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Network-based static output feedback tracking control for fuzzy-model-based nonlinear systems

conference contribution
posted on 06.12.2017, 00:00 by Dawei Zhang, Qing-Long Han, Xin-Chun Jia
This paper is concerned with network-based static output feedback tracking control for a class of nonlinear systems that can not be stabilized by a static output feedback controller without a time-delay, but can be stabilized by a delayed static output feedback controller. For such systems, network-induced delay is intentionally introduced in the feedback loop to produce a stable and satisfactory tracking control. The nonlinear network-based control system is represented by an asynchronous T-S fuzzy system with an interval time-varying sawtooth delay due to sample-and-hold behaviors and network-induced delays. A new discontinuous complete Lyapunov-Krasovskii functional, which makes use of the lower bound of network-induced delays, the sawtooth delay and its upper bound, is constructed to derive a delay-dependent criterion on H∞ tracking performance analysis. Since routine relaxation methods in traditional T-S fuzzy systems can not be employed to reduce the conservatism of the stability criterion, a new relaxation method is proposed by using asynchronous constraints on fuzzy membership functions to introduce some free-weighting matrices. Based on the feasibility of the derived criterion, a particle swarm optimization algorithm is presented to search the minimum H∞ tracking performance and static output feedback gains. An illustrative example is provided to show the effectiveness of the proposed method.

Funding

Category 1 - Australian Competitive Grants (this includes ARC, NHMRC)

History

Start Page

1

End Page

8

Number of Pages

8

Start Date

01/01/2012

Finish Date

01/01/2012

ISSN

1098-7584

ISBN-13

9781467315074

Location

Brisbane, Qld., Australia

Publisher

Institute of Electrical and Electronics Engineers Inc.

Place of Publication

Piscataway, NJ

Peer Reviewed

Yes

Open Access

No

External Author Affiliations

Centre for Intelligent and Networked Systems (CINS); Shanxi da xue; TBA Research Institute;

Era Eligible

Yes

Name of Conference

IEEE World Congress on Computational Intelligence;IEEE International Conference on Fuzzy Systems