scholarly journals Optimal Control of the Separation Process with Flow Restrictions

2019 ◽  
pp. 159-170
Author(s):  
Nikolai D. Demidenko ◽  
Lyudmila V. Kulagina ◽  
Aleksandr G. Nikiforov
Keyword(s):  
Necessary Optimality Conditions ◽  
Optimization Method ◽  
Separation Process ◽  
Optimal Process ◽  
Acid Alkylation ◽  
Sulfuric Acid Alkylation ◽  
Distributed Parameters ◽  
Optimal Process Control ◽  
Stationarity Conditions ◽  
Admissible Controls

Here we formulate the problem of optimal process control with distributed parameters, taking into account the constraints on the control and associated flows. The necessary optimality conditions are obtained. The analysis of the stationarity conditions is carried out and the method for constructing the domain of admissible controls is proposed. The developed optimization method is applied in the automation of industrial distillation plants for the sulfuric acid alkylation of isobutane with butylenes, ortho-xylene production, etc.

scholarly journals METHODS FOR PROBLEMS OF VECTOR GENERALIZED OPTIMAL CONTROL OF SYSTEMS WITH DISTRIBUTED PARAMETERS

2020 ◽  
pp. 71-98
Author(s):  
O. S. Kharkov ◽  
Ya. I. Vedel ◽  
V. V. Semenov
Keyword(s):  
Optimal Control ◽  
Optimal Control Problems ◽  
Necessary Conditions ◽  
Necessary Optimality Conditions ◽  
Quality Criterion ◽  
Control Problems ◽  
Convergence Of Algorithms ◽  
Distributed Parameters ◽  
Admissible Controls ◽  
Systems With Distributed Parameters

The paper develops the theory of existence and necessary optimality conditions for optimal control problems with a vector quality criterion for systems with distributed parameters and generalized impacts. The concept of $(K, e, \epsilon)$-approximate efficiency is investigated. Necessary conditions for $(K, e, \epsilon)$-approximate efficiency of admissible controls in the form of variational inclusions are proved. Methods for solving problems of vector optimization of linear distributed systems with generalized control are proposed. Convergence of algorithms with errors is proved.

scholarly journals Mechanical properties optimization of the steering column based on multi-objective optimization design

2016 ◽  
Vol 8 (12) ◽  
pp. 168781401668294 ◽  
Author(s):  
Si Chen ◽  
Zhaohui Wang ◽  
Mi Lv
Keyword(s):  
Mechanical Properties ◽  
Process Parameters ◽  
Optimization Design ◽  
Strain Difference ◽  
Optimization Method ◽  
Equivalent Strain ◽  
Multi Objective Optimization ◽  
Optimal Process ◽  
Multi Objective ◽  
Initial Results

The mechanical properties of the steering column have a significant influence on the comfort and stability of a vehicle. In order for the mechanical properties to be improved, the rotary swaging process of the steering column is studied in this article. The process parameters, including axial feed rate, hammerhead speed, and hammerhead radial reduction, are systematically analyzed and optimized based on a multi-objective optimization design. The response surface methodology and the genetic algorithm are employed for optimal process parameters to be obtained. The maximum damage value, the maximum forming load, and the equivalent strain difference obtained with the optimal process parameters are, respectively, decreased by 30.09%, 7.44%, and 57.29% compared to the initial results. The comparative results present that the quality of the steering column is improved. The torque experiments and fatigue experiments are conducted with the optimal steering column. The maximum torque is measured to be 260 NM, and the service life is measured to be 2 weeks (40 NM, 2500 times), which are, respectively, increased by 8.3% and 8.69% compared to the initial results. The above results display that the mechanical properties of the steering column are optimized to verify the feasibility of the multi-objective optimization method.

scholarly journals On implicit variables in optimization theory

2021 ◽  
Vol Volume 2 (Original research articles) ◽  
Author(s):  
Matúš Benko ◽  
Patrick Mehlitz
Keyword(s):  
Optimization Problems ◽  
Constraint Qualifications ◽  
Optimization Theory ◽  
Mathematical Optimization ◽  
General Setting ◽  
Necessary Optimality Conditions ◽  
Detailed Comparison ◽  
Mordukhovich Stationarity ◽  
Stationarity Conditions ◽  
The One

Implicit variables of a mathematical program are variables which do not need to be optimized but are used to model feasibility conditions. They frequently appear in several different problem classes of optimization theory comprising bilevel programming, evaluated multiobjective optimization, or nonlinear optimization problems with slack variables. In order to deal with implicit variables, they are often interpreted as explicit ones. Here, we first point out that this is a light-headed approach which induces artificial locally optimal solutions. Afterwards, we derive various Mordukhovich-stationarity-type necessary optimality conditions which correspond to treating the implicit variables as explicit ones on the one hand, or using them only implicitly to model the constraints on the other. A detailed comparison of the obtained stationarity conditions as well as the associated underlying constraint qualifications will be provided. Overall, we proceed in a fairly general setting relying on modern tools of variational analysis. Finally, we apply our findings to different well-known problem classes of mathematical optimization in order to visualize the obtained theory. Comment: 34 pages

scholarly journals THE IMPROVING EFFICIENCY OF AIR COOLING APPARATUS OF THE INSTALLATION OF A SULFURIC ACID ALKYLATION

2020 ◽  
Vol 2020 (1) ◽  
pp. 7-8
Author(s):  
Ekaterina Ahtareeva ◽  
Anatoliy Dement'ev ◽  
Evgeniy Podoplelov
Keyword(s):  
Heat Transfer ◽  
Sulfuric Acid ◽  
Heat Exchange ◽  
Transfer Process ◽  
Heat Transfer Process ◽  
Air Cooling ◽  
Acid Alkylation ◽  
Sulfuric Acid Alkylation

The study of the efficiency of the heat transfer process in the air cooling apparatus, which is part of the installation of a sulfuric acid alkylation, at different finning coefficients of heat exchange pipes

Optimal Process Control Using Neural Networks

2008 ◽  
Vol 5 (2) ◽  
pp. 217-229 ◽  
Author(s):  
Radhakant Padhi ◽  
S. N. Balakrishnan
Keyword(s):  
Neural Networks ◽  
Process Control ◽  
Optimal Process ◽  
Optimal Process Control
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