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Small Unmanned Aircraft : Theory and Practice

By: Randal W. Beard (Author) , Timothy W. McLain (Author)

Extended Catalogue

Ksh 25,400.00

Format: Hardback or Cased Book

ISBN-10: 0691149216

ISBN-13: 9780691149219

Edition Number: 2

Publisher: Princeton University Press

Imprint: Princeton University Press

Country of Manufacture: US

Country of Publication: GB

Publication Date: Feb 26th, 2012

Publication Status: Active

Product extent: 320 Pages

Weight: 772.00 grams

Dimensions (height x width x thickness): 18.20 x 25.50 x 2.30 cms

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Provides key concepts and technologies underlying the dynamics, control, and guidance of fixed-wing unmanned aircraft, and enables students with an introductory-level background in controls or robotics to enter this important area. This title explores the essential underlying physics and sensors of unmanned air vehicles problems.

Autonomous unmanned air vehicles (UAVs) are critical to current and future military, civil, and commercial operations. Despite their importance, no previous textbook has accessibly introduced UAVs to students in the engineering, computer, and science disciplines--until now. Small Unmanned Aircraft provides a concise but comprehensive description of the key concepts and technologies underlying the dynamics, control, and guidance of fixed-wing unmanned aircraft, and enables all students with an introductory-level background in controls or robotics to enter this exciting and important area.


The authors explore the essential underlying physics and sensors of UAV problems, including low-level autopilot for stability and higher-level autopilot functions of path planning. The textbook leads the student from rigid-body dynamics through aerodynamics, stability augmentation, and state estimation using onboard sensors, to maneuvering through obstacles. To facilitate understanding, the authors have replaced traditional homework assignments with a simulation project using the MATLAB/Simulink environment. Students begin by modeling rigid-body dynamics, then add aerodynamics and sensor models. They develop low-level autopilot code, extended Kalman filters for state estimation, path-following routines, and high-level path-planning algorithms. The final chapter of the book focuses on UAV guidance using machine vision.


Designed for advanced undergraduate or graduate students in engineering or the sciences, this book offers a bridge to the aerodynamics and control of UAV flight.


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