YaBeSH Engineering and Technology Library

    • Journals
    • PaperQuest
    • YSE Standards
    • YaBeSH
    • Login
    View Item 
    •   YE&T Library
    • ASME
    • Journal of Dynamic Systems, Measurement, and Control
    • View Item
    •   YE&T Library
    • ASME
    • Journal of Dynamic Systems, Measurement, and Control
    • View Item
    • All Fields
    • Source Title
    • Year
    • Publisher
    • Title
    • Subject
    • Author
    • DOI
    • ISBN
    Advanced Search
    JavaScript is disabled for your browser. Some features of this site may not work without it.

    Archive

    Predictor Based Adaptive Output Feedback Control: Application to Functional Electrical Stimulation of a Human Arm Model

    Source: Journal of Dynamic Systems, Measurement, and Control:;2016:;volume( 138 ):;issue: 011::page 111014
    Author:
    Nguyen, Chuong H.
    ,
    Leonessa, Alexander
    DOI: 10.1115/1.4033863
    Publisher: The American Society of Mechanical Engineers (ASME)
    Abstract: A simulation study to control the motion of a human arm using muscle excitations as inputs is presented to validate a recently developed adaptive output feedback controller for a class of unknown multiinput multioutput (MIMO) systems. The main contribution of this paper is to extend the results of Nguyen and Leonessa (2014, “Adaptive PredictorBased Output Feedback Control for a Class of Unknown MIMO Linear Systems,â€‌ ASME Paper No. DSCC20146214; 2014, “Adaptive PredictorBased Output Feedback Control for a Class of Unknown MIMO Linear Systems: Experimental Results,â€‌ ASME Paper No. DSCC20146217; and 2015, “Adaptive PredictorBased Output Feedback Control for a Class of Unknown MIMO Systems: Experimental Results,â€‌ American Control Conference, pp. 3515–3521) by combining a recently developed fast adaptation technique and a new controller structure to derive a simple approach for a class of high relative degree uncertain systems. Specifically, the presented control approach relies on three components: a predictor, a reference model, and a controller. The predictor is designed to predict the systems output for any admissible control input. A full state feedback control law is then derived to control the predictor output to approach the reference system. The control law avoids the recursive stepbystep design of backstepping and remains simple regardless of the system relative degree. Ultimately, the control objective of driving the actual system output to track the desired trajectory is achieved by showing that the system output, the predictor output, and the reference system trajectories all converge to each other. Thelen and Millard musculotendon models (Thelen, D. G., 2003, “Adjustment of Muscle Mechanics Model Parameters to Simulate Dynamic Contractions in Older Adults,â€‌ ASME J. Biomech. Eng., 125(1), pp. 70–77; Millard, M, Uchida, T, Seth, A, and Delp, Scott L., 2013, “Flexing Computational Muscle: Modeling and Simulation of Musculotendon Dynamics,â€‌ ASME J. Biomech. Eng., 135(2), p. 021005) are used to validate the proposed controller fast tracking performance and robustness.
    • Download: (1.632Mb)
    • Show Full MetaData Hide Full MetaData
    • Get RIS
    • Item Order
    • Go To Publisher
    • Price: 5000 Rial
    • Statistics

      Predictor Based Adaptive Output Feedback Control: Application to Functional Electrical Stimulation of a Human Arm Model

    URI
    http://yetl.yabesh.ir/yetl1/handle/yetl/160761
    Collections
    • Journal of Dynamic Systems, Measurement, and Control

    Show full item record

    contributor authorNguyen, Chuong H.
    contributor authorLeonessa, Alexander
    date accessioned2017-05-09T01:27:19Z
    date available2017-05-09T01:27:19Z
    date issued2016
    identifier issn0022-0434
    identifier otherds_138_11_111014.pdf
    identifier urihttp://yetl.yabesh.ir/yetl/handle/yetl/160761
    description abstractA simulation study to control the motion of a human arm using muscle excitations as inputs is presented to validate a recently developed adaptive output feedback controller for a class of unknown multiinput multioutput (MIMO) systems. The main contribution of this paper is to extend the results of Nguyen and Leonessa (2014, “Adaptive PredictorBased Output Feedback Control for a Class of Unknown MIMO Linear Systems,â€‌ ASME Paper No. DSCC20146214; 2014, “Adaptive PredictorBased Output Feedback Control for a Class of Unknown MIMO Linear Systems: Experimental Results,â€‌ ASME Paper No. DSCC20146217; and 2015, “Adaptive PredictorBased Output Feedback Control for a Class of Unknown MIMO Systems: Experimental Results,â€‌ American Control Conference, pp. 3515–3521) by combining a recently developed fast adaptation technique and a new controller structure to derive a simple approach for a class of high relative degree uncertain systems. Specifically, the presented control approach relies on three components: a predictor, a reference model, and a controller. The predictor is designed to predict the systems output for any admissible control input. A full state feedback control law is then derived to control the predictor output to approach the reference system. The control law avoids the recursive stepbystep design of backstepping and remains simple regardless of the system relative degree. Ultimately, the control objective of driving the actual system output to track the desired trajectory is achieved by showing that the system output, the predictor output, and the reference system trajectories all converge to each other. Thelen and Millard musculotendon models (Thelen, D. G., 2003, “Adjustment of Muscle Mechanics Model Parameters to Simulate Dynamic Contractions in Older Adults,â€‌ ASME J. Biomech. Eng., 125(1), pp. 70–77; Millard, M, Uchida, T, Seth, A, and Delp, Scott L., 2013, “Flexing Computational Muscle: Modeling and Simulation of Musculotendon Dynamics,â€‌ ASME J. Biomech. Eng., 135(2), p. 021005) are used to validate the proposed controller fast tracking performance and robustness.
    publisherThe American Society of Mechanical Engineers (ASME)
    titlePredictor Based Adaptive Output Feedback Control: Application to Functional Electrical Stimulation of a Human Arm Model
    typeJournal Paper
    journal volume138
    journal issue11
    journal titleJournal of Dynamic Systems, Measurement, and Control
    identifier doi10.1115/1.4033863
    journal fristpage111014
    journal lastpage111014
    identifier eissn1528-9028
    treeJournal of Dynamic Systems, Measurement, and Control:;2016:;volume( 138 ):;issue: 011
    contenttypeFulltext
    DSpace software copyright © 2002-2015  DuraSpace
    نرم افزار کتابخانه دیجیتال "دی اسپیس" فارسی شده توسط یابش برای کتابخانه های ایرانی | تماس با یابش
    yabeshDSpacePersian
     
    DSpace software copyright © 2002-2015  DuraSpace
    نرم افزار کتابخانه دیجیتال "دی اسپیس" فارسی شده توسط یابش برای کتابخانه های ایرانی | تماس با یابش
    yabeshDSpacePersian