculating the pitch angle speed of the unmanned aerial vehicle at the time t+delta t in the S21 model>Course angular velocityAnd roll angular velocity>
Wherein m is a time component, m is [ t, t+Δt ];
s23: the upper control module performs continuous iterative optimization of the variation errors along a preset flight path by controlling a first power moment A (t) in the x-axis direction, a second power moment B (t) in the y-axis direction, a third power moment C (t) in the z-axis direction parallel to the north pole of the earth and a resistance moment M (t) which are given to the unmanned aerial vehicle by a throttle in a delta t time interval so as to ensure the pitch angle speed of the unmanned aerial vehicle at the moment t+delta t finally obtained in the step S22Course angular velocity->And roll angular velocity>No deviation is generated;
s24: and determining whether the deviation threshold is exceeded in the last step of each iteration, if not, continuing the step S3, and if so, repeating the steps S21-S23.
The beneficial effects of the invention are as follows:
1. the self-adaptive fault-tolerant unmanned aerial vehicle tracking cruise system and the method provided by the invention can monitor the three-dimensional attitude speed, the position coordinates and the three-dimensional stress condition of the unmanned aerial vehicle in the flight process in real time, and continuously iterate by adopting a random forest optimization method, so that the pitch angle speed of the unmanned aerial vehicle at the time t+delta t obtained in the calculation process is avoidedCourse angular velocity->And roll angular velocity>The phenomenon of deviation occurs, the pre-warning obstacle avoidance control module adopts a Takagi-Sugeno model to process the nonlinearity of the system, active fault tolerance control is carried out, if the tension and gesture command threshold value is exceeded, the alarm is given to the upper control module, the upper control module carries out route planning, task planning and path planning in the S2-S4 steps again, and the unmanned aerial vehicle deviation route can be corrected in real time, so that the unmanned aerial vehicle cruises in a preset target cruising route
2. According to the self-adaptive fault-tolerant unmanned aerial vehicle tracking cruise system, the validity of the unmanned aerial vehicle fault-tolerant path tracking control algorithm based on the random forest optimization method is verified through Matlab\Simulink simulation, and simulation results show that the algorithm can still ensure the robustness of unmanned aerial vehicle tracking control under the condition that external uncertain disturbance exists in a complex environment.
3. According to the self-adaptive fault-tolerant unmanned aerial vehicle tracking cruise system and method provided by the invention, the translation and gesture control are realized through continuous iteration of the upper control module, the effect of stable flight can be achieved, and the improved self-adaptive inverse controller can effectively eliminate static errors and has good interference suppression capability.
4. According to the self-adaptive fault-tolerant unmanned aerial vehicle tracking cruise system and method provided by the invention, the upper control module is adopted to construct the relation between the total upward thrust, the rolling moment, the pitching moment and the yaw moment of the four-axis unmanned aerial vehicle and the four rotating speeds of the rotor, and by utilizing the relation, the constructed total upward thrust, the rolling moment, the pitching moment and the yaw moment and the four rotating speed relation of the rotor are finally distributed to the accelerator control module through the tension and gesture distribution module, and the planned tension command to be executed is distributed to the gesture control module and the position control module respectively for controlling the unmanned aerial vehicle to reach the expected cruise route with the minimum inclination angle and power, so that the unmanned aerial vehicle can be controlled to track and cruise on the cruise route after self-adaptive fault tolerance more accurately, the defect of overlong calculation and execution time caused by the command to be issued and executed through the same module is avoided, and the self-adaptive fault-tolerant unmanned aerial vehicle tracking system and method provided by the invention can be realized without a high-configured chip.
Drawings
The invention will be described in more detail hereinafter on the basis of embodiments and with reference to the accompanying drawings. Wherein:
fig. 1 is an overall schematic diagram of a tracking cruise system of a self-adaptive fault-tolerant unmanned aerial vehicle;
fig. 2 is a schematic diagram of a wireless power supply module in the adaptive fault-tolerant unmanned aerial vehicle tracking cruise system;
FIG. 3 is a schematic flow chart of the adaptive fault tolerant unmanned aerial vehicle tracking cruise method provided by the invention;
fig. 4 is a schematic flow chart of training and optimizing data by an upper control module by adopting a random forest algorithm in the self-adaptive fault-tolerant unmanned aerial vehicle tracking cruising method provided by the invention.
Detailed Description
The following description of the embodiments of the present invention will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present invention, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
Example 1
As shown in fig. 1, the self-adaptive fault-tolerant unmanned aerial vehicle tracking cruise system provided by the invention is used for monitoring the flight route of an unmanned aerial vehicle in real time and carrying out self-fault-tolerant early warning and flight control on the unmanned aerial vehicle, and is characterized by comprising an unmanned aerial vehicle flight parameter acquisition module, a self-adaptive alignment calculation module, an early warning obstacle avoidance control module and a wireless power supply module; the self-adaptive alignment calculation module comprises an upper layer control module and a bottom layer control module, wherein the bottom layer control module comprises a position control module, a tension and gesture distribution module, a gesture control module and an accelerator control module, and the tension and gesture distribution module is used for controlling the position control module, the gesture control module and the accelerator control module to achieve the purpose of reaching a desired cruising route with the minimum inclination angle and power;
the unmanned aerial vehicle flight parameter acquisition module acquires parameters of relevant gestures of the unmanned aerial vehicle at the moment t: unmanned aerial vehicle pitch angle speedCourse angular velocity->Roll angular velocity +.>Pitch angle acceleration->Course angular acceleration->Roll-overAngular acceleration->And mechanical parameters of the unmanned aerial vehicle at time t: the throttle gives a first power moment A (t) in the x-axis direction, a second power moment B (t) in the y-axis direction, a third power moment C (t) in the z-axis direction parallel to the north pole of the earth and a resistance moment M (t) to be received to the unmanned aerial vehicle;
the upper control module adopts a random forest algorithm to train and optimize the data acquired by the unmanned aerial vehicle flight parameter acquisition module for route planning, mission planning and path planning;
the wireless power supply module is used for wirelessly supplying power for tracking and cruising of the unmanned aerial vehicle.
And the early warning obstacle avoidance control module adopts a Takagi-Sugeno model to process the nonlinearity of the system and performs active fault tolerance control.
Example 2
Based on embodiment 1, the attitude controller that this embodiment adopted is the slipform controller, flight parameter collection module includes unmanned aerial vehicle flight three-dimensional speed collection module, unmanned aerial vehicle flight three-dimensional attitude collection module, three-dimensional speed collection module is used for gathering unmanned aerial vehicle's real-time flight speed and real-time flight acceleration in x-axis, y-axis and z-axis, unmanned aerial vehicle flight three-dimensional attitude collection module is used for gathering unmanned aerial vehicle's real-time flight acceleration in x-axis, y-axis and z-axis, unmanned aerial vehicle three-dimensional position collection module is used for gathering unmanned aerial vehicle's real-time flight position coordinate data information in x-axis, y-axis and z-axis, unmanned aerial vehicle three-dimensional moment collection module is used for gathering unmanned aerial vehicle's throttle that receives when the real-time flight of x-axis, y-axis and z-axis gives thrust moment data.
Example 3
On the basis of embodiment 1, the wireless power supply module provided in this embodiment is battery-induced wireless power supply, as shown in fig. 2, and the wireless power supply module includes a direct-current voltage source, a transmitting circuit module, a transmitting coil, and a receiving coil, an AC-DC converter and a DC-DC converter, which are disposed on the unmanned aerial vehicle.
Example 4
On the basis of example 3, the output power of the direct-current voltage source was 25W.
Example 5
The invention also provides a tracking cruising method of the adaptive fault-tolerant unmanned aerial vehicle of any system provided in embodiments 1 to 5, as shown in fig. 3, comprising the following steps:
s1: the unmanned aerial vehicle flight parameter acquisition module acquires parameters of relevant gestures of the unmanned aerial vehicle at the moment t: unmanned aerial vehicle pitch angle speedCourse angular velocity->Roll angular velocity +.>Pitch angle acceleration->Course angular acceleration->Roll angular acceleration->And mechanical parameters of the unmanned aerial vehicle at time t: the throttle gives a first power moment A (t) in the x-axis direction, a second power moment B (t) in the y-axis direction, a third power moment C (t) in the z-axis direction parallel to the north pole of the earth and a resistance moment M (t) to be received to the unmanned aerial vehicle;
s2: transmitting the acquired data to an upper control module, wherein the upper control module adopts a random forest algorithm to train and optimize the data acquired by the unmanned aerial vehicle flight parameter acquisition module for route planning, mission planning and path planning;
s3: the upper control module sends planned route, task and path diameter to the bottom control module, the tension and gesture distribution module distributes a tension instruction to be executed after planning to the accelerator control module, and gesture instructions are respectively distributed to the gesture control module and the position control module and are used for controlling the unmanned aerial vehicle to reach a desired cruising route with minimum inclination angle and power;
s4: the early warning obstacle avoidance control module adopts a Takagi-Sugeno model to process the nonlinearity of the system and performs active fault tolerance control; and if the pulling force and the gesture command threshold value are exceeded, alarming to the upper control module, and re-carrying out route planning, task planning and path planning in the S2-S4 steps by the upper control module, and if the pulling force and the gesture command threshold value are not exceeded, completing self-adaptive fault tolerance.
According to the self-adaptive fault-tolerant unmanned aerial vehicle tracking cruise system, the validity of the unmanned aerial vehicle fault-tolerant path tracking control algorithm based on the random forest optimization method is verified through Matlab\Simulink simulation, and simulation results show that the algorithm can still ensure the robustness of unmanned aerial vehicle tracking control under the condition that external uncertain disturbance exists in a complex environment.
Example 6
On the basis of example 5, as shown in fig. 4, step S2 includes the steps of:
s21: the upper control module constructs the flight arrival position [ x 'y' z 'of the unmanned aerial vehicle in the delta t time interval'] T And (3) calculating a model:
wherein x is the flight coordinate value of the unmanned aerial vehicle at the time t in the x-axis direction, y is the flight coordinate value of the unmanned aerial vehicle at the time t in the y-axis direction, and z is the flight coordinate value of the unmanned aerial vehicle at the time t in the z-axis direction;roll angular velocity of unmanned aerial vehicle at time t+Δt +.>Pitch angle rate of unmanned aerial vehicle at time t+Δt +.>The course angular velocity of the unmanned aerial vehicle at the time t+delta t is set; the flight coordinate value of the unmanned aerial vehicle at the time t+delta t in the x-axis direction, the flight coordinate value of the unmanned aerial vehicle at the time t+delta t in the y-axis direction and the flight coordinate value of the unmanned aerial vehicle at the time t+delta t in the z-axis direction are calculated;
s22: the upper control module acquires pitch angle acceleration according to the moment tCourse angular acceleration->Roll angular acceleration->Calculating the pitch angle speed of the unmanned aerial vehicle at the time t+delta t in the S21 model>Course angular velocity->And roll angular velocity>
Wherein m is a time component, m is [ t, t+Δt ];
s23: the upper control module performs continuous iterative optimization of the variation errors along a preset flight path by controlling a first power moment A (t) in the x-axis direction, a second power moment B (t) in the y-axis direction, a third power moment C (t) in the z-axis direction parallel to the north pole of the earth and a resistance moment M (t) which are given to the unmanned aerial vehicle by a throttle in a delta t time interval so as to ensure the pitch angle speed of the unmanned aerial vehicle at the moment t+delta t finally obtained in the step S22Course angular velocity->And roll angular velocity>No deviation is generated;
s24: and determining whether the deviation threshold is exceeded in the last step of each iteration, if not, continuing the step S3, and if so, repeating the steps S21-S23.
According to the self-adaptive fault-tolerant unmanned aerial vehicle tracking cruise system and method provided by the invention, the translation and gesture control are realized through continuous iteration of the upper control module, so that the effect of stable flight can be achieved, and the improved self-adaptive inverse controller can effectively eliminate static errors and has good interference suppression capability; and the pre-warning obstacle avoidance control module processes the nonlinearity of the system by adopting a Takagi-Sugeno model to perform active fault tolerance control, so that the unmanned aerial vehicle can be corrected from a route in real time, and cruises in a preset target cruising route.
While the invention has been described with reference to a preferred embodiment, various modifications may be made and equivalents may be substituted for elements thereof without departing from the scope of the invention. In particular, the technical features mentioned in the respective embodiments may be combined in any manner as long as there is no structural conflict. The present invention is not limited to the specific embodiments disclosed herein, but encompasses all technical solutions falling within the scope of the claims.
Claims (7)
1. The self-adaptive fault-tolerant unmanned aerial vehicle tracking cruise system is used for monitoring the flight route of the unmanned aerial vehicle in real time and carrying out self-fault-tolerant early warning and flight control on the unmanned aerial vehicle, and is characterized by comprising an unmanned aerial vehicle flight parameter acquisition module, a self-adaptive alignment calculation module, an early warning obstacle avoidance control module and a wireless power supply module; the self-adaptive alignment calculation module comprises an upper layer control module and a bottom layer control module, wherein the bottom layer control module comprises a position control module, a tension and gesture distribution module, a gesture control module and an accelerator control module, and the tension and gesture distribution module is used for controlling the position control module, the gesture control module and the accelerator control module to achieve the purpose of reaching a desired cruising route with the minimum inclination angle and power;
the unmanned aerial vehicle flight parameter acquisition module acquires parameters of relevant gestures of the unmanned aerial vehicle at the moment t: unmanned aerial vehicle pitch angle speedCourse angular velocity->Roll angular velocity +.>Pitch angle acceleration->Course angular acceleration->Roll angular acceleration->And mechanical parameters of the unmanned aerial vehicle at time t: throttle gives unmanned aerial vehicle's in X axleA first power moment A (t) in the direction, a second power moment B (t) in the y-axis direction, a third power moment C (t) in the z-axis direction parallel to the north pole of the earth and a resistance moment M (t) received;
the upper control module adopts a random forest algorithm to train and optimize the data acquired by the unmanned aerial vehicle flight parameter acquisition module for route planning, mission planning and path planning;
the wireless power supply module is used for wirelessly supplying power for tracking and cruising of the unmanned aerial vehicle;
the adaptive fault-tolerant unmanned aerial vehicle tracking cruise system executes the following cruise method:
s1: the unmanned aerial vehicle flight parameter acquisition module acquires parameters of relevant gestures of the unmanned aerial vehicle at the moment t: unmanned aerial vehicle pitch angle speedCourse angular velocity->Roll angular velocity +.>Pitch angle acceleration->Course angular acceleration->Roll angular acceleration->And mechanical parameters of the unmanned aerial vehicle at time t: the throttle gives a first power moment A (t) in the x-axis direction, a second power moment B (t) in the y-axis direction, a third power moment C (t) in the z-axis direction parallel to the north pole of the earth and a resistance moment M (t) to be received to the unmanned aerial vehicle;
s2: transmitting the acquired data to an upper control module, wherein the upper control module adopts a random forest algorithm to train and optimize the data acquired by the unmanned aerial vehicle flight parameter acquisition module for route planning, mission planning and path planning;
s3: the upper control module directly sends the planned route, task and path to the bottom control module, the tension and gesture distribution module distributes the tension instruction to be executed after planning to the accelerator control module, and the gesture instruction is respectively distributed to the gesture control module and the position control module and is used for controlling the unmanned aerial vehicle to reach the expected cruising route with the minimum inclination angle and power;
s4: the early warning obstacle avoidance control module adopts a Takagi-Sugeno model to process the nonlinearity of the system and performs active fault tolerance control; if the pulling force and gesture command threshold value is exceeded, alarming to the upper control module, and the upper control module re-performs route planning, task planning and path planning in the S2-S4 steps, and if the pulling force and gesture command threshold value is not exceeded, completing self-adaptive fault tolerance;
the step S2 comprises the following steps:
s21: the upper control module constructs the flight arrival position [ x 'y' z 'of the unmanned aerial vehicle in the delta t time interval'] T And (3) calculating a model:
wherein x is the flight coordinate value of the unmanned aerial vehicle at the time t in the x-axis direction, y is the flight coordinate value of the unmanned aerial vehicle at the time t in the y-axis direction, and z is the flight coordinate value of the unmanned aerial vehicle at the time t in the z-axis direction;roll angular velocity of unmanned aerial vehicle at time t+Δt +.>Pitch angle rate of unmanned aerial vehicle at time t+Δt +.>The course angular velocity of the unmanned aerial vehicle at the time t+delta t is set; the flight coordinate value of the unmanned aerial vehicle at the time t+delta t in the x-axis direction, the flight coordinate value of the unmanned aerial vehicle at the time t+delta t in the y-axis direction and the flight coordinate value of the unmanned aerial vehicle at the time t+delta t in the z-axis direction are calculated;
s22: the upper control module acquires pitch angle acceleration according to the moment tCourse angular acceleration->Roll angular acceleration->Calculating the pitch angle speed of the unmanned aerial vehicle at the time t+delta t in the S21 model>Course angular velocity->And roll angular velocity>
Wherein m is a time component, m is [ t, t+Δt ];
s23: the upper control module controls the time interval at delta tThe throttle in the system gives the unmanned aerial vehicle a first power moment A (t) in the x-axis direction, a second power moment B (t) in the y-axis direction, a third power moment C (t) in the z-axis direction parallel to the north pole of the earth and a resistance moment M (t) to the unmanned aerial vehicle, and the variation errors of the power moment A (t), the second power moment B (t), the third power moment C (t) and the resistance moment M (t) are continuously and iteratively optimized along a preset flight path so as to ensure the pitch angle speed of the unmanned aerial vehicle at the time t+delta t finally obtained in the step S22Course angular velocity->And roll angular velocity>No deviation is generated;
s24: and determining whether the deviation threshold is exceeded in the last step of each iteration, if not, continuing the step S3, and if so, repeating the steps S21-S23.
2. The adaptive fault-tolerant unmanned aerial vehicle tracking cruise system according to claim 1, wherein the early warning obstacle avoidance control module processes nonlinearity of the system by adopting a Takagi-Sugeno model to perform active fault-tolerant control.
3. The adaptive fault tolerant unmanned aerial vehicle tracking cruise system of claim 1, wherein the attitude control module is a sliding mode controller.
4. The adaptive fault tolerant unmanned aerial vehicle tracking cruise system of claim 1, wherein the flight parameter acquisition module comprises an unmanned aerial vehicle flight three-dimensional speed acquisition module, an unmanned aerial vehicle flight three-dimensional attitude acquisition module, an unmanned aerial vehicle three-dimensional position acquisition module, and an unmanned aerial vehicle flight three-dimensional moment acquisition module.
5. The adaptive fault tolerant unmanned aerial vehicle tracking cruise system of claim 1, wherein the wireless power module is battery-powered inductively wireless.
6. The adaptive fault tolerant unmanned aerial vehicle tracking cruise system of claim 5, wherein the wireless power module comprises a direct current voltage source, a transmit circuit module, a transmit coil disposed at the transmit end, and a receive coil, an AC-DC converter, and a DC-DC converter disposed on the unmanned aerial vehicle.
7. The adaptive fault tolerant unmanned aerial vehicle tracking cruise system of claim 6, wherein the output power of the dc voltage source is 25W.
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