Online Parameter Estimation and Adaptive Control of Permanent-Magnet Synchronous Machines

By S. Underwood, I. Husain. IEEE transactions on industrial electronics (1982. Print), 2010

439 citations recorded by the source corpus.

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

Learning to Adapt: Meta-Learning for Model-Based Control (2018, background): “ists extensive prior work on online adaptation in modelbased reinforcement learning and adaptive control (Sastry and Isidori, 1989). In contrast from inverse model adaptation (Kelouwani et al., 2012; Underwood and Husain, 2010; Pastor et al., 2011; Meier et al., 2016; Meier and Schaal, 2016; Rai et ”
Learning to Adapt in Dynamic, Real-World Environments through Meta-Reinforcement Learning (2018, methodology): “In contrast from inverse model adaptation (Kelouwani et al., 2012; Underwood and Husain, 2010; Pastor et al., 2011; Meier et al., 2016; Meier and Schaal, 2016; Rai et al., 2017), we are concerned in the problem of adapting the forward model, closely related to online system identiﬁcation…”