Integral reinforcement learning-based event-triggered H∞ control algorithm for affine nonlinear systems with asymmetric input saturation and external disturbances
This paper addresses an integral reinforcement learning (IRL)-based novel event-triggered (ET) H∞ control algorithm for affine continuous-time nonlinear systems with completely unknown drift dynamics, asymmetric input saturation, and external disturbances. The algorithm uses a zero-sum game theory t...
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| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2024-09-01
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| Series: | Franklin Open |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2773186324000628 |
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