A Novel Method of Robust Trajectory Linearization Control Based on Disturbance Rejection | Zendy

Xingling Shao | Zendy; Honglun Wang | Zendy

AI Assistant Blog Pricing

Home ZAIA Blog

Open Access

A Novel Method of Robust Trajectory Linearization Control Based on Disturbance Rejection

Author(s) -

Xingling Shao,

Honglun Wang

Publication year - 2014

Publication title -

mathematical problems in engineering

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.262

H-Index - 62

eISSN - 1026-7077

pISSN - 1024-123X

DOI - 10.1155/2014/129247

Subject(s) - control theory (sociology) , feedback linearization , trajectory , tracking error , linearization , active disturbance rejection control , state observer , nonlinear system , controller (irrigation) , stability (learning theory) , mathematics , tracking (education) , state vector , computer science , control engineering , control (management) , engineering , artificial intelligence , psychology , pedagogy , physics , classical mechanics , astronomy , quantum mechanics , machine learning , agronomy , biology

A novel method of robust trajectory linearization control for a class of nonlinear systems with uncertainties based on disturbance rejection is proposed. Firstly, on the basis of trajectory linearization control (TLC) method, a feedback linearization based control law is designed to transform the original tracking error dynamics to the canonical integral-chain form. To address the issue of reducing the influence made by uncertainties, with tracking error as input, linear extended state observer (LESO) is constructed to estimate the tracking error vector, as well as the uncertainties in an integrated manner. Meanwhile, the boundedness of the estimated error is investigated by theoretical analysis. In addition, decoupled controller (which has the characteristic of well-tuning and simple form) based on LESO is synthesized to realize the output tracking for closed-loop system. The closed-loop stability of the system under the proposed LESO-based control structure is established. Also, simulation results are presented to illustrate the effectiveness of the control strategy

The content you want is available to Zendy users.

Already have an account? Click here to sign in.

Having issues? You can contact us here

Accelerating Research