Study of the Practical Convergence of Evolutionary Algorithms for the Optimal Program Control of a Wheeled Robot

2018 ◽  
Vol 57 (4) ◽  
pp. 561-580 ◽  
Author(s):  
A. I. Diveev ◽  
S. V. Konstantinov
Author(s):  
Григорьев ◽  
I. Grigorev ◽  
Мустафина ◽  
S. Mustafina

The article outlines the basic concepts of the numerical solution of optimal control problems based on the method of variations in the control area


2018 ◽  
pp. 24-29
Author(s):  
I. O. Makhonin

When landing an unmanned aerial vehicle (UAV) on a ship, it is required to perform the specified boundary values of the state vector at the moment of approach to the hook equipment. The article considers the solution of the problem of calculating the points of the area of initial positions of UAV. It is mean, that each point provide hitting for the UAV to a predetermined aiming area at a given time in the vicinity of the hitch. In this case, the phase coordinates of the UAV at the time of approach to the hook device have to defined. To calculate the points located on the boundary of the area of initial positions, auxiliary problems of optimal program control have been solved. To solve it, the necessary conditions for the maximum principle of L. S. Pontryagin were used. The article considers the algorithm of the computational solution of the auxiliary problem of optimal program control and the results of calculating points thats located at the far boundary of the area of initial positions, that is mean, that points located at the maximum distance from the aiming point (the location of the hook device).


2020 ◽  
Vol 2020 (1) ◽  
pp. 105-108
Author(s):  
Ali Alsam

Vision is the science that informs us about the biological and evolutionary algorithms that our eyes, opticnerves and brains have chosen over time to see. This article is an attempt to solve the problem of colour to grey conversion, by borrowing ideas from vision science. We introduce an algorithm that measures contrast along the opponent colour directions and use the results to combine a three dimensional colour space into a grey. The results indicate that the proposed algorithm competes with the state of art algorithms.


2019 ◽  
Author(s):  
Anders Andreasen

In this article the optimization of a realistic oil and gas separation plant has been studied. Two different fluids are investigated and compared in terms of the optimization potential. Using Design of Computer Experiment (DACE) via Latin Hypercube Sampling (LHS) and rigorous process simulations, surrogate models using Kriging have been established for selected model responses. The surrogate models are used in combination with a variety of different evolutionary algorithms for optimizing the operating profit, mainly by maximizing the recoverable oil production. A total of 10 variables representing pressure and temperature various key places in the separation plant are optimized to maximize the operational profit. The optimization is bounded in the variables and a constraint function is included to ensure that the optimal solution allows export of oil with an RVP < 12 psia. The main finding is that, while a high pressure is preferred in the first separation stage, apparently a single optimal setting for the pressure in downstream separators does not appear to exist. In the second stage separator apparently two different, yet equally optimal, settings are revealed. In the third and final separation stage a correlation between the separator pressure and the applied inlet temperature exists, where different combinations of pressure and temperature yields equally optimal results.<br>


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