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Control of Microcoaxial Helicopter Based on a Reduced-Order Observer

机译：基于降序观测器的微同轴直升机控制

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Miniature aerial vehicles (MAVs) are finding applications in a number of civilian domains in which their autonomous operations are desirable. Applications of miniature aerial vehicles in different areas are growing exponentially due to technological advancement in areas such as computing, sensing, and communication, and due to advantages offered by these vehicles in terms of safe and economic operations. Due to the drive to keep cost of MAVs low, or lack of available technology and accurate sensors, exact measurement of pertinent signals and states of these kinds of nonlinear systems is not always possible. This necessitates the development of algorithmic tools such as observers that can be used to enhance the performance of sensors and measurement devices. The more complex a control system becomes, the more difficult it becomes to measure the states of the system accurately, which inherently makes the development of observers more challenging. In this paper, state observer and control system design for a small coaxial helicopter are presented. The states are observed with three different methods and compared for designing a classical pole-placement controller (based on a linearized model of the plant) and applied to a coaxial helicopter. The observer design methods used in this paper are based on Kalman filter and full-and reduced-order Luenberger observers. Numerical simulations have been carried out to illustrate the proposed techniques. Comparison of the three proposed methods confirms the intuitive notion that, in case of noisy systems, using Kalman filter method yields more accurate results as compared with the Luenberger methods. (C) 2015 American Society of Civil Engineers.
机译：微型飞行器（MAV）正在许多需要自主操作的民用领域中找到应用。微型计算机在不同领域的应用呈指数增长，这是由于计算，传感和通信等领域的技术进步，以及这些飞机在安全和经济运行方面的优势。由于要使MAV的成本保持在较低水平，或者缺乏可用的技术和精确的传感器，因此并非总是可能对此类非线性系统的相关信号和状态进行准确的测量。这就需要开发可用于增强传感器和测量设备性能的算法工具，例如观察器。控制系统越复杂，准确测量系统状态就越困难，这必然会给观察者的开发带来更大的挑战。本文提出了一种小型同轴直升机的状态观测器和控制系统设计。使用三种不同的方法观察这些状态，并将其比较以设计经典的杆位控制器（基于工厂的线性模型）并应用于同轴直升机。本文使用的观测器设计方法基于卡尔曼滤波器以及全阶和降阶Luenberger观测器。进行了数值模拟以说明所提出的技术。三种建议方法的比较证实了直觉的观念，即在嘈杂的系统中，与Luenberger方法相比，使用Kalman滤波方法可获得更准确的结果。 （C）2015年美国土木工程师学会。

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