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.
S. N. Balakrishnan et al., "Issues on Stability of ADP Feedback Controllers for Dynamical Systems," IEEE Transactions onSystems, Man, and Cybernetics, Part B, Institute of Electrical and Electronics Engineers (IEEE), Aug 2008.
The definitive version is available at https://doi.org/10.1109/TSMCB.2008.926599
Mechanical and Aerospace Engineering
United States. Army Research Office
National Science Foundation (U.S.)
Keywords and Phrases
Adaptive Control; Closed Loop Systems; Dynamic Programming; Feedback; Neurocontrollers; Stability
Article - Journal
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