Stability and control of a quadrocopter despite the complete loss of one, two, or three propellers

Abstract-This paper presents periodic solutions for a quadrocopter maintaining a height around a position in space despite having lost a single, two opposing, or three propellers. In each case the control strategy consists of the quadrocopter spinning about a primary axis, fixed with respect to the vehicle, and tilting this axis for translational control. A linear, timeinvariant description of deviations from the attitude equilibrium is derived, allowing for a convenient cascaded control design. The results for the cases of losing one and two propellers are validated in experiment, while the case of losing three propellers is validated in a nonlinear simulation. These results have application in multicopter fault-tolerant control design, and also point to possible design directions for novel flying vehicles

Global Fault-Tolerant Control of Underactuated Aerial Vehicles with Redundant Actuators

In this paper, we consider the fault-tolerant control problem for aerial vehicles with redundant actuators. The redundant actuator brings difficulty in fault identification and isolation. Active fault-tolerant control is adopted in this paper as it can detect actuator fault. The entire proposed fault-tolerant control algorithm contains a baseline controller, the fault detection and isolation scheme, and the controller reconstruction module. A robust parameter identification method is designed to identify the torque and thrust generated by the actuators. The feasibility of isolating the fault for the redundant actuators is analyzed through mathematical proof. Through the analysis, the practical fault isolation algorithm is also proposed. Two typical aerial vehicles with redundant actuators, an eight-rotor aircraft and a hexa-rotor aircraft, are adopted in numerical simulations to verify the effectiveness of the proposed fault-tolerant control approach

Підвищення надійності квадрокоптера вдосконаленням його системи автоматичного керування

Мета магістерської дисертації полягає у вдосконаленні системи автоматичного керування (САК) квадрокоптера з точки зору підвищення його функціональної надійності, розробка методу ранжування внутрішніх і зовнішніх факторів, що впливають на функціональну надійність квадрокоптера, де враховано основні джерела відмов і впливів на надійність при розробці його САК, а також на їх основі розробка алгоритму функціонування САК квадрокоптера. У розробленому методі ранжування за критерій ранжування було обрано величину статистичної оцінки ймовірності безвідмовної роботи кожної складової квадрокоптера. За розробленим методом ранжування спроектований алгоритм функціонування САК квадрокоптера, який підвищує функціональну надійність САК та квадрокоптера в цілому. Алгоритм представляє собою програмне резервування з точки зору підвищення функціональної надійності САК. Алгоритм включає додаткові програмні дії: при відмові однієї з навігаційних бортових систем, виявленні проблем з бортовим комп’ютером, відключенні в польоті будь-якої з гвинтомоторних груп (використання моделі бікоптера), зникненні сигналу керування з дистанційного пульту при зальоті квадрокоптера за перешкоду, програмне резервування контуру керування, тощо.The purpose of the master's dissertation is to improve the automatic control system (ACS) of a quadcopter in terms of improving its functional reliability, to develop a method of ranking internal and external factors affecting the functional reliability of a quadcopter, which takes into account the main sources of failures and influences on reliability. and also on their basis development of algorithm of functioning of SAC of the quadcopter. In the developed ranking method, the value of statistical estimation of the probability of trouble-free operation of each component of the quadcopter was chosen as the ranking criterion. According to the developed ranking method, the algorithm of SAC quadcopter operation is designed, which increases the functional reliability of SAC and quadcopter in general. The algorithm is a software redundancy in terms of increasing the functional reliability of the SAC. The algorithm includes additional software actions: in case of failure of one of the onboard navigation systems, detection of problems with the onboard computer, disconnection in flight of any of the propeller groups (use of bicopter model), disappearance of control signal from the remote control when quadcopter control circuit redundancy, etc.Цель магистерской диссертации заключается в совершенствовании системы автоматического управления (САУ) квадрокоптера с точки зрения повышения его функциональной надежности, разработка метода ранжирования внутренних и внешних факторов, влияющих на функциональную надежность квадрокоптера, где учтены основные источники отказов и воздействий на надежность при разработке его САК, а также на их основе разработка алгоритма функционирования САК квадрокоптера. В разработанном методе ранжирования критерия ранжирования был избран величину статистической оценки вероятности безотказной работы каждой составляющей квадрокоптера. По разработанным методом ранжирования спроектирован алгоритм функционирования САК квадрокоптера, который повышает функциональную надежность САК и квадрокоптера в целом. Алгоритм представляет собой программное резервирования с точки зрения повышения функциональной надежности САУ. Алгоритм включает дополнительные программные действия при отказе одной из навигационных бортовых систем, выявлении проблем с бортовым компьютером, отключении в полете любой из винтомоторных групп (использование модели бикоптера), исчезновении сигнала управления с дистанционного пульта при залету квадрокоптера за препятствие, программное бронирования контура управления, и тому подобное

Gain-Scheduled Control of a Quadcopter UAV

In this thesis we develop a gain-scheduled control law for the quadcopter unmanned aerial vehicle (UAV). Techniques from linear control theory are introduced and used to construct adaptive proportional and proportional-integral control laws for use with both state and observer-based output feedback. The controller monitors the yaw angle of the quadcopter and updates a gain matrix as the system evolves through operating points. To demonstrate the effectiveness of the gain-scheduled controller, trajectories involving significant variation in the yaw angle are tracked by the quadcopter, including a helix and Lissajous curve. We consider physical implementation of the controller, and offer suggestions for improvement and future work

Survey of Robot 3D Path Planning Algorithms

Robot 3D (three-dimension) path planning targets for finding an optimal and collision-free path in a 3D workspace while taking into account kinematic constraints (including geometric, physical, and temporal constraints). The purpose of path planning, unlike motion planning which must be taken into consideration of dynamics, is to find a kinematically optimal path with the least time as well as model the environment completely. We discuss the fundamentals of these most successful robot 3D path planning algorithms which have been developed in recent years and concentrate on universally applicable algorithms which can be implemented in aerial robots, ground robots, and underwater robots. This paper classifies all the methods into five categories based on their exploring mechanisms and proposes a category, called multifusion based algorithms. For all these algorithms, they are analyzed from a time efficiency and implementable area perspective. Furthermore a comprehensive applicable analysis for each kind of method is presented after considering their merits and weaknesses

ON-BOARD ARTIFICIAL INTELLIGENCE FOR FAILURE DETECTION AND SAFE TRAJECTORY GENERATION

The use of autonomous flight vehicles has recently increased due to their versatility and capability of carrying out different type of missions in a wide range of flight conditions. Adequate commanded trajectory generation and modification, as well as high-performance trajectory tracking control laws have been an essential focus of researchers given that integration into the National Air Space (NAS) is becoming a primary need. However, the operational safety of these systems can be easily affected if abnormal flight conditions are present, thereby compromising the nominal bounds of design of the system\u27s flight envelop and trajectory following. This thesis focuses on investigating methodologies for modeling, prediction, and protection of autonomous vehicle trajectories under normal and abnormal flight conditions. An Artificial Immune System (AIS) framework is implemented for fault detection and identification in combination with the multi-goal Rapidly-Exploring Random Tree (RRT*) path planning algorithm to generate safe trajectories based on a reduced flight envelope. A high-fidelity model of a fixed-wing unmanned aerial vehicle is used to demonstrate the capabilities of the approach by timely generating safe trajectories as an alternative to original paths, while integrating 3D occupancy maps to simulate obstacle avoidance within an urban environment

Flatness-Based Trajectory Planning/Replanning for a Quadrotor Unmanned Aerial Vehicle

International audienceThis paper proposes a flatness-based flight trajectory planning/re-planning strategy for a quad-rotor unmanned aerial vehicle (UAV). In the nominal situation (fault-free case), the objective is to drive the system from an initial position to a final one without hitting the actuator constraints while minimizing the total time of the mission or minimizing the total energy spent. When actuator faults occur, fault-tolerant control is combined with trajectory re-planning to change the reference trajectory in function of the remaining resources in the system. The approach employs differential flatness to express the control inputs to be applied in function of the desired trajectories and formulates the trajectory planning/re-planning problem as a constrained optimization problem

New Development on Sense and Avoid Strategies for Unmanned Aerial Vehicles

Unmanned Aerial Vehicles (UAVs) can carry out more complex civilian and military applications with less cost and more flexibility in comparison of manned aircraft. Mid-air collision thus becomes profoundly important considering the safe operation of air transportation systems, when UAVs are increasingly used more with various applications and share the same airspace with manned air vehicles. To ensure safe flights, UAVs have to configure Sense and Avoid (S&A) systems performing necessary maneuvers to avoid collisions. After analyzing the manner of S&A system, avoidance strategies based on a subset of possible collision scenarios are proposed in this thesis. 1) To avoid a face-to-face intruder, a feasible trajectory is generated by differential geometric guidance, where the constraints of UAV dynamics are considered. 2) The Biogeography Based Optimization (BBO) approach is exploited to generate an optimal trajectory to avoid multiple intruders’ threats in the landing phase. 3) By formulating the collision avoidance problem within a Markov Decision Process (MDP) framework, a desired trajectory is produced to avoid multiple intruders in the 2D plane. 4) MDP optimization method is extended to address the problem of optimal 3D conflict resolution involving multiple aircraft. 5) Considering that the safety of UAVs is directly related to the dynamic constraints, the differential flatness technique is developed to smoothen the optimal trajectory. 6) Energy based controller is designed such that the UAV is capable of following the generated trajectory