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Author: Daniel Genova Publisher: ISBN: 9781658414210 Category : Languages : en Pages :
Book Description
Trajectory tracking with Model Predictive Control (MPC) is a well-researched area in unmanned aerial vehicle (UAV) controls. Most research has gone into developing a robust Unmanned Aerial System (UAS) for a UAV to follow an a priori reference trajectory. This research proposes developing a UAS that extends the use of MPC UAV trajectory tracking to follow a ground target with unknown dynamics. In this scenario, a future reference trajectory is unknown and therefore an imprecise trajectory reference is generated online. This research discusses using polynomial linear regression (PLR) using only a posteriori information of the target to provide a reference trajectory to a non-linear MPC (NMPC) position controller. This work shows that using an NMPC position controller in this fashion still out performs a Proportional Integral Derivative (PID) controller for tracking unknown trajectories. The proposed UAS was able to track a ground robot driven with aggressive, evasive maneuvers with an RMSE error of about 5 cm.
Author: Daniel Genova Publisher: ISBN: 9781658414210 Category : Languages : en Pages :
Book Description
Trajectory tracking with Model Predictive Control (MPC) is a well-researched area in unmanned aerial vehicle (UAV) controls. Most research has gone into developing a robust Unmanned Aerial System (UAS) for a UAV to follow an a priori reference trajectory. This research proposes developing a UAS that extends the use of MPC UAV trajectory tracking to follow a ground target with unknown dynamics. In this scenario, a future reference trajectory is unknown and therefore an imprecise trajectory reference is generated online. This research discusses using polynomial linear regression (PLR) using only a posteriori information of the target to provide a reference trajectory to a non-linear MPC (NMPC) position controller. This work shows that using an NMPC position controller in this fashion still out performs a Proportional Integral Derivative (PID) controller for tracking unknown trajectories. The proposed UAS was able to track a ground robot driven with aggressive, evasive maneuvers with an RMSE error of about 5 cm.
Author: Ruoyu Tan Publisher: ISBN: Category : Languages : en Pages : 95
Book Description
An Unmanned Air Vehicle (UAV) is an aircraft without a human pilot on board. It can be controlled either autonomously by computers onboard, or using a remote control by a pilot on the ground, or in another vehicle. In both military and civilian sectors, UAVs are quickly obtaining popularity and expected to expand dramatically in the years to come. As UAVs gain more attention, one of the immediate requirements would be to have UAVs work as much autonomously as possible. One of the common tasks that UAVs would be engaged in is target tracking which has various potential applications in military field, law-enforcement, wildlife protection effort, and so on. This thesis focuses on development of a controller for UAVs to track ground target. In particular, this thesis focuses on quadrotor UAV, which is a multicopter that is lifted and propelled using four motors. Admittedly, several target tracking control methods have been developed in recent years. However, only a few of them have been applied on a quadrotor. Most of these tracking methods, particularly those based on Proportional Derivative (PD) control laws, which have been applied on quadrotors, are not time efficient due to practical acceleration constraint and a number of parameters that need to be tuned. The UAV control problem can be divided into 4 sub-problems: Position Control, Motor Control, Trajectory Tracking and Trajectory Generation. In this thesis, the dynamic equations of motion for quadrotors and a Proportional Derivative control law is derived to solve the problems of Position Control, Motor Control and Trajectory Tracking. A Proportional Navigation (PN) based switching strategy is proposed to address the problem of Trajectory Generation. The experiments and numerical simulations are performed using non-maneuvering and maneuvering targets. The simulation results show that the proposed PN based switching strategy not only carries out effective tracking but also results into smaller oscillations and errors when compared to the widely used PD tracking method. The switching strategy, as proposed as a solution to target tracking problem, leaves an important question with regard to when should the switching happen. It is intuitive that the time of switching will play a role in how fast the UAV converges to the target. The second problem considered in this thesis relates to the optimal time of switching that would minimize the positional error between the UAV and the target. An optimal switching strategy is proposed to obtain the optimal switching time for both non-maneuvering and maneuvering targets. Analytical solutions that generate trajectories based on PN and PD methods are used in this strategy. The numerical simulations validate the optimality, reliability, and accuracy of the proposed method for both non-maneuvering and maneuvering targets.
Author: Hernán Abaunza Gonzalez Publisher: ISBN: Category : Languages : en Pages : 0
Book Description
The objective of this thesis work is to design control and navigation algorithms for tracking of dynamic ground targets using aerial vehicles. Quaternions, which provide an alternative to the classical representations of aerial vehicle dynamics, have been chosen as a basement to develop robust controllers and agile navigation algorithm, due to their advantages such as the absence of singularities and discontinuities and their mathematical simplicity when handling rotations. The quaternion-based control approaches explored in this thesis range from state feedback, passivity, and energy-based controllers, up to sliding modes, and three-dimensional saturation approaches. Then, autonomous and semi-autonomous navigation strategies for quadrotors were explored. An algorithm has been developed for controlling a quadrotor using gestures from a user wearing an armband. To facilitate the operation of multirotors in adverse scenarios, an aggressive deployment strategy has been proposed where a quadrotor is launched by hand With its motors turned off. Finally, autonomous navigation techniques for tracking dynamic targets have been designed. A trajectory generation algorithm based on differential equations has been introduced to track a land vehicle while describing circles. Finally a distributed path planning algorithm has been developed for a fleet of drones to autonomously track ground targets by solving an online optimization problem.
Author: Yasmina Bestaoui Sebbane Publisher: CRC Press ISBN: 1000049981 Category : Computers Languages : en Pages : 344
Book Description
Multi-robot systems are a major research topic in robotics. Designing, testing, and deploying aerial robots in the real world is a possibility due to recent technological advances. This book explores different aspects of cooperation in multiagent systems. It covers the team approach as well as deterministic decision-making. It also presents distributed receding horizon control, as well as conflict resolution, artificial potentials, and symbolic planning. The book also covers association with limited communications, as well as genetic algorithms and game theory reasoning. Multiagent decision-making and algorithms for optimal planning are also covered along with case studies. Key features: Provides a comprehensive introduction to multi-robot systems planning and task allocation Explores multi-robot aerial planning; flight planning; orienteering and coverage; and deployment, patrolling, and foraging Includes real-world case studies Treats different aspects of cooperation in multiagent systems Both scientists and practitioners in the field of robotics will find this text valuable.
Author: Tristan Charles Flanzer Publisher: ISBN: Category : Languages : en Pages :
Book Description
A robust trajectory optimization method is formulated using a stochastic collocation based approach and is then applied to the design of periodic dynamic soaring trajectories for unmanned aerial vehicles (UAVs). Repetitive control is proposed and evaluated as a means for reducing tracking error for UAVs flying periodic trajectories both in simulation and experimentally. Experiments conducted in an indoor flying laboratory outfitted with a VICON motion capture system demonstrate significant reductions in tracking error even in the presence of large and unknown disturbances.
Author: Yasmina Bestaoui Sebbane Publisher: CRC Press ISBN: 148229916X Category : Computers Languages : en Pages : 434
Book Description
With the extraordinary growth of Unmanned Aerial Vehicles (UAV) in research, military, and commercial contexts, there has been a need for a reference that provides a comprehensive look at the latest research in the area. Filling this void, Smart Autonomous Aircraft: Flight Control and Planning for UAV introduces the advanced methods of flight contr
Author: Frederica Darema Publisher: Springer Nature ISBN: 3031279867 Category : Computers Languages : en Pages : 937
Book Description
This Second Volume in the series Handbook of Dynamic Data Driven Applications Systems (DDDAS) expands the scope of the methods and the application areas presented in the first Volume and aims to provide additional and extended content of the increasing set of science and engineering advances for new capabilities enabled through DDDAS. The methods and examples of breakthroughs presented in the book series capture the DDDAS paradigm and its scientific and technological impact and benefits. The DDDAS paradigm and the ensuing DDDAS-based frameworks for systems’ analysis and design have been shown to engender new and advanced capabilities for understanding, analysis, and management of engineered, natural, and societal systems (“applications systems”), and for the commensurate wide set of scientific and engineering fields and applications, as well as foundational areas. The DDDAS book series aims to be a reference source of many of the important research and development efforts conducted under the rubric of DDDAS, and to also inspire the broader communities of researchers and developers about the potential in their respective areas of interest, of the application and the exploitation of the DDDAS paradigm and the ensuing frameworks, through the examples and case studies presented, either within their own field or other fields of study. As in the first volume, the chapters in this book reflect research work conducted over the years starting in the 1990’s to the present. Here, the theory and application content are considered for: Foundational Methods Materials Systems Structural Systems Energy Systems Environmental Systems: Domain Assessment & Adverse Conditions/Wildfires Surveillance Systems Space Awareness Systems Healthcare Systems Decision Support Systems Cyber Security Systems Design of Computer Systems The readers of this book series will benefit from DDDAS theory advances such as object estimation, information fusion, and sensor management. The increased interest in Artificial Intelligence (AI), Machine Learning and Neural Networks (NN) provides opportunities for DDDAS-based methods to show the key role DDDAS plays in enabling AI capabilities; address challenges that ML-alone does not, and also show how ML in combination with DDDAS-based methods can deliver the advanced capabilities sought; likewise, infusion of DDDAS-like approaches in NN-methods strengthens such methods. Moreover, the “DDDAS-based Digital Twin” or “Dynamic Digital Twin”, goes beyond the traditional DT notion where the model and the physical system are viewed side-by-side in a static way, to a paradigm where the model dynamically interacts with the physical system through its instrumentation, (per the DDDAS feed-back control loop between model and instrumentation).
Author: Sameera S. Ponda Publisher: ISBN: Category : Languages : en Pages : 197
Book Description
(cont.) The UAV trajectory optimization is performed for stationary targets, dynamic targets and multiple targets, for many different scenarios of vehicle motion constraints. The resulting trajectories show spiral paths taken by the UAV, which focus on increasing the angular separation between measurements and reducing the relative range to the target, thus maximizing the information provided by each measurement and improving the performance of the estimation. The main drawback of information based trajectory design is the dependence of the Fisher Information Matrix on the true target location. This issue is addressed in this project by executing simultaneous target location estimation and UAV trajectory optimization. Two estimation algorithms, the Extended Kalman Filter and the Particle Filter are considered, and the trajectory optimization is performed using the mean value of the target estimation in lieu of the true target location. The estimation and optimization algorithms run in sequence and are updated in real-time. The results show spiral UAV trajectories that increase filter convergence and overall estimation accuracy, illustrating the importance of information-based trajectory design for target localization using small UAVs.
Author: Michael Basin Publisher: Springer Science & Business Media ISBN: 3540708022 Category : Technology & Engineering Languages : en Pages : 228
Book Description
0. 1 Introduction Although the general optimal solution of the ?ltering problem for nonlinear state and observation equations confused with white Gaussian noises is given by the Kushner equation for the conditional density of an unobserved state with respect to obser- tions (see [48] or [41], Theorem 6. 5, formula (6. 79) or [70], Subsection 5. 10. 5, formula (5. 10. 23)), there are a very few known examples of nonlinear systems where the Ku- ner equation can be reduced to a ?nite-dimensional closed system of ?ltering eq- tions for a certain number of lower conditional moments. The most famous result, the Kalman-Bucy ?lter [42], is related to the case of linear state and observation equations, where only two moments, the estimate itself and its variance, form a closed system of ?ltering equations. However, the optimal nonlinear ?nite-dimensional ?lter can be - tained in some other cases, if, for example, the state vector can take only a ?nite number of admissible states [91] or if the observation equation is linear and the drift term in the 2 2 state equation satis?es the Riccati equation df /dx + f = x (see [15]). The complete classi?cation of the “general situation” cases (this means that there are no special - sumptions on the structure of state and observation equations and the initial conditions), where the optimal nonlinear ?nite-dimensional ?lter exists, is given in [95].
Author: Daniel Genova
Author: Daniel Genova
Author: Ruoyu Tan
Author: Felipe Gonzalez Toro
Author: Hernán Abaunza Gonzalez
Author: Yasmina Bestaoui Sebbane
Author: Tristan Charles Flanzer
Author: Yasmina Bestaoui Sebbane
Author: Frederica Darema
Author: Sameera S. Ponda
Author: Michael Basin