Neural Network Dynamics for Model-Based Deep Reinforcement Learning with Model-Free Fine-Tuning
, 2017 Model-free deep reinforcement learning algorithms have been shown to be capable of learning a wide range of robotic skills, but typically require a very large number of samples to achieve good performance.
Fearing, Ronald S. +3 more
core +1 more source
Model Pengendalian Demam Berdarah Dengue [PDF]
, 2013 Demam Berdarah Dengue (DBD) adalah penyakit berbasis vektor yang menjadi masalah kesehatan masyarakat di negara-negara tropis termasuk Indonesia. Penelitian ini bertujuan memprediksi kejadian DBD berdasarkan faktor iklim yang meliputi curah hujan ...
Fidayanto, R. (Ringga) +3 more
core +5 more sources
IEEE Access, 2021 The four-switch three-phase (FSTP) inverters are known for their cost-effective advantages and minimal switching losses. However, such inverter topology’s progress is lagging due to control constraints and requirements, including voltage vector ...
Crestian Almazan Agustin +4 more
doaj +1 more source
Decentralized model predictive control for smooth coordination of automated vehicles at intersection [PDF]
, 2015 International audienceWe consider the problem of coordinating a set of automated vehicles at an intersection with no traffic light. The priority-based coordination framework is adopted to separate the problem into a priority assignment problem and a ...
de La Fortelle, Arnaud +3 more
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Model-based design of transverse wall oscillations for turbulent drag reduction
, 2012 Over the last two decades, both experiments and simulations have demonstrated that transverse wall oscillations with properly selected amplitude and frequency can reduce turbulent drag by as much as 40%.
Jovanović, Mihailo R., Moarref, Rashad
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Vanilla PP for Philosophers: A Primer on Predictive Processing [PDF]
, 2017 The goal of this short chapter, aimed at philosophers, is to provide an overview and brief explanation of some central concepts involved in predictive processing (PP). Even those who consider themselves experts on the topic may find it helpful to see how
Metzinger, Thomas, Wiese, Wanja
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Improved Model-Free Predictive Control of a Three-Phase Inverter
EnergiesModel predictive control (MPC) performance depends on the accuracy of the system model. Moreover, the optimization algorithm of MPC requires numerous online computations.
Muhammad Nauman, Wajiha Shireen
doaj +1 more source
Multiple Loop Self-Triggered Model Predictive Control for Network Scheduling and Control
, 2015 We present an algorithm for controlling and scheduling multiple linear time-invariant processes on a shared bandwidth limited communication network using adaptive sampling intervals.
Henriksson, Erik +4 more
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Aerial navigation in obstructed environments with embedded nonlinear model predictive control
, 2018 We propose a methodology for autonomous aerial navigation and obstacle avoidance of micro aerial vehicles (MAV) using nonlinear model predictive control (NMPC) and we demonstrate its effectiveness with laboratory experiments. The proposed methodology can
andersson +5 more
core +1 more source
Wireless model-based predictive networked control system over cooperative wireless network [PDF]
, 2010 Owing to their distributed architecture, networked control systems (NCSs) are proven to be feasible in scenarios where a spatially distributed feedback control system is required. Traditionally, such NCSs operate over real-time wired networks.
Gurbuz, Ozgur +3 more
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