CN-121978890-A - Double-rotor unmanned aerial vehicle control method based on fuzzy control and active disturbance rejection control

CN121978890ACN 121978890 ACN121978890 ACN 121978890ACN-121978890-A

Abstract

The invention discloses a control method of a double-rotor unmanned aerial vehicle based on fuzzy control and active disturbance rejection control, which comprises the following steps of S1, establishing a kinematic and dynamic model of a novel double-rotor unmanned aerial vehicle, establishing a complete model which is input into the control, S2, establishing an extended state observer and a corresponding rule thereof by using the active disturbance rejection control at an inner layer, S3, realizing accurate perception and recording of the attitude of the unmanned aerial vehicle at an outer layer by using the fuzzy control, and S4, establishing a cascade optimization strategy comprising analog control and the active disturbance rejection control. According to the invention, the fuzzy control and the active disturbance rejection control are integrated into the control framework of the double helicopters, so that the complexity of a dynamic model is solved, the unmanned aerial vehicle is ensured to have excellent operability and responsiveness in various foreign scenes, the control method of the double helicopter unmanned aerial vehicle is enhanced, the field of the active disturbance rejection control of the double helicopter unmanned aerial vehicle is particularly concerned, the control effect is good, and the control method can be widely applied to other disturbance rejection control systems.

Inventors

CHEN JIANLIN
YANG ZHENGWEI
LI WENCHAO
JIA ZIYAN
DAI LU

Assignees

西北工业大学

Dates

Publication Date: 20260505
Application Date: 20260203

Claims (7)

1. A dual rotor unmanned aerial vehicle control strategy based on fuzzy control and active disturbance rejection control is characterized by comprising the following steps: s1, establishing a kinematic and dynamic model of the novel double-rotor unmanned aerial vehicle in a Cartesian inertial coordinate system, and establishing a complete model which is input into control; s2, constructing a composite control system comprising fuzzy PID control and active disturbance rejection control to realize cascade control, and constructing an extended state observer and a corresponding rule thereof at an inner layer by using the active disturbance rejection control; S3, realizing accurate sensing and recording of the unmanned aerial vehicle gesture on the outer layer by using fuzzification, fuzzy reasoning and defuzzification of fuzzy control; S4) constructing a cascade optimization strategy comprising analog control and active disturbance rejection control, wherein the yaw angle and the Z axis of the double-rotor unmanned aerial vehicle are directly controlled, the rest position control is calculated by the fuzzy controller and the active disturbance rejection controller in a cooperative mode, and the proper gesture is deduced by a position kinematic formula of the double-rotor unmanned aerial vehicle to realize the control.
2. The control method of the double-rotor unmanned aerial vehicle based on fuzzy control and active disturbance rejection control according to claim 1, wherein the novel double-rotor unmanned aerial vehicle in S1) is provided with two rotors for propulsion and two servo motors for lifting, and the connection between the servo motors and the propulsion rotors adopts a hyperboloid mechanism design; the novel kinematic and dynamic model of the double-rotor unmanned aerial vehicle is as follows: Wherein, the Representing inertial Cartesian coordinate system middle edge An acceleration component of the shaft; respectively representing pitch angle, roll angle and yaw angle; is the quality of the unmanned aerial vehicle; Gravitational acceleration; Respectively is wound around The moment of inertia of the shaft; Respectively represent windings Angular speed of the shaft; And Respectively representing distances from normal directions of the corresponding rotating shafts; Representing a control input, wherein Representing the total lift generated by the two rotors, And Respectively correspond to the control moment of pitching maneuver Is the control moment of yaw maneuver; Wherein the method comprises the steps of Can be expressed as: Wherein, the And Respectively represent the tensile force of two arms of the double-wing unmanned aerial vehicle, And Is two inclination angles.
3. The method for controlling a dual-rotor unmanned aerial vehicle based on fuzzy control and active disturbance rejection control according to claim 2, wherein the step S2) of constructing an extended state observer in an inner layer by using active disturbance rejection control is as follows: first, the power system is connected with The components are further rewritten as: Wherein, the Representing state variables Is used for the purpose of determining the derivative of (c), Is a second one of the state variables, Is a coefficient representing the gain of the system, Is the control input is equal to , Representing external disturbances; is the output of the system, which is equal to the state variable ; The form of the Extended State Observer (ESO) is designed as follows: Wherein, the Representing system status And estimating the state The tracking error between the two is used to determine, And Representing the state of the observer in the expanded state, parameters And In order for the gain of the observer to be achieved, The control input is represented as such, Representing the system gain; in order to meet the requirements of rapid parameter setting and deployment, a composite controller is designed as follows: Wherein, the Representing the desired state And actual state The error between the two is calculated, The control input is represented as such, Indicating the gain of the controller and, Is the system gain.
4. The control method of the double-rotor unmanned aerial vehicle based on the fuzzy control and the active-disturbance-rejection control according to claim 2, wherein S3) the precise sensing and recording of the unmanned aerial vehicle gesture are realized on the outer layer by using the fuzzy control, and the fuzzy logic in the fuzzy control process comprises three main stages, namely fuzzification, fuzzy reasoning and defuzzification; For the position control loop to The channel is a test sample, and according to the input reference value And feedback value Calculating errors And Then the fuzzy logic calculates the fuzzy output And Since the ideal system has no obvious steady state error, the parameters are set Set to 0; the final input to the fuzzy logic control loop may be expressed as: in the case of a fuzzy logic control loop, Input ambiguity domain of (2) is , Input ambiguity domain of (2) is ; Is the output domain of (2) , Is the output domain of (2) 。
5. The method for controlling a dual rotor unmanned aerial vehicle based on fuzzy control and active disturbance rejection control according to claim 2, wherein the input amounts of five elements of a fuzzy subset in the fuzzy control are sequentially in ascending order 。
6. The method for controlling the double rotor unmanned aerial vehicle based on the fuzzy control and the active-disturbance-rejection control according to claim 2, wherein S4) a cascade optimization strategy comprising analog control and active-disturbance-rejection control is constructed, and the cascade control system is constructed based on the active-disturbance-rejection control designed in S2) and the fuzzy control system designed in S3), and comprises an inner loop controller for gesture control and an outer loop fuzzy controller for position control, so that an inner loop-outer loop double-layer control framework is formed; The control strategy is used for directly performing closed-loop control on the yaw angle and a specific axial direction (such as a pitching/rolling shaft) of the unmanned aerial vehicle through the cooperative work of the fuzzy controller and the active disturbance rejection controller; for the rest position control components, the rest position control components are realized by the cooperative calculation of the fuzzy controller and the active disturbance rejection controller; Deducing and constructing an attitude solver based on a position kinematic formula of the double-rotor unmanned aerial vehicle under an approximate stable condition, wherein the attitude solver is used for converting a position control instruction into a desired attitude angle instruction; the fuzzy controller of the outer ring receives the position error signal, outputs the expected attitude angular speed signal after fuzzy reasoning operation, the signal is used as the reference input of the active disturbance rejection controller of the inner ring, the active disturbance rejection controller of the inner ring compares the actually measured angular speed with the reference input, the total disturbance of the system is estimated by using the extended state observer, the final control quantity is generated by the nonlinear state error feedback law, the motor executing mechanism of the double-rotor unmanned aerial vehicle is driven, and the decoupling and the cooperation of the position control and the attitude control are realized by the cascade structure.
7. A dual-rotor unmanned aerial vehicle cascade optimization control system for implementing the dual-rotor unmanned aerial vehicle control method based on fuzzy control and active-disturbance-rejection control as claimed in any one of claims 1 to 6, characterized by comprising a model building module for building a novel dual-rotor unmanned aerial vehicle kinematics and dynamics model; the active disturbance rejection inner loop control module adopts active disturbance rejection control to construct an extended state observer and a corresponding rule thereof in the inner layer; The fuzzy PID outer ring control module adopts a fuzzy logic controller to realize accurate sensing and reasoning on the unmanned aerial vehicle gesture, and realizes the control on the unmanned aerial vehicle gesture through the PID controller; the cascade collaborative optimization execution module is used for constructing a cascade optimization strategy comprising analog control and active disturbance rejection control; The output end of the model building module is connected with the input end of the fuzzy PID outer loop control module and is used for providing system state reference; the output end of the fuzzy PID outer loop control module is connected with the input end of the active disturbance rejection inner loop control module to form a cascade control structure, and the cascade control structure is used for providing a control instruction after dynamic adjustment; The output end of the active disturbance rejection inner loop control module is connected with the input end of the cascade collaborative optimization execution module and is used for transmitting the control signal after disturbance rejection, and the feedback end of the cascade collaborative optimization execution module is connected with the input end of the model building module and is used for forming a closed loop feedback loop.

Description

Double-rotor unmanned aerial vehicle control method based on fuzzy control and active disturbance rejection control Technical Field The invention belongs to the technical field of double-rotor unmanned aerial vehicle control, and particularly relates to a double-rotor unmanned aerial vehicle control method based on fuzzy control and active disturbance rejection control. Background Unmanned Aerial Vehicles (UAVs) find widespread use in performing airborne tasks, the performance of which depends largely on the autonomy and accuracy of the control system. In many forms of unmanned aerial vehicle construction, the two rotor unmanned aerial vehicle is owing to adopt two main rotor to provide lift and mobility, and its dynamics and control scheme have apparent difference with many conventional rotor unmanned aerial vehicle. The aircraft has certain advantages in terms of maneuverability and loading capacity, but also introduces more complex dynamic coupling relation and control problems. In recent years, new designs are presented for the structural form of the double-rotor unmanned aerial vehicle. For example, the dual-rotor aircraft CapsuleBot combines the advantages of flight and ground movement, shows improved maneuverability in small space and complex environments, and improves the gesture control performance through an optimal control strategy and trajectory generation and tracking based on flatness. However, the stability, anti-interference capability and versatility of control strategies of such systems in complex environments are still limited, and their control performance depends largely on model accuracy and parameter settings. When external disturbance or system uncertainty is strong, the control effect of the existing method is often difficult to guarantee. In order to cope with the nonlinear, uncertainty and coupling problems commonly existing in unmanned aerial vehicle systems, various advanced control methods are introduced in a control theory, and research and verification are carried out on platforms such as a four-rotor unmanned aerial vehicle. However, when the methods are directly applied to the double-rotor unmanned aerial vehicle, under-actuated characteristics and closer coupling relations between the gestures and the positions of the double-rotor unmanned aerial vehicle are often difficult to fully consider, so that the design and parameter setting processes of the controller are complex, and the adaptability to the change of the working environment is limited. The fuzzy control is independent of an accurate mathematical model, so that the influence caused by the uncertainty of the model can be relieved to a certain extent, but the control performance of the fuzzy control is highly dependent on the design of an experience rule, and the response speed and the control precision are difficult to be simultaneously considered under the complex working condition. The active disturbance rejection control estimates and compensates the system disturbance through the extended state observer, has certain advantages in the aspect of external disturbance suppression, but in the multi-degree-of-freedom and strong-coupling double-rotor unmanned aerial vehicle system, the coordination problem between the position control and the attitude control is still difficult to effectively process by independently adopting the active disturbance rejection control. The invention strives to solve the complexity of the dynamic model thereof, and ensures that the unmanned aerial vehicle has excellent processing and response capability in a wide range of scenes. The control method of the double-rotor unmanned aerial vehicle is expanded, and the field of anti-interference control of the double-rotor unmanned aerial vehicle is studied. Disclosure of Invention The invention aims to overcome the defects, and the invention aims to provide a double-rotor unmanned aerial vehicle control method based on fuzzy control and active disturbance rejection control, which is used for solving the complexity of a dynamic model of the double-rotor unmanned aerial vehicle, and ensuring that the unmanned aerial vehicle has excellent processing and response capability in a wide scene. In order to achieve the above purpose, the invention provides a control method of a double-rotor unmanned aerial vehicle based on fuzzy control and active disturbance rejection control, comprising the following steps: s1, establishing a kinematic and dynamic model of the novel double-rotor unmanned aerial vehicle in a Cartesian inertial coordinate system, and establishing a complete model which is input into control; s2, constructing a composite control system comprising fuzzy PID control and active disturbance rejection control to realize cascade control, and constructing an extended state observer and a corresponding rule thereof at an inner layer by using the active disturbance rejection control; S3, realizing accurate sensing and recording of the unmanned a