Modified State Observer based Two-Way ETNAC Design for Uncertain Linear Systems
In this study, a neural network (NN) based two-way event-triggered controller (ETC) design is presented for uncertain linear systems. Dynamic triggering conditions are developed for both state and control data transmission. These triggering conditions are based on real performance parameters including estimation/tracking errors which make control execution more relevant instead of the extended time sampling as seen in most ETC literature. The other unique feature of this ETNAC scheme is the online uncertainty approximation even during inter-event time which makes control robust and efficient. A Modified State Observer (MSO) used in this study to replicate the system to estimate the system uncertainty. In this way it not only saves data communication over network but also reduces computational efforts. System stability and event-triggering conditions are established using Lyapunov analysis. A benchmark numerical example is used to illustrate the effectiveness of the proposed method.
A. Ghafoor and S. N. Balakrishnan, "Modified State Observer based Two-Way ETNAC Design for Uncertain Linear Systems," Proceedings of the International Joint Conference on Neural Networks (2019, Budapest, Hungary), Institute of Electrical and Electronics Engineers (IEEE), Jul 2019.
The definitive version is available at https://doi.org/10.1109/IJCNN.2019.8852071
2019 International Joint Conference on Neural Networks, IJCNN 2019 (2019: Jul. 14-19, Budapest, Hungary)
Mechanical and Aerospace Engineering
Keywords and Phrases
Linear systems; Numerical methods; State estimation; System stability, Computational effort; Data-communication; Dynamic triggering; Lyapunov analysis; Neural network (nn); Performance parameters; System uncertainties; Uncertain linear system, Uncertainty analysis
International Standard Book Number (ISBN)
Article - Conference proceedings
© 2019 Institute of Electrical and Electronics Engineers (IEEE), All rights reserved.
01 Jul 2019