PPT-Optimal PID control

of double integrating processes Chriss Grimholt and Sigurd Skogestad Present affiliation ABB Olso Double integrators Outline They are common They are difficult to . 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 Benjamin Stephens. Robotics Institute. Compliant Balance and Push Recovery. Full body compliant control. Robustness to large disturbances. Perform useful tasks in human environments. Motivation. Improve the performance and usefulness of complex robots, simplifying controller design by focusing on simpler models that capture important features of the desired behavior. control and pricing. Desmond . Cai. Caltech (CS). . John Ledyard Caltech (. Ec. ). . Steven Low Caltech (CS and EE). With a lot of help from others at . Caltech . and Southern California Edison. Benjamin Stephens. Robotics Institute. Compliant Balance and Push Recovery. Full body compliant control. Robustness to large disturbances. Perform useful tasks in human environments. Motivation. Improve the performance and usefulness of complex robots, simplifying controller design by focusing on simpler models that capture important features of the desired behavior. Spring 2012. Optimal Control. Static optimization (finite dimensions). Calculus of variations (infinite dimensions). Maximum principle (. Pontryagin. ) / minimum principle. Based on state space models. 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. Sina Dehghan. , PhD student in ME. MESA. (Mechatronics, Embedded Systems and Automation) . LAB. University of California, Merced. E: sdehghan@ucmerced.edu . Under supervision of:. YangQuan Chen . . 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; . 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, Alan L. Jennings & Ra. úl Ordóñez, . ajennings1. , . raul.ordonez@notes.udayton.edu. Electrical and Computer Engineering, University of Dayton. Frederick G. Harmon, . frederick.harmon@afit.edu. Motivation and IntroductionHow to employ data for optimal control? Plant DisturbanceInputController CostsConstraints State •Model-Free RL simultaneously parameterize -Poor data efficiency-Dynamic 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, . Paula A. Gonzalez-Parra. 1. Leticia Velazquez. 1,2. Sunmi Lee. 3. Carlos Castillo-Chavez. 3. 1. Program in Computational Science, University of Texas at El Paso. 2 . Department in Mathematical Sciences, University of Texas at El Paso.