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Iterative Learning Control×Klizno-režimska kontrola×
OblastTeorija upravljanjaTeorija upravljanja
PorodicaMachine learningMachine learning
Godina nastanka19841977
TvoracSuguru ArimotoVadim Utkin
Tipalgorithmalgorithm
Temeljni izvorArimoto, S., Kawamura, S., & Miyazaki, F. (1984). Bettering operation of robots by learning. Journal of Robotic Systems, 1(2), 123-140. DOI ↗Utkin, V. I. (1977). Variable structure systems with sliding modes. IEEE Transactions on Automatic Control, 22(2), 212-222. DOI ↗
Drugi naziviILC, Learning Control, Repetitive ControlSMC, Variable Structure Control, Robust Control with Discontinuities
Srodne44
SažetakIterative Learning Control (ILC) is a control method for systems that perform the same task repeatedly (trajectory tracking over a fixed time interval). The key idea is to use error information from previous trials to update the input for the next trial, progressively improving tracking accuracy. Pioneered by Arimoto et al. in 1984, ILC is ideal for robotic manufacturing, semiconductor processing, and any application where the same motion must be repeated many times with high precision.Sliding Mode Control (SMC) is a robust nonlinear control technique that forces a system to follow a predetermined surface (the sliding surface) in state space by using discontinuous (bang-bang or high-frequency switching) control inputs. Developed by Utkin and further advanced by Slotine, SMC is remarkably insensitive to parameter variations and disturbances—once the system reaches the sliding surface, its behavior is determined solely by the surface geometry, not by uncertainty. This makes SMC powerful for nonlinear systems, manipulators, and uncertain systems where robustness is paramount.
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ScholarGateUporedite metode: Iterative Learning Control · Sliding Mode Control. Preuzeto 2026-06-15 sa https://scholargate.app/sr/compare