Semi-global sampled-data output feedback disturbance rejection control for a class of uncertain nonlinear systems

ABSTRACT

This paper investigates the semi-global output feedback disturbance rejection control problem for a class of uncertain nonlinear systems with additive disturbances using linear sampled-data control. Aiming to reject the adverse effects caused by the uncertainties and unknown nonlinear perturbations which may not satisfy the strict feedback or feedforward structure, a new generalised discrete-time extended state observer is proposed to estimate the disturbance at sampling points. An output feedback disturbance rejection control law is then constructed in a sampled-data form which facilitates digital implementations. By selecting adequate control gains and a sufficiently small sampling period to restrain the state growth under a zero-order-hold input, the semi-global asymptotic stability of the hybrid closed-loop system and the disturbance rejection ability are proved. Both numerical example and an application of a single-link robot arm system demonstrate the feasibility and efficacy of the proposed method.

KEYWORDS:

• Robust control
• hybrid systems
• nonlinear systems
• disturbance attenuation control

Acknowledgments

The authors sincerely thank the editor and all anonymous reviewers for their valuable comments which helped improve the quality of this paper.

Disclosure statement

No potential conflict of interest was reported by the authors.

Additional information

Funding

This work is supported in part by Leading Talent Program of Shanghai, Sailing Program of Shanghai Science and Technology Commission [grant number 15YF1404500]; National Natural Science Foundation of China [grant number 61503236], [grant number 61473080], [grant number 61573099]; “Chenguang Program” supported by Shanghai Education Development Foundation and Shanghai Municipal Education Commission [grant number 15CG56]; Engineering Research Center of Shanghai Science and Technology Commission Program [grant number 14DZ2251100]; Natural Science Foundation of Jiangsu Province [grant number BK2012327], [grant number BK20130018].