1st Edition

Intelligent Control Systems with an Introduction to System of Systems Engineering

    442 Pages 318 B/W Illustrations
    by CRC Press

    From aeronautics and manufacturing to healthcare and disaster management, systems engineering (SE) now focuses on designing applications that ensure performance optimization, robustness, and reliability while combining an emerging group of heterogeneous systems to realize a common goal.
    Use SoS to Revolutionize Management of Large Organizations, Factories, and Systems
    Intelligent Control Systems with an Introduction to System of Systems Engineering integrates the fundamentals of artificial intelligence and systems control in a framework applicable to both simple dynamic systems and large-scale system of systems (SoS). For decades, NASA has used SoS methods, and major manufacturers—including Boeing, Lockheed-Martin, Northrop-Grumman, Raytheon, BAE Systems—now make large-scale systems integration and SoS a key part of their business strategies, dedicating entire business units to this remarkably efficient approach.
    Simulate Novel Robotic Systems and Applications
    Transcending theory, this book offers a complete and practical review of SoS and some of its fascinating applications, including:

    • Manipulation of robots through neural-based network control
    • Use of robotic swarms, based on ant colonies, to detect mines
    • Other novel systems in which intelligent robots, trained animals, and humans cooperate to achieve humanitarian objectives

    Training engineers to integrate traditional systems control theory with soft computing techniques further nourishes emerging SoS technology. With this in mind, the authors address the fundamental precepts at the core of SoS, which uses human heuristics to model complex systems, providing a scientific rationale for integrating independent, complex systems into a single coordinated, stabilized, and optimized one. They provide readers with MATLAB® code, which can be downloaded from the publisher's website to simulate presented results and projects that offer practical, hands-on experience using concepts discussed throughout the book.



    Elements of a Classical Control System

    How the Model of a Dynamic System Can Help to Control It

    Control of Robot Manipulators



    System of Systems Simulation

    SoS in a Nutshell

    An SoS Simulation Framework

    SoS Simulation Framework Examples

    Agent-in-the-Loop Simulation of an SoS




    Observer Design and Kalman Filtering

    State Space Methods for Model-Based Control

    Observing and Filtering Based on Dynamic Models

    Derivation of the Discrete Kalman Filter

    Worked Out Project on the Inverted Pendulum

    Particle Filters


    Fuzzy Systems—Sets, Logic, and Control

    Classical Sets

    Classical Set Operations

    Properties of Classical Set

    Fuzzy Sets

    Fuzzy Set Operations

    Properties of Fuzzy Sets

    Classical Relations versus Fuzzy Relations

    Predicate Logic

    Fuzzy Logic

    Approximate Reasoning

    Fuzzy Control



    Neural Network-Based Control

    NN-Based Identification of Dynamics of a Robot Manipulator

    Structure of NNs

    Generating Training Data for an NN

    Dynamic Neurons

    Attractors, Strange Attractors, and Chaotic Neurons

    Cerebellar Networks and Exposition of Neural Organization to Adaptively Enact Behavior


    Introduction to System of Systems

    Definitions of SoS

    Challenging Problems in SoS



    Control of System of Systems

    Hierarchical Control of SoS

    Decentralized Control of SoS

    Other Control Approaches



    Reward-Based Behavior Adaptation

    Markov Decision Process

    Temporal Difference-Based Learning

    Extension to Q Learning

    Exploration versus Exploitation

    Vector Q Learning


    An Automated System to Induce and Innovate Advanced Skills in a Group of Networked Machine Operators

    Visual Inspection and Acquisition of Novel Motor Skills

    Experimental Setup

    Dynamics of Successive Improvement of Individual Skills

    Proposed Model of Internal Model Construction and Learning

    Discussion and Conclusion


    A System of Intelligent Robots-TrainedAnimals-Humans in a Humanitarian Demining Application

    A Novel Legged Field Robot for Landmine Detection

    Combining a Trained Animal with the Robot

    Simulations on Multirobot Approaches to Landmine Detection


    Robotic Swarms for Mine Detection System of Systems Approach

    SoS Approach to Robotic Swarms

    Designing System of Swarm Robots: GroundScouts

    Mine Detection with Ant Colony-Based Swarm Intelligence






    Thrishantha Nanayakkara was a postdoctoral research fellow at the Department of Biomedical Engineering, School of Medicine, Johns Hopkins University, Baltimore, Maryland. From 2003 to 2007, he was a faculty member at the University of Moratuwa, Sri Lanka, and was the principal investigator of the "Laboratory for Intelligent Field Robots" at the Department of Mechanical Engineering. Dr. Nanayakkara was also the founding general chair of the International Conference on Information and Automation, and is an associate editor of the Journal of Control and Intelligent Systems. At present, he is a fellow in the Radcliffe Institute, Harvard University, and a research affiliate of the Computer Science and Artificial Intelligence Laboratory of the Massachusetts Institute of Technology.

    Ferat Sahin currently serves as the deputy editor-in-chief for International Journal of Computers and Electrical Engineering and an associate editor for IEEE Systems Journal and AutoSoft Journal, as also serves as the technical cochair of the IEEE SMC International Conference on System of Systems Engineering (SOSE 2008 and SOSE 2009). He is also the director of the Multi Agent Bio-Robotics Laboratory at Rochester Institute of Technology (RIT), where he is also currently an associate professor.

    Mo M. Jamshidi has served in various capacities with the U.S. Air Force Research Laboratory, the U.S. Department of Energy, NASA Headquarters, NASA JPL, Oak Ridge National Laboratory, and the Los Alamos National Laboratory. He has also served in various academic and industrial positions at various national and international organizations including IBM and GM Corporation. In 1999, he was a NATO Distinguished Professor in Portugal, and in 2008, he was a UK Royal Academy of Engineering fellow in the UK. Dr. Jamshidi is currently the Lutcher Brown endowed chair professor at the University of Texas, San Antonio.