Cyber–Physical–Human Systems A comprehensive edited volume exploring the latest in the interactions between cyber–physical systems and humans In Cyber–Physical–Human Systems: Fundamentals and Applications, a team of distinguished researchers delivers a robust and up-to-date volume of contributions from leading researchers on Cyber–Physical–Human Systems, an emerging class of systems with increased interactions between cyber–physical, and human systems communicating with each other at various levels across space and time, so as to achieve desired performance related to human welfare, efficiency, and sustainability. The editors have focused on papers that address the power of emerging CPHS disciplines, all of which feature humans as an active component during cyber and physical interactions. Articles that span fundamental concepts and methods to various applications in engineering sectors of transportation, robotics, and healthcare and general socio-technical systems such as smart cities are featured. Together, these articles address challenges and opportunities that arise due to the emerging interactions between cyber–physical systems and humans, allowing readers to appreciate the intersection of cyber–physical system research and human behavior in large-scale systems. In the book, readers will also find: A thorough introduction to the fundamentals of cyber–physical–human systems In-depth discussions of cyber–physical–human systems with applications in transportation, robotics, and healthcare A comprehensive treatment of socio-technical systems, including social networks and smart cities Perfect for cyber–physical systems researchers, academics, and graduate students, Cyber–Physical–Human Systems: Fundamentals and Applications will also earn a place in the libraries of research and development professionals working in industry and government agencies.

This brief focuses on stochastic energy optimization for distributed energy resources in smart grids. Along with a review of drivers and recent developments towards distributed energy resources, this brief presents research challenges of integrating millions of distributed energy resources into the grid. The brief then proposes a novel three-level hierarchical architecture for effectively integrating distributed energy resources into smart grids. Under the proposed hierarchical architecture, distributed energy resource management algorithms at the three levels (i.e., smart home, smart neighborhood, and smart microgrid) are developed in this brief based on stochastic optimization that can handle the involved uncertainties in the system.

The two volumes of Signal Processing are based on lectures delivered during a six week program held at the IMA from June 27 to August 5, 1988. The first two weeks of the program dealt with general areas and methods of Signal Pro cessing. The problem areas included imaging and analysis of recognition, x-ray crystallography, radar and sonar, signal analysis and 1-D signal processing, speech, vision, and VLSI implementation. The methods discussed included harmonic anal ysis and wavelets, operator theory, algorithm complexity, filtering and estimation, and inverse scattering. The topics of weeks three and four were digital filter, VLSI implementation, and integrable circuit modelling. In week five the concentration was on robust and nonlinear control with aerospace applications, and in week six the emphasis was on problems in radar, sonar and medical imaging. Because of the large overlap between the various one-week and two-week seg ments of the program, we found it more convenient to divide the material somewhat differently. Part I deals with general signal process theory and Part II deals with (i) application of signal processing, (ii) control theory related themes. We are grateful to the scientific organizers: Tom Kailath (Chairman), Louis Aus lander, F. Alberto Grunbaum, J. William Helton, Pramod P. Khargonekar and Sanjoy K. Mitter. We are also grateful for the generous support given to the IMA program by the Office of Naval Research, the Air Force Office of Scientific Research, the Army Research Office and the National Security Agency."

Robust control originates with the need to cope with systems with modeling uncertainty. There have been several mathematical techniques developed for robust control system analysis. The articles in this volume cover all of the major research directions in the field.