Documents disponibles écrits par cet auteur

Combined H (infinity) -feedback control and iterative learning control design with application to nanopositioning systems / Brian E. Helfrich in IEEE Transactions on control systems technology, Vol. 18 N° 2 (Mars 2010) 

Public ISBD [article]  in IEEE Transactions on control systems technology > Vol. 18 N° 2 (Mars 2010) . - pp. 336-351 Titre : Combined H (infinity) -feedback control and iterative learning control design with application to nanopositioning systems Type de document : texte imprimé Auteurs : Brian E. Helfrich, Auteur ; Chibum Lee, Auteur ; Douglas A. Bristow, Auteur Année de publication : 2011 Article en page(s) : pp. 336-351 Note générale : Génie Aérospatial Langues : Anglais (eng) Mots-clés : Iterative  learning  control  (ILC)  Nanopositioning  Precision  motion  control  (PMC) Index. décimale : 629.1 Résumé : This paper examines a coordinated feedback and feedforward control design strategy for precision motion control (PMC) systems. It is assumed that the primary exogenous signals are repeated; including disturbances and references. Therefore, an iterative learning control (ILC) feedforward strategy can be used. The introduction of additional non-repeating exogenous signals, including disturbances, noise, and reset errors, necessitates the proper coordination between feedback and feedforward controllers to achieve high performance. A novel ratio of repeated versus non-repeated signal power in the frequency domain is introduced and defined as the repetitive-to-non-repetitive (RNR) ratio. This frequency specific ratio allows for a new approach to delegating feedback and feedforward control efforts based on RNR value. A systematic procedure for control design is given whereby the feedback addresses the non-repeating exogenous signal content (RNR ≪ 0 dB) and the feedforward ILC addresses the repeating signal content (RNR ≫ 0 dB). To illustrate the design approach, two case studies using different nano-positioning devices are given. DEWEY : 629.1 ISSN : 1063-6536 En ligne : http://ieeexplore.ieee.org/xpl/freeabs_all.jsp?arnumber=5169845 [article] Combined H (infinity) -feedback control and iterative learning control design with application to nanopositioning systems [texte imprimé] / Brian E. Helfrich, Auteur ; Chibum Lee, Auteur ; Douglas A. Bristow, Auteur . - 2011 . - pp. 336-351. Génie Aérospatial Langues : Anglais (eng) in IEEE Transactions on control systems technology > Vol. 18 N° 2 (Mars 2010) . - pp. 336-351 Mots-clés : Iterative  learning  control  (ILC)  Nanopositioning  Precision  motion  control  (PMC) Index. décimale : 629.1 Résumé : This paper examines a coordinated feedback and feedforward control design strategy for precision motion control (PMC) systems. It is assumed that the primary exogenous signals are repeated; including disturbances and references. Therefore, an iterative learning control (ILC) feedforward strategy can be used. The introduction of additional non-repeating exogenous signals, including disturbances, noise, and reset errors, necessitates the proper coordination between feedback and feedforward controllers to achieve high performance. A novel ratio of repeated versus non-repeated signal power in the frequency domain is introduced and defined as the repetitive-to-non-repetitive (RNR) ratio. This frequency specific ratio allows for a new approach to delegating feedback and feedforward control efforts based on RNR value. A systematic procedure for control design is given whereby the feedback addresses the non-repeating exogenous signal content (RNR ≪ 0 dB) and the feedforward ILC addresses the repeating signal content (RNR ≫ 0 dB). To illustrate the design approach, two case studies using different nano-positioning devices are given. DEWEY : 629.1 ISSN : 1063-6536 En ligne : http://ieeexplore.ieee.org/xpl/freeabs_all.jsp?arnumber=5169845

Optimizing learning convergence speed and converged error for precision motion control / Douglas A. Bristow in Transactions of the ASME . Journal of dynamic systems, measurement, and control, Vol. 130 N°5 (Septembre 2008) 

Public ISBD [article]  in Transactions of the ASME . Journal of dynamic systems, measurement, and control > Vol. 130 N°5 (Septembre 2008) . - 8 p. Titre : Optimizing learning convergence speed and converged error for precision motion control Type de document : texte imprimé Auteurs : Douglas A. Bristow, Auteur ; Alleyne, Andrew G., Auteur ; Marina Tharayil, Auteur Année de publication : 2008 Article en page(s) : 8 p. Note générale : dynamic systems Langues : Anglais (eng) Mots-clés : design;  errors;  filters;  iterative  learning  control;  accuracy;  motion  control Résumé : This brief paper considers iterative learning control (ILC) for precision motion control (PMC) applications. This work develops a methodology to design a low pass filter, called the Q-filter, that is used to limit the bandwidth of the ILC to prevent the propagation of high frequencies in the learning. A time-varying bandwidth Q-filter is considered because PMC reference trajectories can exhibit rapid changes in acceleration that may require high bandwidth for short periods of time. Time-frequency analysis of the initial error signal is used to generate a shape function for the bandwidth profile. Key parameters of the bandwidth profile are numerically optimized to obtain the best tradeoff in converged error and convergence speed. Simulation and experimental results for a permanent-magnet linear motor are included. Results show that the optimal time-varying Q-filter bandwidth provides faster convergence to lower error than the optimal time-invariant bandwidth. En ligne : http://dynamicsystems.asmedigitalcollection.asme.org/issue.aspx?journalid=117&is [...] [article] Optimizing learning convergence speed and converged error for precision motion control [texte imprimé] / Douglas A. Bristow, Auteur ; Alleyne, Andrew G., Auteur ; Marina Tharayil, Auteur . - 2008 . - 8 p. dynamic systems Langues : Anglais (eng) in Transactions of the ASME . Journal of dynamic systems, measurement, and control > Vol. 130 N°5 (Septembre 2008) . - 8 p. Mots-clés : design;  errors;  filters;  iterative  learning  control;  accuracy;  motion  control Résumé : This brief paper considers iterative learning control (ILC) for precision motion control (PMC) applications. This work develops a methodology to design a low pass filter, called the Q-filter, that is used to limit the bandwidth of the ILC to prevent the propagation of high frequencies in the learning. A time-varying bandwidth Q-filter is considered because PMC reference trajectories can exhibit rapid changes in acceleration that may require high bandwidth for short periods of time. Time-frequency analysis of the initial error signal is used to generate a shape function for the bandwidth profile. Key parameters of the bandwidth profile are numerically optimized to obtain the best tradeoff in converged error and convergence speed. Simulation and experimental results for a permanent-magnet linear motor are included. Results show that the optimal time-varying Q-filter bandwidth provides faster convergence to lower error than the optimal time-invariant bandwidth. En ligne : http://dynamicsystems.asmedigitalcollection.asme.org/issue.aspx?journalid=117&is [...]