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A process system faces the challenge of uncertainty throughout its lifetime. At the design stage, uncertainty originates from inaccurate knowledge of design parameters and unmeasured or unmeasurable ambient disturbances. Oftentimes, designers choose to increase system size to account for uncertainty and fluctuations; however, this approach has an economic limit, past which the capital expenditure outweighs the potential operational benefits. In the operational stage, uncertainty is manifest, amongst others, in fluctuations in operating conditions, market demand and raw material availability. Another type of uncertainty in (modern) process operations is related to the quality of process models that are used for making control and operational decisions. Of particular importance is the quality of the dynamic models that are used in real-time optimal control computations. The chemical industry has been the pioneer (and is currently the leader) of model predictive control (MPC) implementations, whereby the control moves are computed, over a receding time horizon, by solving an optimal control problem at each time step. While uniquely able to deal with large-scale, non-square constrained systems, MPC is vitally dependent on the predictive abilities of the built-in model. Changes in plant conditions are a a source of uncertainty in this case as-well, leading to a discrepancy (mismatch) between the model predictions and the true plant behavior. In this dissertation, I address the problems of design under uncertainty and plant-model mismatch. For the former, identification-based optimization (IBO) framework is proposed as a new, computationally efficient framework for optimizing the design of dynamic systems under uncertainty problem. The framework uses properly designed pseudo-random multilevel signals (PRMS) to represent time-varying uncertain variables. This allows us to formulate the design under uncertainty problem as a dynamic optimization problem. A solution algorithm is proposed using a sequential approach. Several application examples are discussed, demonstrating the superior computational performance of the IBO approach. Furthermore, an extension of the method that explicitly considers the tradeoff between conservativeness and dynamic performance is introduced. The latter, plant-model mismatch problem, is addressed using a novel autocovariance-based approach. Under appropriate assumptions, an explicit relation is established between the autocovariance of the process output and the plant-model mismatch terms, represented either in a step response model or a transfer function model. It is demonstrated that an asymptotically correct set of estimates of the values of plant-model mismatch for each model parameters is the global minimizer of the discrepancy between the autocovariance predicted using the relation and the autocovariance calculated from a data set collected from closed-loop operating data. Extensions of this approach handle cases where the active set of the MPC is changing over time and there are setpoint change and measurable disturbances occur in the control loop.
Most existing robust design books address design for static systems, or achieve robust design from experimental data via the Taguchi method. Little work considers model information for robust design particularly for the dynamic system. This book covers robust design for both static and dynamic systems using the nominal model information or the hybrid model/data information, and also integrates design with control under a large operating region. This design can handle strong nonlinearity and more uncertainties from model and parameters.
Presents a state-of-the-art review of model error concepts, their characterization and compensation in estimation and control problems, with particular emphasis on error propagation, model order selection, performance guarantees, sensitivity and adaptive methods. Main topics covered include linear and nonlinear systems, identification, robotics, computer-aided design, signal processing, computers and communication in control, automation and real time control of processes.
The existence of interactions between the design of a process and that of its control system have been known to industrial practitioners for a long time. In the past decade academic research has produced methodologies and tools that begin to address the issue of designing processes that are flexible, can be controlled reliably, and are inherently safe. This publication unites the work of academics and practitioners with interests in the integration of process design and control, in order to examine the state of the art in methodologies and applications. The scope covers the design of chemical plants at different stages of detail. It also examines control issues from the plantwide level, where, for example, recycles between units can be important, to the specific unit level, where the availability or selection of measurements might be the most important factor.
This comprehensive volume brings together an extensive collection of systematic computer-aided tools and methods developed in recent years for CO2 capture applications, and presents a structured and organized account of works from internationally acknowledged scientists and engineers, through: Modeling of materials and processes based on chemical and physical principles Design of materials and processes based on systematic optimization methods Utilization of advanced control and integration methods in process and plant-wide operations The tools and methods described are illustrated through case studies on materials such as solvents, adsorbents, and membranes, and on processes such as absorption / desorption, pressure and vacuum swing adsorption, membranes, oxycombustion, solid looping, etc. Process Systems and Materials for CO2 Capture: Modelling, Design, Control and Integration should become the essential introductory resource for researchers and industrial practitioners in the field of CO2 capture technology who wish to explore developments in computer-aided tools and methods. In addition, it aims to introduce CO2 capture technologies to process systems engineers working in the development of general computational tools and methods by highlighting opportunities for new developments to address the needs and challenges in CO2 capture technologies.
With a specific focus on the needs of the designers and engineers in industrial settings, The Mechanical Systems Design Handbook: Modeling, Measurement, and Control presents a practical overview of basic issues associated with design and control of mechanical systems. In four sections, each edited by a renowned expert, this book answers diverse questions fundamental to the successful design and implementation of mechanical systems in a variety of applications. Manufacturing addresses design and control issues related to manufacturing systems. From fundamental design principles to control of discrete events, machine tools, and machining operations to polymer processing and precision manufacturing systems. Vibration Control explores a range of topics related to active vibration control, including piezoelectric networks, the boundary control method, and semi-active suspension systems. Aerospace Systems presents a detailed analysis of the mechanics and dynamics of tensegrity structures Robotics offers encyclopedic coverage of the control and design of robotic systems, including kinematics, dynamics, soft-computing techniques, and teleoperation. Mechanical systems designers and engineers have few resources dedicated to their particular and often unique problems. The Mechanical Systems Design Handbook clearly shows how theory applies to real world challenges and will be a welcomed and valuable addition to your library.
This is the biggest, most comprehensive, and most prestigious compilation of articles on control systems imaginable. Every aspect of control is expertly covered, from the mathematical foundations to applications in robot and manipulator control. Never before has such a massive amount of authoritative, detailed, accurate, and well-organized information been available in a single volume. Absolutely everyone working in any aspect of systems and controls must have this book!