Linear Time-Varying Parameter Estimation: Maximum A Posteriori Approach via Semidefinite Programming

We study the problem of identifying a linear time-varying output map from measurements and linear time-varying system states, which are perturbed with Gaussian observation noise and process uncertainty, respectively. Employing a stochastic model as prior knowledge for the parameters of the unknown output map, we reconstruct their estimates...

Model Predictive Control in buildings with thermal and visual comfort constraints

Model Predictive Control can cope with conflicting control objectives in building energy managements. In terms of user satisfaction, visual comfort has been proven in several studies to be a crucial factor, however thermal comfort is typically considered the only important aspect. Besides human well-being, visual comfort strongly impacts the...

The existence and uniqueness of solutions for kernel-based system identification

The notion of reproducing kernel Hilbert space (RKHS) has emerged in system identification during the past decade. In the resulting framework, the impulse response estimation problem is formulated as a regularized optimization defined on an infinite-dimensional RKHS consisting of stable impulse responses. The consequent estimation problem is...

Representer Theorem for Learning Koopman Operators

In this work, we consider the problem of learning the Koopman operator for discrete-time autonomous systems. The learning problem is formulated as a generic constrained regularized empirical loss minimization in the infinite-dimensional space of linear operators. We show that a representer theorem holds for the introduced learning problem...

Kernel-based Impulse Response Identification with Side-Information on Steady-State Gain

In this article, we consider the problem of system identification when side-information is available on the steady-state gain (SSG) of the system. We formulate a general nonparametric identification method as an infinite-dimensional constrained convex program over the reproducing kernel Hilbert space (RKHS) of stable impulse responses. The...

Kernel-based identification with frequency domain side-information

This paper discusses the problem of system identification when frequency domain side-information is available. We mainly consider the case where the side-information is provided as the H_∞-norm of the system being bounded by a given scalar. This framework allows considering different forms of frequency domain side-information, such...

Viscoelastic and dry-sliding wear properties of basalt fiber-reinforced composites based on a surface-modified graphene oxide/epoxy matrix

The current study focuses on the development of silanized graphene oxide reinforced basalt fiber/epoxy composites for enhanced tribological and viscoelastic properties. The modified-graphene oxide nanoplatelets were characterized using energy-dispersive X-ray spectroscopy, and Raman analyses. Pin-on-disk wear test and dynamic mechanical...

The Nomos of the Sea: Pirates, DJs, Hackers, and the Architecture of Contingent Labor