Smart Structures and Systems
Volume 25, Number 4, 2020, pages 401-408
DOI: 10.12989/sss.2020.25.4.401
PDC Intelligent control-based theory for structure system dynamics
Tim Chen, Megan Lohnash, Emmanuel Owens and 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.