Real‐Time Results for High Order Neural Identification and Block Control Transformation Form Using High Order Sliding Modes. Issue 6 (14th April 2015)

• Record Type: Journal Article
• Authors: Rodríguez, Sergio Alvarez; Castañeda Hdez, Carlos E.; Morfin G., Onofre A.; Jurado, Francisco; Prado, P. Esquivel
• Is Part Of: Asian journal of control. Volume 17:Issue 6(2015:Nov.)
• Page Start: 2435
• Page End: 2451
• Publication Date: 2015-04-14
• Subjects: High order neural networks, high order sliding modes, nonlinear block control, chattering‐effect; Automatic control -- Periodicals; Control theory -- Periodicals; 629.805
• DOI: 10.1002/asjc.1139
• Languages: English
• ISSNs: 1561-8625

Abstract

Abstract: In this paper, real‐time results for a novel continuous‐time adaptive tracking controller algorithm for nonlinear multiple input multiple output systems are presented. The control algorithm includes the combination of a recurrent high order neural network with block control transformation using a high order sliding modes technique as control law. A neural network is used to identify the dynamic plant behavior where a filtered error algorithm is used to train the neural identifier. A decentralized high order sliding mode, named the twisting algorithm, is used to design chattering‐reduced independent controllers to solve the trajectory tracking problem for a robot arm with three degrees of freedom. Stability analyses are given via a Lyapunov approach.