Fixed-wing unmanned aerial vehicle formation finite time fault-tolerant control method based on neural network

Abstract

The invention discloses a fixed-wing unmanned aerial vehicle finite time formation fault-tolerant control method based on a neural network, and the method comprises the steps: firstly, carrying out the formation control through a virtual leader-follower structure, and carrying out the information interaction through a distributed formation method, based on this, designing a corresponding communication topological graph and calculating a corresponding adjacency matrix and a Laplacian matrix; then, aiming at a longitudinal model of the fixed-wing unmanned aerial vehicle, simplifying a dynamic model into a strict feedback form based on a reasonable assumed condition, and considering a failure fault of elevator deflection; on the basis of a backstepping method, sliding mode control is combined, an unknown nonlinear function of a model is processed through a radial basis function neural network, and the failure fault of the elevator is estimated in a self-adaptive mode, so that fault-tolerant control within finite time is achieved. The problem that formation fault-tolerant control is difficult due to the fact that the longitudinal model of the fixed-wing unmanned aerial vehicle serves as a high-order nonlinear system is solved, and the system has high robustness and can be stable within finite time.

Description

technical field [0001] The invention relates to a limited-time formation fault-tolerant control method for a fixed-wing unmanned aerial vehicle based on a neural network, and belongs to the technical field of multi-agent systems based on an intelligent control method. Background technique [0002] In recent years, Unmanned Aerial Vehicle (UAV) has been widely used due to its unique advantages such as low cost, high maneuverability, light weight, and autonomous flight function. Compared with rotary-wing UAVs, fixed-wing UAVs have the advantages of faster speed, larger payload, higher flight altitude, longer endurance and longer range. Compared with a single UAV, the formation system composed of multiple UAVs is not only superior in endurance, coverage and task execution efficiency, but also can complete more and more complex tasks. Therefore, the research of fixed-wing UAV formation system has broad application prospects. [0003] Since fixed-wing UAVs are underactuated, st...

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Problems solved by technology

[0005] In order to solve the technical problems raised by the above-mentioned background technology, the present invention aims to provide a finite-time formation fault-tolerant control method for fixed-wing unmanned aerial vehicles based on neural networks, which overcomes the difficulty of realizing formation fault-tolerant control due to the complexity of high-order nonlinear models. problems, and is committed to achieving finite time convergence to achieve faster and more reliable control effects

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