title: Issues on stability of ADP feedback controllers for dynamical systems.
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.
authors.affiliation: Department of Mechanical and Aerospace Engineering, Missouri University of Science and Technology, Rolla, MO 65401, USA. bala@mst.edu
authors.forename: S N
authors.initials: SN
authors.lastname: Balakrishnan
authors.forename: Jie
authors.initials: J
authors.lastname: Ding
authors.forename: Frank L
authors.initials: FL
authors.lastname: Lewis
mesh_terms: D003198:Computer Simulation; D005246:Feedback; D008962:Models, Theoretical; D016571:Neural Networks, Computer; D017711:Nonlinear Dynamics; D011382:Programming, Linear; D013598:Systems Theory