This paper presents a geometric adaptive control scheme for a quadrotor unmanned aerial vehicle, where the effects of unknown, unstructured disturbances are mitigated by a multilayer neural network that is adjusted online. The stability of the proposed controller is analyzed with Lyapunov stability theory on the special Euclidean group, and it is shown that the tracking errors are uniformly ultimately bounded with an ultimate bound that can be abridged arbitrarily. A mathematical model of wind disturbance on the quadrotor dynamics is presented, and it is shown that the proposed adaptive controller is capable of rejecting the effects of wind disturbances successfully. These are illustrated by numerical examples.
King Fahd University of Petroleum and Minerals（法赫德石油和矿产大学）
In this work, the autonomous control of a quadrotor-manipulator unmanned aerial vehicle is treated using an extended dynamic model. Due to persistent aerodynamic disturbances and dynamic couplings, the control of a quadrotor-manipulator unit is cumbersome. Active disturbance rejection control (ADRC) is proposed for the cancellation of the undesirable dynamics while a PD controller is developed for set-point tracking. Parameters were tuned using Gradient Descent-Sequential Quadratic Programming in Simulink design optimization
This study has developed a fault-tolerant controller that is able to recover a quadrotor from arbitrary initial orientations and angular velocities, despite the complete failure of a rotor. This cascaded control method includes a position/altitude controller, an almost-global convergence attitude controller, and a control allocation method based on quadratic programming. As a major novelty, a constraint of undesirable angular velocity is derived and fused into the control allocator, which significantly improves the recovery performance. For validation, we have conducted a set of Monte-Carlo si…
A Sliced Learning Framework for Online Disturbance Identification in Quadrotor SO(3) Attitude Control
Intelligent Systems Research Institute, National Institute of Advanced Industrial Science and Technology (AIST), Japan（国家先进工业科学与技术研究院智能系统研究所，日本）；Graduate School of Systems and Information Engineering, University of Tsukuba, Japan（茨大大学系统与信息工程研究生院，日本）
Enforcing safety on precise trajectory tracking is critical for aerial robotics subject to wind disturbances. In this paper, we present a learning-based safety-preserving cascaded quadratic programming control (SPQC) for safe trajectory tracking under wind disturbances. The SPQC controller consists of a position-level controller and an attitude-level controller. Gaussian Processes (GPs) are utilized to estimate the uncertainties caused by wind disturbances, and then a nominal Lyapunov-based cascaded quadratic program (QP) controller is designed to track the reference trajectory. To avoid unexp…
International Institute of Information Technology Hyderabad（国际信息技术学院海得拉巴分校）
With the advent of intelligent transport, quadrotors are becoming an attractive solution while lifting or dropping payloads during emergency evacuations, construction works, etc. During such operations, dynamic variations in (possibly unknown) payload cause considerable changes in the system dynamics. However, a systematic control solution to tackle such varying dynamical behaviour is still missing. In this work, two control solutions are proposed to solve two specific problems in aerial transportation of payload, as mentioned below. In the first work, we explore the tracking control problem f…
Accuracy and stability are common requirements for Quadrotor trajectory tracking systems. Designing an accurate and stable tracking controller remains challenging, particularly in unknown and dynamic environments with complex aerodynamic disturbances. We propose a Quantile-approximation-based Distributional-reinforced Uncertainty Estimator (QuaDUE) to accurately identify the effects of aerodynamic disturbances, i.e., the uncertainties between the true and estimated Control Contraction Metrics (CCMs). Taking inspiration from contraction theory and integrating the QuaDUE for uncertainties, our n…
Redundant Observer-Based Tracking Control for Object Extraction Using a Cable Connected UAV
Department of Aeronautical and Automotive Engineering, Loughborough University（航空与汽车工程系，洛桑大学）；Department of Computer Science, University College London（计算机科学系，伦敦大学学院）；Department Of Computer Science, University of Liverpool（计算机科学系，利物浦大学）
Design and Control of an Actively Morphing Quadrotor with Vertically Foldable Arms
School of Automation and Intelligent Sensing, Shanghai Jiao Tong University and State Key Laboratory of Avionics Integration and Aviation System-of-Systems Synthesis（自动化与智能感知学院，上海交通大学；航空集成与航空系统-系统综合国家重点实验室）
In this paper, we tackle the problem of flying a quadrotor using time-optimal control policies that can be replanned online when the environment changes or when encountering unknown disturbances. This problem is challenging as the time-optimal trajectories that consider the full quadrotor dynamics are computationally expensive to generate (order of minutes or even hours). We introduce a sampling-based method for efficient generation of time-optimal paths of a point-mass model. These paths are then tracked using a Model Predictive Contouring Control approach that considers the full quadrotor dy…
Pontifical Catholic University of Rio de Janeiro（里约热内卢天主教大学）
Purpose: Real-life applications using quadrotors introduce a number of disturbances and time-varying properties that pose a challenge to flight controllers. We observed that, when a quadrotor is tasked with picking up and dropping a payload, traditional PID and RL-based controllers found in literature struggle to maintain flight after the vehicle changes its dynamics due to interaction with this external object. Methods: In this work, we introduce domain randomization during the training phase of a low-level waypoint guidance controller based on Soft Actor-Critic. The resulting controller is e…
SwordRiding: A Unified Navigation Framework for Quadrotors in Unknown Complex Environments via Online Guiding Vector Fields
Pengcheng Laboratory, Shenzhen, Guangdong, China（鹏城实验室，深圳，广东，中国）；School of Automation, Beijing Institute of Technology, Beijing, China（自动化学院，北京理工大学，北京，中国）；School of Artificial Intelligence and Robotics, Hunan University（人工智能与机器人学院，湖南大学）；Department of Control Science and Engineering, Harbin Institute of Technology（控制科学与工程学院，哈尔滨工业大学）；National Key Laboratory of Autonomous Intelligent Unmanned Systems（自主智能无人系统国家重点实验室）；Department of Mechanical and Automation Engineering, the Chinese University of Hong Kong, Hong Kong, China（机械与自动化工程系，香港中文大学，香港，中国）
A Whole-Body Disturbance Rejection Control Framework for Dynamic Motions in Legged Robots
School of Artificial Intelligence and Automation, Huazhong University of Science and Technology（人工智能与自动化学院，华中科技大学）；Huazhong University of Science and Technology（华中科技大学）；State Key Laboratory of Intelligent Manufacturing Equipment and Technology, Huazhong University of Science and Technology（智能制造装备及技术国家重点实验室，华中科技大学）
Australian National University（澳大利亚国立大学）；I3S (University Côte d’Azur, CNRS, Sophia Antipolis)（I3S（蔚蓝海岸大学、法国国家科学研究中心、索菲亚·安提波利斯））
High performance trajectory tracking control of quadrotor vehicles is an important challenge in aerial robotics. Symmetry is a fundamental property of physical systems and offers the potential to provide a tool to design high-performance control algorithms. We propose a design methodology that takes any given symmetry, linearises the associated error in a single set of coordinates, and uses LQR design to obtain a high performance control; an approach we term Equivariant Regulator design. We show that quadrotor vehicles admit several different symmetries: the direct product symmetry, the extend…
A Three-Level Whole-Body Disturbance Rejection Control Framework for Dynamic Motions in Legged Robots
School of Artificial Intelligence and Automation, Huazhong University of Science and Technology（人工智能与自动化学院，华中科技大学）；State Key Laboratory of Intelligent Manufacturing Equipment and Technology, Huazhong University of Science and Technology（智能制造装备与技术国家重点实验室，华中科技大学）
The Robotics Institute, Carnegie Mellon University（卡内基梅隆大学机器人研究所）
This paper enhances the feedback linearization controller for multirotors with a learned acceleration error model and a thrust input delay mitigation model. Feedback linearization controllers are theoretically appealing but their performance suffers on real systems, where the true system does not match the known system model. We take a step in reducing these robustness issues by learning an acceleration error model, applying this model in the position controller, and further propagating it forward to the attitude controller. We show how this approach improves performance over the standard feed…
DroneDiffusion: Robust Quadrotor Dynamics Learning with Diffusion Models
Department of Computer Science, The University of Manchester（曼彻斯特大学计算机科学系）；Department of Cognitive Robotics, Delft University of Technology（代尔夫特理工大学认知机器人系）；Department of Computer Science, Aalto University（艾尔沃斯大学计算机科学系）
Ability to recover from faults and continue mission is desirable for many quadrotor applications. The quadrotor's rotor may fail while performing a mission and it is essential to develop recovery strategies so that the vehicle is not damaged. In this paper, we develop a model-free deep reinforcement learning approach for a quadrotor to recover from a single rotor failure. The approach is based on Soft-actor-critic that enables the vehicle to hover, land, and perform complex maneuvers. Simulation results are presented to validate the proposed approach using a custom simulator. The results show …
Quadrotor stabilizing controllers often require careful, model-specific tuning for safe operation. We use reinforcement learning to train policies in simulation that transfer remarkably well to multiple different physical quadrotors. Our policies are low-level, i.e., we map the rotorcrafts' state directly to the motor outputs. The trained control policies are very robust to external disturbances and can withstand harsh initial conditions such as throws. We show how different training methodologies (change of the cost function, modeling of noise, use of domain randomization) might affect flight…
Micro Aerial Vehicles (MAVs) are limited in their operation outdoors near obstacles by their ability to withstand wind gusts. Currently widespread position control methods such as Proportional Integral Derivative control do not perform well under the influence of gusts. Incremental Nonlinear Dynamic Inversion (INDI) is a sensor-based control technique that can control nonlinear systems subject to disturbances. It was developed for the attitude control of manned aircraft or MAVs. In this paper we generalize this method to the outer loop control of MAVs under severe gust loads. Significant impro…
University of Zurich（苏黎世大学）；ETH Zurich（苏黎世联邦理工学院）；LAAS-CNRS（法国国家科学研究中心图卢兹自动化与系统分析实验室）；Université de Toulouse（图卢兹大学）；CNRS（法国国家科学研究中心）
In this paper, we prove that the dynamical model of a quadrotor subject to linear rotor drag effects is differentially flat in its position and heading. We use this property to compute feed-forward control terms directly from a reference trajectory to be tracked. The obtained feed-forward terms are then used in a cascaded, nonlinear feedback control law that enables accurate agile flight with quadrotors. Compared to state-of-the-art control methods, which treat the rotor drag as an unknown disturbance, our method reduces the trajectory tracking error significantly. Finally, we present a method…
Quadrotors are one of the popular unmanned aerial vehicles (UAVs) due to their versatility and simple design. However, the tuning of gains for quadrotor flight controllers can be laborious, and accurately stable control of trajectories can be difficult to maintain under exogenous disturbances and uncertain system parameters. This paper introduces a novel robust and adaptive control synthesis methodology for a quadrotor robot's attitude and altitude stabilization. The developed method is based on the fuzzy reinforcement learning and Strictly Negative Imaginary (SNI) property. The first stage of…
Autonomous UAV Pipeline Near-proximity Inspection via Disturbance-Aware Predictive Visual Servoing
School of Automation, Key Laboratory of Measurement and Control of CSE, Ministry of Education, Southeast University（自动化学院、CSE测量与控制重点实验室、教育部、东南大学）；Department of Aeronautical and Automotive Engineering, Loughborough University（航空与汽车工程系、罗汉布大学）；Research Centre for Low Altitude Economy and the Department of Aeronautical and Aviation Engineering, The Hong Kong Polytechnic University（低空经济研究中心和航空与航空工程系、香港理工大学）
This paper is concerned with mismatched disturbance rejection control for the second-order discrete-time systems.Different from previous work, the controllability of the system is applied to design the disturbance compensation gain, which does not require any coordinate transformations. Via this new idea, it is shown that disturbance in the regulated output is immediately and directly compensated in the case that the disturbance is known. When the disturbance is unknown, an extra generalized extended state observer is applied to design the controller. Two examples are given to show the effecti…
This study focuses on the problem of optimal mismatched disturbance rejection control for uncontrollable linear discrete-time systems. In contrast to previous studies, by introducing a quadratic performance index such that the regulated state can track a reference trajectory and minimize the effects of disturbances, mismatched disturbance rejection control is transformed into a linear quadratic tracking problem. The necessary and sufficient conditions for the solvability of this problem over a finite horizon and a disturbance rejection controller are derived by solving a forward-backward diffe…
In this paper, an optimal output consensus problem is studied for discrete-time linear multiagent systems subject to external disturbances. Each agent is assigned with a local cost function which is known only to itself. Distributed protocols are to be designed to guarantee an output consensus for these high-order agents and meanwhile minimize the aggregate cost as the sum of these local costs. To overcome the difficulties brought by high-order dynamics and external disturbances, we develop an embedded design and constructively present a distributed rule to solve this problem. The proposed con…
