Purpose

This study aims to deal with the problem of trajectory tracking control for the quadrotor under external environmental disturbance and variable payloads.

Design/methodology/approach

In the field of unmanned aerial vehicle (UAV) control, external environmental disturbance and internal variable payloads as two major interference factors lead to control performance degradation or even instability, thus a trajectory tracking controller which innovatively combines sliding mode control technology and model-free control technique is proposed. The proposed controller is constructed with a learning rate-based sliding mode controller and an ultra-local model. Based on the proposed controller, the nonlinear system model of variable load quadrotor is locally estimated and the system’s uncertainties and disturbances can be compensated.

Findings

The simulation and actual test results demonstrate the satisfactory control performance and the robustness of the proposed controller compared with the PID and Backstepping controller under external environmental disturbance and variable payloads. Moreover, the proposed controller solves the trajectory tracking control problem not only when payloads change at the center of gravity but also when the position of load variation deviates from the center of gravity.

Practical implications

In both military and civilian domains, the quadrotor may encounter such situations that the payloads change, such as transporting goods, aerial refueling and so on. As a large internal interference factor, variable load tends to lead to unstable control. The research results provide theoretical guidance and technical support for trajectory tracking control of quadrotor under variable payloads.

Originality/value

The proposed controller combines learning rate-based sliding mode controller and model-free control technique to achieve a more efficient and accurate trajectory control of the quadrotor when considering system uncertainties and the load variation that happens in the unknown location.

中文翻译：

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基于无模型控制器和滑模控制技术的可变载荷下四旋翼飞行器轨迹跟踪控制

目的

本研究旨在解决外部环境干扰和可变载荷下四旋翼飞行器的轨迹跟踪控制问题。

设计/方法/方法

在无人机（UAV）控制领域，外部环境扰动和内部可变载荷作为两大干扰因素导致控制性能下降甚至不稳定，因此创新地结合滑模控制技术和无模型控制的轨迹跟踪控制器技术提出。所提出的控制器由基于学习率的滑模控制器和超局部模型构成。基于所提出的控制器，对可变负载四旋翼飞行器的非线性系统模型进行了局部估计，并且可以补偿系统的不确定性和扰动。

发现

仿真和实际测试结果表明，在外部环境干扰和可变有效载荷下，与 PID 和 Backstepping 控制器相比，所提出的控制器具有令人满意的控制性能和鲁棒性。此外，所提出的控制器不仅解决了当有效载荷在重心处发生变化时，而且当载荷变化位置偏离重心时的轨迹跟踪控制问题。

实际影响

在军用和民用领域，四旋翼飞行器可能会遇到载荷发生变化的情况，如运输货物、空中加油等。作为一个较大的内部干扰因素，可变负载往往会导致控制不稳定。研究成果为可变载荷下四旋翼飞行器轨迹跟踪控制提供理论指导和技术支持。

原创性/价值

所提出的控制器结合了基于学习率的滑模控制器和无模型控制技术，在考虑系统不确定性和未知位置发生的负载变化时，实现了更有效、更准确的四旋翼飞行器轨迹控制。