Bøger af Panagiotis D. Christofides

This book is focused on the development of rigorous, yet practical, methods for the design of advanced process control systems to improve process operational safety and cybersecurity for a wide range of nonlinear process systems. Process Operational Safety and Cybersecurity develops designs for novel model predictive control systems accounting for operational safety considerations, presents theoretical analysis on recursive feasibility and simultaneous closed-loop stability and safety, and discusses practical considerations including data-driven modeling of nonlinear processes, characterization of closed-loop stability regions and computational efficiency. The text then shifts focus to the design of integrated detection and model predictive control systems which improve process cybersecurity by efficiently detecting and mitigating the impact of intelligent cyber-attacks. The book explores several key areas relating to operational safety and cybersecurity including:machine-learning-based modeling of nonlinear dynamical systems for model predictive control;a framework for detection and resilient control of sensor cyber-attacks for nonlinear systems; insight into theoretical and practical issues associated with the design of control systems for process operational safety and cybersecurity; and a number of numerical simulations of chemical process examples and Aspen simulations of large-scale chemical process networks of industrial relevance. A basic knowledge of nonlinear system analysis, Lyapunov stability techniques, dynamic optimization, and machine-learning techniques will help readers to understand the methodologies proposed. The book is a valuable resource for academic researchers and graduate students pursuing research in this area as well as for process control engineers.Advances in Industrial Control reportsand encourages the transfer of technology in control engineering. The rapid development of control technology has an impact on all areas of the control discipline. The series offers an opportunity for researchers to present an extended exposition of new work in all aspects of industrial control.

This book presents general methods for the design of economic model predictive control (EMPC) systems for broad classes of nonlinear systems that address key theoretical and practical considerations including recursive feasibility, closed-loop stability, closed-loop performance, and computational efficiency.

This book offers a rich collection of state-of-the art, practical methods, new research topics, and references to significant work on the design of integrated fault detection and isolation and fault-tolerant control systems for chemical processes.

This book-the first of its kind-presents general methods for feedback controller synthesis and optimization of multiscale systems, illustrating their application to thin-film growth, sputtering processes, and catalytic systems of industrial interest.

Control of Nonlinear and Hybrid Process Systems includes numerous comments and remarks providing insight and fundamental understanding into the feedback control of nonlinear and hybrid systems, as well as applications that demonstrate the implementation and effectiveness of the presented control methods.

This book offers rigorous, yet practical, methods for the design of networked and distributed predictive control systems, including new techniques for system design, insight into likely issues and challenges, and integrated exposition of novel research topics.

The interest in control of nonlinear partial differential equation (PDE) sys tems has been triggered by the need to achieve tight distributed control of transport-reaction processes that exhibit highly nonlinear behavior and strong spatial variations.

Particulate processes are characterized by the co-presence of a contin uous phase and a dispersed (particulate) phase, and are widely used in industry for the manufacturing of many high-value products.