Abstract

This paper traces the development of neural-network (NN)-based feedback controllers that are derived from the principle of adaptive/approximate dynamic programming (ADP) and discusses their closed-loop stability. Different versions of NN structures in the literature, which embed mathematical mappings related to solutions of the ADP-formulated problems called “adaptive critics” or “action-critic” networks, are discussed. Distinction between the two classes of ADP applications is pointed out. Furthermore, papers in “model-free” development and model-based neurocontrollers are reviewed in terms of their contributions to stability issues. Recent literature suggests that work in ADP-based feedback controllers with assured stability is growing in diverse forms.

Department(s)

Mechanical and Aerospace Engineering

Sponsor(s)

United States. Army Research Office
National Science Foundation (U.S.)

Keywords and Phrases

Adaptive Control; Closed Loop Systems; Dynamic Programming; Feedback; Neurocontrollers; Stability

Document Type

Article - Journal

Document Version

Final Version

File Type

text

Language(s)

English

Rights

© 2008 Institute of Electrical and Electronics Engineers (IEEE), All rights reserved.

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