2020
DOI: 10.1007/s11633-020-1229-0
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Controller Optimization for Multirate Systems Based on Reinforcement Learning

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Cited by 8 publications
(1 citation statement)
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“…Such systems are considered due to the need to optimize the performances of systems with different dynamic modes and efficiently use available hardware resources [1,2]. Usually, MIMO stabilization systems are considered, which have vector characters of control, disturbances, parameters of the control system, and outputs [3][4][5][6][7]. There are two approaches to the description of the multirate continuous-discrete system: models in the time domain and models obtained using the discrete Laplace transform or z-transform.…”
Section: Introductionmentioning
confidence: 99%
“…Such systems are considered due to the need to optimize the performances of systems with different dynamic modes and efficiently use available hardware resources [1,2]. Usually, MIMO stabilization systems are considered, which have vector characters of control, disturbances, parameters of the control system, and outputs [3][4][5][6][7]. There are two approaches to the description of the multirate continuous-discrete system: models in the time domain and models obtained using the discrete Laplace transform or z-transform.…”
Section: Introductionmentioning
confidence: 99%