Accurate and precise trajectory tracking is crucial for unmanned aerial vehicle (UAVs) to operate in disturbed environments. This paper presents a novel tracking hybrid controller for a quadrotor UAV that combines the robust adaptive neuro-fuzzy inference system (ANFIS) controller and Improved Particle Swarm Optimization algorithm (IPSO) model based on functional inertia weight. The controller is implemented in a three degrees of freedom (3 DOF) quadrotor symbolized with its non-linear dynamical mathematical model. To achieve Cartesian position trajectory tracking capability, the construction of the controller can be divided into two stages: a regular ANFIS controller to guarantee fast convergence rapidity and IPSO aims to facilitate convergence to the ANFIS’s optimal parameters to accurately reproduce a desired reference trajectory. Simulation results are given to confirm the advantages of the proposed intelligent control, compared with ANFIS and PID control methods.

中文翻译：

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基于ANFIS-IPSO系统的无人机最优轨迹跟踪控制

准确和精确的轨迹跟踪对于无人驾驶飞机（UAV）在受干扰的环境中运行至关重要。本文提出了一种新颖的四旋翼无人机跟踪混合控制器，该控制器结合了鲁棒的自适应神经模糊推理系统（ANFIS）控制器和基于功能惯性权重的改进粒子群优化算法（IPSO）模型。控制器以三自由度（3 DOF）四旋翼飞机实现，该四旋翼飞机用其非线性动力学数学模型表示。为了实现笛卡尔位置轨迹跟踪能力，控制器的结构可分为两个阶段：常规ANFIS控制器可确保快速收敛速度，而IPSO旨在促进收敛到ANFIS的最佳参数以准确地再现所需的参考轨迹。