Neural algorithm for optimization of multidimensional object controller parameters

Optimal control of multivariable systems is a complex dynamic process that minimizes the cost function to obtain the optimal control strategy. Unfortunately, for nonlinear systems, it is not possible to use the traditional linear quadratic regulator (LQR), which would be optimal over the entire rang...

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Bibliographic Details
Published in:	Neural computing & applications Vol. 36; no. 25; pp. 15907 - 15924
Main Authors:	Bałazy, Patryk, Lalik, Krzysztof, Knap, Paweł
Format:	Journal Article
Language:	English
Published:	London Springer London 01.09.2024 Springer Nature B.V
Subjects:	Algorithms Artificial Intelligence Computational Biology/Bioinformatics Computational Science and Engineering Computer Science Control systems Controllers Cost analysis Cost function Cranes Data Mining and Knowledge Discovery Image Processing and Computer Vision Linear quadratic regulator Multivariable control Nonlinear control Nonlinear systems Nonlinearity Optimal control Original Article Parameters Probability and Statistics in Computer Science System dynamics System effectiveness Model-free Neural network Adaptive control Reinforcement learning
ISSN:	0941-0643, 1433-3058
Online Access:	Get full text
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