ePrints@IIScePrints@IISc Home | About | Browse | Latest Additions | Advanced Search | Contact | Help

A single network adaptive critic (SNAC) architecture for optimal control synthesis for a class of nonlinear systems

Padhi, Radhakant and Unnikrishnan, Nishant and Wang, Xiaohua and Balakrishnan, SN (2006) A single network adaptive critic (SNAC) architecture for optimal control synthesis for a class of nonlinear systems. In: Neural Networks, 19 (10). pp. 1648-1660.

[img] PDF
A_single_network_adaptive_critic_(SNAC)_architecture.pdf
Restricted to Registered users only

Download (1MB) | Request a copy

Abstract

Even though dynamic programming offers an optimal control solution in a state feedback form, the method is overwhelmed by computational and storage requirements. Approximate dynamic programming implemented with an Adaptive Critic (AC) neural network structure has evolved as a powerful alternative technique that obviates the need for excessive computations and storage requirements in solving optimal control problems. In this paper, an improvement to the AC architecture, called the Single Network Adaptive Critic (SNAC) is presented. This approach is applicable to a wide class of nonlinear systems where the optimal control (stationary) equation can be explicitly expressed in terms of the state and costate variables. The selection of this terminology is guided by the fact that it eliminates the use of one neural network (namely the action network) that is part of a typical dual network AC setup. As a consequence, the SNAC architecture offers three potential advantages: a simpler architecture, lesser computational load and elimination of the approximation error associated with the eliminated network. In order to demonstrate these benefits and the control synthesis technique using SNAC, two problems have been solved with the AC and SNAC approaches and their computational performances are compared. One of these problems is a real-life Micro-Electro-Mechanical-system (MEMS) problem, which demonstrates that the SNAC technique is applicable to complex engineering systems.

Item Type: Journal Article
Publication: Neural Networks
Publisher: Elsevier
Additional Information: Copyright of this article belongs to Elsevier
Keywords: Optimal control; Nonlinear control; Approximate dynamic programming; Adaptive critic; Single network adaptive critic; SNAC architecture
Department/Centre: Division of Mechanical Sciences > Aerospace Engineering(Formerly Aeronautical Engineering)
Date Deposited: 25 Aug 2008
Last Modified: 19 Sep 2010 04:34
URI: http://eprints.iisc.ac.in/id/eprint/9707

Actions (login required)

View Item View Item