Optimization and Control of Batch Chemical Processes

2011 ◽  
Author(s):  
Shi Hongyan ◽  
Yuan Decheng ◽  
Wang Guogang
Keyword(s):  
Chemical Processes ◽  
Optimization And Control ◽  
And Control

scholarly journals Special Issue on “Advances in Condition Monitoring, Optimization and Control for Complex Industrial Processes”

Processes ◽  
2021 ◽  
Vol 9 (4) ◽  
pp. 664
Author(s):  
Zhiwei Gao ◽  
Michael Z. Q. Chen ◽  
Dapeng Zhang
Keyword(s):  
Smart Grids ◽  
Manufacturing Systems ◽  
Chemical Processes ◽  
Industrial Processes ◽  
Network Systems ◽  
Automation Systems ◽  
Optimization And Control ◽  
Power And Energy Systems ◽  
Power And Energy ◽  
And Control

Complex industrial automation systems and processes, such as chemical processes, manufacturing systems, wireless network systems, power and energy systems, smart grids and so forth, have greatly contributed to our daily life [...]

Five-Lump Kinetic Model for the Catalytic Cracking Process\

2018 ◽  
Vol 69 (10) ◽  
pp. 2633-2637
Author(s):  
Raluca Dragomir ◽  
Paul Rosca ◽  
Cristina Popa
Keyword(s):  
Kinetic Model ◽  
Programming Language ◽  
Catalytic Cracking ◽  
Computational Method ◽  
Industrial Data ◽  
New Model ◽  
Optimization And Control ◽  
Cracking Process ◽  
And Control ◽  
Matlab Programming

The main objectives of the present paper are to adaptation the five-kinetic model of the catalytic cracking process and simulation the riser to predicts the FCC products yields when one of the major input variable of the process is change. The simulation and adaptation are based on the industrial data from Romanian refinery. The adaptation is realize using a computational method from Optimization Toolbox from Matlab programming language. The new model can be used for optimization and control of FCC riser.

Optimization and Control Petroleum Refinery Wastewater Treatment Systems — Status, Trends and Needs

1989 ◽  
Vol 24 (3) ◽  
pp. 463-477
Author(s):  
Stephen G. Nutt
Keyword(s):  
Wastewater Treatment ◽  
Process Control ◽  
Petroleum Refinery ◽  
Control Strategies ◽  
Refinery Wastewater ◽  
Statistical Process ◽  
Petroleum Refinery Wastewater ◽  
Optimization And Control ◽  
And Control ◽  
Wastewater Treatment Systems

Abstract Based on discussions in workshop sessions, several recurring themes became evident with respect to the optimization and control of petroleum refinery wastewater treatment systems to achieve effective removal of toxic contaminants. It was apparent that statistical process control (SPC) techniques are finding more widespread use and have been found to be effective. However, the implementation of real-time process control strategies in petroleum refinery wastewater treatment systems is in its infancy. Considerable effort will need to be expended to demonstrate the practicality of on-line sensors, and the utility of automated process control in petroleum refinery wastewater treatment systems. This paper provides a summary of the discussions held at the workshop.

scholarly journals A Multi-Timescale Bilinear Model for Optimization and Control of HVAC Systems with Consistency

Energies ◽  
2021 ◽  
Vol 14 (2) ◽  
pp. 400 ◽  
Author(s):  
Zelin Nie ◽  
Feng Gao ◽  
Chao-Bo Yan
Keyword(s):  
Optimization Model ◽  
Air Conditioning ◽  
State Of The Art ◽  
Hvac Systems ◽  
Practical Significance ◽  
Hvac System ◽  
Bilinear Model ◽  
Optimization And Control ◽  
And Control ◽  
Slow Timescale

Reducing the energy consumption of the heating, ventilation, and air conditioning (HVAC) systems while ensuring users’ comfort is of both academic and practical significance. However, the-state-of-the-art of the optimization model of the HVAC system is that either the thermal dynamic model is simplified as a linear model, or the optimization model of the HVAC system is single-timescale, which leads to heavy computation burden. To balance the practicality and the overhead of computation, in this paper, a multi-timescale bilinear model of HVAC systems is proposed. To guarantee the consistency of models in different timescales, the fast timescale model is built first with a bilinear form, and then the slow timescale model is induced from the fast one, specifically, with a bilinear-like form. After a simplified replacement made for the bilinear-like part, this problem can be solved by a convexification method. Extensive numerical experiments have been conducted to validate the effectiveness of this model.

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