Abstract: A system identification and model updating methodology that accounts for factors influencing the reliability of identification is proposed. An important aspect of this methodology is the generation of a population of ...

Abstract: This paper focuses on the study of tensegrity active control in situations of partially defined loading and damage events. Self-diagnosis and self-repair methodologies are proposed and validated experimentally on a full-scale ...

Abstract: This study focuses on improving structural control through reinforcement learning. For the purposes of this study, structural control involves controlling the shape of an active tensegrity structure. Although the learning ...

Abstract: A multiobjective search method is adapted for supporting structural control of an active tensegrity structure. Structural control is carried out by modifying the self-stress state of the structure in order to satisfy a ...

Abstract: System identification involves identification of a behavioral model that best explains the measured behavior of a structure. This research uses a strategy of generation and iterative filtering of multiple candidate models ...