Journal article
Adaptive Regulation of Block-Oriented Nonlinear Systems Using Binary Sensors With Applications to Automotive Engine Control
W Zhao, E Weyer, G Yin, D Dong, Y Zhang, T Shen
IEEE Transactions on Automatic Control | IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC | Published : 2023
Abstract
In this article, adaptive regulation of block-oriented nonlinear systems, i.e., Hammerstein and Wiener systems, with binary-valued measurements of the regulation errors is considered. Compared with the classical framework for stochastic adaptive control, the new feature here is that only binary-valued observations of regulation errors are available to the controller. An adaptive regulator based on the stochastic approximation algorithm is proposed and it is proved that the regulator is optimal in the sense that it minimizes the long-run average of the squared regulation errors almost surely. Numerical examples as well as real applications of the proposed algorithms to automotive engine contr..
View full abstractGrants
Awarded by Australian Research Council
Funding Acknowledgements
The work of W. Zhao was supportedin part by the National Key Research and Development Program of China under Grant 2018YFA0703800, in part by the National Nature Science Foundation of China under Grant 61822312, in part by the Chinese Academy of Sciences (CAS) Project for Young Scientists in Basic Research under Grant YSBR-008, and in part by the Strategic PriorityResearch Program of CAS under Grant XDA27000000. The work of E.Weyer was supported by the Australian Research Council's DiscoveryProjects funding scheme under Grant DP130104028. The work of G.Yin was supported in part by the Air Force Office of Scientific Researchunder Grant FA9550-18-1-0268. The work of D. Dong was supported bythe Australian Research Council's Discovery Projects funding schemeunder Grant DP190101566. The work of T. Shen and Y. Zhang wassupported by Toyota Motor Corporation, Japan. Recommended by As-sociate Editor S.-J. Chung.