Please use this identifier to cite or link to this item: https://hdl.handle.net/20.500.12104/40701
Title: Discrete-time decentralized inverse optimal neural control for a shrimp robot
Author: Lopez-Franco, M.
Sanchez, E.N.
Alanis, A.Y.
Arana-Daniel, N.
Issue Date: 2013
Abstract: This paper deals with an decentralized inverse optimal neural controller for discrete-time unknown nonlinear systems, in presence of external disturbances and parameter uncertainties. It is based on two techniques: first, an identifier using a discrete-time recurrent high order neural network (RHONN), trained with an extended Kalman filter (EKF) algorithm; second, a controller which on the basis of inverse optimal control to avoid solving the Hamilton Jacobi Bellman (HJB) equation. Computer simulations are presented which illustrate the effectiveness of the proposed tracking control law. � 2013 AACC American Automatic Control Council.
URI: http://www.scopus.com/inward/record.url?eid=2-s2.0-84883533090&partnerID=40&md5=f5e9f153e87a1ad07f43b17201e84c2c
http://hdl.handle.net/20.500.12104/40701
Appears in Collections:Producción científica UdeG

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