PPT-Constrained Near-Optimal Control Using a Numerical Kinetic Solver

Alan L Jennings amp Ra úl Ordóñez ajennings1 raulordoneznotesudaytonedu Electrical and Computer Engineering University of Dayton Frederick G Harmon frederickharmonafitedu. Bi kh Bh tt ac arya Professor Department of Mechanical Engineering IIT Kanpur Joint Initiative of IITs and IISc Funded by MHRD brPage 2br NPTEL Mechanical Engineering Modeling and Control of Dynamic electroMechanical System Module 4 Lecture 33 Jo Pieter . Abbeel. UC Berkeley EECS. Many slides and figures adapted from Stephen Boyd. [. optional] Boyd and . Vandenberghe. , Convex Optimization, Chapters 9 . – . 11. [. optional] Betts, Practical Methods for Optimal Control Using Nonlinear Programming. and . Exothermic/Endothermic Reactions. Kinetic Theory. Kinetic Theory . - . A theory concerning the thermodynamic behavior of matter, especially the relationships among pressure, volume, and temperature in gases. . Pg. 171 - 176. Kinetic Energy. Recall:. A moving object has the ability to do work because it can apply a force to another object and displace it. The energy possessed by moving objects is called . kinetic energy (. What is Energy? . . The ability to do ______. Two Types of Energy. . ___________ . Energy. . ___________. Energy. work. Potential. Kinetic. What is Potential Energy?. __________________. : the . GGCM Modeling (MHD Backbone). Jodie Barker Ream. UCLA, ESS. June 16, 2013. Magnetohydrodynamics (MHD). ‘Derivation’. Equations. Resistivity. General info on MHD modeling. Representative Global MHD Models. Dr. Ron Lembke. Formulating in Excel. Write the LP out on paper, with all constraints and the objective function.. Decide on cells to represent variables.. Enter coefficients of each variable in each constraint in a block of cells.. 442. Fall 2015. Kris Hauser. Toy Nonlinear Systems. Cart-pole. Acrobot. Mountain car. Optimal Control. So far in our discussion, we have not explicitly defined the criterion for determining a “good” control. Introduction. In this chapter, we show how many complex problems can be modeled using . 0–1 variables and . other variables that are constrained to have integer values. . A . 0–1 variable . is a . PowerPoint Presentation by. Peggy Batchelor, Furman University. Learning Objectives. Recognize decision-making situations which that may benefit from an optimization modeling approach.. Formulate algebraic models for linear programming problems.. Andrew B. . Kahng. and . Siddhartha . Nath. VLSI CAD LABORATORY, UC San Diego. Outline. Motivation. Previous Work. Our Work. Problem Formulation. Optimal (Discretized) Solution Flow. Results. Conclusions. A Brown Bag discussion for N-81. 26 Sept 2012. THIS PRESENTATION IS UNCLASSIFIED. Purpose. This Talk promises to:. (re)introduce some powerful tools in Excel. Optimization – centric functions. Goal seek. Optimal Control of Flow and Sediment in River and Watershed National Center for Computational Hydroscience and Engineering (NCCHE) The University of Mississippi Presented in 35th IAHR World Congress, September 8-13,2013, Chengdu, Hyun-. Gyu. Kang. 1. , Katherine J. Evans. 1. , Philip W. Jones. 2. , Mark R. Petersen. 2. ,. Andrew G. Salinger. 3. , and Raymond S. Tuminaro. 4. 1. Oak Ridge National Laboratory. 2. Los Alamos National Laboratory.