This article deals with the issue of designing a flight tracking controller for an unmanned aerial vehicle type of quadrotor based on an optimal model-free fuzzy logic control approach. The main design objective is to perform an automatic flight trajectory tracking under multiple model uncertainties related to the knowledge of the nonlinear dynamics of the system. The optimal control is also addressed taking into consideration unknown external disturbances. To achieve this goal, we propose a new optimal model-free fuzzy logic–based decentralized control strategy where the influence of the interconnection term between the subsystems is minimized. A model-free controller is firstly designed to achieve the convergence of the tracking error. For this purpose, an adaptive estimator is proposed to ensure the approximation of the nonlinear dynamic functions of the quadrotor. The fuzzy logic compensator is then introduced to deal with the estimation error. Moreover, the optimization problem to select the optimal design parameters of the proposed controller is solved using the bat algorithm. Finally, a numerical validation based on the Parrot drone platform is conducted to demonstrate the effectiveness of the proposed control method with various flying scenarios.

本文讨论了基于最优无模型模糊逻辑控制方法为四旋翼无人机类型设计飞行跟踪控制器的问题。主要设计目标是在与系统非线性动力学知识相关的多个模型不确定性下执行自动飞行轨迹跟踪。还考虑到未知的外部干扰来解决最优控制。为了实现这一目标，我们提出了一种新的基于最佳无模型模糊逻辑的分散控制策略，其中子系统之间互连项的影响最小。首先设计了一种无模型控制器来实现跟踪误差的收敛。以此目的，提出了一种自适应估计器，以确保四旋翼飞行器的非线性动态函数的逼近。然后引入模糊逻辑补偿器来处理估计误差。此外，使用bat算法解决了选择所提出控制器的最佳设计参数的优化问题。最后，基于 Parrot 无人机平台进行了数值验证，以证明所提出的控制方法在各种飞行场景下的有效性。