Conferencia Internacional: Adaptive Dynamic Programming : A New Tool for Intelligent Control

Professor, Ph.D Derong Liu

Institute of Automation, Chinese Academy of Sciences

University of Chicago

Abstract

Adaptive Dynamic Programming (ADP) has received increasing attention recently. ADP scheme is a design that approximates dynamic programming in the general case, i.e., approximates optimal control over time in noisy, nonlinear environments. There are many engineering problems in practice which can be formulated as cost maximization or minimization problems. Dynamic programming is a very useful tool in solving these problems. However, it is often computationally untenable to run dynamic programming due to the backward numerical process required for its solutions. Over the years, progress has been made to provide approximate solutions to dynamic programming. The idea is to approximate dynamic programming solutions by using neural networks to approximate the cost function. The methodology is a very useful tool for building intelligent agents/controllers in almost any environment. This talk will review the theoretical development of ADP. Details about the training of the neural networks used in the present design will also be presented. The pole balancing (inverted pendulum) problem will be used as the benchmark in this presentation to show the applicability of ADP.

Lunes 16 de Septiembre de 2013 – 18:00 hs

Auditorio CCT – CONICET – Universidad Nacional de Córdoba

Facultad de Ciencias Exactas, Físicas y Naturales
Av. Vélez Sarsfield 1611 – Ciudad Universitaria – Córdoba Capital

Más información en: http://site.ieee.org/argentina-cis/seminarios-de-divulgacion/