Multi-unmanned aerial vehicle formation fault-tolerant control method based on extended state observer

Abstract

The invention relates to a multi-unmanned aerial vehicle formation fault-tolerant control method based on an extended state observer. The method comprises the following steps: firstly, establishing a dynamic model of a multi-unmanned aerial vehicle formation; a multi-unmanned aerial vehicle formation communication topological structure is constructed according to the actual demand of a formation task, and information interaction among multiple unmanned aerial vehicles is realized based on a piloting-following method architecture and a distributed control method; establishing a global position tracking error and a speed tracking error by using the states of the adjacent unmanned aerial vehicles; introducing an extended state observer to estimate the unknown state of the formation system in real time; and a sliding-mode adaptive fault-tolerant controller is designed to effectively deal with the influence of actuator faults, system uncertainty and unknown external disturbance on formation performance, and stable control of the multi-unmanned aerial vehicle formation system is realized. According to the method, under the condition that a single unmanned aerial vehicle or multiple unmanned aerial vehicles break down, reliable transmission of task information and effective keeping of the formation can still be guaranteed, and the method has high system robustness and environment adaptability and is suitable for complex flight task scenes.

Description

Technical Field

[0001] The present invention relates to the technical field of multi-UAV formation fault tolerance, and in particular to a multi-UAV formation fault tolerance control method based on an extended state observer. Background Art

[0002] Multi-agent systems represented by multi-UAV formations have demonstrated good coordination capabilities and high flexibility in various complex tasks, and have become an important research direction in the current field of intelligent control.

[0003] However, in actual operations, they often face interference from multiple external complex disturbances such as sudden wind disturbances, airflow shear, and changes in illumination. They may also be affected by internal factors such as response lag, sensor anomalies, and actuator failures. Actuator failure, a key challenge to system reliability, is sudden and unpredictable, and can easily lead to information transmission errors and control deviations during system control coupling, causing localized flight state anomalies. In severe cases, this can disrupt the overall formation or cause system failure, seriously threatening the collaborative stability and safety of the multi-UAV formation system. Summary of the Invention

[0004] In response to the shortcomings of the existing technology, the present invention provides a fault-tolerant control method for multi-UAV formations based on an extended state observer, which solves the problem of the impact of unknown external interference and sudden actuator failures on the formation performance of multi-UAV formations in actual operating environments.

[0005] In order to solve the above technical problems, the present invention is achieved through the following technical solutions: The present invention provides a multi-UAV formation fault-tolerant control method based on an extended state observer, comprising the following steps: S1. Considering the influence of actuator failure, system uncertainty and unknown external disturbance on the following UAV in the formation system, the system uncertainty and unknown external disturbance are regarded as unknown lumped disturbances, and the first dynamic model of the following UAV failure is established: in, , Indicates the number of following drones, Indicates the location of the following drone. Indicates the x-axis position of the following drone, Indicates the y-axis position of the following drone, Indicates the speed of following the drone. Indicates the x-axis speed of the following drone, Indicates the y-axis speed of the following drone, represents the transpose of the matrix, and denote the first-order time derivatives of position and velocity, respectively, represents the control input, represents a nonlinear function that includes system uncertainty, represents the unknown aggregate disturbance to which the following UAV is subjected, represents the efficiency factor of the actuator; make , redefine the first dynamic model when a failure occurs in the following UAV in the formation system: in, Represents the virtual control input of the following drone.

[0006] S2. Based on the information exchange between the pilot UAV and the follower UAV, a dynamic model of the pilot UAV is established: in, Indicates the position of the pilot drone. Indicates the x-axis position of the pilot drone, Indicates the y-axis position of the pilot drone, Indicates the speed of the pilot drone. Indicates the x-axis speed of the pilot drone, Indicates the y-axis speed of the pilot drone, Indicates the specified control input.

[0007] S3. Construct a multi-UAV formation communication topology structure based on the actual needs of the formation mission ,Combining the pilot-follower architecture with distributed control methods,,the information transmission between multiple UAVs is realized; S4. Determine the formation's global position tracking error based on the state information between adjacent drones and speed error ; S5. Based on the formation dynamics equation, an expanded state space equation is established and an expanded state observer is introduced to observe the unknown system state in real time; S6. Establish a sliding surface based on the formation's global position tracking error and velocity tracking error ; S7. Design a virtual sliding mode fault-tolerant formation controller based on the sliding surface ; S8. Introduce new uncertain variables and establish the first dynamic model of the formation system when the following drone fails under the new variables; design a sliding mode adaptive fault-tolerant formation controller based on the sliding mode surface and adaptive law. ; S9. The Lyapunov stability analysis method is used to prove that when time tends to infinity, the formation position tracking error and velocity tracking error converge to zero asymptotically in a finite time.

[0008] Preferably, in step S4, the formation global position tracking error and velocity error are designed as follows: in, , , represents the estimated value of the drone’s position, represents the estimated value of the drone's speed, , , Indicates the trajectory information of the pilot drone. Indicates the formation to be maintained. The derivative of ; Represents the adjacency matrix The elements in Representation matrix Elements in; adjacency matrix ,matrix .

[0009] Preferably, in step S5, the expanded state space equation established is: in, Indicates the location of the following drone. Indicates the speed of following the drone. represents the unknown aggregate disturbance to which the following UAV is subjected. express The first time derivative of express The first time derivative of express The first time derivative of represents a bounded smooth function, Represents the output of the system.

[0010] Preferably, in step S5, the extended state observer introduced is: in, 、 and They are the observation position states of the following drones , Observation speed state and observe the unknown lumped disturbance The first time derivative of express The estimated value of express The estimated value of express The estimated value of , , , are the parameters to be designed, for The square of for The cube of .

[0011] Preferably, in step S6, the sliding surface is established as: in, are the parameters to be designed.

[0012] As a preference, in step S7, a virtual sliding mode fault-tolerant formation controller is designed. for: in, represents the inverse matrix of the matrix, express The estimated value of express The first time derivative of are the parameters to be designed, represents the symbolic function, are the parameters to be designed, , .

[0013] As a preference, in step S8, a new uncertainty variable is introduced to define , , the first dynamic model of the design formation system when the following UAV fails is: in, , express The estimation error, express estimated value.

[0014] Design of sliding mode adaptive fault-tolerant formation controller for: in, express estimated value.

[0015] The designed adaptive law is: in, express The first time derivative of .

[0016] Compared with the prior art, the present invention has the following advantages: First, by introducing the extended state observer, the unknown state of the system can be observed in real time, effectively responding to the impact of actuator failures, system uncertainties and external disturbances, and improving the robustness of formation control.

[0017] Second, by adopting the pilot-follower architecture and distributed control method, and by building the corresponding communication topology structure, the coordination and adaptability of multi-UAV formations are enhanced to meet the needs of complex missions.

[0018] 3. Based on the global position tracking error and velocity tracking error, a sliding surface is designed, and a sliding mode adaptive fault-tolerant formation controller and adaptive law are designed to ensure that the formation position error and velocity error converge to zero asymptotically within a finite time. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] Figure 1 Schematic diagram of the communication topology structure of a multi-UAV formation in an implementation case of the present invention.

[0020] Figure 2 Schematic diagram of the pentagonal formation layout at 10s, 20s, and 30s in the implementation case of the present invention.

[0021] FIG3( a ) is a graph showing the observation error of the x-axis position of the following drone by the extended state observer in an embodiment of the present invention.

[0022] FIG3( b ) is a graph showing the observation error of the extended state observer on the y-axis position of the following drone in an embodiment of the present invention.

[0023] Figure 4 This is a curve diagram of the global position tracking error of the following drone formation in the implementation case of the present invention.

[0024] As shown in the figure: UAV0-leading UAV, UAV1-following UAV No. 1, UAV2-following UAV No. 2, UAV3-following UAV No. 3, UAV4-following UAV No. 4, UAV5-following UAV No. 5, x-pentagonal formation layout curve at 10s, 20s, and 30s. DETAILED DESCRIPTION

[0025] In order to clearly illustrate the technical features of this solution, this solution is described below through specific implementation methods.

[0026] The embodiment of the present invention discloses a multi-UAV formation fault-tolerant control method based on an extended state observer, comprising the following steps: Define the first dynamic model when a failure occurs in the following UAV in the formation system: in, , Indicates the number of following drones. Indicates the location of the following drone. Indicates the x-axis position of the following drone, Indicates the y-axis position of the following drone, Indicates the speed of following the drone. Indicates the x-axis speed of the following drone, Indicates the y-axis speed of the following drone, represents the transpose of the matrix, and denote the first-order time derivatives of position and velocity, respectively, represents the control input, represents a nonlinear function that includes system uncertainty, represents the unknown aggregate disturbance to which the following UAV is subjected, Represents the efficiency factor of the actuator.

[0027] make , redefine the first dynamic model when a failure occurs in the following UAV in the formation system: in, Represents the virtual control input of the following drone.

[0028] Determine the topological structure of the formation system based on the relevant knowledge of basic graph theory , using the pilot-follower architecture and distributed control method, the global position tracking error and velocity tracking error based on adjacent UAVs are established as: in, , , represents the estimated value of the position of the following drone, represents the estimated value of the speed of the following drone, , , Indicates the trajectory information of the pilot drone. Indicates the formation maintained. The derivative of ; Represents the adjacency matrix The elements in Representation matrix The elements in the adjacency matrix ,matrix .

[0029] According to the multi-UAV formation dynamics model, the expanded state space equation is established as: in, Indicates the location of the following drone. Indicates the speed of following the drone. represents the unknown aggregate disturbance to which the following UAV is subjected. express The first time derivative of express The first time derivative of express The first time derivative of represents a bounded smooth function, Represents the output of the system.

[0030] In order to solve the problem of unknown system state of multi-UAV formation, an extended state observer is introduced to observe the system state in real time: in, 、 and They are the observation position states of the following drones , Observation speed state and observe unknown external disturbances The first time derivative of express The estimated value of express The estimated value of express The estimated value of , , , are the parameters to be designed, for The square of for The cube of .

[0031] Design the sliding surface based on the formation position tracking error and speed tracking error for in, are the parameters to be designed.

[0032] Based on the above, a virtual sliding mode fault-tolerant formation controller is designed. for: in, represents the inverse matrix of the matrix, express The estimated value of express The first time derivative of are the parameters to be designed, represents the symbolic function, are the parameters to be designed, , .

[0033] definition , , then the first dynamic model when the following UAV fails in the formation system is: in, , express The estimation error, express estimated value.

[0034] definition , then the sliding mode adaptive fault-tolerant formation controller is: in, express Estimates.

[0035] At the same time, considering the impact of actuator failures in the platooning system, an adaptive algorithm is used for estimation, and the adaptive law is designed as follows: in, express The first time derivative of .

[0036] The Lyapunov stability analysis method is used to prove that when time tends to infinity, the formation position tracking error and velocity tracking error converge to zero asymptotically in a finite time.

[0037] The effectiveness of the fault-tolerant control method for multi-UAV formation proposed in this invention is simulated and verified, and the values ​​of the relevant parameters involved are as follows: Set the reference trajectory of the leader UAV in the formation to , No. The formation vector of the UAVs is defined as .

[0038] The external disturbance is defined as: , , , , , , , , , , , , , , , , , , , , , The simulation results are as follows: Figures 1 to 4 shown.

[0039] like Figure 1 As shown in the figure, a communication topology diagram for a multi-UAV formation is established using a pilot-follower architecture and distributed control methods. The diagram includes five follower UAVs and one pilot UAV. The first and second follower UAVs can receive mission information from the pilot UAV and exchange information with neighboring UAVs.

[0040] like Figure 2 As shown, the drones in the formation can fly according to the predetermined flight trajectory. At the same time, the 10th, 20th, and 30th seconds of the mission are extracted. It can be seen that the follower drones can form a time-varying pentagonal formation layout around the pilot drone.

[0041] As shown in Figure 3, the designed extended state observer can achieve accurate estimation of the unknown state of the following UAV, and the x-axis observation error and y-axis observation error asymptotically approach zero.

[0042] like Figure 4 As shown in Figure 3, after injecting actuator faults, the formation position tracking error can converge to zero in a finite time, maintaining the stable state of the formation.

[0043] It can be seen from the above technical solution that the multi-UAV formation fault-tolerant control method based on the extended state observer proposed in the present invention has strong robustness and adaptability.

[0044] Of course, the above description is not limited to the above examples. Technical features not described in the present invention can be achieved by or by adopting existing technologies, which will not be described here. The above embodiments and drawings are only used to illustrate the technical solutions of the present invention and are not limitations of the present invention. The present invention is described in detail with reference to the preferred implementation methods. Ordinary technicians in this field should understand that changes, modifications, additions or substitutions made by ordinary technicians in this technical field within the essential scope of the present invention do not depart from the purpose of the present invention and should also fall within the scope of protection of the claims of the present invention.

Claims

1. A fault-tolerant control method for multi-UAV formation based on an extended state observer, characterized by: The following steps are involved: S1. Considering the influence of actuator failure, system uncertainty and unknown external disturbance on the following UAV in the formation system, the system uncertainty and unknown external disturbance are regarded as unknown lumped disturbances, and the first dynamic model of the following UAV failure is established: in, , Indicates the number of following drones, Indicates the location of the following drone. Indicates the x-axis position of the following drone. Indicates the position of the y-axis of the following drone, Indicates the speed of following drone, Indicates the speed of the x-axis following the drone. Indicates the speed of the y-axis following the drone, represents the transpose of the matrix, and denote the first-order time derivatives of position and velocity, respectively, represents the control input, represents a nonlinear function that includes system uncertainty, represents the unknown aggregate disturbance to which the following UAV is subjected, represents the efficiency factor of the actuator; make , we redefine the first dynamic model when a failure occurs in the following UAV in the formation system as: in, represents the virtual control input of the following drone; S2. Based on the information exchange between the pilot UAV and the follower UAV, a dynamic model of the pilot UAV is established: in, Indicates the position of the pilot drone. Indicates the x-axis position of the pilot drone, Indicates the y-axis position of the pilot drone, Indicates the speed of the pilot drone. Indicates the x-axis speed of the pilot drone, Indicates the y-axis speed of the pilot drone, Indicates the specified control input; S3. Construct a multi-UAV formation communication topology structure based on the actual needs of the formation mission ,Combining the pilot-follower architecture with distributed control methods,,the information transmission between multiple UAVs is realized; S4. Determine the formation's global position tracking error based on the state information between adjacent drones and velocity tracking error ; S5. Based on the formation dynamics equation, an expanded state space equation is established and an expanded state observer is introduced to observe the unknown system state in real time; S6. Establish a sliding surface based on the formation's global position tracking error and velocity tracking error ; S7. Design a virtual sliding mode fault-tolerant formation controller based on the sliding surface ; S8. Introduce new uncertain variables and establish the first dynamic model of the formation system when the following drone fails under the new variables; design a sliding mode adaptive fault-tolerant formation controller based on the sliding mode surface and adaptive law. ; S9. The Lyapunov stability analysis method is used to prove that when time tends to infinity, the formation position tracking error and velocity tracking error converge to zero asymptotically in a finite time.

2. The fault-tolerant control method for multi-UAV formation based on extended state observer according to claim 1 is characterized by: The formation global position tracking error established based on the state information between adjacent UAVs in S3 and S4 and velocity tracking error for: in, , , represents the estimated value of the position of the following drone, represents the estimated value of the speed of the following drone, , , Indicates the trajectory information of the pilot drone. A structure representing the shape of the formation being maintained, The derivative of ; Represents the adjacency matrix The elements in Representation matrix Elements in; adjacency matrix ,matrix .

3. The fault-tolerant control method for multi-UAV formation based on extended state observer according to claim 1, characterized in that: In step S5, the expanded state space equation is established as: in, Indicates the location of the following drone. Indicates the speed of following drone, represents the unknown aggregate disturbance to which the following UAV is subjected. express The first time derivative of express The first time derivative of express The first time derivative of represents a bounded smooth function, Represents the output of the system.

4. The fault-tolerant control method for multi-UAV formation based on extended state observer according to claim 1, characterized in that: In step S5, in order to observe the state of the formation system in real time, the extended state observer introduced is: in, 、 and They are the observation position status of the following drone , Observation speed state and observe the unknown lumped disturbance The first time derivative of express The estimated value of express The estimated value of express The estimated value of , , , are the parameters to be designed, for The square of for The cube of .

5. The fault-tolerant control method for multi-UAV formation based on extended state observer according to claim 1, characterized in that: In step S6, the sliding surface is designed based on the position tracking error and the velocity tracking error. for: in, are the parameters to be designed.

6. The fault-tolerant control method for multi-UAV formation based on extended state observer according to claim 1, characterized in that: In step S7, the virtual sliding mode fault-tolerant formation controller The design is as follows: in, represents the inverse matrix of the matrix, express The estimated value of express The first time derivative of are the parameters to be designed, represents the symbolic function, are the parameters to be designed, , .

7. The fault-tolerant control method for multi-UAV formation based on extended state observer according to claim 1, characterized in that: In step S8, a new uncertainty variable is introduced and defined as , , then the first dynamic model when the following UAV fails in the formation system is: in, , express The estimation error, express estimated value of; Based on the sliding surface and adaptive law, a sliding mode adaptive fault-tolerant formation controller is designed. for: in, express estimates; At the same time, considering the impact of actuator failures in the platooning system, an adaptive algorithm is used for estimation, and the adaptive law is designed as follows: in, express The first time derivative of .

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