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• Safety Instrumented Systems Analysis
• Risks assessment of critical industrial control systems
• Machine Learning based Predictive Maintenance of Infrastructure Facilities in the Cryolithozone
• Cybersecurity Threats, Vulnerability and Analysis in Safety Critical Industrial Control System (ICS)
• Automatic Attack Graph Generation for Industrial Controlled Systems
• Determining Resiliency Using Attack Graphs
• Modern methods for analyzing malware targeting control systems
• Multi-stage cyber-attacks detection in the Industrial Control Systems
• Using Honeypots for ICS threats evaluation
• Intrusion detection on ICS and SCADA networks
• Security evaluation of sensor networks
• Innovative hardware-based cybersecurity solutions
• Legal issues of deception systems in the Industrial Control Systems.

This book provides profound insights into industrial control system resilience, exploring fundamental and advanced topics and including practical examples and scenarios to support the theoretical approaches. It examines issues related to the safe operation of control systems, risk analysis and assessment, use of attack graphs to evaluate the resiliency of control systems, preventive maintenance, and malware detection and analysis. The book also discusses sensor networks and Internet of Things devices. Moreover, it covers timely responses to malicious attacks and hazardous situations, helping readers select the best approaches to handle such unwanted situations. The book is essential reading for engineers, researchers, and specialists addressing security and safety issues related to the implementation of modern industrial control systems. It is also a valuable resource for students interested in this area.

This video will show how to use MATLAB to determine if a discrete-time system in state space representation is controllable and/or observable

This video will show how to use MATLAB to determine if a continuous-time system in state space representation is controllable and/or observable

• Part I. Introduction.- Introductory Remarks.- Historical Perspective.- Outline of Contents.- Part II. Problem Statement.- Deterministic Systems.- Stochastic Systems.- General Problem.- Part III. The Direct Method Approach: Generalities.- General Approach.- Gradient and Integration Methods.- Representation Methods.- Part IV. Gradient and Integration Methods in Control Problems.- Computation of Gradients for ODE Problems.- Computation of Gradients for PDE Problems.- Integration Methods.- Part V. Representation Methods.- Ritz-Galerkin Expansion.- Karhunen-Loeve Expansion.- Levy Processes.- Bibliography.- Index
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Various general techniques have been developed for control and systems problems, many of which involve indirect methods. Because these indirect methods are not always effective, alternative approaches using direct methods are of particular interest and relevance given the advances of computing in recent years. The focus of this book, unique in the literature, is on direct methods, which are concerned with finding actual solutions to problems in control and systems, often algorithmic in nature. Throughout the work, deterministic and stochastic problems are examined from a unified perspective and with considerable rigor. Emphasis is placed on the theoretical basis of the methods and their potential utility in a broad range of control and systems problems. The book is an excellent reference for graduate students, researchers, applied mathematicians, and control engineers and may be used as a textbook for a graduate course or seminar on direct methods in control. .
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• Luenberger Observer Design for Uncertainty Nonlinear Systems.- Hill Equation: From 1 to 2 Degrees of Freedom.- Sliding Mode Control devoid of State Measurements.- Design of Asymptotic Second-order Sliding Mode Control System.- Fractional Order Model Reference Adaptive Controllers for First Order Integer Plants.- Sliding Modes for Switched Uncertain Linear Time Invariant Systems: An Output Integral Sliding Mode Approach.- Discontinuous Integral Control for Systems with relative degree two.- Theory of dierential inclusions and its application in mechanics.- Stability probabilities of sliding mode control of linear continuous Markovian jump systems.- Adaptive Sliding Mode Control using Monitoring Functions.- Fast Control Systems: Nonlinear Approach.- Finite-Time Sliding Mode Controller with State-Dependent GainParameter.- Setting Nash vs. Kalai-Smorodinsky Bargaining Approach: Computing the Continuous Time Controllable Markov Game.-
• H1- Stabilization of a 3D Bipedal Locomotion Under a Unilateral Constraint.- Event-Triggered Sliding Mode Control Strategies for a Class ofNonlinear Uncertain Systems.- Sliding Mode Control Design Procedure For Power Electronic Converters Used In Energy Conversion Systems.- Hybrid-Impulsive Higher Order Sliding Mode Control.-.
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This edited monograph contains research contributions on a wide range of topics such as stochastic control systems, adaptive control, sliding mode control and parameter identification methods. The book also covers applications of robust and adaptice control to chemical and biotechnological systems. This collection of papers commemorates the 70th birthday of Dr. Alexander S. Poznyak.
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• 1. Optimality conditions (in Pontryagain form) / Maria Soledad Aronna, Daniela Tonon, Andrea Boccia, Cédric Martínez Campos, Marco Mazzola, Luong Van Nguyen, Michele Palladino, Teresa Scarinci, and Francisco J. Silva
• 2. Hamilton-Jacobi-Bellman equations / Adriano Festa, Roberto Guglielmi, Christopher Hermosilla, Athena Picarelli, Smita Sahu, Achille Sassi, and Francisco J. Silva
• 3. Direct optimal control and model predictive control / Marion Zanon, Andrea Boccia, Vryan Gil S. Palma, Sonja Parenti, and Ilaria Xausa.

Focusing on applications to science and engineering, this book presents the results of the ITN-FP7 SADCO network's innovative research in optimization and control in the following interconnected topics: optimality conditions in optimal control, dynamic programming approaches to optimal feedback synthesis and reachability analysis, and computational developments in model predictive control. The novelty of the book resides in the fact that it has been developed by early career researchers, providing a good balance between clarity and scientific rigor. Each chapter features an introduction addressed to PhD students and some original contributions aimed at specialist researchers. Requiring only a graduate mathematical background, the book is self-contained. It will be of particular interest to graduate and advanced undergraduate students, industrial practitioners and to senior scientists wishing to update their knowledge.
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• Mathematical Preliminaries
• Transfer Functions
• Feedback - An Introduction
• The Routh-Hurwitz Criterion
• The Principle of the Argument and Its Consequences
• The Root Locus Diagram
• Compensation
• Some Nonlinear Control Theory
• An Introduction to Modern Control
• Control of Hybrid Systems
• Answers to Selected Exercises--.
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Striking a nice balance between mathematical rigor and engineering-oriented applications, this second edition covers the bedrock parts of classical control theory - the Routh-Hurwitz theorem and applications, Nyquist diagrams, Bode plots, root locus plots, and the design of controllers (phase-lag, phase-lead, lag-lead, and PID). It also covers three more advanced topics - non-linear control, modern control, and discrete-time control. This invaluable book makes effective use of MATLAB(R) as a tool in design and analysis. Containing 75 solved problems and 200 figures, this edition will be useful for junior and senior level university students in engineering who have a good knowledge of complex variables and linear algebra.
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• Introduction
• Basics of Classical Control Theory
• Euclidean Group on Modern Robotics and Biomechanics
• Quantum Control: Theory and Measurement
• Control and Synchronization in Complex Systems and Human Crowds.
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New Trends in Control Theory is a graduate-level monographic textbook. It is a contemporary overview of modern trends in control theory. The introductory chapter gives the geometrical and quantum background, which is a necessary minimum for comprehensive reading of the book. The second chapter gives the basics of classical control theory, both linear and nonlinear. The third chapter shows the key role that Euclidean group of rigid motions plays in modern robotics and biomechanics. The fourth chapter gives an overview of modern quantum control, from both theoretical and measurement perspectives. The fifth chapter presents modern control and synchronization methods in complex systems and human crowds. The appendix provides the rest of the background material complementary to the introductory chapter.The book is designed as a one-semester course for engineers, applied mathematicians, computer scientists and physicists, both in industry and academia. It includes a most relevant bibliography on the subject and detailed index.
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• I MATRICES AND RELATED TOPICS
• 1 Determinants
• 2 Matrices and Matrix Operations
• 3 Eigenvalues and Eigenvectors
• 4 Matrix Transformations
• 5 Matrix Functions
• 6 Moore-Penrose Pseudoinverse
• 7 Hermitian and Quadratic Forms
• 8 Linear Matrix Equations
• 9 Stable Matrices and Polynomials
• 10 Algebraic Riccati Equation
• 11 Linear Matrix Inequalities
• 12 Miscellaneous
• II ANALYSIS
• 13 The Real and Complex Number Systems
• 14 Sets, Functions and Metric Spaces
• 15 Integration
• 16 Selected Topics of Real Analysis
• 17 Complex Analysis
• 18 Topics of Functional Analysis
• III DIFFERENTIAL EQUATIONS AND OPTIMIZATION
• 19 Ordinary Differential Equations
• 20 Elements of Stability Theory
• 21 Finite-Dimensional Optimization
• 22 Variational Calculus and Optimal Control
• 23 H2 and H[infinity] Optimization 811.

This book provides a blend of Matrix and Linear Algebra Theory, Analysis, Differential Equations, Optimization, Optimal and Robust Control. It contains an advanced mathematical tool which serves as a fundamental basis for both instructors and students who study or actively work in Modern Automatic Control or in its applications. It is includes proofs of all theorems and contains many examples with solutions. It is written for researchers, engineers, and advanced students who wish to increase their familiarity with different topics of modern and classical mathematics related to System and Automatic Control Theories * Provides comprehensive theory of matrices, real, complex and functional analysis * Provides practical examples of modern optimization methods that can be effectively used in variety of real-world applications * Contains worked proofs of all theorems and propositions presented.

• Introduction.- Optimal Control.- Optimal State Feedback Control.- Differenital Games.- Solutions to Exercises.- References.- Index.
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Introduces a variety of problem statements in classical optimal control, in optimal estimation and filtering, and in optimal control problems with non-scalar-valued performance criteria. This book includes solved example problems.
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• Hybrid Estimation at a Glance.- Probabilistic Hybrid Automata.- Hybrid Estimation.- Case Studies.- Conclusion.
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This monograph provides a tool-set for hybrid estimation that can successfully monitor the behavior of complex artifacts with a large number of possible operational and failure modes such as production plants, automotive or aeronautic systems, and autonomous robots. For this purpose, ideas from the fields of System Theory and Artificial Intelligence are taken and hybrid estimation is reformulated as a search problem. This allows to focus the estimation onto highly probably operational modes, without missing symptoms that might be hidden among the noise in the system. Additionally a novel approach to continue hybrid estimation in the presence of unknown behavioral modes and to automate system analysis and synthesis tasks for on-line operation are presented. This leads to a flexible model-based hybrid estimation scheme for complex artifacts that robustly copes with unforeseen situations.
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• General Characteristic of Control Systems.- Formal Models of Control Systems.- Control for the Given State (the Given Output).- Optimal Control with Complete Information on the Plant.- Parametric Optimization.- Application of Relational Description of Uncertainty.- Application of Probabilistic Descriptions of Uncertainty.- Uncertain Variables and Their Applications.- Fuzzy Variables, Analogies and Soft Variables.- Control in Closed-loop System. Stability.- Adaptive and Learning Control System.- Intelligent and Complex Control Systems.- Control of Operation Systems.
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This compact and uniform textbook presents the contemporary state of the art of control theory and its applications. It introduces traditional problems useful in the automatic control of technical processes, as well as current issues, such as decision taking in conditions of uncertainty, use of artificial intelligence methods, or control of complex operations. The methods covered are introduced in a practice-oriented way that allows the reader to easily apply them for the determination of decision algorithms in computer control and management systems. This concise textbook is aimed at students of automatics, robotics, control engineering, and computer sciences.
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• Preliminaries.- Linear Impulsive Control.- Comparison Methods.- Impulsive Control with Fixed-time Impulses.- Impulsive Control with Impulses at Variable Time.- Practical Stability of Impulsive Control.- Other Impulsive Control Strategies.- Impulsive Computational Verb Control.- Impulsive Control of Periodic Motions.- Impulsive Control of Almost Periodic Motions.- Applications to Nanoelectronics.
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This book presents a unified theoretical framework of some recent developments on the impulsive control theory and its applications to engineering problems. Different structures of impulsive control systems and impulsive control strategies are presented. The following theoretical aspects are also addressed: basic knowledge of impulsive differential equations; controllability and stability of linear impulsive control systems; stability of nonlinear impulsive control systems including: practical stability, global stability, absolute stability, stability in terms of two measures; and optimal impulsive control. This book presents also some engineering applications of impulsive control theory. The readers of this book are scientists, engineers, researchers and graduate students interested in impulsive control, nonlinear control systems, chaotic communications systems and nano-electronics.
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• Preface. Introduction. Representation of linear systems. Properties of linear systems. Sampled data systems. Disturbance models. The closed loop system. Limitations and conflicts. Controller structures and design. Minimization of quadratic criteria : LQG. Shaping the loop again. Description of nonlinear systems. Stability of nonlinear systems. Qualitative behaviour. Phase Plane. Oscillations and describing functions. Controller synthesis for nonlinear systems. Model predictive.
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• Preface. Introduction.
• 1. Representation of linear systems
• 2. Properties of linear systems
• 3. Sampled data systems
• 4. Disturbance models
• 5. The closed loop system
• 6. Limitations and conflicts
• 7. Controller structures and design
• 8. Minimization of quadratic criteria
• 9. Shaping the loop again
• 10. Descriptions of nonlinear systems
• 11. Stability of nonlinear systems
• 12. Qualitative beviour. Phase Plane
• 13. Oscillations and describing functions
• 14. Controller synthesis for nonlinear systems
• 15. Model predictive control : MPC, GPC, and DMM
• 16. To compensate exactly for nonlinearities
• 17. Optimal control
• 18. Conclusion. Literature. Index. Index of examples.
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This textbook is designed for an advanced course in control theory. Basic courses in control typically cover linear time invariant systems with one input and one output. Since industrial processes often have several inputs and outputs and contain nonlinearities, these topics need to be covered in a second course. "Control Theory" explains current developments in multivariable and nonlinear control techniques, and looks at tools for computer aided design, for example Matlab and its toolboxes.It is now possible for practical engineering to use many of the recent developments based on deep mathematical results, such as H-Infinity methods and exact linearization. To make full use of computer design tools, a good understanding of their theoretical basis is necessary, and to enable this the book presents relevant mathematics clearly and simply. The practical limits of control systems are explored, and the relevance of these to control design are discussed. The book is ideal for a final year undergraduate.
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• Path Integrals and Stability, J.C. Willems * The Estimation Algebra of Nonlinear Filtering Systems, Wing Shing Wong, Stephen S.T. Yau * Feedback Linearization, A.J. Krener * On the Global Analysis of Linear Systems, Christopher I. Byrnes * Geometry and Optimal Control, H.J. Sussmann * Languages, Behaviors, Hybrid Architectures and Motion Control, Vikram Manikonda, P.S. Krishnaprasad, James Hendler * Optimal Control, Geometry and Mechanics, V. Jurdjevic * Optimal Control, Optimization and Analytical Mechanics, Anthony M. Bloch, Peter E. Crouch * The Geometry of Controlled Mechanical Systems, J. Baillieul.
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This self-contained volume surveys three decades of mathematical control theory and at the same time describes how the work of Roger Brockett shaped and influenced its development. Nine survey articles written by leading experts in the field, who have also been closely associated with Roger Brockett at various stages in his career, treat the subject cohesively and in depth. This volume will provide an important reference for graduate students and researchers, as well as for mathematicians, engineers and scientists whose work involves concepts and the language of control and systems theory.
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• Introduction and motivation
• foundation
• linear controllability
• nonlinear controllability
• applications and related topics
• conclusions.
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The book gives a novel treatment of recent advances on constrained control problems of discrete processes. The new proposed approach provides the right setting for the study of qualitative properties of general types of dynamical systems in both discrete-time and continuous-time systems with possible applications to some control engineering models. Most of the material appears for the first time in a book form. The book is addressed to advanced students, postgraduate students and researchers interested in control system theory and optimal control.
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• Elements of the theory of systems with aftereffect The dynamic programming method Optimality conditions for deterministic systems with aftereffect Investigation of self-adjusting systems with reference model Optimal control of stochastic systems Optimal control of systems defined by stochastic integro-functional equations Optimal estimation Optimal control with incomplete data Bibliography.
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The study of natural and social phemomena indicates that the future development of many processes depends not only on their present state, but also on their history. Such processes can be described mathematically by using the machinery of equations with aftereffect. This book is a comprehensive, up-to-date presentation of control theory for hereditary systems of various types. Topics covered include background of the theory of hereditary equations, their applications in modeling real phenomena, optimal control of deterministic and stochastic systems, optimal estimation of systems with delay, and optimal control with uncertainties. The exposition is illustrated by examples, figures, and tables.
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