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Position control of servomotors using neural dynamic sliding mode / A. Karami-Mollaee in Transactions of the ASME . Journal of dynamic systems, measurement, and control, Vol. 133 N° 6 (Novembre 2011) 

Public ISBD [article]  in Transactions of the ASME . Journal of dynamic systems, measurement, and control > Vol. 133 N° 6 (Novembre 2011) . - 10 p. Titre : Position control of servomotors using neural dynamic sliding mode Type de document : texte imprimé Auteurs : A. Karami-Mollaee, Auteur ; N. Pariz, Auteur ; H. M. Shanechi, Auteur Année de publication : 2012 Article en page(s) : 10 p. Note générale : Dynamic systems Langues : Anglais (eng) Mots-clés : Adaptive  control  Learning  (artificial  intelligence)  Machine  control  Neurocontrollers  Nonlinear  control  systems  PI  control  Position  control  Radial  basis  function  networks  Robust  control  Servomotors  State  feedback  Variable  structure  systems Index. décimale : 553 Géologie économique. Minérographie. Minéraux. Formation et gisements de minerais Résumé : In this paper, position control of servomotors is addressed. A radial basis function neural network is employed to identify the unknown nonlinear function of the plant model, and then a robust adaptive law is developed to train the parameters of the neural network, which does not require any preliminary off-line weight learning. Moreover, base on the identified model, we propose a new dynamic sliding mode control (DSMC) for a general class of nonaffine nonlinear systems by defining a new adaptive proportional-integral sliding surface and employing a linear state feedback. The main property of proposed controller is that it does not need an upper bound for the uncertainty and identified model; moreover, the switching gain increases and decreases according to the system circumstance by employing an adaptive procedure. Then, chattering is removed completely by using the DSMC with a small switching gain. DEWEY : 553 ISSN : 0022-0434 En ligne : http://asmedl.org/getabs/servlet/GetabsServlet?prog=normal&id=JDSMAA000133000006 [...] [article] Position control of servomotors using neural dynamic sliding mode [texte imprimé] / A. Karami-Mollaee, Auteur ; N. Pariz, Auteur ; H. M. Shanechi, Auteur . - 2012 . - 10 p. Dynamic systems Langues : Anglais (eng) in Transactions of the ASME . Journal of dynamic systems, measurement, and control > Vol. 133 N° 6 (Novembre 2011) . - 10 p. Mots-clés : Adaptive  control  Learning  (artificial  intelligence)  Machine  control  Neurocontrollers  Nonlinear  control  systems  PI  control  Position  control  Radial  basis  function  networks  Robust  control  Servomotors  State  feedback  Variable  structure  systems Index. décimale : 553 Géologie économique. Minérographie. Minéraux. Formation et gisements de minerais Résumé : In this paper, position control of servomotors is addressed. A radial basis function neural network is employed to identify the unknown nonlinear function of the plant model, and then a robust adaptive law is developed to train the parameters of the neural network, which does not require any preliminary off-line weight learning. Moreover, base on the identified model, we propose a new dynamic sliding mode control (DSMC) for a general class of nonaffine nonlinear systems by defining a new adaptive proportional-integral sliding surface and employing a linear state feedback. The main property of proposed controller is that it does not need an upper bound for the uncertainty and identified model; moreover, the switching gain increases and decreases according to the system circumstance by employing an adaptive procedure. Then, chattering is removed completely by using the DSMC with a small switching gain. DEWEY : 553 ISSN : 0022-0434 En ligne : http://asmedl.org/getabs/servlet/GetabsServlet?prog=normal&id=JDSMAA000133000006 [...]