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Sketching is more than making correct drawings [PDF]
, 2011 Sketching in the context of a design process is not a goal in itself, but can be considered as a tool to\ud make better designs. Sketching as a design tool has several useful effects as: ordering your thoughts,\ud better understanding of difficult shapes,
Eggink, Wouter +2 more
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Synchronization of Fractional-Order Reaction–Diffusion Neural Networks via ETILC
Fractal and FractionalThis paper focuses on the synchronization of fractional-order reaction–diffusion neural networks (FORDNN) under sampling event-triggered iterative learning control.
Xisheng Dai +4 more
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Data loss for PLC of nonlinear systems Iterative Learning Control Algorithm
MATEC Web of Conferences, 2016 When we use power line as data carrier, due to the complexity of the PLC network environment, data packet loss frequently, so the paper deal with the iterative learning control for a class of nonlinear systems with measurement dropouts in the PLC, and ...
Zhang Yinjun +3 more
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Optimized Iterative Learning Control for Linear Discrete-Time-Invariant Systems
IEEE Access, 2019 In this paper, an optimized first-order iterative learning control (OILC) scheme is explored for a class of linear discrete-time-invariant systems with Markov parameters available and the system relative degree being unity.
Yan Liu, Xiaoe Ruan, Xiaohui Li
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Inferential Iterative Learning Control: A 2D-system approach
Automatica, 2016 zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Bolder, J.J., Oomen, T.A.E.
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Probabilistic Guarantees for Safe Deep Reinforcement Learning
, 2020 Deep reinforcement learning has been successfully applied to many control tasks, but the application of such agents in safety-critical scenarios has been limited due to safety concerns.
E Ohn-Bar +14 more
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Tracking Control of Electronic Cam Trajectory based on the Electromagnetic Linear Actuator
Jixie chuandong, 2017 An electronic cam based on the electromagnetic linear actuator is proposed,by tracking the given trajectory to realize the required linear motion law and substitute the traditional cam mechanism.
Wang Cai, Chang Siqin
doaj
Discrete Dynamics in Nature and Society, 2016 We propose an iterative learning control algorithm (ILC) that is developed using a variable forgetting factor to control a mobile robot. The proposed algorithm can be categorized as an open-closed-loop iterative learning control, which produces control ...
Hongbin Wang, Jian Dong, Yueling Wang
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GPU Based Path Integral Control with Learned Dynamics [PDF]
, 2015 We present an algorithm which combines recent advances in model based path integral control with machine learning approaches to learning forward dynamics models.
Daniel, Tom +2 more
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Learning Lyapunov (Potential) Functions from Counterexamples and Demonstrations
, 2017 We present a technique for learning control Lyapunov (potential) functions, which are used in turn to synthesize controllers for nonlinear dynamical systems.
Ravanbakhsh, Hadi +1 more
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