Learning‐based T ‐sHDP() for optimal control of a class of nonlinear discrete‐time systems-Reference-Cited by-同舟云学术

Learning‐based T ‐sHDP() for optimal control of a class of nonlinear discrete‐time systems

Published:2021-10-24 Issue: Volume: Page:
ISSN:1049-8923
Container-title:International Journal of Robust and Nonlinear Control
language:en
Short-container-title:Int J Robust Nonlinear Control

Author:

Yu Luyang¹,Liu Weibo²,Liu Yurong¹³^ORCID,Alsaadi Fawaz E.⁴

Affiliation:

1. Department of Mathematics Yangzhou University Yangzhou China

2. Department of Computer Science Brunel University London Uxbridge UK

3. Key Laboratory of Advanced Perception and Intelligent Control of High‐end Equipment, Ministry of Education Anhui Polytechnic University Wuhu China

4. Department of Information Technology, Faculty of Computing and Information Technology King Abdulaziz University Jeddah Saudi Arabia

Funder

National Natural Science Foundation of China

Department of Sport and Recreation, Government of Western Australia

Publisher

Wiley

Subject

Electrical and Electronic Engineering,Industrial and Manufacturing Engineering,Mechanical Engineering,Aerospace Engineering,Biomedical Engineering,General Chemical Engineering,Control and Systems Engineering

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1002/rnc.5847

Reference46 articles.

1. Security Control for Discrete-Time Stochastic Nonlinear Systems Subject to Deception Attacks

2. Finite-horizon filtering for a class of nonlinear time-delayed systems with an energy harvesting sensor

3. Chance-constrained H∞ control for a class of time-varying systems with stochastic nonlinearities: The finite-horizon case

4. Event-Based Adaptive Neural Tracking Control for Discrete-Time Stochastic Nonlinear Systems: A Triggering Threshold Compensation Strategy

5. A Novel Framework for Backstepping-Based Control of Discrete-Time Strict-Feedback Nonlinear Systems With Multiplicative Noises

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