PDC Intelligent control-based theory for structure system dynamics
Applied Data Science
Smart Structures and Systems
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.
Automated design, Bayesian additive model, Intelligent control function
Tim Chen, Megan Lohnash, Emmanuel Owens, and C. Y.J. Chen. "PDC Intelligent control-based theory for structure system dynamics" Smart Structures and Systems (2020): 401-408. https://doi.org/10.12989/sss.2020.25.4.401