activity
20192021
collaborators

7 papers

eess.SY2021

Design of input for data-driven simulation with Hankel and Page matrices

Andrea Iannelli, Mingzhou Yin, Roy S. Smith

The paper deals with the problem of designing informative input trajectories for data-driven simulation. First, the excitation requirements in the case of noise-free data are discu…

eess.SY2020

On Low-Rank Hankel Matrix Denoising

Mingzhou Yin, Roy S. Smith

The low-complexity assumption in linear systems can often be expressed as rank deficiency in data matrices with generalized Hankel structure. This makes it possible to denoise the…

eess.SY2020

Experiment design for impulse response identification with signal matrix models

Andrea Iannelli, Mingzhou Yin, Roy S. Smith

This paper formulates an input design approach for truncated infinite impulse response identification in the context of implicit model representations recently used as basis for da…

eess.SY2020

Maximum Likelihood Signal Matrix Model for Data-Driven Predictive Control

Mingzhou Yin, Andrea Iannelli, Roy S. Smith

The paper presents a data-driven predictive control framework based on an implicit input-output mapping derived directly from the signal matrix of collected data. This signal matri…

eess.SY2020

Subspace Identification of Linear Time-Periodic Systems with Periodic Inputs

Mingzhou Yin, Andrea Iannelli, Roy S. Smith

This paper proposes a new methodology for subspace identification of linear time-periodic (LTP) systems with periodic inputs. This method overcomes the issues related to the comput…

eess.SY2020

Probabilistic Flight Envelope Estimation with Application to Unstable Overactuated Aircraft

Mingzhou Yin, Q. P. Chu, Y. Zhang +2

This paper proposes a novel and practical framework for safe flight envelope estimation and protection, in order to prevent loss-of-control-related accidents. Conventional analytic…