Lighter than Air Robots Guidance and Control of Autonomous Airships

Lighter than Air Robots Guidance and Control of Autonomous Airships / by Yasmina Bestaoui Sebbane.

An aerial robot is a system capable of sustained flight with no direct human control and able to perform a specific task. A lighter than air robot is an aerial robot that relies on the static lift to balance its own weight. It can also be defined as a lighter than air unmanned aerial vehicle or an u...

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Bibliographic Details
Main Author: Bestaoui Sebbane, Yasmina (Author)
Corporate Author: SpringerLink (Online service)
Format: eBook
Language:English
Published: Dordrecht : Springer Netherlands : Imprint: Springer, 2012.
Edition:1st ed. 2012.
Series:Intelligent Systems, Control and Automation: Science and Engineering, 58
Springer eBook Collection.
Subjects:
Robotics.
Automation.
Computers.
Aerospace engineering.
Astronautics.
Electronic resources (E-books)
Online Access:Click to view e-book
Holy Cross Note:Loaded electronically.
Electronic access restricted to members of the Holy Cross Community.
Table of Contents:
  • 1 Introduction
  •  1.1 Aerial robotics
  •  1.2 Outline of the book
  •  2 Modeling
  •  2.1 Introduction
  •  2.2 Kinematics
  •  2.2.1 Euler angles
  •  2.2.2 Euler parameters
  •  2.3 Dynamics
  •  2.3.1 Mass Characteristics
  •  2.3.2 6 DOF Dynamics : Newton-Euler Approach
  •  2.3.3 6 DOF Dynamics : Lagrange Approach
  •  2.3.4 Translational Dynamics .
  •  2.4 Aerology Characteristics
  •  2.4.1 Wind Profile
  •  2.4.2 Down burst
  •  2.5 Conclusions
  •  3 Mission Planning
  •  3.1 Introduction
  •  3.2 Flight Planning
  •  3.3 Motion Planning Algorithms Review
  •  3.3.1 Overall Problem description
  •  3.3.2 Problem Types
  •  3.4 Planning with differential constraints
  •  3.4.1 Roadmap algorithm
  •  3.4.2 Artificial Potential Methods
  •  3.4.3 Sampling based trajectory planning
  •  3.4.4 Decoupled Trajectory Planning
  •  3.4.5 The Finite State Motion Model: The Maneuver Automaton
  •  3.4.6 Mathematical Programming
  •  3.4.7 Receding Horizon Control
  •  3.4.8 Reactive Planning
  •  3.4.9 Probabilistic Roadmap Methods: PRM
  •  3.4.10 Rapidly Expanding Random Tree (RRT)
  •  3.4.11 Guided Expansive Search Trees
  •  3.5 Planning with Uncertain Winds
  •  3.5.1 Receding Horizon Approach
  •  3.5.2 Markov Decision Process Approach
  •  3.5.3 Chance constrained predictive control under stochastic uncertainty
  •  3.6 Planning in Strong Winds
  •  3.7 Task Assignment
  •  3.8 Conclusions
  •  4.1 Introduction
  •  4.2 Trajectory Generation in Hover
  •  4.2.1 Trim Trajectories
  •  4.2.2 Under-actuation at Hover
  •  4.3 Lateral planning in cruising flight
  •  4.3.1 Lateral dynamics of the lighter than air robot
  •  4.3.2 Time Optimal Extremals
  •  4.4 Zermelo Navigation Problem
  •  4.4.1 Navigation equation
  •  4.4.2 One particular solution
  •  4.5 3D Trajectory design with wind
  •  4.5.1 Determination of the Reference Controls
  •  4.5.2 Accessibility and Controllability
  •  4.5.3 Motion Planning when wind can be neglected
  •  4.5.4 Determination of the Minimum Energy Trajectories
  •  4.5.5 Determination of Time Optimal Trajectories
  •  4.6 Parametric Curves
  •  4.6.1 Cartesian polynomials
  •  4.6.2 Trim Flight Paths
  •  4.6.3 Non Trim Flight Paths
  •  4.6.4 Maneuvers between two different trims
  •  4.6.5 Frenet -Serret Approach
  •  4.6.6 Pythagorean Hodograph
  •  4.6.7 h3 Splines
  •  4.7 Conclusions
  •  5 Control
  •  5.1 Introduction
  •  5.2 Linear Control
  •  5.2.1 Linear Formulation in Cruising flight
  •  5.2.2 Flying and Handling Qualities
  •  5.2.3 Classical Linear Control
  •  5.2.4 Linear Robust Control
  •  5.3 Nonlinear Control
  •  5.3.1 Dynamic Inversion
  •  5.3.2 Trajectory Tracking in a High Constant Altitude Flight
  •  5.3.3 Variable Structure Robust Control
  •  5.3.4 Back stepping controller design
  •  5.3.5 Line tracking by path curvature and torsion
  •  5.3.6 Intelligent Control
  •  5.4 System Health Management
  •  5.4.1 Health Monitoring
  •  5.4.2 Diagnosis, Response to systems failure
  •  5.5 Conclusions
  •  6 General Conclusions
  •  7 References
  •  References
  •  A Current Projects
  •  A.1 Introduction
  •  A.2 Artic Airship
  •  A.2.1 Vehicle Description
  •  A.2.2 Weight, mass distribution and balance
  •  A.2.3 Modeling and identification
  •  A.2.4 Aerodynamics
  •  A.2.5 Localization and positioning
  •  A.2.6 Navigation and Path Planner
  •  A.2.7 Feeding the path planner with realistic wind information
  •  A.2.8 Data processing and transmission
  •  A.2.9 Airship Piloting and Response to wind disturbances
  •  A.2.10 Loading and unloading lifts
  •  A.2.11 Diagnosis, Response to systems failure
  •  A.2.12 Flight dynamics simulator
  •  A.2.13 Small scale delta-wing quad-rotor airship
  •  A.2.14 Ground handling
  •  A.3 Bridge Monitoring
  •  A.4 Monitoring of high voltage power networks
  •  A.4.1 Current market for inspection of electrical networks
  •  A.4.2 Project Goals
  •  A.5 FAA Recommendations
  •  A.6 Indoor Lighter Than Air Robot : A Differential Geometry Modeling Approach
  •  Index.

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