Tag: Optimal

Free Download Optimization and Optimal Control in a Nutshell
English | 2024 | ISBN: 9819781663 | 144 Pages | PDF EPUB (True) | 28 MB
This book concisely presents the optimization process and optimal control process with examples and simulations to help self-learning and better comprehension. It starts with function optimization and constraint inclusion and then extends to functional optimization using the calculus of variations. The development of optimal controls for continuous-time, linear, open-loop systems is presented using Lagrangian and Pontryagin-Hamiltonian methods, showing how to introduce the end-point conditions in time and state. The closed-loop optimal control for linear systems with a quadratic cost function, well-known as the linear quadratic regulator (LQR) is developed for both time-bound and time-unbounded conditions. Some control systems need to maximize performance alongside cost minimization. The Pontryagin’s maximum principle is presented in this regard with clear examples that show the practical implementation of it. It is shown through examples how the maximum principle leads to control switching and Bang-Bang control in certain types of systems. The application of optimal controls in discrete-time open-loop systems with the quadratic cost is presented and then extended to the closed-loop control, which results in the model predictive control (MPC). Throughout the book, examples and Matlab simulation codes are provided for the learner to practice the contents in each section. The aligned lineup of content helps the learner develop knowledge and skills in optimal control gradually and quickly.

Free Download Optimal Control Theory for Infinite Dimensional Systems By Xunjing Li, Jiongmin Yong (auth.)
1995 | 450 Pages | ISBN: 146128712X | PDF | 10 MB
Infinite dimensional systems can be used to describe many phenomena in the real world. As is well known, heat conduction, properties of elastic plastic material, fluid dynamics, diffusion-reaction processes, etc., all lie within this area. The object that we are studying (temperature, displace ment, concentration, velocity, etc.) is usually referred to as the state. We are interested in the case where the state satisfies proper differential equa tions that are derived from certain physical laws, such as Newton’s law, Fourier’s law etc. The space in which the state exists is called the state space, and the equation that the state satisfies is called the state equation. By an infinite dimensional system we mean one whose corresponding state space is infinite dimensional. In particular, we are interested in the case where the state equation is one of the following types: partial differential equation, functional differential equation, integro-differential equation, or abstract evolution equation. The case in which the state equation is being a stochastic differential equation is also an infinite dimensional problem, but we will not discuss such a case in this book.

Free Download Probabilistic Forecasts and Optimal Decisions
English | 2025 | ISBN: 139422186X | 540 Pages | PDF, EPUB (True) | 43 MB
Decision theory is a body of thought and research seeking to apply a mathematical-logical framework to assessing probability and optimizing decision-making. It has developed robust tools for addressing all major challenges to decision making. Yet the number of variables and uncertainties affecting each decision outcome, many of them beyond the decider’s control, mean that decision-making is far from a ‘solved problem’. The tools created by decision theory remain to be refined and applied to decisions in which uncertainties are prominent.

Free Download Optimal Design and Control: Proceedings of the Workshop on Optimal Design and Control Blacksburg, Virginia April 8-9, 1994 By Natalia Alexandrov, J. E. Dennis Jr. (auth.), Jeffrey Borggaard, John Burkardt, Max Gunzburger, Janet Peterson (eds.)
1995 | 288 Pages | ISBN: 1461269164 | PDF | 7 MB
This volume is the proceedings of the Workshop on Optimal Design and Control that was held in Blacksburg, Virginia, April 8-9, 1994. The workshop was spon sored by the Air Force Office of Scientific Research through the Air Force Center for Optimal Design and Control (CODAC) at Virginia Tech. The workshop was a gathering of engineers and mathematicians actively in volved in innovative research in control and optimization, with emphasis placed on problems governed by partial differential equations. The interdisciplinary nature of the workshop and the wide range of subdisciplines represented by the partici pants enabled an exchange of valuable information and also led to significant dis cussions about multidisciplinary optimization issues. One of the goals of the work shop was to include laboratory, industrial, and academic researchers so that anal yses, algorithms, implementations, and applications could all be well-represented in the talks; this interdisciplinary nature is reflected in these proceedings. An overriding impression that can be gleaned from the papers in this volume is the complexity of problems addressed by not only those authors engaged in appli cations, but also by those engaged in algorithmic development and even mathemat ical analyses. Thus, in many instances, systematic approaches using fully nonlin ear constraint equations are routinely used to solve control and optimization prob lems, in some cases replacing ad-hoc or empirically based procedures.

Free Download Control and Optimal Design of Distributed Parameter Systems By Giovanni Crosta (auth.), John E. Lagnese, David L. Russell, Luther W. White (eds.)
1995 | 246 Pages | ISBN: 1461384621 | PDF | 7 MB
The articles in this volume focus on control theory of systems governed by nonlinear linear partial differential equations, identification and optimal design of such systems, and modelling of advanced materials. Optimal design of systems governed by PDEs is a relatively new area of study, now particularly relevant because of interest in optimization of fluid flow in domains of variable configuration, advanced and composite materials studies and "smart" materials which include possibilities for built in sensing and control actuation. The book will be of interest to both applied mathematicians and to engineers.

Free Download Lori A. Dalton, Edward R. Dougherty, "Optimal Bayesian Classification"
English | 2020 | pages: 360 | ISBN: 1510630694 | PDF | 4,2 mb
The most basic problem of engineering is the design of optimal operators. Design takes different forms depending on the random process constituting the scientific model and the operator class of interest. For classification, the random process is a feature-label distribution, and a Bayes classifier minimizes classification error. Rarely do we know the feature-label distribution or have sufficient data to estimate it. To best use available knowledge and data, this book takes a Bayesian approach to modeling the feature-label distribution and designs an optimal classifier relative to a posterior distribution governing an uncertainty class of feature-label distributions. The origins of this approach lie in estimating classifier error when there are insufficient data to hold out test data, in which case an optimal error estimate can be obtained relative to the uncertainty class. A natural next step is to forgo classical ad hoc classifier design and find an optimal classifier relative to the posterior distribution over the uncertainty class this being an optimal Bayesian classifier.

Free Download Optimal Web Server Setup on Kali Linux: Apache2, PHP 8.x, and MariaDB Installation Guide (Python: Stock Market data Analysis using AI Models and the Python Programming Language) by Richard Buchanan
English | June 17, 2024 | ISBN: N/A | ASIN: B0D7CC4CXG | 73 pages | EPUB | 0.50 Mb
Optimal Web Server Setup on Kali Linux: Apache2, PHP 8.x, and MariaDB Installation Guide

Free Download Fiscalization, Internal Control, and Optimal Tax Compliance by Uwem Essia
English | January 15, 2024 | ISBN: N/A | ASIN: B0CSGRNVSY | 134 pages | EPUB | 1.65 Mb
The book "Fiscalization, Internal Control, and Optimal Tax Compliance" is the fifth of the Series titled Public Finance, Fiscal Policy and Tax Management. It explores the strategic nexus of internal controls, tax compliance, fiscalization, and broader organizational objectives. Navigate the landscape of compliance risk management, where comprehensive strategies, data management, and long-term viability considerations converge. Uncover the strategic dimensions of taxpayer compliance enhancement, from understanding root causes to fostering trust. Embark on a journey through strategic frameworks, annual compliance programs, and effective evaluation methodologies. Conclude with a transformative exploration of electronic fiscal reporting, illuminating the role of technology in shaping tax compliance. A comprehensive guide empowering individuals and organizations on the path to optimal tax compliance excellence.

Free Download Marc S. Schulz, "Strengthening Couple Relationships for Optimal Child Development: Lessons from Research and Intervention"
English | ISBN: 1433805472 | 2009 | 244 pages | PDF | 12 MB
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Free Download Chaotic Meta-heuristic Algorithms for Optimal Design of Structures (Studies in Computational Intelligence, 1129) by Ali Kaveh, Hossein Yousefpoor
English | January 30, 2024 | ISBN: 3031489179 | 354 pages | MOBI | 38 Mb
In this book, various chaos maps are embedded in eleven efficient and well-known metaheuristics and a significant improvement in the optimization results is achieved. The two basic steps of metaheuristic algorithms consist of exploration and exploitation. The imbalance between these stages causes serious problems for metaheuristic algorithms, which are immature convergence and stopping in local optima. Chaos maps with chaotic jumps can save algorithms from being trapped in local optima and lead to convergence toward global optima. Embedding these maps in the exploration phase, exploitation phase, or both simultaneously corresponds to three efficient and useful scenarios. By creating competition between different modes and increasing diversity in the search space and creating sudden jumps in the search phase, improvements are achieved for chaotic algorithms. Four Chaotic Algorithms, including Chaotic Cyclical Parthenogenesis Algorithm, Chaotic Water Evaporation Optimization, Chaotic Tug-of-War Optimization, and Chaotic Thermal Exchange Optimization are developed.