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- W4387423518 abstract "In this paper, a novel non-backstepping adaptive control approach is presented for the hydraulic servo systems, aiming to mitigate the “explosion of complexity” issue and achieve matching of full-state known conditions. This approach enables one-step control through coordinate transformation. To address the control singularity problem, two radial basis function neural networks (RBFNNs) are utilized to estimate the separate sets of lumped unknown dynamics. Additionally, an adaptive controller is designed where the neural network weights are updated online using a weight error variable. This ensures that the estimated weights converge closely to their true values, allowing for accurate identification of the unknown dynamics. Theoretical analysis and numerical simulation are conducted verity the correctness and effectiveness of the proposed method." @default.
- W4387423518 created "2023-10-08" @default.
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- W4387423518 date "2023-01-01" @default.
- W4387423518 modified "2023-10-08" @default.
- W4387423518 title "Adaptive Non-backstepping Output-Feedback Control for Hydraulic Servo System Subject to Uncertain Dynamics" @default.
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- W4387423518 doi "https://doi.org/10.1007/978-981-99-6886-2_50" @default.
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