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. The authors demonstrate the advantages of the methods presented for control and optimization through extensive simulations. Included in the work are new techniques for feedback controller design and optimization of multiscale process systems that are not included in other books. The book also contains a rich collection of new research topics and references to significant recent work.

Microelectronic market imposes tight requirements upon thin film properties, including specific growth rate, surface roughness and thickness of the film. In the thin film deposition process, the microscopic events determine the configuration of the thin film surface while manipulating variables at the macroscopic level, such as bulk precursor mole fraction and substrate temperature, are essential to product quality. Despite the extensive body of research on control and optimization in this process, there is still a significant discrepancy between the expected performance and the actual yield that can be accomplished employing existing methodologies. This gap is mainly related to the complexities associated with the multiscale nature of the thin film deposition process, lack of practical online in-situ sensors at the fine-scale level, and uncertainties in the mechanisms and parameters of the system. The main goal of this research is developing robust control and optimization strategies for this process while uncertainty analysis is performed using power series expansion (PSE). The deposition process is a batch process where the measurements are available at the end of the batch; accordingly, optimization and control approaches that do not need to access online fine-scale measurements are required. In this research, offline optimization is performed to obtain the optimal temperature profile that results in specific product quality characteristics in the presence of model-plant mismatch. To provide a computationally tractable optimization, the sensitivities in PSEs are numerically evaluated using reduced-order lattices in the KMC models. A comparison between bounded and distributional parametric uncertainties has illustrated that inaccurate assumption for uncertainty description can lead to economic losses in the process. To accelerate the sensitivity analysis of the process, an algorithm has been presented to determine the upper and lower bounds on the outputs through distributions of the microscopic events. In this approach, the sensitivities in the series expansions of events are analytically evaluated. Current multiscale models are not available in closed-form and are computationally prohibitive for online applications. Thus, closed-form models have been developed in this research to predict the control objectives efficiently for online control applications in the presence of model-plant mismatch. The robust performance is quantified by estimates of the distributions of the controlled variables employing PSEs. Since these models can efficiently predict the controlled outputs, they can either be used as an estimator for feedback control purposes in the lack of sensors, or as a basis to design a nonlinear model predictive control (NMPC) framework. Although the recently introduced optical in-situ sensors have motivated the development of feedback control in the thin film deposition process, their application is still limited in practice. Thus, a multivariable robust estimator has been developed to estimate the surface roughness and growth rate based on the substrate temperature and bulk precursor mole fraction. To ensure that the control objective is met in the presence of model-plant mismatch, the robust estimator is designed such that it predicts the upper bound on the process output. The estimator is coupled with traditional feedback controllers to provide a robust feedback control in the lack of online measurements. In addition, a robust NMPC application for the thin film deposition process was developed. The NMPC makes use of closed-from models, which has been identified offline to predict the controlled outputs at a predefined specific probability. The shrinking horizon NMPC minimizes the final roughness, while satisfying the constraints on the control actions and film thickness at the end of the deposition process. Since the identification is performed for a fixed confidence level, hard constraints are defined for thin film properties. To improve the robust performance of NMPC using soft constraints, a closed-form model has been developed to estimate the first and second- order statistical moments of the thin film properties under uncertainty in the multiscale model parameters. Employing this model, the surface roughness and film thickness can be estimated at a desired probability limit during the deposition. Thus, an NMPC framework is devised that successfully minimizes the surface roughness at the end of the batch, while the film thickness meets a minimum specification at a desired probability. Therefore, the methods developed in this research enable accurate online control of the key properties of a multiscale system in the presence of model-plant mismatch.

Model reduction and coarse-graining are important in many areas of science and engineering. How does a system with many degrees of freedom become one with fewer? How can a reversible micro-description be adapted to the dissipative macroscopic model? These crucial questions, as well as many other related problems, are discussed in this book. All contributions are by experts whose specialities span a wide range of fields within science and engineering.

At publication, The Control Handbook immediately became the definitive resource that engineers working with modern control systems required. Among its many accolades, that first edition was cited by the AAP as the Best Engineering Handbook of 1996. Now, 15 years later, William Levine has once again compiled the most comprehensive and authoritative resource on control engineering. He has fully reorganized the text to reflect the technical advances achieved since the last edition and has expanded its contents to include the multidisciplinary perspective that is making control engineering a critical component in so many fields. Now expanded from one to three volumes, The Control Handbook, Second Edition organizes cutting-edge contributions from more than 200 leading experts. The second volume, Control System Applications, includes 35 entirely new applications organized by subject area. Covering the design and use of control systems, this volume includes applications for: Automobiles, including PEM fuel cells Aerospace Industrial control of machines and processes Biomedical uses, including robotic surgery and drug discovery and development Electronics and communication networks Other applications are included in a section that reflects the multidisciplinary nature of control system work. These include applications for the construction of financial portfolios, earthquake response control for civil structures, quantum estimation and control, and the modeling and control of air conditioning and refrigeration systems. As with the first edition, the new edition not only stands as a record of accomplishment in control engineering but provides researchers with the means to make further advances. Progressively organized, the other two volumes in the set include: Control System Fundamentals Control System Advanced Methods

Safety and Reliability – Theory and Applications contains the contributions presented at the 27th European Safety and Reliability Conference (ESREL 2017, Portorož, Slovenia, June 18-22, 2017). The book covers a wide range of topics, including: • Accident and Incident modelling • Economic Analysis in Risk Management • Foundational Issues in Risk Assessment and Management • Human Factors and Human Reliability • Maintenance Modeling and Applications • Mathematical Methods in Reliability and Safety • Prognostics and System Health Management • Resilience Engineering • Risk Assessment • Risk Management • Simulation for Safety and Reliability Analysis • Structural Reliability • System Reliability, and • Uncertainty Analysis. Selected special sessions include contributions on: the Marie Skłodowska-Curie innovative training network in structural safety; risk approaches in insurance and fi nance sectors; dynamic reliability and probabilistic safety assessment; Bayesian and statistical methods, reliability data and testing; oganizational factors and safety culture; software reliability and safety; probabilistic methods applied to power systems; socio-technical-economic systems; advanced safety assessment methodologies: extended Probabilistic Safety Assessment; reliability; availability; maintainability and safety in railways: theory & practice; big data risk analysis and management, and model-based reliability and safety engineering. Safety and Reliability – Theory and Applications will be of interest to professionals and academics working in a wide range of industrial and governmental sectors including: Aeronautics and Aerospace, Automotive Engineering, Civil Engineering, Electrical and Electronic Engineering, Energy Production and Distribution, Environmental Engineering, Information Technology and Telecommunications, Critical Infrastructures, Insurance and Finance, Manufacturing, Marine Industry, Mechanical Engineering, Natural Hazards, Nuclear Engineering, Offshore Oil and Gas, Security and Protection, Transportation, and Policy Making.

At publication, The Control Handbook immediately became the definitive resource that engineers working with modern control systems required. Among its many accolades, that first edition was cited by the AAP as the Best Engineering Handbook of 1996. Now, 15 years later, William Levine has once again compiled the most comprehensive and authoritative resource on control engineering. He has fully reorganized the text to reflect the technical advances achieved since the last edition and has expanded its contents to include the multidisciplinary perspective that is making control engineering a critical component in so many fields. Now expanded from one to three volumes, The Control Handbook, Second Edition brilliantly organizes cutting-edge contributions from more than 200 leading experts representing every corner of the globe. They cover everything from basic closed-loop systems to multi-agent adaptive systems and from the control of electric motors to the control of complex networks. Progressively organized, the three volume set includes: Control System Fundamentals Control System Applications Control System Advanced Methods Any practicing engineer, student, or researcher working in fields as diverse as electronics, aeronautics, or biomedicine will find this handbook to be a time-saving resource filled with invaluable formulas, models, methods, and innovative thinking. In fact, any physicist, biologist, mathematician, or researcher in any number of fields developing or improving products and systems will find the answers and ideas they need. As with the first edition, the new edition not only stands as a record of accomplishment in control engineering but provides researchers with the means to make further advances.