Integral Reinforcement Learning-Based Stochastic Guaranteed Cost Control for Time-Varying Systems with Asymmetric Saturation Actuators

This study explores a stochastic guarantee cost control (GCC) for time-varying systems with random parameters and asymmetric saturation actuators by employing the integral reinforcement learning (IRL) method in the dynamic event-triggered (DET) mode. Firstly, a modified Hamilton–Jacobi–Isaac (HJI) e...

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Vydané v:	Actuators Ročník 14; číslo 10; s. 506
Hlavní autori:	Liang, Yuling, Xie, Mengjia, Zhang, Juan, Ming, Zhongyang, Gao, Zhiyun
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	Basel MDPI AG 01.10.2025
Predmet:	Actuators adaptive dynamic programming Aircraft Algorithms Analysis asymmetric saturation actuators Asymmetry Collocation methods Communication Cost control Design Dynamic programming Economic aspects Methods multivariate probabilistic collocation method Optimal control Ordinary differential equations Random variables Simulation Stability stochastic systems Systems stability Time varying control systems
ISSN:	2076-0825, 2076-0825
On-line prístup:	Získať plný text
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