Written by an expert with more than 30 years of experience, Guidance of Unmanned Aerial Vehicles contains new analytical results, taken from the author’s research, which can be used for analysis and design of unmanned aerial vehicles guidance and control systems. This book progresses from a clear elucidation of guidance laws and unmanned aerial vehicle dynamics to the modeling of their guidance and control systems.
Special attention is paid to guidance of autonomous UAVs, which differs from traditional missile guidance. The author explains UAV applications, contrasting them to a missile’s limited ability (or inability) to control axial acceleration. The discussion of guidance laws for UAVs presents a generalization of missile guidance laws developed by the author. The computational algorithms behind these laws are tested in three applications—for the surveillance problem, the refueling problem, and for the motion control of a swarm of UAVs. The procedure of choosing and testing the guidance laws is also considered in an example of future generation of airborne interceptors launched from UAVs.
The author provides an innovative presentation of the theoretical aspects of unmanned aerial vehicles’ guidance that cannot be found in any other book. It presents new ideas that, once crystallized, can be implemented in the new generation of unmanned aerial systems.
Basics of Guidance
Guidance Process
Missile Guidance
Guidance of Cruise Missiles and UAVs
Representation of Motion
Line-of-Sight
Longitudinal and Lateral Motions
Control of Lateral Motion
Parallel Navigation
Proportional Navigation: Planar Engagement
Proportional Navigation: Three-Dimensional Engagement
Augmented Proportional Navigation
Proportional Navigation as a Control Problem
Augmented Proportional Navigation as a Control Problem
When Is the PN law Optimal?
Control of Longitudinal and Lateral Motions
Guidance Correction Controls
Lyapunov Approach to Control Law Design
Bellman-Lyapunov Approach: Optimal Guidance Parameters
Modified Linear Planar Model of Engagement
General Planar Case
Three-Dimensional Engagement Model
Generalized Guidance Laws
Modifies Generalized Guidance Laws
Examples
Analysis of Proportional Navigation Guided Systems in Time Domain
Inertialess PN Guidance System
Method of Adjoints
Analysis of Proportional Navigation Guided Systems in the Frequency Domain
Adjoint Method: Generalized Model
Frequency Domain Analysis
Steady-State Miss Analysis
Weave Maneuver Analysis
Example
Frequency Analysis and Miss Step Response
Bounded Input—Bounded Output Stability
Frequency Response of the Generalized Guidance Model
Design of Guidance Laws Implementing Parallel Navigation: Frequency-Domain Approach
Neoclassical Missile Guidance
Pseudoclassical Missile Guidance
Example Systems
Guidance Law Performance Analysis Under Stochastic Inputs
Brief Discussion of Stochastic Processes
Random Target Maneuvers
Analysis of Influence of Noises on Miss Distance
Effect of Random Target Maneuvers on Miss Distance
Computational Aspects
Examples
Filtering
Guidance of UAVs
Basic Guidance Laws and Vision-Based Navigation
Generalized Guidance Laws for UAVs
Guidance of a Swarm of UAVs
Obstacle Avoidance Algorithms
Testing Guidance Laws Performance
Forces Acting on Unmanned Aerial Vehicles
Reference Systems and Transformations
Unmanned Aerial Vehicles Dynamics
Autopilot and Actuator Model
Seeker Model
Filtering and Estimation
Kappa Guidance
Lambert Guidance
Simulation Models of Unmanned Aerial Vehicles
Integrated Design
Integrated Guidance and Control Model
Synthesis of Control Laws
Integration and Decomposition
Guidance Laws for Boost-Phase Interceptors Launched from UAVs
Kill Vehicles for Boost-Phase Defense
Development of the Missile Model and Selection of Guidance Law Parameters
Endgame Requirements and the Comparative Analysis of Efficiency of Guidance Laws
Advanced Guidance Laws Applied to Boost Stage
Interceptor’s Performance With Axial Control
Comparative Analysis with Lambert Guidance
Appendices
Biography
Rafael Yanushevsky was born in Kiev, Ukraine. He received a BS in mathematics and a MS (with honors) in electromechanical engineering from Kiev University and the Kiev Polytechnic Institute, respectively. He earned a Ph.D in optimization of multivariable systems in 1968 from the Institute of Control Sciences of the USSR Academy of Sciences, Moscow, Russia. After immigration to the United States in December 1987, he started teaching at the University of Maryland, first in the Department of Electrical Engineering, then in the Department of Mechanical Engineering, He also taught at the University of the District of Columbia in the Department of Mathematics. Since 1999, Dr. Yanushevsky has been involved in projects related to the aerospace industry.
This book provides very detailed analytical descriptions of guidance laws for UAVs … I think it is a good reference book for those who are involved or are interested in autonomous UAV control systems. The concrete theoretical aspects provided in this book will help reader to further explore optimal solutions towards future and autonomous UAVs.
—Dr. Shigang Yue, The Aeronautical Journal, May 2012