Data-driven LPV model predictive control of a cold atmospheric plasma jet for biomaterials processing

D Gidon, HS Abbas, AD Bonzanini, DB Graves… - Control Engineering …, 2021 - Elsevier
Cold atmospheric plasmas (CAPs) are increasingly used for treatment of complex surfaces
in biomedical and biomaterials processing applications. However, the multivariable …

[PDF][PDF] An overview of data-driven modeling and learning-based control design methods for nonlinear systems in LPV framework

Y Bao, JM Velni - Proc. 5th IFAC Workshop Linear …, 2022 - sssc2022.encs.concordia.ca
This paper presents an overview of research on data-driven modeling and learningbased
control of nonlinear systems in linear parameter-varying (LPV) framework. Data-driven …

Epistemic uncertainty quantification in state-space LPV model identification using Bayesian neural networks

Y Bao, JM Velni, M Shahbakhti - IEEE Control Systems Letters, 2020 - ieeexplore.ieee.org
This letter presents a variational Bayesian inference Neural Network (BNN) approach to
quantify uncertainties in matrix function estimation for the state-space linear parameter …

Deep-learning-based identification of LPV models for nonlinear systems

C Verhoek, GI Beintema, S Haesaert… - 2022 IEEE 61st …, 2022 - ieeexplore.ieee.org
The Linear Parameter-Varying (LPV) framework provides a modeling and control design
toolchain to address nonlinear (NL) system behavior via linear surrogate models. Despite …

A learning-and scenario-based MPC design for nonlinear systems in LPV framework with safety and stability guarantees

Y Bao, HS Abbas… - International Journal of …, 2023 - Taylor & Francis
This paper presents a learning-and scenario-based model predictive control (MPC) design
approach for systems modelled in the linear parameter-varying (LPV) framework. Using …

Robust variational inference for LPV dual-rate systems with randomly delayed outputs

X Liu, X Yang - IEEE Transactions on Instrumentation and …, 2021 - ieeexplore.ieee.org
This article proposes a variational Bayesian (VB) approach for the identification of linear
parameter-varying (LPV) dual-rate systems when the measured data are contaminated with …

An online transfer learning approach for identification and predictive control design with application to RCCI engines

Y Bao, J Mohammadpour Velni… - Dynamic systems …, 2020 - asmedigitalcollection.asme.org
This paper presents a framework to refine identified artificial neural networks (ANN) based
state-space linear parameter-varying (LPV-SS) models with closed-loop data using online …

Safe control of nonlinear systems in LPV framework using model-based reinforcement learning

Y Bao, J Mohammadpour Velni - International Journal of Control, 2023 - Taylor & Francis
This paper presents a safe model-based reinforcement learning (MBRL) approach to control
nonlinear systems described by linear parameter-varying (LPV) models. A variational …

Q-Markov Covariance equivalent realizations for unstable and marginally stable systems

Y Shen, M Chen, M Majji, RE Skelton - Mechanical Systems and Signal …, 2023 - Elsevier
An observer-based q-Markov Covariance equivalent realization (QMC) formulation is
presented in the paper. It is shown that by inserting an observer in the input–output …

[PDF][PDF] Towards efficient identification of linear parameter-varying state-space models

PB Cox - 2018 - research.tue.nl
Today, the need to increase efficiency and performance of dynamical systems leads to
innovative control solutions that rely on accurate representations of the underlying system …