Real-Time PDE-Constrained Optimization

Real-Time PDE-Constrained Optimization

Author: Lorenz T. Biegler

Publisher: SIAM

Published: 2007-07-12

Total Pages: 322

ISBN-13: 0898716217

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“…a timely contribution to a field of growing importance. This carefully edited book presents a rich collection of chapters ranging from mathematical methodology to emerging applications. I recommend it to students as a rigorous and comprehensive presentation of simulation-based optimization and to researchers as an overview of recent advances and challenges in the field.” — Jorge Nocedal, Professor, Northwestern University.Many engineering and scientific problems in design, control, and parameter estimation can be formulated as optimization problems that are governed by partial differential equations (PDEs). The complexities of the PDEs—and the requirement for rapid solution—pose significant difficulties. A particularly challenging class of PDE-constrained optimization problems is characterized by the need for real-time solution, i.e., in time scales that are sufficiently rapid to support simulation-based decision making. Real-Time PDE-Constrained Optimization, the first book devoted to real-time optimization for systems governed by PDEs, focuses on new formulations, methods, and algorithms needed to facilitate real-time, PDE-constrained optimization. In addition to presenting state-of-the-art algorithms and formulations, the text illustrates these algorithms with a diverse set of applications that includes problems in the areas of aerodynamics, biology, fluid dynamics, medicine, chemical processes, homeland security, and structural dynamics. Despite difficulties, there is a pressing need to capitalize on continuing advances in computing power to develop optimization methods that will replace simple rule-based decision making with optimized decisions based on complex PDE simulations. Audience The book is aimed at readers who have expertise in simulation and are interested in incorporating optimization into their simulations, who have expertise in numerical optimization and are interested in adapting optimization methods to the class of infinite-dimensional simulation problems, or who have worked in “offline” optimization contexts and are interested in moving to “online” optimization.Contents Preface; Part I: Concepts and Properties of Real-Time, Online Strategies. Chapter 1: Constrained Optimal Feedback Control of Systems Governed by Large Differential Algebraic Equations; Chapter 2: A Stabilizing Real-Time Implementation of Nonlinear Model Predictive Control; Chapter 3: Numerical Feedback Controller Design for PDE Systems Using Model Reduction: Techniques and Case Studies; Chapter 4: Least-Squares Finite Element Method for Optimization and Control Problems; Part II: Fast PDE-Constrained Optimization Solvers. Chapter 5: Space-Time Multigrid Methods for Solving Unsteady Optimal Control Problems; Chapter 6: A Time-Parallel Implicit Methodology for the Near-Real-Time Solution of Systems of Linear Oscillators; Chapter 7: Generalized SQP Methods with “Parareal” Time-Domain Decomposition for Time-Dependent PDE-Constrained Optimization; Chapter 8: Simultaneous Pseudo-Timestepping for State-Constrained Optimization Problems in Aerodynamics; Chapter 9: Digital Filter Stepsize Control in DASPK and Its Effect on Control Optimization Performance; Part III: Reduced Order Modeling. Chapter 10: Certified Rapid Solution of Partial Differential Equations for Real-Time Parameter Estimation and Optimization; Chapter 11: Model Reduction for Large-Scale Applications in Computational Fluid Dynamics; Chapter 12: Suboptimal Feedback Control of Flow Separation by POD Model Reduction; Part IV: Applications. Chapter 13: A Combined Shape-Newton and Topology Optimization Technique in Real-Time Image Segmentation; Chapter 14: COFIR: Coarse and Fine Image Registration; Chapter 15: Real-Time, Large Scale Optimization of Water Network Systems Using a Sub-domain Approach; Index.


New Optimization Techniques in Engineering

New Optimization Techniques in Engineering

Author: Godfrey C. Onwubolu

Publisher: Springer

Published: 2013-03-14

Total Pages: 716

ISBN-13: 3540399305

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Presently, general-purpose optimization techniques such as Simulated Annealing, and Genetic Algorithms, have become standard optimization techniques. Concerted research efforts have been made recently in order to invent novel optimization techniques for solving real life problems, which have the attributes of memory update and population-based search solutions. The book describes a variety of these novel optimization techniques which in most cases outperform the standard optimization techniques in many application areas. New Optimization Techniques in Engineering reports applications and results of the novel optimization techniques considering a multitude of practical problems in the different engineering disciplines – presenting both the background of the subject area and the techniques for solving the problems.


Monocular Pose and Shape Estimation of Moving Targets, for Autonomous Rendezvous and Docking

Monocular Pose and Shape Estimation of Moving Targets, for Autonomous Rendezvous and Docking

Author: Sean Augenstein

Publisher: Stanford University

Published: 2011

Total Pages: 125

ISBN-13:

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This thesis describes the design and implementation of an algorithm for tracking a moving (e.g., `tumbling') target. No a priori information about the target is assumed, and only a single camera is used. The motivation is to enable autonomous rendezvous, inspection, and docking by robots in remote environments, such as space and underwater. Tracking refers to the simultaneous estimation of both the target's 6DOF pose and 3D shape (in the form of a point cloud of recognizable features), a problem of the SLAM (`Simultaneous Localization and Mapping') and SFM (`Structure from Motion') research fields. This research extends SLAM/SFM to deal with non-communicative moving targets (rigid bodies) with unknown, arbitrary 6DOF motion and no a priori knowledge of mass properties, dynamics, shape, or appearance. Specifically, a hybrid algorithm for real-time frame-to-frame pose estimation and shape reconstruction is presented. The algorithm combines concepts from two existing approaches to pose tracking, Bayesian estimation methods and nonlinear optimization techniques, to achieve a real-time capable, feasible, smooth estimate of the relative pose between a robotic platform and a moving target. The rationale for a hybrid approach is explained, and an algorithm is presented. A specific implementation using a modified Rao-Blackwellized particle filter is described and tested. Field demonstrations were performed in conjunction with the Monterey Bay Aquarium Research Institute, using the camera-equipped Remotely Operated Vehicle (ROV) Ventana to observe, reconstruct, and track the pose of an underwater tethered target in Monterey Bay. Results are included which demonstrate the performance and viability of the hybrid approach.