Architectures for neural networks as surrogates for dynamic systems in chemical engineering

E Esche, J Weigert, GB Rihm, J Göbel… - … Research and Design, 2022 - Elsevier
Surrogate models for dynamic systems in chemical engineering are increasingly of interest.
Neural networks have already been applied in research, but it remains unclear which types …

RST controller design for a non-uniform multi-rate control system

A Cuenca, J Salt - Journal of Process Control, 2012 - Elsevier
In this work, a non-uniform multi-rate controller which includes an RST control stage is
introduced. Due to several issues, in some systems the use of non-uniform (irregular) multi …

Development of adaptive dual predictive control schemes based on Wiener–Hammerstein models

K Kumar, SC Patwardhan, S Noronha - Journal of Process Control, 2022 - Elsevier
Adaptive MPC schemes often employ local linear approximation of the system dynamics,
which may not be adequate to capture the dynamic behavior of systems exhibiting strongly …

Development of Wiener-Hammerstein models parameterized using orthonormal basis filters and deep neural network

JM Patel, K Kumar, SC Patwardhan - IFAC-PapersOnLine, 2022 - Elsevier
Many chemical or biochemical processes exhibit strongly nonlinear dynamic behavior in the
desired region of operations. To develop effective monitoring and control schemes for such …

Wiener models

M Ławryńczuk, M Ławryńczuk - Nonlinear predictive control using Wiener …, 2022 - Springer
This chapter is concerned with Wiener models. At first, input-output structures are described:
one SISO case and five MIMO ones. Next, state-space models are detailed: one SISO case …

Adaptive control of the ore crushing process in cone crushers based on nonlinear predictive model

O Mykhailenko, V Shchokin, O Shchokina - 2018 - ds.knu.edu.ua
The paper deals with the development adaptive control system of the ore crushing process
based on nonlinear block-oriented dynamic models. It is define that the best dynamic …