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This paper gives a variety of theoretical results associated with the Adaptive Neural Control (ANC) architecture and its application to the control of flexible structures. ANC is a new parallel processing, decentralized architecture for identification and adaptive control that has been under development by the author and associates over the past five years. The ANC architecture consists of a hierarchy of standardized modules and rules for combining them. In this paper, we give a step-by-step description of the ANC components and present basic theorems on convergence and stability for applications involving both identification and adaptive control. (Author)

Connectionist algorithms for identification and control - System structure and convergence analysis