모델 예측 제어와 네트워크 지연 보상 기법을 이용한 무인기의 네트워크 제어

학위논문 (석사)-- 서울대학교 대학원 : 공과대학 기계항공공학부, 2019. 2. 김현진.본 연구는 시간에 따라 변화하는 네트워크 지연이 존재하는 네트워크 환경에서의 무인 항공기 (UAV)의 제어 기법에 대하여 소개한다. 네트워크 지연은 주로 상태 피드백과 제어 입력의 지연을 야기시키고, 이로 인해 UAV 제어 시스템의 안정성에 악영향을 미친다. 이와 같은 네트워크 지연에 대처하기 위하여 몇 가지 네트워크 제어 알고리즘이 제안되었지만 대부분의 기존 연구에서는 플랜트 동역학이 매우 단순하거나 정확히 알고 있다고 가정하였고, 일정한 네트워크 지연이 발생하는 상황에서만 수행되었다. 하지만 이러한 가정은 비선형 모델 및 시간에 민감한 제어 특성을 가지는 멀티로터 형태의 UAV에 적합하지 않다. 이러한 문제를 해결하기 위하여 멀티로터의 특성을 고려하여 설계된 모델 예측 제어 (MPC)를 이용한 네트워크 제어 시스템을 제안한다. 또한 경로 계획 및 상태 추정의 정확도를 높이고자 가우시안 프로세스 (GP) 기법을 적용하여, 멀티로터 동역학에 고려되지 않은 미지의 모델을 학습하도록 한다. 실내 비행 실험을 통하여 제안 된 알고리즘이 네트워크 지연을 효과적으로 보상하고 가우시안 프로세스 학습이 UAV의 경로 추적 성능을 향상 시킨다는 것을 보여준다.This study addresses an operation of unmanned aerial vehicles (UAVs) in a network environment where there is time-varying network delay. The network delay entails undesirable effects on the stability of the UAV control system due to delayed state feedback and outdated control input. Although several networked control algorithms have been proposed to deal with the network delay, most existing studies have assumed that the plant dynamics is known and simple, or the network delay is constant. These assumptions are improper to multirotor-type UAVs because of their nonlinearity and time-sensitive characteristics. To deal with these problems, we propose a networked control system using model predictive control (MPC) designed under the consideration of multirotor characteristics. We also apply a Gaussian process (GP) to learn an unknown nonlinear model, which increases the accuracy of path planning and state estimation. Flight experiments show that the proposed algorithm successfully compensates the network delay and Gaussian process learning improves the UAVs path tracking performance.Abstract . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . iii Table of Contents . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . iv List of Figures . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . v List of Tables . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . vi Chapter 1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 1.1 Literature review . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 1.2 Thesis contribution . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3 1.3 Thesis outline . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3 2 Problem statement . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4 2.1 GP-MPC for path planning . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6 2.2 Uplink delay compensation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7 2.3 Downlink delay compensation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8 2.4 Clock synchronization . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9 3 Model learning using Gaussian process . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10 3.1 System dynamics for multirotor . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10 3.2 Gaussian process to improve dynamic model . . . . . . . . . . . . . . . . . . . . . . 11 4 Model predictive control for networked UAV . . . . . . . . . . . . . . . . . . . . . . . . . 14 4.1 MPC formulation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14 4.2 MPC formulation for networked control systems . . . . . . . . . . . . . . . . . . . 15 5 Flight experiment . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17 5.1 Delay analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17 5.2 Experimental setup . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 18 5.3 Experiment 1: circular flight with network delays . . . . . . . . . . . . . . . . . . . 20 5.4 Experiment 2: two UAVs control with different network delays . . . . . . . . . . . 24 6 Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 27Maste

A Review of Consensus-based Multi-agent UAV Implementations

In this paper, a survey on distributed control applications for multi Unmanned Aerial Vehicles (UAVs) systems is proposed.The focus is on consensus-based control, and both rotary-wing and fixed-wing UAVs are considered. On one side, the latest experimental configurations for the implementation of formation flight are analysed and compared for multirotor UAVs. On the other hand, the control frameworks taking into account the mobility of the fixed-wing UAVs performing target tracking are considered. This approach can be helpful to assess and compare the solutions for practical applications of consensus in UAV swarms

The role of closed-loop attitude dynamics in adaptive UAV position control

This paper presents the design and the stability analysis of an adaptive position controller for Unmanned Aerial Vehicles (UAVs). Considering a hierarchical control scheme, the novelty of this work is the definition of a systematic approach to design a position controller based on Model Reference Adaptive Control (MRAC) theory taking into account not-fast closed-loop attitude dynamics. After having reformulated the problem considering the attitude dynamics as pseudo-actuator, the authors exploit an existing Linear Matrix Inequality (LMI) based hedging framework designed such that the adaptation performance is not affected by the presence of actuator dynamics. Results from simulations and from experiments on a platform designed to replicate the longitudinal motion of quadrotors are provided to illustrate the performance of the proposed control scheme

The MRS UAV System: Pushing the Frontiers of Reproducible Research, Real-world Deployment, and Education with Autonomous Unmanned Aerial Vehicles

We present a multirotor Unmanned Aerial Vehicle control (UAV) and estimation system for supporting replicable research through realistic simulations and real-world experiments. We propose a unique multi-frame localization paradigm for estimating the states of a UAV in various frames of reference using multiple sensors simultaneously. The system enables complex missions in GNSS and GNSS-denied environments, including outdoor-indoor transitions and the execution of redundant estimators for backing up unreliable localization sources. Two feedback control designs are presented: one for precise and aggressive maneuvers, and the other for stable and smooth flight with a noisy state estimate. The proposed control and estimation pipeline are constructed without using the Euler/Tait-Bryan angle representation of orientation in 3D. Instead, we rely on rotation matrices and a novel heading-based convention to represent the one free rotational degree-of-freedom in 3D of a standard multirotor helicopter. We provide an actively maintained and well-documented open-source implementation, including realistic simulation of UAV, sensors, and localization systems. The proposed system is the product of years of applied research on multi-robot systems, aerial swarms, aerial manipulation, motion planning, and remote sensing. All our results have been supported by real-world system deployment that shaped the system into the form presented here. In addition, the system was utilized during the participation of our team from the CTU in Prague in the prestigious MBZIRC 2017 and 2020 robotics competitions, and also in the DARPA SubT challenge. Each time, our team was able to secure top places among the best competitors from all over the world. On each occasion, the challenges has motivated the team to improve the system and to gain a great amount of high-quality experience within tight deadlines.Comment: 28 pages, 20 figures, submitted to Journal of Intelligent & Robotic Systems (JINT), for the provided open-source software see http://github.com/ctu-mr

RISE-Based Adaptive Control with Mass-Inertia Parameter Estimation for Aerial Transportation of Multi-Rotor UAVs

This paper proposes an adaptive tracking strategy with mass-inertia estimation for aerial transportation problems of multi-rotor UAVs. The dynamic model of multi-rotor UAVs with disturbances is firstly developed with a linearly parameterized form. Subsequently, a cascade controller with the robust integral of the sign of the error (RISE) terms is applied to smooth the control inputs and address bounded disturbances. Then, adaptive estimation laws for mass-inertia parameters are designed based on a filter operation. Such operation is introduced to extract estimation errors exploited to theoretically guarantee the finite-time (FT) convergence of estimation errors. Finally, simulations are conducted to verify the effectiveness of the designed controller. The results show that the proposed method provides better tracking and estimation performance than traditional adaptive controllers based on sliding mode control algorithms and gradient-based estimation strategies

Design, Development and Implementation of Intelligent Algorithms to Increase Autonomy of Quadrotor Unmanned Missions

This thesis presents the development and implementation of intelligent algorithms to increase autonomy of unmanned missions for quadrotor type UAVs. A six-degree-of freedom dynamic model of a quadrotor is developed in Matlab/Simulink in order to support the design of control algorithms previous to real-time implementation. A dynamic inversion based control architecture is developed to minimize nonlinearities and improve robustness when the system is driven outside bounds of nominal design. The design and the implementation of the control laws are described. An immunity-based architecture is introduced for monitoring quadrotor health and its capabilities for detecting abnormal conditions are successfully demonstrated through flight testing. A vision-based navigation scheme is developed to enhance the quadrotor autonomy under GPS denied environments. An optical flow sensor and a laser range finder are used within an Extended Kalman Filter for position estimation and its estimation performance is analyzed by comparing against measurements from a GPS module. Flight testing results are presented where the performances are analyzed, showing a substantial increase of controllability and tracking when the developed algorithms are used under dynamically changing environments. Healthy flights, flights with failures, flight with GPS-denied navigation and post-failure recovery are presented

Nonlinear Control Strategies for Outdoor Aerial Manipulators

In this thesis, the design, validation and implementation of nonlinear control strategies for aerial manipulators {i.e. aerial robots equipped with manipulators{ is studied, with special emphasis on the internal coupling of the system and its resilience against external disturbances. For the rst, di erent decentralised control strategies {i.e. using di erent control typologies for each one of the subsystems{ that indirectly take into account this coupling have been analysed. As a result, a nonlinear strategy composed of two controllers is proposed. A higher priority is given to the manipulation accuracy, relaxing the platform tracking, and hence obtaining a solution improving the manipulation capabilities with the surrounding environment. To validate these results, thorough stability and robustness analyses are provided, both theoretically and in simulation. On the other hand, a signi cant e ort has been devoted to improving the response and applicability of robot manipulators used in ight via control. In particular, the design of controllers for lightweight exible manipulators {that reduce the consequences of incidents involving unforeseen contacts{ is analysed. Although their inherent nature perfectly ts for aerial manipulation applications, the added exibility produces unwanted behaviours, such as second-order modes and uncertainties. To cope with them, an adaptable position nonlinear control strategy is proposed. To validate this contribution, the stability of the approach is studied in theory and its capabilities are proven in several experimental scenarios. In these, the robustness of the solution against unforeseen impacts and contact with uncharacterised interfaces is demonstrated. Subsequently, this strategy has been enriched with {multiaxis{ force control capabilities thanks to the inclusion of an outer control loop modifying the manipulator reference. Accordingly, this additional applicationfocused capability is added to the controlled system without loosing the modulated response of the inner-loop position strategy. It is also worth noting that, thanks to the cascade-like nature of the modi cation, the transition between position and force control modes is inherently smooth and automatic. The stability of this expanded strategy has been theoretically analysed and the results validated in a set of experimental scenarios. To validate the rst nonlinear approach with realistic outdoor simulations before its implementation, a computational uid dynamics analysis has been performed to obtain an explicit model of the aerodynamic forces and torques applied to the blunt-body of the aerial platform in ight. The results of this study have been compared to the most common alternative nowadays, being highlighted that the proposed model signi cantly surpasses this option in terms of accuracy. Moreover, it is worth underscoring that this characterisation could be also employed in the future to develop control solutions with enhanced rejection capabilities against wind conditions. Finally, as the focus of this thesis is on the use of novel control strategies on real aerial manipulation outdoors to improve their accuracy while performing complex tasks, a modular autopilot solution to be able to implement them has been also developed. This general-purpose autopilot allows the implementation of new algorithms, and facilitates their theory-to-experimentation transition. Taking into account this perspective, the proposed tool employs the simple and widely-known MAS interface and the highly reliable PX4 autopilot as backup, thus providing a redundant approach to handle unexpected incidents in ight.En esta tesis se ha estudiado el diseño, validación e implementación de estrategias de control no lineales para robots manipuladores aéreos –esto es, robots aéreos equipados con un sistema de manipulación robótica–, dándose especial énfasis a las interacciones internas del sistema y a su resiliencia frente a efectos externos. Para lo primero, se han analizado diferentes estrategias de control descentralizado –es decir, que usan tipologías de control diferentes para cada uno de los subsistemas–, pero que tienen indirectamente en consideración la interacción entre manipulación y vuelo. Como resultado de esta línea, se propone una estretegia de control conformada por dos controladores. Estos se coordinan de tal forma que se le da prioridad a la manipulación sobre el seguimiento de posiciones del vehículo, produciéndose un sistema de control que mejora la precisión de las interacciones entre el sistema manipulador y el entorno. Para validar estos resultados, se ha analizado su estabilidad y robustez tanto teóricamente como mediante simulaciones numéricas. Por otro lado, se ha buscado mejorar la respuesta y aplicabilidad de los manipuladores que se usan en vuelo mediante su control. Dentro de esta tendencia, la tesis se ha centrado en el diseño de controladores para manipuladores ligeros flexibles, ya que estos permiten reducir el peso del sistema completo y reducen el riesgo de incidentes debidos a contactos inesperados. Sin embargo, la flexibilidad de estos produce comportamientos indeseados durante la operación, como la aparición de modos de segundo orden y cierta incentidumbre en su comportamiento. Para reducir su impacto en la precisión de las tareas de manipulación, se ha desarrollado un controlador no lineal adaptable. Para validar estos resultados, se ha analizado la estabilidad del sistema teóricamente y se han desarrollado una serie de experimentos. En ellos, se ha comprobado su robustez ante impactos inesperados y contactos con elementos no caracterizados. Posteriormente, esta estrategia para manipuladores flexibles ha sido ampliada al añadir un bucle externo que posibilita el control en fuerzas en varias direcciones. Esto permite, mediante un único controlador, mantener la suave respuesta de la estrategia. Además cabe destacar que, al contar esta estrategia con un diseño en cascade, la transición entre los segmentos de desplazamiento del brazo y de aplicación de fuerzas es fluida y automática. La estabilidad de esta estrategia ampliada ha sido analizada teóricamente y los resultados han sido validados experimentalmente. Para validar la primera estrategia mediante simulaciones que representen fielmente las condiciones en exteriores antes de su implementación, ha sido necesario realizar un estudio mediante mecánica de fluidos computacional para obtener un modelo explícito de las fuerzas y momentos aerodinámicos a los que se efrenta la plataforma en vuelo. Los resultados de este estudio han sido comparados con la alternativa más empleada actualmente, mostrándose que los avances del método propuesto son sustanciales. Asimismo, es importante destacar que esta caracterización podría también usarse en el futuro para desarrollar controladores con una respuesta mejorada ante perturbaciones aerodinámicas, como en el caso de volar con viento. Finalmente, al ser esta una tesis centrada en las estrategias de control novedosas en sistemas reales para la mejora de su rendimiento en misiones complejas, se ha desarrollado un autopiloto modular fácilmente modificable para implementarlas. Este permite validar experimentalmente nuevos algoritmos y facilita la transición entre teoría y práctica. Para ello, esta herramienta se basa en una interfaz sencilla ampliamente conocida por los investigadores de robótica, Simulink®, y cuenta con un autopiloto de respaldo, PX4, para enfrentarse a los incidentes inesperados que pudieran surgir en vuelo

Active Disturbance Rejection Control for the Robust Flight of a Passively Tilted Hexarotor

This paper presents a robust control strategy for controlling the flight of a passively (fixed) tilted hexarotor unmanned aerial vehicle (UAV). The proposed controller is based on a robust extended-state observer to estimate and reject internal dynamics and external disturbances at run-time. Both stability and convergence of the observer are proved using Lyapunov-based perturbation theory and an ultimate bound approach. Such a controller is implemented within a highly realistic simulation environment that includes physics motors, devising an almost transparent behaviour with respect to the real UAV. The controller is tested for flying under normal conditions and in the presence of different types of disturbances showing successful results. Furthermore, the proposed control system is compared against another robust control approach, presenting a better performance regarding the attenuation of the error signals