PPT-Nonlinear Optimization for Optimal Control

Part 2 Pieter Abbeel UC Berkeley EECS TexPoint fonts used in EMF Read the TexPoint manual before you delete this box A A A A A A A A A A A A From linear to nonlinear Modelpredictive control MPC. . . . . N.D.Tantaroudas. . . K.J.Badcock,A.Da. . Ronch. University . Framework in . Py. . A. . Da. . Ronch. University of. L. iverpool. , . UK. Liverpool, . 16. March 2012. Target. . Nonlinear models . for flexible aircraft (hierarchy). Nonlinear . model reduction. 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. Optimal and Feasible Attitude Motions for Microspacecraft. January 2013. Albert Caubet. Astronet. School – Rome. Background. Universitat. . Politecnica. de . Catalunya. (UPC) – Aeronautical Engineering (specialization space vehicles). A. . Da . Ronch. , K. J. . Badcock. University of. . L. iverpool, Liverpool, U.K.. Y. Wang, A. Wynn, and R. Palacios. Imperial College, London, U.K.. AIAA Paper 2012-. 4404. Minneapolis, 13 August 2012. Approximate Algorithms. Alessandro Farinelli. Approximate Algorithms: outline. No guarantees. DSA-1, MGM-1 (exchange individual assignments). Max-Sum (exchange functions). Off-Line guarantees. K-optimality and extensions. An optimization problem is a problem in which we wish to determine the best values for decision variables that will maximize or minimize a performance measure subject to a set of constraints. A feasible solution is set of values for the decision variables which satisfy all of the constraints. 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. Introduction. In many complex optimization problems, the objective and/or the constraints are . nonlinear functions . of the decision variables. Such optimization problems are called . nonlinear programming . 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 many complex optimization problems, the objective and/or the constraints are . nonlinear functions . of the decision variables. Such optimization problems are called . nonlinear programming . . TPA Optimization. For . large, complex service organizations, . a . thoughtful approach to . assurance . can save time, money, and lead to more satisfied clients and . prospects. Understand. Integrate. 2DEVELOPMENT OF SHIP MANEUVERING CONTROL SYSTEMWITH ONLINE NONLINEAR OPTIMAL CONTROLINTRODUCTIONMOTIVATIONREVIEW OF THE OPTIMAL CONTROL PROBLEMOPTIMAL THRUST ALLOCATIONEXPERIMENTAL RESULTSROUTE TRACKI 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, .