Adaptive Neural Network Finite-Time Output Feedback Control of Quantized Nonlinear Systems

• Published in: IEEE transactions on cybernetics Vol. 48; no. 6; pp. 1839 - 1848
• Main Authors: Wang, Fang, Chen, Bing, Lin, Chong, Zhang, Jing, Meng, Xinzhu
• Format: Journal Article
• Language: English
• Published: United States IEEE 01.06.2018; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Adaptive control; Adaptive neural control; Adaptive systems; Artificial neural networks; Feedback control; finite-time; Neural networks; Nonlinear control; Nonlinear systems; Output feedback; Process controls; quantized nonlinear systems; Stability analysis; Stability criteria; State observers
• ISSN: 2168-2267; 2168-2275; 2168-2275
• DOI: 10.1109/TCYB.2017.2715980

This paper addresses the finite-time tracking issue for nonlinear quantized systems with unmeasurable states. Compared with the existing researches, the finite-time quantized feedback control is considered for the first time. By proposing a new finite-time stability criterion and designing a state observer, a novel adaptive neural output-feedback control strategy is raised by backstepping technique. Under the presented control scheme, the finite-time quantized feedback control problem is coped with without limiting assumption for nonlinear functions.