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- W1805200023 abstract "Based on the state space control theory and a neural network architecture, the authors present a stochastic neural direct adaptive control algorithm (SNDAC) for partially known state space nonlinear time varying plants. A neural network is used to generate the control signal, which minimizes a quadratic one-step-ahead prediction performance index based on the minimum variance optimization approach. The SNDAC can be used for both deterministic and stochastic control problems and is computationally efficient and effective. >" @default.
- W1805200023 created "2016-06-24" @default.
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- W1805200023 date "2003-01-02" @default.
- W1805200023 modified "2023-09-25" @default.
- W1805200023 title "Stochastic neural direct adaptive control based on minimum variance optimization" @default.
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- W1805200023 doi "https://doi.org/10.1109/isic.1992.225080" @default.
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