Download or read book Analysis Design and Control Optimization of Process Systems Under Uncertainty written by Vikrant Bansal and published by . This book was released on 2000 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Aerospace System Analysis and Optimization in Uncertainty written by Loïc Brevault and published by Springer Nature. This book was released on 2020-08-26 with total page 477 pages. Available in PDF, EPUB and Kindle. Book excerpt: Spotlighting the field of Multidisciplinary Design Optimization (MDO), this book illustrates and implements state-of-the-art methodologies within the complex process of aerospace system design under uncertainties. The book provides approaches to integrating a multitude of components and constraints with the ultimate goal of reducing design cycles. Insights on a vast assortment of problems are provided, including discipline modeling, sensitivity analysis, uncertainty propagation, reliability analysis, and global multidisciplinary optimization. The extensive range of topics covered include areas of current open research. This Work is destined to become a fundamental reference for aerospace systems engineers, researchers, as well as for practitioners and engineers working in areas of optimization and uncertainty. Part I is largely comprised of fundamentals. Part II presents methodologies for single discipline problems with a review of existing uncertainty propagation, reliability analysis, and optimization techniques. Part III is dedicated to the uncertainty-based MDO and related issues. Part IV deals with three MDO related issues: the multifidelity, the multi-objective optimization and the mixed continuous/discrete optimization and Part V is devoted to test cases for aerospace vehicle design.

Download or read book Probabilistic and Randomized Methods for Design under Uncertainty written by Giuseppe Calafiore and published by Springer Science & Business Media. This book was released on 2006-03-06 with total page 454 pages. Available in PDF, EPUB and Kindle. Book excerpt: Probabilistic and Randomized Methods for Design under Uncertainty is a collection of contributions from the world’s leading experts in a fast-emerging branch of control engineering and operations research. The book will be bought by university researchers and lecturers along with graduate students in control engineering and operational research.

Download or read book Optimization Under Stochastic Uncertainty written by Kurt Marti and published by Springer Nature. This book was released on 2020-11-10 with total page 390 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book examines application and methods to incorporating stochastic parameter variations into the optimization process to decrease expense in corrective measures. Basic types of deterministic substitute problems occurring mostly in practice involve i) minimization of the expected primary costs subject to expected recourse cost constraints (reliability constraints) and remaining deterministic constraints, e.g. box constraints, as well as ii) minimization of the expected total costs (costs of construction, design, recourse costs, etc.) subject to the remaining deterministic constraints. After an introduction into the theory of dynamic control systems with random parameters, the major control laws are described, as open-loop control, closed-loop, feedback control and open-loop feedback control, used for iterative construction of feedback controls. For approximate solution of optimization and control problems with random parameters and involving expected cost/loss-type objective, constraint functions, Taylor expansion procedures, and Homotopy methods are considered, Examples and applications to stochastic optimization of regulators are given. Moreover, for reliability-based analysis and optimal design problems, corresponding optimization-based limit state functions are constructed. Because of the complexity of concrete optimization/control problems and their lack of the mathematical regularity as required of Mathematical Programming (MP) techniques, other optimization techniques, like random search methods (RSM) became increasingly important. Basic results on the convergence and convergence rates of random search methods are presented. Moreover, for the improvement of the – sometimes very low – convergence rate of RSM, search methods based on optimal stochastic decision processes are presented. In order to improve the convergence behavior of RSM, the random search procedure is embedded into a stochastic decision process for an optimal control of the probability distributions of the search variates (mutation random variables).

Download or read book Multi Parametric Programming written by and published by Wiley-VCH. This book was released on 2007-04-09 with total page 324 pages. Available in PDF, EPUB and Kindle. Book excerpt: This first book to cover all aspects of multi-parametric programming and its applications in process systems engineering includes theoretical developments and algorithms in multi-parametric programming with applications from the manufacturing sector and energy and environment analysis. The volume thus reflects the importance of fundamental research in multi-parametric programming applications, developing mechanisms for the transfer of the new technology to industrial problems. Since the topic applies to a wide range of process systems, as well as due to the interdisciplinary expertise required to solve the challenge, this reference will find a broad readership. Inspired by the leading authority in the field, the Centre for Process Systems Engineering at Imperial College London.

Download or read book European Symposium on Computer Aided Process Engineering 12 written by J. Grievink and published by Elsevier. This book was released on 2002-04-29 with total page 1059 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book contains 182 papers presented at the 12th Symposium of Computer Aided Process Engineering (ESCAPE-12), held in The Hague, The Netherlands, May 26-29, 2002. The objective of ESCAPE-12 is to highlight advances made in the development and use of computing methodologies and information technology in the area of Computer Aided Process Engineering and Process Systems Engineering. The Symposium addressed six themes: (1) Integrated Product&Process Design; (2) Process Synthesis & Plant Design; (3) Process Dynamics & Control; (4) Manufacturing & Process Operations; (5) Computational Technologies; (6) Sustainable CAPE Education and Careers for Chemical Engineers. These themes cover the traditional core activities of CAPE, and also some wider conceptual perspectives, such as the increasing interplay between product and process design arising from the often complex internal structures of modern products; the integration of production chains creating the network structure of the process industry and optimization over life span dimensions, taking sustainability as the ultimate driver.

Download or read book Introduction to Process Control written by Victor A. Skormin and published by Springer. This book was released on 2016-10-19 with total page 265 pages. Available in PDF, EPUB and Kindle. Book excerpt: This textbook is intended for an introductory graduate level on process control, taught in most engineering curricula. It focuses on the statistical techniques and methods of control and system optimization needed for the mathematical modeling, analysis, simulation, control and optimization of multivariable manufacturing processes. In four sections, it covers: Relevant mathematical methods, including random events, variables and processes, and their characteristics; estimation and confidence intervals; Bayes applications; correlation and regression analysis; statistical cluster analysis; and singular value decomposition for classification applications. Mathematical description of manufacturing processes, including static and dynamic models; model validation; confidence intervals for model parameters; principal component analysis; conventional and recursive least squares procedures; nonlinear least squares; and continuous-time, discrete-time, s-domain and Z-domain models. Control of manufacturing processes, including transfer function/transfer matrix models; state-variable models; methods of discrete-time classical control; state variable discrete-time control; state observers/estimators in control systems; methods of decoupling control; and methods of adaptive control. Methods and applications of system optimization, including unconstrained and constrained optimization; analytical and numerical optimization procedures; use of penalty functions; methods of linear programming; gradient methods; direct search methods; genetic optimization; methods and applications of dynamic programming; and applications to estimation, design, control, and planning. Each section of the book will include end-of-chapter exercises, and the book will be suitable for any systems, electrical, chemical, or industrial engineering program, as it focuses on the processes themselves, and not on the product being manufactured. Students will be able to obtain a mathematical model of any manufacturing process, to design a computer-based control system for a particular continuous manufacturing process, and be able to formulate an engineering problem in terms of optimization, as well as the ability to choose and apply the appropriate optimization technique.

Download or read book Addressing Uncertainty and Modeling Error in the Design and Control of Process Systems written by Siyun Wang (Ph. D.) and published by . This book was released on 2016 with total page 456 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Download or read book Integrated Process Design and Operational Optimization via Multiparametric Programming written by Baris Burnak and published by Morgan & Claypool Publishers. This book was released on 2020-09-04 with total page 260 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents a comprehensive optimization-based theory and framework that exploits the synergistic interactions and tradeoffs between process design and operational decisions that span different time scales. Conventional methods in the process industry often isolate decision making mechanisms with a hierarchical information flow to achieve tractable problems, risking suboptimal, even infeasible operations. In this book, foundations of a systematic model-based strategy for simultaneous process design, scheduling, and control optimization is detailed to achieve reduced cost and improved energy consumption in process systems. The material covered in this book is well suited for the use of industrial practitioners, academics, and researchers. In Chapter 1, a historical perspective on the milestones in model-based design optimization techniques is presented along with an overview of the state-of-the-art mathematical tools to solve the resulting complex problems. Chapters 2 and 3 discuss two fundamental concepts that are essential for the reader. These concepts are (i) mixed integer dynamic optimization problems and two algorithms to solve this class of optimization problems, and (ii) developing a model based multiparametric programming model predictive control. These tools are used to systematically evaluate the tradeoffs between different time-scale decisions based on a single high-fidelity model, as demonstrated on (i) design and control, (ii) scheduling and control, and (iii) design, scheduling, and control problems. We present illustrative examples on chemical processing units, including continuous stirred tank reactors, distillation columns, and combined heat and power regeneration units, along with discussions of other relevant work in the literature for each class of problems.

Download or read book Modeling Design and Simulation of Systems with Uncertainties written by Andreas Rauh and published by Springer Science & Business Media. This book was released on 2011-06-06 with total page 356 pages. Available in PDF, EPUB and Kindle. Book excerpt: To describe the true behavior of most real-world systems with sufficient accuracy, engineers have to overcome difficulties arising from their lack of knowledge about certain parts of a process or from the impossibility of characterizing it with absolute certainty. Depending on the application at hand, uncertainties in modeling and measurements can be represented in different ways. For example, bounded uncertainties can be described by intervals, affine forms or general polynomial enclosures such as Taylor models, whereas stochastic uncertainties can be characterized in the form of a distribution described, for example, by the mean value, the standard deviation and higher-order moments. The goal of this Special Volume on Modeling, Design, and Simulation of Systems with Uncertainties is to cover modern methods for dealing with the challenges presented by imprecise or unavailable information. All contributions tackle the topic from the point of view of control, state and parameter estimation, optimization and simulation. Thematically, this volume can be divided into two parts. In the first we present works highlighting the theoretic background and current research on algorithmic approaches in the field of uncertainty handling, together with their reliable software implementation. The second part is concerned with real-life application scenarios from various areas including but not limited to mechatronics, robotics, and biomedical engineering.

Download or read book Product Driven Process Design written by Edwin Zondervan and published by Walter de Gruyter GmbH & Co KG. This book was released on 2020-01-20 with total page 492 pages. Available in PDF, EPUB and Kindle. Book excerpt: Product-driven process design – from molecule to enterprise provides process engineers and process engineering students with access to a modern and stimulating methodology to process and product design. Throughout the book the links between product design and process design become evident while the reader is guided step-by-step through the different stages of the intertwining product and process design activities. Both molecular and enterprise-wide considerations in design are introduced and addressed in detail. Several examples and case studies in emerging areas such as bio- and food-systems, pharmaceuticals and energy are discussed and presented. This book is an excellent guide and companion for undergraduate, graduate students as well as professional practitioners.

Download or read book 13th International Symposium on Process Systems Engineering PSE 2018 July 1 5 2018 written by Mario R. Eden and published by Elsevier. This book was released on 2018-07-19 with total page 2620 pages. Available in PDF, EPUB and Kindle. Book excerpt: Process Systems Engineering brings together the international community of researchers and engineers interested in computing-based methods in process engineering. This conference highlights the contributions of the PSE community towards the sustainability of modern society and is based on the 13th International Symposium on Process Systems Engineering PSE 2018 event held San Diego, CA, July 1-5 2018. The book contains contributions from academia and industry, establishing the core products of PSE, defining the new and changing scope of our results, and future challenges. Plenary and keynote lectures discuss real-world challenges (globalization, energy, environment and health) and contribute to discussions on the widening scope of PSE versus the consolidation of the core topics of PSE. - Highlights how the Process Systems Engineering community contributes to the sustainability of modern society - Establishes the core products of Process Systems Engineering - Defines the future challenges of Process Systems Engineering

Download or read book 12th International Symposium on Process Systems Engineering and 25th European Symposium on Computer Aided Process Engineering written by and published by Elsevier. This book was released on 2015-07-14 with total page 2667 pages. Available in PDF, EPUB and Kindle. Book excerpt: 25th European Symposium on Computer-Aided Process Engineering contains the papers presented at the 12th Process Systems Engineering (PSE) and 25th European Society of Computer Aided Process Engineering (ESCAPE) Joint Event held in Copenhagen, Denmark, 31 May - 4 June 2015. The purpose of these series is to bring together the international community of researchers and engineers who are interested in computing-based methods in process engineering. This conference highlights the contributions of the PSE/CAPE community towards the sustainability of modern society. Contributors from academia and industry establish the core products of PSE/CAPE, define the new and changing scope of our results, and future challenges. Plenary and keynote lectures discuss real-world challenges (globalization, energy, environment, and health) and contribute to discussions on the widening scope of PSE/CAPE versus the consolidation of the core topics of PSE/CAPE. - Highlights how the Process Systems Engineering/Computer-Aided Process Engineering community contributes to the sustainability of modern society - Presents findings and discussions from both the 12th Process Systems Engineering (PSE) and 25th European Society of Computer-Aided Process Engineering (ESCAPE) Events - Establishes the core products of Process Systems Engineering/Computer Aided Process Engineering - Defines the future challenges of the Process Systems Engineering/Computer Aided Process Engineering community

Download or read book European Symposium on Computer Aided Process Engineering 11 written by R. Gani and published by Elsevier. This book was released on 2001-04-30 with total page 1205 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book contains papers presented at the 11th Symposium of Computer Aided Process Engineering (ESCAPE-11), held in Kolding, Denmark, from May 27-30, 2001. The objective of ESCAPE-11 is to highlight the use of computers and information technology tools, that is, the traditional CAPE topics as well as the new CAPE topics of current and future interests.The main theme for ESCAPE-11 is process and tools integration with emphasis on hybrid processing, cleaner and efficient technologies (process integration), computer aided systems for modelling, design, synthesis, control (tools integration) and industrial case studies (application of integrated strategies). The papers are arranged in terms of the following themes: computer aided control/operations, computer aided manufacturing, process and tools integration, and new frontiers in CAPE. A total of 188 papers, consisting of 5 keynote and 183 contributed papers are included in this book.

Download or read book FOCAPD 19 Proceedings of the 9th International Conference on Foundations of Computer Aided Process Design July 14 18 2019 written by Salvador Garcia Munoz and published by Elsevier. This book was released on 2019-07-09 with total page 514 pages. Available in PDF, EPUB and Kindle. Book excerpt: FOCAPD-19/Proceedings of the 9th International Conference on Foundations of Computer-Aided Process Design, July 14 - 18, 2019, compiles the presentations given at the Ninth International Conference on Foundations of Computer-Aided Process Design, FOCAPD-2019. It highlights the meetings held at this event that brings together researchers, educators and practitioners to identify new challenges and opportunities for process and product design. - Combines presentations from the Ninth International Conference on Foundations of Computer-Aided Process Design, FOCAPD-2019

Download or read book Uncertainty aware Integration of Control with Process Operations and Multi parametric Programming Under Global Uncertainty written by Vassilis M. Charitopoulos and published by Springer Nature. This book was released on 2020-02-05 with total page 285 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book introduces models and methodologies that can be employed towards making the Industry 4.0 vision a reality within the process industries, and at the same time investigates the impact of uncertainties in such highly integrated settings. Advances in computing power along with the widespread availability of data have led process industries to consider a new paradigm for automated and more efficient operations. The book presents a theoretically proven optimal solution to multi-parametric linear and mixed-integer linear programs and efficient solutions to problems such as process scheduling and design under global uncertainty. It also proposes a systematic framework for the uncertainty-aware integration of planning, scheduling and control, based on the judicious coupling of reactive and proactive methods. Using these developments, the book demonstrates how the integration of different decision-making layers and their simultaneous optimisation can enhance industrial process operations and their economic resilience in the face of uncertainty.

Download or read book Integration of Design and Control Under Uncertainty written by Siddharth Mehta and published by . This book was released on 2016 with total page 94 pages. Available in PDF, EPUB and Kindle. Book excerpt: Chemical process design is still an active area of research since it largely determines the optimal and safe operation of a new process under various conditions. The design process involves a series of steps that aims to identify the most economically attractive design typically using steady-state optimization. However, optimal steady-state designs may fail to comply with the process constraints when the system under analysis is subject to process disturbances (e.g. the composition of a reactant in a feed stream) or parameter uncertainty (e.g. the activation energy in a chemical reaction). Moreover, the practice of overdesigning a process to ensure feasibility under process disturbances and parameter uncertainty has been proven to be costly. Therefore, a new methodology for simultaneous design and control for dynamic systems under uncertainty has been proposed. The proposed methodology uses Power Series Expansions (PSE) to obtain analytical expressions for the process constrains and cost function. The key idea is to use the back off approach from the optimal steady state design to address the simultaneous process and design problem in an efficient systematic manner using PSE approximations. The challenge in this method is to determine the magnitude of the back-off needed to accommodate the transient and feasible operation of the process in presence of disturbances and parameter uncertainty. In this approach, PSE functions are used to obtain analytical expressions of the actual process constraints and are explicitly defined in terms of system's uncertain parameter and the largest variability in a constraint function due to time-varying changes in the disturbances. Also, the PSE approximation for each constraint is developed around a nominal point in the optimization variables and for each realization considered for the uncertain parameters. The PSE-based constraint represents the actual process constraint and can be evaluated faster since it is explicitly defined in the terms of the optimization variables. The work focuses on calculating various optimal design and control parameters by solving various sets of optimization problems using mathematical expressions obtained from power series expansions. These approximations are used to determine the direction in the search of optimal design parameters and operating conditions required for an economically attractive, dynamically feasible process. The proposed methodology was tested on an isothermal storage tank and a step by step procedure to develop the methodology has been presented. The methodology was also tested on a non-isothermal CSTR and the results were compared with the formal integration process. Effect of tuning parameter, which is a key parameter in the methodology, have been studied and the results show that the quality of the results improves when smaller values of tuning parameter are used but at the expense of higher computational costs. The effect of the order of the PSE approximation used in the calculations has also been studied and it shows that the quality in the results is improved when higher orders in the PSE approximations are used at the expense of higher computational costs. The methodology was also tested on a large-scale Waste Water treatment plant. A comparison was made for different values of tuning parameters and the most feasible value was chosen for the case study. Effects of different disturbances profiles such as step and ramp changes were also studied. The studies concluded that a lower cost value is obtained when ramps are used as disturbance profile when compared with step changes. The methodology was also tested when parameter uncertainty was introduced and the results show a higher cost is required when uncertainty is present in the system when compared with no uncertainty. The results show that this method has the potential to address the integration of design and control of dynamic systems under uncertainty at low computational costs.