FRINK Linked Data Fragments server

Matches in SemOpenAlex for { <https://semopenalex.org/work/W3010920281> ?p ?o ?g. }

• W3010920281 endingPage "178" @default.
• W3010920281 startingPage "167" @default.
• W3010920281 abstract "Model-based predictive controllers are used to tackle control tasks in which constraints on state, input or both need to be satisfied. These controllers commonly optimize a fixed finite-horizon cost, which relates to an infinite-horizon (IH) cost profile, while the resulting closed-loop under the predictive controller yields an in general suboptimal IH cost. To capture the optimal IH cost and the associated control policy, reinforcement learning methods, such as Q-learning, that approximate said cost via a parametric architecture can be employed. Conversely to predictive controllers, however, closed-loop stability has rarely been investigated under the approximation associated controller in explicit dependence of these parameters. It is the aim of this work to incorporate model-based Q-learning into a predictive control setup as to provide closed-loop stability in online learning, while eventually improving the performance of finite-horizon controllers. The proposed scheme provides nominal asymptotic stability and the observation was made that the suggested learning approach could in fact improve the performance against a baseline predictive controller." @default.
• W3010920281 created "2020-03-23" @default.
• W3010920281 creator A5050202669 @default.
• W3010920281 creator A5065280230 @default.
• W3010920281 creator A5067098516 @default.
• W3010920281 date "2020-11-01" @default.
• W3010920281 modified "2023-09-24" @default.
• W3010920281 title "A Q-learning predictive control scheme with guaranteed stability" @default.
• W3010920281 cites W1493395914 @default.
• W3010920281 cites W173093232 @default.
• W3010920281 cites W1976277608 @default.
• W3010920281 cites W1978956894 @default.
• W3010920281 cites W1979760373 @default.
• W3010920281 cites W1983089547 @default.
• W3010920281 cites W1983523797 @default.
• W3010920281 cites W2005437559 @default.
• W3010920281 cites W2006859604 @default.
• W3010920281 cites W2013895638 @default.
• W3010920281 cites W2027968610 @default.
• W3010920281 cites W2041109651 @default.
• W3010920281 cites W2041185529 @default.
• W3010920281 cites W2045332133 @default.
• W3010920281 cites W2048687352 @default.
• W3010920281 cites W2050838777 @default.
• W3010920281 cites W2062915697 @default.
• W3010920281 cites W2067390368 @default.
• W3010920281 cites W2072931156 @default.
• W3010920281 cites W2090643498 @default.
• W3010920281 cites W2091565802 @default.
• W3010920281 cites W2093831009 @default.
• W3010920281 cites W2107726111 @default.
• W3010920281 cites W2114669221 @default.
• W3010920281 cites W2115304548 @default.
• W3010920281 cites W2132858840 @default.
• W3010920281 cites W2133289369 @default.
• W3010920281 cites W2134882417 @default.
• W3010920281 cites W2139418546 @default.
• W3010920281 cites W2139595765 @default.
• W3010920281 cites W2142493442 @default.
• W3010920281 cites W2150339816 @default.
• W3010920281 cites W2151088727 @default.
• W3010920281 cites W2154077222 @default.
• W3010920281 cites W2161009228 @default.
• W3010920281 cites W2165545652 @default.
• W3010920281 cites W2165726932 @default.
• W3010920281 cites W2168027532 @default.
• W3010920281 cites W2329769476 @default.
• W3010920281 cites W2462102501 @default.
• W3010920281 cites W2476930474 @default.
• W3010920281 cites W2767143830 @default.
• W3010920281 cites W2822752092 @default.
• W3010920281 cites W2887344203 @default.
• W3010920281 cites W2900691863 @default.
• W3010920281 cites W2900806034 @default.
• W3010920281 cites W2901005637 @default.
• W3010920281 cites W2963393268 @default.
• W3010920281 cites W2964171912 @default.
• W3010920281 cites W3041202696 @default.
• W3010920281 cites W3101479673 @default.
• W3010920281 cites W32403112 @default.
• W3010920281 doi "https://doi.org/10.1016/j.ejcon.2020.03.001" @default.
• W3010920281 hasPublicationYear "2020" @default.
• W3010920281 type Work @default.
• W3010920281 sameAs 3010920281 @default.
• W3010920281 citedByCount "9" @default.
• W3010920281 countsByYear W30109202812021 @default.
• W3010920281 countsByYear W30109202812022 @default.
• W3010920281 crossrefType "journal-article" @default.
• W3010920281 hasAuthorship W3010920281A5050202669 @default.
• W3010920281 hasAuthorship W3010920281A5065280230 @default.
• W3010920281 hasAuthorship W3010920281A5067098516 @default.
• W3010920281 hasConcept C105795698 @default.
• W3010920281 hasConcept C112972136 @default.
• W3010920281 hasConcept C117251300 @default.
• W3010920281 hasConcept C119857082 @default.
• W3010920281 hasConcept C121332964 @default.
• W3010920281 hasConcept C126255220 @default.
• W3010920281 hasConcept C127413603 @default.
• W3010920281 hasConcept C133731056 @default.
• W3010920281 hasConcept C134306372 @default.
• W3010920281 hasConcept C154945302 @default.
• W3010920281 hasConcept C158622935 @default.
• W3010920281 hasConcept C159176650 @default.
• W3010920281 hasConcept C167964875 @default.
• W3010920281 hasConcept C172205157 @default.
• W3010920281 hasConcept C203479927 @default.
• W3010920281 hasConcept C2524010 @default.
• W3010920281 hasConcept C2775924081 @default.
• W3010920281 hasConcept C33923547 @default.
• W3010920281 hasConcept C41008148 @default.
• W3010920281 hasConcept C47446073 @default.
• W3010920281 hasConcept C62520636 @default.
• W3010920281 hasConcept C6557445 @default.
• W3010920281 hasConcept C77618280 @default.
• W3010920281 hasConcept C86803240 @default.
• W3010920281 hasConcept C91575142 @default.
• W3010920281 hasConcept C97541855 @default.
• W3010920281 hasConceptScore W3010920281C105795698 @default.

• next