Zobrazeno 1 - 10
of 37
pro vyhledávání: '"Rohit S. Patwardhan"'
Publikováno v:
Industrial & Engineering Chemistry Research. 58:11338-11351
The well-instrumented process industry collects vast amounts of structured and unstructured data from its assets in real time. Some of this data gets stored as conventional time series data, while ...
Publikováno v:
Mechanical Systems and Signal Processing. 162:108100
For a structural dynamics engineer assessing a system’s vibration characteristics, the frequency response function (FRF) is indispensable, irrespective of whether the setup being tested is experimental, numerical or analytical. This paper outlines
Autor:
Kalpesh M. Patel, Rohit S. Patwardhan
Publikováno v:
Day 3 Wed, March 20, 2019.
Data Analytics is an emerging area that involves using advanced statistical and machine learning algorithms to discover information & relationsips present in different types of data. The work described in this paper illustrates the application of mac
Publikováno v:
IFAC-PapersOnLine. 48:531-538
With decades of successful application of model predictive control (MPC) to industrial processes, practitioners are now focused on ease of commissioning, monitoring, and automation of maintenance. Many industries do not necessarily need better algori
Publikováno v:
2017 6th International Symposium on Advanced Control of Industrial Processes (AdCONIP).
This paper presents a novel method∗ for implementing a split range control using a Proportional-Integral (PI) controller where two valves, a big and a small valve, can be used to simultaneously control the underlying process. The proposed control s
Publikováno v:
Journal of Process Control. 24:188-202
The identification of high fidelity models is a critical element in the implementation of high performance model predictive control (MPC) applications in the industry. These controllers can vary in size with input–ouput dimensions ranging from 5 ×
Publikováno v:
Journal of Process Control. 24:48-56
This work studies k-step-ahead prediction error model identification and its relationship to MPC control. The use of error criteria in parameter estimation will be discussed, where the identified model is used in model predictive control (MPC). Assum
Autor:
R.B. Gopaluni, Rohit S. Patwardhan
Publikováno v:
IFAC Proceedings Volumes. 46:577-582
The quality of a model determines the closed loop performance of model predictive controllers. However, identification of high quality multivariable models is a time and energy intensive exercise. The industrial model predictive controllers are desig
Publikováno v:
Computers & Chemical Engineering. 51:124-135
The high cost of model predictive control (MPC) technology has hampered its wide application in process industries beyond the refining/petrochemical industry. This work strives to increase the efficiency of MPC deployment. First, a semi-automatic MPC
Publikováno v:
Control Engineering Practice. 20:219-235
This paper presents two case studies on the performance evaluation and model validation of two industrial multivariate model predictive control (MPC) based controllers: (1) a 7-output, 3-input MPC with three measured disturbance variables for control