Modeling and iterative learning control of spatially distributed parameter systems with sensing and actuation over a selected area of the domain

0545245 - ÚTIA 2022 RIV US eng J - Článek v odborném periodiku
Cichy, B. - Augusta, Petr - Galkowski, K. - Rogers, E.
Modeling and iterative learning control of spatially distributed parameter systems with sensing and actuation over a selected area of the domain.
Multidimensional Systems and Signal Processing. Roč. 32, č. 1 (2021), s. 1237-1258. ISSN 0923-6082. E-ISSN 1573-0824
Institucionální podpora: RVO:67985556
Klíčová slova: Spatially distributed parameter systems * Iterative learning control
Obor OECD: Robotics and automatic control
Impakt faktor: 2.030, rok: 2021
Způsob publikování: Omezený přístup
https://link.springer.com/article/10.1007/s11045-021-00780-1

This paper gives new contributions to the development of iterative learning control for distributed parameter systems, based on using finite difference schemes to construct a finitedimensional approximate model of the dynamics for control law design. To form a basis for the new results, systems whose dynamics are described by a fourth-order partial differential equation are considered together with the associated accuracy and numerical stability checks. Some previous control law designs use only a spatial variable as the control input, which can be a serious obstacle to practical implementation since many actuators and sensors must be deployed. This paper’s new design is based on spatially homogeneous sensing and excitation over a selected sub-area of the domain considered. Supporting numerical case studies are given to support the analysis.
Trvalý link: http://hdl.handle.net/11104/0322151