A Reinforcement Learning Control in Hot Stamping for Cycle Time Optimization. [PDF]
Materials (Basel), 2022 Nievas N +6 more
europepmc +1 more source
Scaling Reinforcement Learning Paradigms for Motor Control
, 2003 Reinforcement learning offers a general framework to explain rewardrelated learning in artificial and biological motor control. However, current reinforcement learning methods rarely scale to high dimensional movement systems and mainly operate in ...
Vijayakumar, S.; id_orcid +2 more
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Organizing planning knowledge for automated vehicles and intelligent transportation systems
IET Intelligent Transport SystemsIntelligent Transportation Systems (ITS) are crucial for developing fully automated vehicles. While significant progress has been made with advanced driver assistance systems and automation technology, challenges remain, such as improving traffic ...
David Yagüe‐Cuevas +3 more
doaj +1 more source
Fixed-Time Recurrent NN Learning Control of Uncertain Robotic Manipulators with Time-Varying Constraints: Experimental Verification. [PDF]
Sensors (Basel), 2023 Shi Q, Li C, He R, Zhu X, Duan X.
europepmc +1 more source
Iterative Learning Control Applied to a Gantry Robot and Conveyor System
, 2010 Synchronisation is routinely required to coordinate the actions of the various sub-systems involved in process applications. This is commonly achieved through direct mechanical coupling, involving gears, drive belts and cams.
Ratcliffe, James +3 more
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Learning of Iterative Learning Control for Flexible Manufacturing of Batch Processes. [PDF]
ACS Omega, 2022 Xu L +5 more
europepmc +1 more source
VET transition : support online learning at university
, 2011 In the research of VET transition a significant literature focuses on pathway and student academic literacy support (Aird et al. 2010, Willcoxson, 2010).
Catterall, Janice (R12324) +2 more
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A Hybrid Controller for a Soft Pneumatic Manipulator Based on Model Predictive Control and Iterative Learning Control. [PDF]
Sensors (Basel), 2023 Dai Y, Deng Z, Wang X, Yuan H.
europepmc +1 more source
Learning the Globally Optimal Distributed LQ Regulator
We study model-free learning methods for the output-feedback Linear Quadratic (LQ) control problem in finite-horizon subject to subspace constraints on the control policy.
Kamgarpour, Maryam +2 more
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