Bettering operation of Robots by learning

By S. Arimoto, S. Kawamura, F. Miyazaki. 1984

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Citations in the corpus

Reinforcement learning in robotics: A survey (2013, neutral): “This approach is known as iterative learning control (Arimoto et al., 1984).”
Discrete-time inverse model-based iterative learning control: stability, monotonicity and robustness (2005, methodology): “…ILC uses information from previous executions of the task in an attempt to improve performance from repetition to repetition in the sense that the tracking error (between the output and a specified reference trajectory) is sequentially reduced to zero (see Arimoto et al. (1984) and Moore (1993)).”
Experimentally verified generalized KYP Lemma based iterative learning control design (2016, background): “Since the original work, widely credited to (Arimoto et al., 1984), ILC has remained as a significant area of control systems research with, especially for linear model based designs, many algorithms experimentally verified in the research laboratory and applied in industrial and other applications.”
Internal-model-based design of repetitive and iterative learning controllers for linear multivariable systems (2000, background): “In the literature, two types of compensators can be found which accomplish this: the repetitive controller (see, e.g. Inoue et al. 1981, Hara et al. 1988, Tomizuka et al. 1989, Sadegh 1991) , and the iterative learning controller (see, e.g. Arimoto et al. 1984, Bondi et al. 1988, Moore et al. 1992).”
Convergence Properties of Iterative Learning Control Processes in the Sense of the Lebesgue‐P Norm (2012, background): “, f m(t)]T and a real number >0, the -norm is defined in [6] as:”
A stochastic iterative learning control algorithm with application to an induction motor (2004, background): “Subsequent to the work initiated by Arimoto et al. (1984), iterative learning control systems have generated considerable research interests both in theoretical and experimental domains.”
Model-based iterative learning control with a quadratic criterion for time-varying linear systems (2000, unknown): “Examples of this type include D-type (Arimoto et al., 1984), PID-type (Bondi, Casalino & Gambradella, 1988), and their variants.”
Observer-based iterative learning control for a class of time-varying nonlinear systems (2003, background): “1 In fact, several contributions have been made, since the work of [2], toward improving ILC performance and relaxing ILC design constraints.”
Learning-based identification and iterative learning control of direct-drive robots (2005, methodology): “After being introduced in robotics [16], ILC has evolved into a control discipline utilizing a number of algorithms [1], [13], [14], [17]–[19].”
Trajectory generation and control for precise aggressive maneuvers with quadrotors (2012, methodology): “It is difﬁcult to accurately model these effects so we iterate on experimental trials to achieve the goal state G using a form of iterative learning (Arimoto et al. 1984).”
Dual-stage Optimal Iterative Learning Control for Nonlinear Non-affine Discrete-time Systems (2007, unknown): “The iterative learning control (ILC) was originally presented for robot applications[ 1 ].”
On Iterative Learning Control of parabolic distributed parameter systems (2009, methodology): “Iterative Learning Control (ILC) is a relatively new control technique originally proposed for the operation of mechanical robots carrying out repetitive trajectory tracking tasks (see, e.g., [ 1 ]).”
A survey of iterative learning control (2006, methodology): “systems can be found in [5], [36], [115].”
2-D analysis for iterative learning controller for discrete-time systems with variable initial conditions (2003, background): “Because of its appealing ability, various schemes of ILC have been proposed [1-13].”