learning control

learning control

[′lərn·iŋ kən‚trōl]
(control systems)
A type of automatic control in which the nature of control parameters and algorithms is modified by the actual experience of the system.
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Thrilling experiences with a strong emotional impact, and an excellent way of learning control and safety in even the most extreme road conditions.
She wants her readers to know she and the other storytellers in her book "get it," and that it's possible to take over control of PTSD through strategies such as therapy, joining a community, learning control techniques, taking medication, and more.
Iterative Learning Control is an intelligent control strategy to deal with repetitive processes.
As we know, iterative learning control is based upon the idea that the performance of a system that performs the same task repeatedly can be improved by learning from previous iterations [20].
In [5, 6], the iterative learning control was applied to deal with the consensus problem of multiagent systems, while the same problem was studied by using linear quadratic regulator (LQR) in [7, 8].
(i) Lebesgue-p norm convergence analysis of PD"-type iterative learning control for fractional order nonlinear systems,
Carroll is learning control in the one-wall venue, and after losing the first game 21-11, he trounced Polanco 21-4 in Game 2.
[8.] Suzuki, T., Zhu, C., Sakai, T., and Okada, Y., "Power Assistance of an Omnidirectional Hybrid Walker and Wheelchair with Admittance Model and Iterative Learning Control, " Presented at IEEE 13th International Workshop on Advanced Motion Control (AMC) 2014, March 2014, doi: 10.1109/AMC.2014.6823323.
Yang, "Parameter-dependent Lyapunov function-based robust iterative learning control for discrete systems with actuator faults," International Journal of Adaptive Control and Signal Processing, vol.
Ho et al., "Iterative learning control with initial rectifying action for nonlinear continuous systems," Control Theory & Applications, vol.
Graphical profile generation [18], wave-form profiles [19], iterative learning control [20], and discrete-time command profiles [21] were all used to produce shaped commands for crane maneuvers involving simultaneous travel and hoist.

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