Decentralized Output-Feedback Neural Control for Systems With Unknown Interconnections

• Published in: IEEE transactions on systems, man and cybernetics. Part B, Cybernetics Vol. 38; no. 1; pp. 258 - 266
• Main Authors: Chen, Weisheng, Li, Junmin
• Format: Journal Article
• Language: English
• Published: United States IEEE 01.02.2008
• Subjects: Adaptive control; Adaptive control systems; Algorithms; Backstepping; Centralized control; Computer Simulation; Control systems; Cybernetics; decentralized control; Distributed control; Feedback; Interconnections; Large-scale systems; Models, Statistical; Neural networks; Neural Networks (Computer); neural networks (NNs); Nonlinear control systems; Nonlinear Dynamics; Programmable control; Reference signals; Reproducibility of Results; Sensitivity and Specificity; Signal design; Tracking errors; Backstepping; decentralized control; neural networks (NNs); large-scale systems

An adaptive backstepping neural-network control approach is extended to a class of large-scale nonlinear output-feedback systems with completely unknown and mismatched interconnections. The novel contribution is to remove the common assumptions on interconnections such as matching condition, bounded...