Open AccessAdaptive multi‐dimensional Taylor network tracking control for SISO uncertain stochastic non‐linear systems
Author(s) -
Han YuQun,
Yan HongSen
Publication year - 2018
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.2017.0538
Subject(s) - control theory (sociology) , backstepping , computer science , controller (irrigation) , tracking error , randomness , bounded function , lyapunov function , adaptive control , stability (learning theory) , linear system , nonlinear system , mathematical optimization , mathematics , control (management) , artificial intelligence , mathematical analysis , statistics , physics , quantum mechanics , machine learning , agronomy , biology
In this study, the problem of adaptive multi‐dimensional Taylor network (MTN) control for single‐input single‐output (SISO) uncertain stochastic non‐linear systems is investigated. How to minimise the influence of randomness and uncertain non‐linearity for less complex computation, and how to improve the real‐time performance of the controller are of great significance. To this end, a control approach based on MTN is proposed for tracking control of stochastic non‐linear systems. MTNs are used to approximate the non‐linearities, and the backstepping technique is employed to construct the MTN controller (MTNC). MTNC involves only addition and multiplication, featuring desirable simplicity and real‐time performance. Stability of the system is guaranteed via Lyapunov approach, and it is proved that the proposed controller can guarantee that all signals of the closed‐loop system remain bounded in probability, and the tracking error converges to an arbitrarily small neighbourhood around the origin. Finally, a numerical example is given to illustrate the effectiveness of the proposed design approach, and simulation results demonstrate that the method presented in this study has good real‐time performance and control quality.