基于蚁群算法的无人机轨迹跟踪最优MIMO滑模控制器

Khedidja Bouhabza, M. Guiatni, Y. Bouzid, M. Hamerlain
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引用次数: 0

摘要

针对存在传感器噪声的四旋翼无人机,设计了一种优化的非线性鲁棒多输入多输出(MIMO)滑模控制器。为了实现四旋翼飞行器非线性微分输入输出模型的渐近线性化,该方法采用了一种新颖的滑动面选择方法。为了在跟踪误差和能量消耗之间取得平衡,采用蚁群优化算法对控制器参数进行了选择。采用广义Lyapunov方法来评价系统的整体稳定性,系统是一个具有动态反馈的典型状态空间。仿真结果验证了所提控制器的有效性,并对其性能进行了评价。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
ACO Based Optimal MIMO Sliding Mode Controller for UAV Trajectory Tracking in the Presence of Sensor Noises
In this paper, an optimized nonlinear robust Multi-Input Multi-Output (MIMO) Sliding Mode Controller is designed to control and stabilize a Quadrotor Unmanned Aerial Vehicle (UAV) in the presence of sensor noises. To achieve asymptotic linearisation of the nonlinear differential input-output model of the Quadrotor, the proposed method employs a novel sliding surface choice. The parameters of the proposed controller have been selected using the Ant Colony Optimization (ACO) algorithm considering a performance criteria in order to achieve a trade-off between the tracking error and the consumed energy. A generalized Lyapunov approach is used to evaluate the overall system's stability, which is a canonical state space with dynamic feedback. Simulation results are provided to validate the pro-posed controller and evaluate its performance.
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