Decentralized adaptive tracking of interconnected non-affine systems with time delays and quantized inputs

• Published in: Neurocomputing (Amsterdam) Vol. 141; pp. 194 - 201
• Main Authors: Xiao, Xiao-Shi, Wu, Lianghong
• Format: Journal Article
• Language: English
• Published: Amsterdam Elsevier B.V 02.10.2014; Elsevier
• Subjects: Adaptive fuzzy control; Adaptive systems; Applied sciences; Artificial intelligence; Computer science; control theory; systems; Control system analysis; Control system synthesis; Control theory. Systems; Decentralized; Decentralized control; Differential scanning calorimetry; Dynamic surface control (DSC); Dynamical systems; Dynamics; Exact sciences and technology; Fuzzy; Fuzzy set theory; Minimal-learning-parameters (MLP); Non-affine systems; System theory; Time delay; Tracking; Adaptive fuzzy control; Non-affine systems; Time delay; Minimal-learning-parameters (MLP); Decentralized control; Dynamic surface control (DSC); Parameter estimation; Disturbance rejection; On line; Tracking; Adaptive algorithm; Lyapunov method; Feedback regulation; Adaptive control; Adaptive method; Dynamic method; Fuzzy control; Uncertain system; Fuzzy algorithm; Signal quantization; Set covering; Delay time; Non affine transform; Learning algorithm; Closed loop; Interconnected power system; Delay system; Neural network; Mean value; Backstepping control; Closed feedback; Low pass filter; Fuzzy number; Artificial intelligence; Lyapunov function; Multilayer network

The problem of decentralized adaptive tracking is investigated for a class of uncertain non-affine systems with time-delay interconnections, quantized inputs and external disturbances. By using mean value theorem, Lyapunov–Krasovskii functional method and dynamic surface control (DSC) technique alon...