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Journal of Advanced Mechanical Design, Systems, and Manufacturing, 2008 This paper describes the motion control of hyper redundant robots using a learning control scheme based on linear combination of error history. The learning control scheme is formulated with three elements: general solution of inverse kinematics with ...
Daisuke MATSUURA, Nobuyuki IWATSUKI
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Machine learning and control theory [PDF]
, 2022 We survey in this article the connections between Machine Learning and Control Theory. Control Theory provide useful concepts and tools for Machine Learning. Conversely Machine Learning can be used to solve large control problems. In the first part of the paper, we develop the connections between reinforcement learning and Markov Decision Processes ...
Alain Bensoussan +5 more
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Adaptive-Attentive Geolocalization From Few Queries: A Hybrid Approach
Frontiers in Computer Science, 2022 We tackle the task of cross-domain visual geo-localization, where the goal is to geo-localize a given query image against a database of geo-tagged images, in the case where the query and the database belong to different visual domains.
Valerio Paolicelli +5 more
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A new adaptive controller of facts-based FMRLC aimed at improving power system stability [PDF]
Serbian Journal of Electrical Engineering, 2008 Various control techniques using Advanced Super-conducting Magnetic Energy Storage (ASMES) aimed at improving power system stability have been proposed. As fuzzy controller has proved its value in some applications, the number of investigations employing
Abdellatif Naceri +2 more
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Secure energy efficiency: Power allocation and outage analysis for SWIPT-in-DAS based IoT
ICT Express, 2022 In this paper, we study secure energy efficiency (SEE) for simultaneous wireless information and power transfer (SWIPT) in a distributed antenna system (DAS) based IoT network.
Aaqib Bulla, Shahid M. Shah
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IEEE Access, 2021 A well-designed demand response (DR) program is essential in smart home to optimize energy usage according to user preferences. In this study, we proposed a multiobjective reinforcement learning (MORL) algorithm to design a DR program.
Song-Jen Chen, Wei-Yu Chiu, Wei-Jen Liu
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Learning Controllers for Industrial Robots [PDF]
Machine Learning, 1996 One of the most significant cost factors in robotics applications is the design and development of real-time robot control software. Control theory helps when linear controllers have to be developed, but it doesn’t sufficiently support the generation of non-linear controllers, although in many cases (such as in compliance control), nonlinear control is
Baroglio, C. +4 more
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Robust Tracking Control of Aerial Robots Via a Simple Learning Strategy-Based Feedback Linearization
IEEE Access, 2020 To facilitate accurate tracking in unknown/uncertain environments, this paper proposes a simple learning (SL) strategy for feedback linearization control (FLC) of aerial robots subject to uncertainties.
Mohit Mehndiratta +3 more
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On the Role of Models in Learning Control: Actor-Critic Iterative Learning Control
IFAC-PapersOnLine, 2020 6 pages, 4 figures, 21st IFAC World Congress ...
Poot, M.M., Portegies, Jim, Oomen, Tom
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On the Development of Learning Control for Robotic Manipulators
Robotics, 2017 Learning control for robotic manipulators has been developed over the past decade and to the best of the authors’ knowledge, it is still in its infant development stage; the authors believe that it will become one of the most promising directions in the ...
Dan Zhang, Bin Wei
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