title: Analysis of artificial neural networks for pattern-based adaptive control.
abstract: Adaptive pattern-based control strategies adapt their parameters from an analysis of response patterns exhibited by the system. This work presents an analysis of a class of artificial neural network (ANN) pattern-based adaptive control. It provides conditions under which the adaptive algorithm will converge, and it also characterizes the closed-loop stability properties. In addition, a method for monitoring the adaptation is also proposed. Several simulation examples illustrate our findings.
authors.affiliation: Department of Electrical Engineering, Universidad de Concepción, Concepción 4089100, Chile. daniel.sbarbaro@udec.cl
authors.forename: Daniel
authors.initials: D
authors.lastname: Sbarbaro
authors.forename: Tor A
authors.initials: TA
authors.lastname: Johansen
mesh_terms: D000465:Algorithms; D001185:Artificial Intelligence; D016000:Cluster Analysis; D003198:Computer Simulation; D003205:Computing Methodologies; D005246:Feedback; D008962:Models, Theoretical; D016571:Neural Networks, Computer; D010363:Pattern Recognition, Automated / Q000379:methods*