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Output information-based intermittent optimal control for continuous-time nonlinear systems with unmatched uncertainties via adaptive dynamic programming.
- Source :
- ISA Transactions; Apr2024, Vol. 147, p163-175, 13p
- Publication Year :
- 2024
-
Abstract
- Intermittent control stands as a valuable strategy for resource conservation and cost reduction across diverse systems. Nonetheless, prevailing research is intractable to address the challenges posed by robust optimal intermittent control of nonlinear input-affine systems with unmatched uncertainties. This paper aims to fill this gap. Initially, we introduce an enhanced finite-time intermittent control approach to ensure stability within nonlinear dynamic systems harboring bounded errors. A neural networks (NNs) state observer is constructed to estimate system information. Subsequently, an optimal intermittent controller that operates within a finite time span, guaranteeing system stability by employing the Hamilton–Jacobi–Bellman (HJB) methodology. Furthermore, we devise an output information-based event-triggered intermittent (ETI) approach rooted in the robust adaptive dynamic programming (ADP) algorithm, furnishing an optimal intermittent control law. In this process, a critic NNs is introduced to estimate the cost function and optimal intermittent controller. Simulation results show that our proposed method is superior to existing intermittent control strategies. • We study the robust intermittent affine control system with unmatched uncertainties. • In contrast to the existing ET ADP, we introduce a novel intermittent ET ADP. • The proposed optimal output intermittent control show better control performance. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 00190578
- Volume :
- 147
- Database :
- Supplemental Index
- Journal :
- ISA Transactions
- Publication Type :
- Academic Journal
- Accession number :
- 176539117
- Full Text :
- https://doi.org/10.1016/j.isatra.2024.02.009