PDC Intelligent control-based theory for structure system dynamics

Tim Chen , Megan Lohnash , Emmanuel Owens , C.Y.J. Chen

Abstract

This paper deals with the problem of global stabilization for a class of nonlinear control systems. An effective approach is proposed for controlling the system interaction of structures through a combination of parallel distributed compensation (PDC) intelligent controllers and fuzzy observers. An efficient approximate inference algorithm using expectation propagation and a Bayesian additive model is developed which allows us to predict the total number of control systems, thereby contributing to a more adaptive trajectory for the closed-loop system and that of its corresponding model. The closed-loop fuzzy system can be made as close as desired, so that the behavior of the closed-loop system can be rigorously predicted by establishing that of the closed-loop fuzzy system.

Key Words

intelligent control function; Bayesian additive model; automated design

Address

(1) Tim Chen — AI LAB, Faculty of Information Technology, Ton Duc Thang University, Ho Chi Minh City, Vietnam
(2) Megan Lohnash — Data Analysis Research Centre, San Jose State University, OneWashington Square; San José, CA 95192-0029, USA
(3) Emmanuel Owens — Innovative InformationCentre, Liverpool JohnMoores University, 98Mount Pleasant, Liverpool L3 5UZ, UK
(4) C.Y.J. Chen — Faculty of Engineering, King Abdulaziz University, Abdullah Sulayman, Jeddah 21589, Saudi Arabia.

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