PPT-Understandable Optimal Control and Cooling Optomechanical Systems

Shai Machnes Ulm University Safed 92012 Why does this work or sometimes doesnt The Model System a optical cavity modes Laser driving b mech modes Cavity is inherently dissipative . New York Chichester Brisbane Toronto brPage 3br Copyright 0 1972 by Jom Wiley Sons Inc All rights reserved Published simultaneously in Canada Reproduclion or translation of any part of this work beyond that permitted by Sections 107 or 108 of the of double integrating processes. Chriss Grimholt* and Sigurd Skogestad. *Present . affiliation. : ABB, . Olso. Double integrators: . Outline. They. . are. . common. They. . are. . difficult. to . AND . OPTIMISATION OF A DUAL CIRCUIT INDUCED DRAFT COOLING WATER SYSTEM. February 2016. C.J. . Muller. Sasol. ;. University . of . Pretoria. Under supervision of:. Prof. I.K. . Craig . University . Dr Rob Lamb . FInstR. CEng. Group Sales & Marketing Director. Overview. Reducing cooling requirement. Component selection. Changing temperature. Measurement and analysis. Some Numbers. 80%. 10%. Dr. Imtiaz Hussain. email: . imtiaz.hussain@faculty.muet.edu.pk. URL :. http://imtiazhussainkalwar.weebly.com/. Lecture-41-42. Design of Control Systems in Sate Space. Quadratic Optimal Control. Outline. 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. OBJECTIVES. Investigate the effects of unreliable communication network (e.g. TCP) on the stability of the NCS with unknown dynamics. Develop an adaptive observer (AO) to estimate networked control system (NCS) states; . CS 659. Kris Hauser. Control Theory. The use of . feedback. to regulate a signal. Controller. Plant. Desired signal x. d. Signal x. Control input u. Error e = x-x. d. (By convention, x. d. = 0). x’ = f(x,u). 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, Motivation and IntroductionHow to employ data for optimal control? Plant DisturbanceInputController CostsConstraints State •Model-Free RL simultaneously parameterize -Poor data efficiency-Dynamic Voltage Dehumidi�cation Rated Power Humidi�cation Rated Power Refrigerant Round Inlet & Outlet Weight kg HEDE Series From the Manufacturer of Hi-Velocity Systems www.hi-velocity. A PRIORI BOUNDS ON THE PERFORMANCE OFOPTIMAL SYSTEMSbyROBERTO CANALES RUIZIE Universidad de los Andes1963BS Massachusetts Institute of Technology1963MS Massachusetts Institute of Technology1965SUBMITT May 2020 – PNNL-SA-153210. Prepared by Pacific Northwest National Laboratory for the . U.S. Department of Energy. PNNL and DOE would like to thank ASHRAE Standing Standard Project Committee 90.1 for their contributions to the development of this presentation and their technical review of the content.. Identification . of . Dynamic Models . of . Biosystems. Julio R. . Banga. IIM-CSIC, Vigo, . Spain. julio@iim.csic.es. CUNY-Courant Seminar in Symbolic-Numeric Computing. CUNY . Graduate. . Center. , Friday, .