基于几何稳定的自主微型旋翼无人机低能耗多层次混合消振研究

Multi-source complex vibrations in micro rotor-based unmanned aerial vehicles (MAVs) pose a great challenge to achieve durably stable autonomous navigation and control tasks.The drawbacks of existing vibration control methods include unsatisfied compensation results over all types of vibrations and higher energy consumption. In order to resolve the challenging research problem that compensates all types of MAVs vibrations in the entire amplitude and frequency spectrum, the reduced-energy multilayer integrated vibration control system of autonomous MAVs and its stability analysis will be investigated.In order to counteract rotor vibration and hovering vibration caused by uncertain errors of autonomous sensors, the rotor damping configuration and the compensation method of autonomous sensor errors will first be discussed. In addition, reduced-energy multilayer integrated vibration control method of autonomous MAVs will be proposed. This work will provide several key contributions. Firstly, based on geometric stability mechanism, the new rotor configuration will be designed to damp the rotor vibration. Secondly, in order to control hovering vibration caused by sensor errors, a new nonlinear perturbed complementary filter will be developed to compensate uncertain errors of autonomous sensors. Finally, the stability of the reduced-energy multilayer integrated vibration control system will be analyzed based on switching system stability theory. The research results will put forward new ideas on MAV rotor damping configuration, multi-sensor data fusion in unknown constrained areas and stability analysis of the reduced-energy multilayer integrated vibration control system. Furthermore, the theoretical methods and technical support will be provided for our MAVs to implement durably stable autonomous navigation and control tasks under multi-source complex vibrations and unknown constrained environments.

多源复杂振动是影响微型旋翼无人机长时自主稳定导航与控制的重要因素。目前消振方法能耗大且抑制振动类型单一。针对同时削弱微型旋翼无人机所有类型振动这一亟待解决的难点问题，本项目着重研究自主微型旋翼无人机低能耗多层次混合消振系统及其稳定性。研究过程从旋翼消振结构和消弱自主传感器误差引起的振动入手，研究自主微型旋翼无人机低能耗多层次混合消振技术。研究内容包括：基于几何稳定机理的旋翼消振结构设计方法；基于非线性摄动补偿滤波的不确定自主多传感器误差及悬停振动抑制；基于切换系统稳定性理论的低能耗多层次混合消振系统稳定性条件。研究成果将在微型旋翼无人机旋翼消振结构、未知约束区域内自主多传感器信息处理、低能耗混合消振控制系统稳定性分析等方面提出新思路，为我国微型旋翼无人机在多源复杂振动及未知约束环境下的长时自主稳定导航与控制提供理论方法与技术支持。

多源复杂振动是影响微型旋翼无人机长时自主稳定导航与控制的重要因素。为了保证能够有效削弱微型旋翼无人机多类型振动，本项目着重研究了自主微型旋翼无人机低能耗多层次混合消振问题。主要研究内容如下：. 高速旋转旋翼及旋翼质心不平衡导致的旋翼交变振动是微型旋翼无人机振动的主要因素和源泉。研究过程以环形框架旋翼结构为对象，基于旋转弹性梁理论分析并建立了旋翼的交变振动非线性模型，揭示了非线性不稳定旋翼交变振动与机体振动速度之间的关系。在此基础上，结合框架陀螺稳定原理设计了基于几何稳定的新型陀螺环形框架式旋翼消振结构，并在搭建的微小型共轴双旋翼无人机测试平台上，通过非线性PID控制等算法仿真验证了该消振结构隔离旋翼振动对机身影响的有效性。. 微机电惯性信息的精度和可靠性是消弱悬停振动、保证微型旋翼无人机稳定自主悬停的关键因素。为了提高惯性信息的精度和可靠性，研究了基于粒子群算法的非线性惯性信息最优预处理方法。在此基础上，将非惯性信息引入到微机电惯性不确定姿态和速度误差抑制环节，通过非线性补偿滤波、模糊自适应非线性H∞滤波等技术完成多传感器信息融合。此外，研究了基于因子图的复杂振动环境下多传感器混成滤波技术，并在相关测试评价平台上完成仿真验证。试验结果表明，多传感器信息的有效融合能够从导航层面抑制多类型振动，提高微型旋翼无人机自主导航精度。. 不同飞行状态与振动情况下，振动控制方法之间以及信息融合方法之间的相互切换，是抑制振动并降低能量消耗的一种有效手段。研究了具有切换特性的自适应鲁棒卡尔曼滤波方法以及滑动变结构信息融合方法，平衡状态突变情况下多源传感器信息融合的自适应性与鲁棒性，有效抑制振动对导航参数的影响。针对不同状态下的运载体运动学模型，仿真验证了各种振动控制方法的有效性，在此基础上研究了基于切换思想的混合式振动控制方法，以便低能耗削弱微型旋翼无人机所有类型振动，为微型旋翼无人机自主安全稳定飞行提供保障。