Steady-state real-time optimization using transient measurements and approximated Hammerstein dynamic model: A proof of concept in an experimental rig
An attractive method for steady-state real-time optimization (RTO) using transient
measurements consists of a persistent parameter adaptation throughout a dynamic …
measurements consists of a persistent parameter adaptation throughout a dynamic …
An integrated real-time optimization, control, and estimation scheme for post-combustion CO2 capture
This study presents a novel operational scheme for post-combustion CO 2 capture (PCC)
plants downstream from fuel-fired power plants. The approach is comprised of real-time …
plants downstream from fuel-fired power plants. The approach is comprised of real-time …
Recursive least squares with variable-rate forgetting based on the f-test
A variable-rate forgetting factor for recursive least squares is developed for parameter
identification of time-varying systems. The variable-rate forgetting factor uses the F-test to …
identification of time-varying systems. The variable-rate forgetting factor uses the F-test to …
Parameter estimation of isotropic PMSMs based on multiple steady-state measurements collected during regular operations
This article proposes a novel method to estimate the parameters of isotropic PMSMs which
uses only steady-state measurements of load conditions commonly available during the …
uses only steady-state measurements of load conditions commonly available during the …
Development of Steady-State and Dynamic Mass and Energy Constrained Neural Networks for Distributed Chemical Systems Using Noisy Transient Data
The paper presents the development of algorithms for mass and energy constrained neural
network models that can exactly conserve the overall mass and energy of distributed …
network models that can exactly conserve the overall mass and energy of distributed …
Automated multistep parameter identification of spmsms in large-scale applications using cloud computing resources
Parameter identification of permanent magnet synchronous machines (PMSMs) represents
a well-established research area. However, parameter estimation of multiple running …
a well-established research area. However, parameter estimation of multiple running …
Real-time Optimization with persistent parameter adaptation using online parameter estimation
One of the major drawbacks of traditional Real-time Optimization (RTO) is the steady-state
wait before estimating the parameters. This paper proposes an alternative solution called …
wait before estimating the parameters. This paper proposes an alternative solution called …
NOx formation model for utility boilers using robust two-step steady-state detection and multimodal residual convolutional auto-encoder
Background To achieve carbon neutrality, thermal power plants will take on greater peak-
shaving responsibilities, resulting in utility boilers running at more frequently-changing …
shaving responsibilities, resulting in utility boilers running at more frequently-changing …
[HTML][HTML] Optimisation of the resource efficiency in an industrial evaporation system
JL Pitarch, CG Palacín, C De Prada, B Voglauer… - Journal of Process …, 2017 - Elsevier
This work deals with the problem of resource efficiency monitoring in a multiple-effect
evaporation process. The approach considers first a grey-box nonlinear stationary model of …
evaporation process. The approach considers first a grey-box nonlinear stationary model of …
Automated parameter identification of spmsms based on two steady states using cloud computing resources
E Brescia, P Serafino, D Cascella… - 2021 International …, 2021 - ieeexplore.ieee.org
This paper proposes a novel offline parameter identification method of surface permanent
magnet synchronous machines (SPMSMs) suitable for large-scale industrial applications …
magnet synchronous machines (SPMSMs) suitable for large-scale industrial applications …