Open AccessAdaptive tracking control for a class of stochastic non‐linear systems with input delay: a novel approach based on multi‐dimensional Taylor network
Author(s) -
Han YuQun
Publication year - 2020
Publication title -
iet control theory and applications
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.059
H-Index - 108
eISSN - 1751-8652
pISSN - 1751-8644
DOI - 10.1049/iet-cta.2020.0336
Subject(s) - backstepping , control theory (sociology) , controller (irrigation) , stability (learning theory) , adaptive control , lyapunov stability , nonlinear system , tracking (education) , computer science , lyapunov function , scheme (mathematics) , class (philosophy) , mathematics , control (management) , artificial intelligence , psychology , mathematical analysis , pedagogy , physics , quantum mechanics , machine learning , agronomy , biology
In this study, by means of the techniques of adaptive multi‐dimensional Taylor network (MTN) control, the tracking problem of a class of stochastic non‐linear systems with input delay is studied. Firstly, based on the Padé approximation method, a new variable is employed to overcome the problem of input delay, and MTNs are applied to estimate the non‐linear functions in the design of the controller. Secondly, an adaptive MTN controller design scheme is developed in the framework of backstepping. Thirdly, the stability of the closed‐loop system is analysed using Lyapunov's stability theory. Finally, the effectiveness of the proposed design approach is demonstrated by two examples.