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Author: Mousumi Ahmed Publisher: ISBN: Category : Aerospace engineering Languages : en Pages :
Book Description
Designing the control technique for nonlinear dynamic systems is a signi cant challenge. Approaches to designing a nonlinear controller are studied and an extensive study on backstepping based technique is performed in this research with the purpose of tracking a moving target autonomously. Our main motivation is to explore the controller for cooperative and coordinating unmanned vehicles in a target tracking application. To start with, a general theoretical framework for target tracking is studied and a controller in three dimensional environment for a single UAV is designed. This research is primarily focused on nding a generalized method which can be applied to track almost any reference trajectory. The backstepping technique is employed to derive the controller for a simpli ed UAV kinematic model. This controller can compute three autopilot modes i.e. velocity, ground heading (or course angle), and ight path angle for tracking the unmanned vehicle. Numerical implementation is performed in MATLAB with the assumption of having perfect and full state information of the target to investigate the accuracy of the proposed controller. This controller is then frozen for the multi-vehicle problem. Distributed or decentralized cooperative control is discussed in the context of multi-agent systems. A consensus based cooperative control is studied; such consensus based control problem can be viewed from the algebraic graph theory concepts. The communication structure between the UAVs is represented by the dynamic graph where UAVs are represented by the nodes and the communication links are represented by the edges. The previously designed controller is augmented to account for the group to obtain consensus based on their communication. A theoretical development of the controller for the cooperative group of UAVs is presented and the simulation results for di erent communication topologies are shown. This research also investigates the cases where the communication topology switches to a di erent topology over particular time instants. Lyapunov analysis is performed to show stability in all cases. Another important aspect of this dissertation research is to implement the controller for the case, where perfect or full state information is not available. This necessitates the design of an estimator to estimate the system state. A nonlinear estimator, Extended Kalman Filter (EKF) is rst developed for target tracking with a single UAV. The uncertainties involved with the measurement model and dynamics model are considered as zero mean Gaussian noises with some known covariances. The measurements of the full state of the target are not available and only the range, elevation, and azimuth angle are available from an onboard seeker sensor. A separate EKF is designed to estimate the UAV's own state where the state measurement is available through on-board sensors. The controller computes the three control commands based on the estimated states of target and its own states. Estimation based control laws is also implemented for colored noise measurement uncertainties, and the controller performance is shown with the simulation results. The estimation based control approach is then extended for the cooperative target tracking case. The target information is available to the network and a separate estimator is used to estimate target states. All of the UAVs in the network apply the same control law and the only di erence is that each UAV updates the commands according to their connection. The simulation is performed for both cases of xed and time varying communication topology. Monte Carlo simulation is also performed with di erent sample noises to investigate the performance of the estimator. The proposed technique is shown to be simple and robust to noisy environments.
Author: Mousumi Ahmed Publisher: ISBN: Category : Aerospace engineering Languages : en Pages :
Book Description
Designing the control technique for nonlinear dynamic systems is a signi cant challenge. Approaches to designing a nonlinear controller are studied and an extensive study on backstepping based technique is performed in this research with the purpose of tracking a moving target autonomously. Our main motivation is to explore the controller for cooperative and coordinating unmanned vehicles in a target tracking application. To start with, a general theoretical framework for target tracking is studied and a controller in three dimensional environment for a single UAV is designed. This research is primarily focused on nding a generalized method which can be applied to track almost any reference trajectory. The backstepping technique is employed to derive the controller for a simpli ed UAV kinematic model. This controller can compute three autopilot modes i.e. velocity, ground heading (or course angle), and ight path angle for tracking the unmanned vehicle. Numerical implementation is performed in MATLAB with the assumption of having perfect and full state information of the target to investigate the accuracy of the proposed controller. This controller is then frozen for the multi-vehicle problem. Distributed or decentralized cooperative control is discussed in the context of multi-agent systems. A consensus based cooperative control is studied; such consensus based control problem can be viewed from the algebraic graph theory concepts. The communication structure between the UAVs is represented by the dynamic graph where UAVs are represented by the nodes and the communication links are represented by the edges. The previously designed controller is augmented to account for the group to obtain consensus based on their communication. A theoretical development of the controller for the cooperative group of UAVs is presented and the simulation results for di erent communication topologies are shown. This research also investigates the cases where the communication topology switches to a di erent topology over particular time instants. Lyapunov analysis is performed to show stability in all cases. Another important aspect of this dissertation research is to implement the controller for the case, where perfect or full state information is not available. This necessitates the design of an estimator to estimate the system state. A nonlinear estimator, Extended Kalman Filter (EKF) is rst developed for target tracking with a single UAV. The uncertainties involved with the measurement model and dynamics model are considered as zero mean Gaussian noises with some known covariances. The measurements of the full state of the target are not available and only the range, elevation, and azimuth angle are available from an onboard seeker sensor. A separate EKF is designed to estimate the UAV's own state where the state measurement is available through on-board sensors. The controller computes the three control commands based on the estimated states of target and its own states. Estimation based control laws is also implemented for colored noise measurement uncertainties, and the controller performance is shown with the simulation results. The estimation based control approach is then extended for the cooperative target tracking case. The target information is available to the network and a separate estimator is used to estimate target states. All of the UAVs in the network apply the same control law and the only di erence is that each UAV updates the commands according to their connection. The simulation is performed for both cases of xed and time varying communication topology. Monte Carlo simulation is also performed with di erent sample noises to investigate the performance of the estimator. The proposed technique is shown to be simple and robust to noisy environments.
Author: Yue Wang Publisher: John Wiley & Sons ISBN: 1119266122 Category : Technology & Engineering Languages : en Pages : 314
Book Description
A comprehensive review of the state of the art in the control of multi-agent systems theory and applications The superiority of multi-agent systems over single agents for the control of unmanned air, water and ground vehicles has been clearly demonstrated in a wide range of application areas. Their large-scale spatial distribution, robustness, high scalability and low cost enable multi-agent systems to achieve tasks that could not successfully be performed by even the most sophisticated single agent systems. Cooperative Control of Multi-Agent Systems: Theory and Applications provides a wide-ranging review of the latest developments in the cooperative control of multi-agent systems theory and applications. The applications described are mainly in the areas of unmanned aerial vehicles (UAVs) and unmanned ground vehicles (UGVs). Throughout, the authors link basic theory to multi-agent cooperative control practice — illustrated within the context of highly-realistic scenarios of high-level missions — without losing site of the mathematical background needed to provide performance guarantees under general working conditions. Many of the problems and solutions considered involve combinations of both types of vehicles. Topics explored include target assignment, target tracking, consensus, stochastic game theory-based framework, event-triggered control, topology design and identification, coordination under uncertainty and coverage control. Establishes a bridge between fundamental cooperative control theory and specific problems of interest in a wide range of applications areas Includes example applications from the fields of space exploration, radiation shielding, site clearance, tracking/classification, surveillance, search-and-rescue and more Features detailed presentations of specific algorithms and application frameworks with relevant commercial and military applications Provides a comprehensive look at the latest developments in this rapidly evolving field, while offering informed speculation on future directions for collective control systems The use of multi-agent system technologies in both everyday commercial use and national defense is certain to increase tremendously in the years ahead, making this book a valuable resource for researchers, engineers, and applied mathematicians working in systems and controls, as well as advanced undergraduates and graduate students interested in those areas.
Author: Tal Shima Publisher: SIAM ISBN: 0898718589 Category : Mathematics Languages : en Pages : 180
Book Description
Unmanned aerial vehicles (UAVs) are increasingly used in military missions because they have the advantages of not placing human life at risk and of lowering operation costs via decreased vehicle weight. These benefits can be fully realized only if UAVs work cooperatively in groups with an efficient exchange of information. This book provides an authoritative reference on cooperative decision and control of UAVs and the means available to solve problems involving them.
Author: Rajdeep Dutta Publisher: ISBN: 9781369061123 Category : Drone aircraft Languages : en Pages : 124
Book Description
In this dissertation, we present novel solutions to cooperative control of autonomous multi-agent network topologies pertaining to the area of hostile target tracking by multiple unmanned aerial vehicles (UAVs). The present work assumes an undirected graph comprising point-mass UAVs with time-varying communication topology among agents. The level of information sharing ability among agents in a multi-agent network, i.e. the network connectivity, plays pivotal role in group dynamics. A neighborhood information based decentralized controller is proposed in order to drive UAVs into a symmetric formation of polygon shape surrounding a mobile target, simultaneously with maintaining and controlling connectivity during the formation process. Appropriate controller parameter selection schemes, both for controller weights and gains, are adapted for dynamic topologies to maintain the connectivity measure above zero at all times. A challenging task of tracking a desired connectivity profile along with the formation control, is accomplished by using time-varying controller gains throughout agents dynamics. We next present a generalized formation controller, which in fact generates a family of UAV trajectories satisfying the control criteria. The proposed decentralized controller contains additional tuning parameters as fractional powers on proportional and derivative terms, rendering flexibility in achieving the control objective. The proposed controller with proper fractional powers, results in gradual state changes in UAV dynamics by using limited control inputs. Moreover, we extend our work by addressing a ground target tracking and reacquiring problem using the visual information gathered by flying UAV. The proposed guidance law uses line-of-sight guidance to track the target pushing it towards the image center captured by UAV, and exploits UAV-target mutual information to reacquire the target in case it steers away from the field-of-view for a short time. The convergence of the closed loop systems under the proposed controllers are shown using Lyapunov theory. Simulation results validate the effectiveness and novelty of the proposed control laws. In addition to the above, this work focuses on categorizing multi-agent topologies in concern with the network dynamics and connectivity to analyze, realize, and visualize multi-agent interactions. In order to explore various useful agents reconfiguration possibilities without compromising the network connectivity, the present work aims at determining distinct topologies with the same connectivity or isoconnected topologies. Different topologies with identical connectivity are found out with the help of analytic techniques utilizing matrix algebra and calculus of variation. Elegant strategies for preserving connectivity in a network with a single mobile agent and rest of the stationary members, are proposed in this work as well. The proposed solutions are validated with the help of sufficient examples. For visual understanding of how agents locations and topology configurations influence the network connectivity, a MATLAB based graphical user interface is designed to interact with multi-agent graphs in a user-friendly manner. To this end, the present work succeeds to determine solutions to challenging multi-UAV cooperative control problems, such as: (1) Symmetric formation control surrounding a mobile target; (2) Maintaining, improving and controlling the network connectivity during a mission; and (3) Categorizing different multi-agent topologies to unravel useful reconfiguration options for a group. The proposed theories with appropriate analysis, and the simulation results suffice to show the contribution and novelty of this work.
Author: Khaled Ali Shaaban Ghamry Publisher: ISBN: Category : Languages : en Pages : 202
Book Description
Since several decades ago, unmanned aerial vehicles (UAVs) have attracted a great deal of attention in academic, industrial and military communities. Recently, multiple cooperative UAVs have been applied in various applications such as forest fire detection and fighting, search and exploration, environmental monitoring and surveillance.The main objectives of this dissertation are to design novel algorithms for single quadrotor UAV trajectory tracking control and multiple UAVs for cooperative/formation control. Then, applying these algorithms in forest monitoring and fire detection application, where a group of detection UAVs is required to surround and track the fire perimeter for monitoring and observation mission. Furthermore, a new algorithm for fault-tolerant cooperative control (FTCC) is proposed, in order to mitigate potential UAV fault effect for reliable and safe mission completion. Finally, a fire fighting algorithm is developed for achieving minimum distances for forest fire UAVs to arrive at their assigned fire spots destinations. A combination of sliding mode control (SMC) and linear quadratic regulator (LQR) is used to design a single quadrotor UAV controller, which is then used to design a formation controller of multiple UAVs. Moreover, another formation controller is designed based on SMC to achieve robust formation control against modeling uncertainties and disturbances.Cooperative UAVs are applied in forest monitoring and fire detection application through three stages: search, confirmation and observation. UAVs are assigned to search for potential forest fires in a certain area, once a fire is detected and a fire alarm will be generated by one or more of the UAVs. The UAVs team then reconfigures its formation by following an elliptic fire perimeter, calculated by the ground station (GS) using a fire spread model. Afterward, the fire alarm confirmation stage begins and all UAVs start evenly distributed for surrounding the fire spot according to the UAVs number in the team. When the fire alarm is confirmed, the observation stage starts and UAVs continue tracking the fire along the fire perimeter. SMC is used to design a formation reconfigurable controller to switch between a predefined formation shape during the search stage, to a dynamic surrounding formation. This controller guarantees even distribution of UAVs surrounding the fire spots and the robustness against disturbances. In addition, task assignment is used with multiple fire spots and multiple UAVs teams in order to reduce the mission execution time. Moreover, the proposed control algorithms are implemented to a team of UAVs paired with a team of unmanned ground vehicles (UGVs), by using these UGVs as a take-off and landing platform in forest monitoring and fire detection application.Meanwhile, UAVs may need to leave formation for refueling/recharging during the mission of search, confirmation and observation, or if a fault occurred during the mission due to fire flames, heat or UAV's internal fault sources. Therefore, an FTCC algorithm is designed based on the graph theory to mitigate the fault effect on mission completion, and ensure complete surrounding and data gathering of the fire spots using different fire sensors such as infrared cameras, charge-coupled devices (CCD) cameras and thermal cameras etc.Afterward, data gathered during observation stage are processed in the GS, then dangerous fire spots coordinates are sent to the fire fighting UAVs. The leader UAV, the GS or both can perform the task assignment process using an auction-based or Hungarian algorithms to assign each UAV to a fire spot for deploying fire suppressant. Furthermore, a hybrid approach of control parametrization and time discretization (CPTD) and particle swarm optimization (PSO) is proposed to achieve minimum flight distance for each UAV to arrive at its destination, minimizing fuel/battery consumption. Since PSO cannot solve the continuous control inputs, CPTD is used to provide an approximate piecewise linearization of the control inputs. Thus, PSO can be adopted to achieve the global optimum solution.Finally, the proposed algorithms are being implemented on single and multiple quadrotor UAVs in simulations. While, the leader-follower approach is used in cooperative control in a decentralized manner to avoid the disadvantages of centralization. Thereafter, the proposed algorithms are verified on a set of Qball-X4 quadrotor UAVs and QGV unmanned ground vehicles (UGVs) platforms in real-time experiments through different scenarios.
Author: Ugur Zengin Publisher: ISBN: 9781109964431 Category : Languages : en Pages : 215
Book Description
The research presented in this dissertation is aimed at developing rule-based autonomous and cooperative guidance strategies for UAVs to perform missions such as path planning, target tracking and rendezvous while reducing their risk/threat exposure level, and avoiding threats and/or obstacles by utilizing measurement information provided by sensors.
Author: Hyo-Sung Ahn Publisher: Springer ISBN: 3030151875 Category : Technology & Engineering Languages : en Pages : 360
Book Description
This monograph introduces recent developments in formation control of distributed-agent systems. Eschewing the traditional concern with the dynamic characteristics of individual agents, the book proposes a treatment that studies the formation control problem in terms of interactions among agents including factors such as sensing topology, communication and actuation topologies, and computations. Keeping pace with recent technological advancements in control, communications, sensing and computation that have begun to bring the applications of distributed-systems theory out of the industrial sphere and into that of day-to-day life, this monograph provides distributed control algorithms for a group of agents that may behave together. Unlike traditional control laws that usually require measurements with respect to a global coordinate frame and communications between a centralized operation center and agents, this book provides control laws that require only relative measurements and communications between agents without interaction with a centralized operator. Since the control algorithms presented in this book do not require any global sensing and any information exchanges with a centralized operation center, they can be realized in a fully distributed way, which significantly reduces the operation and implementation costs of a group of agents. Formation Control will give both students and researchers interested in pursuing this field a good grounding on which to base their work.
Author: Everett A. Bryan Publisher: ISBN: Category : Electronic dissertations Languages : en Pages : 51
Book Description
Target tracking is an important part of video surveillance from a UAV. Tracking a target in an urban environment can be difficult because of the number of occlusions present in the environment. If multiple UAVs are used to track a target and the target behavior is learned autonomously by the UAV then the task may become easier. This thesis explores the hypothesis that an existing cooperative control algorithm can be enhanced by a language modeling algorithm to improve over time the target tracking performance of one or more ground targets in a dense urban environment. Observations of target behavior are reported to the Sequence Memoizer which uses the observations to create a belief model of future target positions. This belief model is combined with a kinematic belief model and then used in a cooperative auction algorithm for UAV path planning. The results for tracking a single target using the combined belief model outperform other belief models and improve over the duration of the mission. Results from tracking multiple targets indicate that algorithmic enhancements may be needed to find equivalent success. Future target tracking algorithms should involve machine learning to enhance tracking performance.
Author: Mousumi Ahmed
Author: Mousumi Ahmed
Author: Yue Wang
Author: Mingfeng Zhang
Author: Tal Shima
Author: Rajdeep Dutta
Author: Khaled Ali Shaaban Ghamry
Author: Ugur Zengin
Author: Hyo-Sung Ahn
Author: Everett A. Bryan
Author: Dustin Michael Geletko