Solving multiobjective random interval programming problems by a capable neural network framework

In this paper, the stability of a class of nonlinear control systems is analyzed. We first construct an optimal control problem by inserting a suitable performance index, which this problem is referred to as an infinite horizon problem. By a suitable change of variable, the infinite horizon problem...

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Vydané v:	Applied intelligence (Dordrecht, Netherlands) Ročník 49; číslo 4; s. 1566 - 1579
Hlavní autori:	Arjmandzadeh, Ziba, Nazemi, Alireza, Safi, Mohammadreza
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	New York Springer US 01.04.2019 Springer Nature B.V
Predmet:	Artificial Intelligence Computer Science Control stability Control systems design Controllers Dynamic stability Feedback control Machine learning Machines Manufacturing Mechanical Engineering Multiple objective analysis Neural networks Nonlinear analysis Nonlinear control Nonlinear programming Nonlinear systems Optimal control Performance indices Processes Stability analysis Random interval parameters Neural network models Satisficing solution Stability Fractile model Convergence
ISSN:	0924-669X, 1573-7497
On-line prístup:	Získať plný text
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