멀티로터 기반 다목적 비행 로봇 플랫폼을 위한 강건 제어 및 완전구동 비행 매커니즘

학위논문(박사)--서울대학교 대학원 :공과대학 기계항공공학부,2020. 2. 김현진.오늘날 멀티로터 무인항공기는 단순한 비행 및 공중 영상 촬영용 장비의 개념을 넘어 비행 매니퓰레이션, 공중 화물 운송 및 공중 센싱 등의 다양한 임무에 활용되고 있다. 이러한 추세에 맞추어 로보틱스 분야에서 멀티로터 무인항공기는 부과된 임무에 맞추어 원하는 장비 및 센서를 자유로이 탑재하고 비행할 수 있는 다목적 공중 로봇 플랫폼으로 인식되고 있다. 그러나 현재의 멀티로터 플랫폼은 돌풍 등의 외란에 다소 강건하지 못한 제어성능을 보인다. 또한, 병진운동의 제어를 위해 비행 중 지속적으로 동체의 자세를 변경해야 해 센서 등 동체에 부착된 탑재물의 자세 또한 지속적으로 변화한다는 단점을 가지고 있다. 위의 두 가지 문제들을 해결하고자 본 연구에서는 외란에 강건한 멀티로터 제어기법과, 병진운동과 자세운동을 독립적으로 제어할 수 있는 새로운 형태의 완전구동 멀티로터 비행 매커니즘을 소개한다. 강건 제어기법의 경우, 먼저 정확한 병진운동 제어를 위한 병진 힘 생성 기법을 소개하고 뒤이어 병진 힘 외란에 강건한 제어를 위한 외란관측기 기반 강건 제어 알고리즘의 설계 방안을 논의한다. 제어기의 피드백 루프 안정성은 mu 안정성 분석 기법을 통해 검증되며, mu 안정성 분석이 가지는 엄밀한 안정성 분석의 결과를 검증하기 위해 스몰게인 이론 (Small Gain Theorem) 기반의 안정성 분석 결과가 동시에 제시 및 비교된다. 최종적으로, 개발된 제어기를 도입한 멀티로터의 3차원 병진 가속도 제어 성능 및 힘 벡터의 형태로 인가되는 병진 운동 외란에 대한 극복 성능을 실험을 통해 검증하여, 제안된 제어기법의 효과적인 비행 지점 및 궤적 추종 능력을 확인한다. 완전 구동 멀티로터의 경우, 기존의 완전구동 멀티로터가 가진 과도한 중량 증가 및 저조한 에너지 효율을 극복하기 위한 새로운 매커니즘을 소개한다. 새로운 매커니즘은 기존 멀티로터와 최대한 유사한 형태를 가지되 완전구동을 위해 오직 두 개의 서보모터만을 포함하며, 이로 인해 기존 멀티로터와 비교해 최소한의 형태의 변형만을 가지도록 설계된다. 새로운 플랫폼의 동적 특성에 대한 분석과 함께 유도된 운동방정식을 기반으로 한 6자유도 비행 제어기법이 소개되며, 최종적으로 다양한 실험과 그 결과들을 통해 플랫폼의 완전구동 비행 능력을 검증한다. 추가적으로 본 논문에서는 완전구동 멀티로터가 가지는 여분의 제어입력(redundancy)를 활용한 쿼드콥터의 단일모터 고장 대비 비상 비행 기법을 소개한다. 비상 비행 전략에 대한 자세한 소개 및 실현 방법, 비상 비행 시의 동역학적 특성에 대한 분석 결과가 소개되며, 실험결과를 통해 제안된 기법의 타당성을 검증한다.Recently, multi-rotor unmanned aerial vehicles (UAVs) are used for a variety of missions beyond its basic flight, including aerial manipulation, aerial payload transportation, and aerial sensor platform. Following this trend, the multirotor UAV is recognized as a versatile aerial robotics platform that can freely mount and fly the necessary mission equipment and sensors to perform missions. However, the current multi-rotor platform has a relatively poor ability to maintain nominal flight performance against external disturbances such as wind or gust compared to other robotics platforms. Also, the multirotor suffers from maintaining a stable payload attitude, due to the fact that the attitude of the fuselage should continuously be changed for translational motion control. Particularly, unstabilized fuselage attitude can be a drawback for multirotor's mission performance in such cases as like visual odometry-based flight, since the fuselage-attached sensor should also be tilted during the flight and therefore causes poor sensor information acquisition. To overcome the above two problems, in this dissertation, we introduce a robust multirotor control method and a novel full-actuation mechanism which widens the usability of the multirotor. The goal of the proposed control method is to bring robustness to the translational motion control against various weather conditions. And the goal of the full actuation mechanism is to allow the multi-rotor to take arbitrary payload/fuselage attitude independently of the translational motion. For robust multirotor control, we first introduce a translational force generation technique for accurate translational motion control and then discuss the design method of disturbance observer (DOB)-based robust control algorithm. The stability of the proposed feedback controller is validated by the mu-stability analysis technique, and the results are compared to the small-gain theorem (SGT)-based stability analysis to validate the rigorousness of the analysis. Through the experiments, we validate the translational acceleration control performance of the developed controller and confirm the robustness against external disturbance forces. For a fully-actuated multirotor platform, we propose a new mechanism called a T3-Multirotor that can overcome the excessive weight increase and poor energy efficiency of the existing fully-actuated multirotor. The structure of the new platform is designed to be as close as possible to the existing multi-rotor and includes only two servo motors for full actuation. The dynamic characteristics of the new platform are analyzed and a six-degree-of-freedom (DOF) flight controller is designed based on the derived equations of motion. The full actuation of the proposed platform is then validated through various experiments. As a derivative study, this paper also introduces an emergency flight technique to prepare for a single motor failure scenario of a multi-rotor using the redundancy of the T3-Multirotor platform. The detailed introduction and implementation method of the emergency flight strategy with the analysis of the dynamic characteristics during the emergency flight is introduced, and the experimental results are provided to verify the validity of the proposed technique.1 Introduction 1 1.1 Motivation 1 1.2 Literature survey 3 1.2.1 Robust translational motion control 3 1.2.2 Fully-actuated multirotor platform 4 1.3 Research objectives and contributions 5 1.3.1 Goal #I: Robust multirotor motion control 5 1.3.2 Goal #II: A new fully actuated multirotor platform 6 1.3.3 Goal #II-A: T3-Multirotor-based fail-safe flight 7 1.4 Thesis organization 7 2 Multi-Rotor Unmanned Aerial Vehicle: Overview 9 2.1 Platform overview 9 2.2 Mathematical model of multi-rotor UAV 10 3 Robust Translational Motion Control 13 3.1 Introduction 14 3.2 Translational force/acceleration control 14 3.2.1 Relationship between \mathbf{r} and \tilde{\ddot{\mathbf{X}}} 15 3.2.2 Calculation of \mathbf{r}_d from \tilde{\ddot{\mathbf{X}}}_d considering dynamics 16 3.3 Disturbance observer 22 3.3.1 An overview of the disturbance-merged overall system 22 3.3.2 Disturbance observer 22 3.4 Stability analysis 26 3.4.1 Modeling of P(s) considering uncertainties 27 3.4.2 \tau-determination through \mu-analysis 30 3.5 Simulation and experimental result 34 3.5.1 Validation of acceleration tracking performance 34 3.5.2 Validation of DOB performance 34 4 Fully-Actuated Multirotor Mechanism 39 4.1 Introduction 39 4.2 Mechanism 40 4.3 Modeling 42 4.3.1 General equations of motion of TP and FP 42 4.3.2 Simplified equations of motion of TP and FP 46 4.4 Controller design 49 4.4.1 Controller overview 49 4.4.2 Independent roll and pitch attitude control of TP and FP 50 4.4.3 Heading angle control 54 4.4.4 Overall control scheme 54 4.5 Simulation result 56 4.5.1 Scenario 1: Changing FP attitude during hovering 58 4.5.2 Scenario 2: Fixing FP attitude during translation 58 4.6 Experimental result 60 4.6.1 Scenario 1: Changing FP attitude during hovering 60 4.6.2 Scenario 2: Fixing FP attitude during translation 60 4.7 Applications 63 4.7.1 Personal aerial vehicle 63 4.7.2 High MoI payload transportation platform - revisit of [1] 63 4.7.3 Take-off and landing on an oscillating landing pad 64 5 Derived Research: Fail-safe Flight in a Single Motor Failure Scenario 67 5.1 Introduction 67 5.1.1 Related works 68 5.1.2 Contributions 68 5.2 Mechanism and dynamics 69 5.2.1 Mechanism 69 5.2.2 Platform dynamics 70 5.3 Fail-safe flight strategy 75 5.3.1 Fail-safe flight method 75 5.3.2 Hardware condition for single motor fail-safe flight 80 5.4 Controller design 83 5.4.1 Faulty motor detection 83 5.4.2 Controller design 84 5.4.3 Attitude dynamics in fail-safe mode 86 5.5 Experiment result 90 5.5.1 Experimental settings 90 5.5.2 Stability and control performance review 92 5.5.3 Flight results 93 6 Conclusions 96 Abstract (in Korean) 107Docto

경첩문을 여는 비행 매니퓰레이터에 대한 모델 예측 제어

학위논문 (석사) -- 서울대학교 대학원 : 공과대학 기계항공공학부, 2020. 8. 김현진.From aerial pick-and-place to aerial transportation, aerial manipulation has been extensively studied in recent years thanks to its mobility and dexterity, each of which is a merit of an aerial vehicle and a robotic arm. However, to fully harness the concept of aerial manipulation, more complex tasks including interaction with movable structures should also be considered. Among various types of movable structures, this paper presents a multirotor-based aerial manipulator opening a daily-life moving structure, a hinged door. Two additional issues that would arise in interaction with a movable structure are addressed: 1) a constrained motion of the structure, and 2) collision avoidance with a moving structure. To handle these issues, we formulate a model predictive control (MPC) problem with a system dynamics constraint and state constraints for collision avoidance. A coupled system dynamics of a multirotor-based aerial manipulator and a hinged door is derived and later simplified for faster computation in MPC. State constraints for collision avoidance with itself, a door, and a doorframe are generated. By implementing a constrained version of differential dynamic programming (DDP), we can generate reference trajectories through MPC in real-time. The proposed method is validated through simulation results and experiments with a real-like hinged door in which a disturbance observer (DOB) based robust motion controller is employed.비행 매니퓰레이터는 3차원 공간 속에 빠르게 위치할 수 있는 비행체의 장점과 외부와의 상호작용이 가능한 로봇팔의 장점이 결합된 비행체로, 최근 물건 집고 옮기기부터 물품 운송까지 다양한 임무를 수행하기 위해 활발하게 연구되어 왔다. 그러나, 온전히 비행 매니퓰레이터의 가능성을 활용하기 위해서는 움직일 수 있는 외부 구조와의 상호작용과 같이 더욱 복잡한 임무 또한 수행할 수 있어야 할 것이다. 여러 종류의 움직일 수 있는 구조물 중 본 논문에서는 일상 속에서 쉽게 마주칠 수 있는 경첩문을 여는 멀티로터 기반의 비행 매니퓰레이터에 대해 제시한다. 정적인 구조물과의 상호작용과는 달리 동적인 구조물과의 상호작용에 있어서 발생할 수 있는 1) 구조물의 제약된 움직임, 그리고 2) 움직이는 구조물과의 충돌 회피의 2가지 추가적인 문제에 대해 다루었다. 이러한 문제를 다루기 위해 모델 예측 제어 (MPC)를 적용하였으며, 시스템 동역학에 대한 제약조건 및 충돌 회피에 대한 제약 조건을 부여하였다. 멀티로터 기반의 비행 매니퓰레이터와 경첩문의 결합 시스템에 대한 동역학을 유도하였으며, 이후 모델 예측 제어에서의 빠른 계산 속도를 위해 단순화되었다. 충돌 회피에 대한 제약 조건은 모두 상태 변수로 표현되었으며, 비행 매니퓰레이터의 멀티로터 프레임과 로봇팔 사이의 충돌 (자기 충돌), 문과의 충돌, 그리고 문틀과의 충돌을 고려하였다. 미분 기반의 동적 프로그래밍 기법 (differential dynamic programming)에 제약조건이 고려된 알고리즘을 구현함으로써 모델 기반 예측 제어를 통해 실시간으로 경로를 계획할 수 있다. 제안된 방법은 시뮬레이션과 실제 크기의 문을 활용한 실험을 통해 검증되었으며, 외란 관측기 기반의 강건 제어 기법이 실험에 활용되었다.1 Introduction 1 1.1 Literature review 2 1.2 Thesis contribution 3 1.3 Thesis outline 3 2 Equations of motion 4 2.1 Assumption 4 2.2 Kinematics 5 2.3 Dynamics 6 2.4 Simpli ed dynamics 8 3 Model predictive control 10 3.1 Problem formulation 10 3.1.1 Objective function 11 3.1.2 Hard constraints 11 3.2 Collision avoidance constraints 11 3.2.1 Self collision avoidance 13 3.2.2 Door collision avoidance 13 3.2.3 Doorframe collision avoidance 14 3.3 Optimal control solver 14 3.3.1 Differential dynamic programming 14 3.3.2 DDP with augmented Lagrangian method 15 4 Experimental setup 17 4.1 Door state estimation 17 4.2 Multirotor robust controller 18 4.3 Hardware setup 19 5 Results 20 5.1 Simulation results 20 5.2 Experimental results 25 6 Conclusion 29Maste

CONTROL STRATEGY OF MULTIROTOR PLATFORM UNDER NOMINAL AND FAULT CONDITIONS USING A DUAL-LOOP CONTROL SCHEME USED FOR EARTH-BASED SPACECRAFT CONTROL TESTING

Over the last decade, autonomous Unmanned Aerial Vehicles (UAVs) have seen increased usage in industrial, defense, research, and academic applications. Specific attention is given to multirotor platforms due to their high maneuverability, utility, and accessibility. As such, multirotors are often utilized in a variety of operating conditions such as populated areas, hazardous environments, inclement weather, etc. In this study, the effectiveness of multirotor platforms, specifically quadrotors, to behave as Earth-based satellite test platforms is discussed. Additionally, due to concerns over system operations under such circumstances, it becomes critical that multirotors are capable of operation despite experiencing undesired conditions and collisions which make the platform susceptible to on-board hardware faults. Without countermeasures to account for such faults, specifically actuator faults, a multirotors will experience catastrophic failure. In this thesis, a control strategy for a quadrotor under nominal and fault conditions is proposed. The process of defining the quadrotor dynamic model is discussed in detail. A dual-loop SMC/PID control scheme is proposed to control the attitude and position states of the nominal system. Actuator faults on-board the quadrotor are interpreted as motor performance losses, specifically loss in rotor speeds. To control a faulty system, an additive control scheme is implemented in conjunction with the nominal scheme. The quadrotor platform is developed via analysis of the various subcomponents. In addition, various physical parameters of the quadrotor are determined experimentally. Simulated and experimental testing showed promising results, and provide encouragement for further refinement in the future

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

Aerial Manipulation: A Literature Review

Aerial manipulation aims at combining the versatil- ity and the agility of some aerial platforms with the manipulation capabilities of robotic arms. This letter tries to collect the results reached by the research community so far within the field of aerial manipulation, especially from the technological and control point of view. A brief literature review of general aerial robotics and space manipulation is carried out as well

Fault Diagnosis and Fault-Tolerant Control of Unmanned Aerial Vehicles

With the increasing demand for unmanned aerial vehicles (UAVs) in both military and civilian applications, critical safety issues need to be specially considered in order to make better and wider use of them. UAVs are usually employed to work in hazardous and complex environments, which may seriously threaten the safety and reliability of UAVs. Therefore, the safety and reliability of UAVs are becoming imperative for development of advanced intelligent control systems. The key challenge now is the lack of fully autonomous and reliable control techniques in face of different operation conditions and sophisticated environments. Further development of unmanned aerial vehicle (UAV) control systems is required to be reliable in the presence of system component faults and to be insensitive to model uncertainties and external environmental disturbances. This thesis research aims to design and develop novel control schemes for UAVs with consideration of all the factors that may threaten their safety and reliability. A novel adaptive sliding mode control (SMC) strategy is proposed to accommodate model uncertainties and actuator faults for an unmanned quadrotor helicopter. Compared with the existing adaptive SMC strategies in the literature, the proposed adaptive scheme can tolerate larger actuator faults without stimulating control chattering due to the use of adaptation parameters in both continuous and discontinuous control parts. Furthermore, a fuzzy logic-based boundary layer and a nonlinear disturbance observer are synthesized to further improve the capability of the designed control scheme for tolerating model uncertainties, actuator faults, and unknown external disturbances while preventing overestimation of the adaptive control parameters and suppressing the control chattering effect. Then, a cost-effective fault estimation scheme with a parallel bank of recurrent neural networks (RNNs) is proposed to accurately estimate actuator fault magnitude and an active fault-tolerant control (FTC) framework is established for a closed-loop quadrotor helicopter system. Finally, a reconfigurable control allocation approach is combined with adaptive SMC to achieve the capability of tolerating complete actuator failures with application to a modified octorotor helicopter. The significance of this proposed control scheme is that the stability of the closed-loop system is theoretically guaranteed in the presence of both single and simultaneous actuator faults

Onboard Robust Nonlinear Control for Multiple Multirotor UAVs

In this thesis, we focus on developing and validating onboard robust nonlinear control approaches for multiple multirotor unmanned aerial vehicles (UAVs), for the promise of achieving nontrivial tasks, such as path following with aggressive maneuvers, navigation in complex environments with obstacles, and formation in group. To fulfill these challenging missions, the first concern comes with the stability of flight control for the aggressive UAV maneuvers with large tilted angles. In addition, robustness of control is highly desired in order to lead the multirotor UAVs to safe and accurate performance under disturbances. Furthermore, efficiency of control algorithm is a crucial element for the onboard implementation with limited computational capability. Finally, the potential to simultaneously control a group of UAVs in a stable fashion is required. All of these concerns motivate our work in this thesis in the following aspects. We first propose the problem of robust control for the nontrivial maneuvers of a multirotor UAV under disturbances. A complete framework is developed to enable the UAV to achieve the challenging tasks, which consists of a nonlinear attitude controller based on the solution of global output regulation problems for the rigid body rotations SO(3), a backstepping-like position controller, a six-dimensional (6D) wrench observer to estimate the unknown force and torque disturbances, and an online trajectory planner based on a model predictive control (MPC) method. We prove the strong convergence properties of the proposed method both in theory and via intensive real-robot experiments of aggressive waypoint navigation and large-tilted path following tasks in the presence of external disturbances, e.g. wind gusts. Secondly, we propose the problem of autonomous navigation of a multirotor UAV in complex scenarios. We present an effective and robust control approach, namely a fast MPC method with the inclusion of nonlinear obstacle avoiding constraints, and implement it onboard the UAV at 50Hz. The developed approach enables the navigation for a multirotor UAV in 3D environments with multiple obstacles, by autonomously deciding to fly over or around the randomly located obstacles. The third problem that is addressed in our work is formation control for a group of multirotor UAVs. We solve this problem by proposing a distributed formation control algorithm for multiple UAVs based on the solution of retraction balancing problem. The algorithm brings the whole group of UAVs simultaneously to a prescribed submanifold that determines the formation shape in an asymptotically stable fashion in 2D and 3D environments. We validate our proposed algorithm via a series of hardware-in-the-loop simulations and real-robot experiments in various formation cases of arbitrary time-varying (e.g. expanding, shrinking or moving) shapes. In the actual experiments, up to 4 multirotors have been implemented to form arbitrary triangular, rectangular and circular shapes drawn by the operator via a human-robot-interaction device. We have also carried out virtual tests using up to 6 onboard computers to achieve a spherical formation and a formation moving through obstacles.In dieser Arbeit konzentrieren wir uns auf die Entwicklung und Validierung von robusten nichtlinearen On-Bord Steuerungsansatzen für mehrere unbemannte Multirotor-Luftfahrzeuge (UAVs), mit dem Ziel, nicht triviale Aufgaben zu erledigen wie z.B. Wegfolge mit aggressiven Manovern, Navigation in komplexen Umgebungen mit Hindernissen und Formationsflug in einer Gruppe. Um diese anspruchsvollen Missionen zu erfullen liegt unser Hauptaugenmerk bei der Stabilität der Flugsteuerung für aggressive UAV Manöver mit steilen Lagewinkeln. Des weiteren ist Kontroll-robustheit sehr wünschenswert, um die Multirotor-UAVs unter Beeinflussung sicher und genau zu steuern. Daruber hinaus ist die Effizienz des Kontrollalgorithmus ein wichtiges Element für die Onboard-Implementierung mit eingeschrankter Rechenfähigkeit. Abschliessend ist das Potenzial, gleichzeitig eine Gruppe von UAVs in stabiler Weise zu kontrollieren, erforderlich. All dies motiviert uns zur Arbeit an den folgenden Aspekten: Zuerst behandeln wir das Problem der robusten Steuerung nichttrivialer Manöver eines Multirotor UAV unter Störeinfluss. Ein komplettes Framework wird entwickelt, welches dem UAV ermöglicht diese anspruchsvollen Aufgaben zu bewältigen. Es beinhaltet einem nichtlinearen Lageregler, basierend auf der Lösung von globalen Ausgangsrege lungsproblemen für Starrkörperrotationen SO(3), einem backstepping basierten Positionsregler, einen sechsdimensionalen (6D) wrench observer um die unbekannten Kraftund Drehmomenteinflusse zu schätzen, sowie einem Online-Trajektorienplaner basierend auf Model Predictive Control (MPC). Wir weisen die starken Konvergenzcharakteristiken der vorgeschlagenen Methode nach, sowohl in der Theorie als auchmittels intensiver Real-roboter-Experimente, mit aggressiver Wegpunktnavigation und Wegfindungsaufgaben in extremer Fluglage in Gegenwart externer Einflüsse, z.B. Windböen. Als nächstes bearbeiten wir das Problem der autonomen Navigation eines Multirotor UAV in komplexen Szenarien. Wir stellen einen effektiven und robusten Steuerungsansatz dar, nämlich eine schnelle MPC-Methode mit der Einbeziehung von nichtlinearer Einschränkungen zur Hindernisvermeidung, und implmenetieren diese an Bord des UAV mit 50Hz. Der entwickelte Ansatz ermöglicht die Navigation eines Multirotor UAVs in 3D-Umgebungen mit mehreren Hindernissen, wobei autonom entschieden wir, über oder um die zufällig gelegenen Hindernisse zu fliegen. Das dritte Problem, das in unserer Arbeit angesprochen wird, ist die Bildungssteuerung für eine Gruppe von Multirotor UAVs. Wir lösen dieses Problem, indem wir einen verteilten Formationskontrollalgorithmus für mehrere UAVs auf der Grundlage der Lösung des Retraction Balancing Problems vorschlagen. Der Algorithmus bringt die ganze Gruppe von UAVs gleichzeitig auf eine vorgeschriebene Untermanigfaltigkeit, welche die Formation in asymtotisch stabiler Weise in 2D- und 3D-Umgebungen bestimmt. Wir validieren unseren vorgeschlagenen Algorithmus uber eine Reihe von Hardware-in-the- ¨ Loop-Simulationen und Real-Roboter-Experimente mit verschiedenen Formationsvarianten in beliebigen zeitveränderlichen (z. B. expandierenden, schrumpfenden oder bewegten) Formen. In den eigentlichen Experimenten wurden bis zu 4 Multirotoren eingesetzt, um beliebige dreieckige, rechteckige und kreisförmige Formen zu bilden, die vom Bediener über eine Mensch-Roboter-Interaktionsvorrichtung vorgezeichnet wurden. Wir haben auch virtuelle Tests mit bis zu 6 Onboard-Computern durchgeführt, um eine sphärische Formation und eine Formation zu erreichen, die sich durch Hindernisse. bewegt