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101A Advanced PID Control
Robust Control I
Real Circumstances and Expectation for
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actual adaptive algorithm analysis Application approach approximate bound condition considered constant constraints control system defined described Detection determined developed distribution dynamic effect efficient Electric element Engineering equation error estimation evaluated example exists expressed Figure filter force frequency function fuzzy gain given IEEE improved initial input Inst Japan learning length linear manipulator matrix means Measurement method neural network noise nonlinear nonlinear systems object observer obtained operation optimal output parameters performance phase plant position predictive presented problem proposed reference region Research respectively response robot robust sampling satisfying sensor shown shows SICE signal similar simulation solution sound stability step structure Table Tech technique theory tion Tokyo Tottori tracking traffic Trans Univ University variable vector weighting