Books in the Lecture Notes in Control and Information Sciences series

1. Introduction.- 2. Fault Tolerance in Networked Control Systems by Flexible Task Assignment.- 3. Resilient Control under Denial-of-Service: Results and Research Directions.- 4. Stealthy False Data Injection Attacks in Feedback Systems Revisited.- 5. Detection of Attacks in Cyber-Physical Systems: Theory and Applications.- 6. Security Metrics for Control Systems.- 7. The Secure State Estimation Problem.- 8. A Survey on Watermark Design For Cyber-Physical Systems.- 9. Detection of Cyber-Attacks: a Multiplicative Watermarking Scheme.- 9. Differentially Private Anomaly Detection for Interconnected Systems.- 10. Remote State Estimation in the Presence of an Eavesdropper.- 11. Secure Networked Control Systems Design using semi-homomorphic Encryption.- 12. Deception-As-Defense Framework for Cyber-Physical Systems.- 13. Cyber Risk: CPS vs. ITS.- 14. Cyber Insurance.- 15. Conclusions.

This book extrapolates many of the concepts that are well defined for discrete-time deterministic sliding-mode control for use with discrete-time stochastic systems.

Part I: Control Design, Observation, and Identification.- Linear Observer Synthesis for Nonlinear Systems.- Linear Predictors for Nonlinear Dynamical Systems.- Global Stability Analysis.- Pulse-based Optimal Control.- Parameter Estimation and Identification of Nonlinear Systems.- Koopman Spectrum and Stability of Cascaded Dynamical Systems.- Open and Closed Loop Control of PDEs via Switched Systems and Koopman operator based reduced order models.- Part II: Data-Driven Analysis.- Data-driven Approximations of Dynamical Systems Operators for Control.- Operator Theoretic-based Data-driven Approach for Optimal Stabilization of Nonlinear System.- Manifold Learning for Data-Driven Dynamical Systems Analysis.- Use of Data-Driven Koopman Spectrum Computation and Delay Embedding.- Part III: Applications.- Modeling of Advective Heat Transfer in a Practical Building Atrium via Koopman Mode Decomposition.- Phase-amplitude Reduction of Limit-cycling Systems.- Exploiting Effects of Network Topology on Performance in Nonlinear Consensus Networks.- Koopman Operators in Embedded Control.

This book investigates the performance limitation issues in networked feedback systems. The fact that networked feedback systems consist of control and communication devices and systems calls for the integration of control theory and information theory.

This edited volume includes thoroughly collected on sensing and control for autonomous vehicles. There is a growing interest for cooperative and coordinated multi-vehicle systems, real-time re-planning, robust autonomous navigation systems and robust autonomous control of vehicles.

This book bridges the gap between system theory and global climate change research, and benefits both. A representative set of systems problems is listed indicating how such cross-fertilization would enhance present understanding of global problems while assisting the extension of systems theory.

Dynamic Programming for Impulse Feedback and Fast Controls offers a description of feedback control in the class of impulsive inputs. This book deals with the problem of closed-loop impulse control based on generalization of dynamic programming techniques in the form of variational inequalities of the Hamilton-Jacobi-Bellman type. It provides exercises and examples in relation to software, such as techniques for regularization of ill-posed problems. It also gives an introduction to applications such as hybrid dynamics, control in arbitrary small time, and discontinuous trajectories.This book walks the readers through:the design and description of feedback solutions for impulse controls;the explanation of impulses of higher order that are derivatives of delta functions;the description of their physically realizable approximations - the fast controls and their approximations;the treatment of uncertainty in impulse control and the applications of impulse feedback.Of interest to both academics and graduate students in the field of control theory and applications, the book also protects users from common errors , such as inappropriate solution attempts, by indicating Hamiltonian techniques for hybrid systems with resets.

Stochastic Recursive Algorithms for Optimization presents algorithms for constrained and unconstrained optimization and for reinforcement learning.

This edited volume includes thoroughly collected on sensing and control for autonomous vehicles. There is a growing interest for cooperative and coordinated multi-vehicle systems, real-time re-planning, robust autonomous navigation systems and robust autonomous control of vehicles.

The purpose of the Conference on Optimal Control of Partial Differential Equations was to bring together leading experts in this field and to exchange ideas and information about recent advances in control theory connected with partial differential equations.

These notes are an introduction to implicit models of linear dynamical systems, with applications to modelling, control system design, and identification, intended for control-system engineers at the beginning graduate level.

The three Workshops on Control Mechanics held annually since 1988 at the University of Southern California made substantial contribution to the above set of topics and have established a tradition in the interface between mechanics and control.

This class of systems includes various interconnections of linear dynamic blocks and static nonlinear elements, e.g., Hammerstein system, Wiener system, Wiener-Hammerstein ("sandwich") system and additive NARMAX systems with feedback.

Finite-time stability (FTS) is a more practical concept than classical Lyapunov stability, useful for checking whether the state trajectories of a system remain within pre-specified bounds over a finite time interval.

A principal objective of control engineering is to design control systems which are robust with respect to external disturbances and modelling uncertainty. More precisely, "Time-Varying Sliding Modes for Second and Third Order Systems" focuses on only one, but very important aspect of the sliding mode system design, i.e.

These include further applications of the abstract model based stability theory which, in particular, shows the critical importance to the dynamics developed of the structure of the initial conditions at the start of each new pass, the development of stability tests and performance bounds in terms of so-called 1D and 2D Lyapunov equations.

How can a robot decide what motions to perform in order to achieve tasks in the physical world? Robot motion planning encompasses several different disciplines, most notably robotics, computer science, control theory and mathematics.