Optimal Iterative Learning Control of Quantized Signals Based on Encoding-Decoding Method

2021 IEEE 10th Data Driven Control and Learning Systems Conference (DDCLS)(2021)

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摘要
This paper considers optimal iterative learning control (ILC) to solve the trajectory tracking problem of systems using a network to transmit signals. Assuming that the relative quantization error of the logarithmic quantizer is white noise uniformly distributed in a known range, a cost function in the sense of mathematical expectation is established to deal with the relative quantization error, s...
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关键词
Learning systems,Quantization (signal),Trajectory tracking,Design methodology,White noise,Control systems,Encoding
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