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...

Ausführliche Beschreibung

Gespeichert in:

Bibliographische Detailangaben
Veröffentlicht in:	Applied intelligence (Dordrecht, Netherlands) Jg. 49; H. 4; S. 1566 - 1579
Hauptverfasser:	Arjmandzadeh, Ziba, Nazemi, Alireza, Safi, Mohammadreza
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	New York Springer US 01.04.2019 Springer Nature B.V
Schlagworte:	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
Online-Zugang:	Volltext
Tags:	Tag hinzufügen Keine Tags, Fügen Sie den ersten Tag hinzu!

Schreiben Sie den ersten Kommentar!