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Switched manual pursuit tracking to measure motor performance in Parkinson's disease

IET CONTROL THEORY AND APPLICATIONS 2011年第17期5卷 1970-1977页

作者： Ashoori, A. McKeown, M. J. Oishi, M. M. K. Univ British Columbia Dept Elect & Comp Engn Vancouver BC V5Z 1M9 Canada Univ British Columbia Dept Neurol Vancouver BC V5Z 1M9 Canada

Control theoretic measures are proposed to assess motor performance in Parkinson's disease (PD), a neurodegenerative disorder that impairs motor skills, speech, and aspects of cognition. Ten normal and 14 PD subjects performed a series of manual pursuit tracking tasks: three tasks were first performed separately, then as a merged sequence with sudden, unenunciated task changes. The tasks differed in whether the tracking errors appeared amplified, attenuated or unaltered. From the discrete block experiments, subject- and task-specific second-order, linear time invariant models were derived, with the trajectory subjects are asked to track as input and the subject's motor response as output. Multiple model adaptive estimation was employed on the merged sequences to determine whether, and with what delay, each subject modified their performance after a task change. Although all normal subjects detected the task change, less than one-third of PD subjects did (and with longer delay). Further, those PD subjects who detected the task change had estimators with higher damping ratio than those PD subjects who did not. Since cerebellar structures may affect damping ratio, and the basal ganglia are often associated with switching behaviour, the proposed method provides a comprehensive assessment of motor structures that may be affected in PD.

关键词： diseases cognition linear systems Parkinson disease basal ganglia linear time invariant model damping ratio adaptive control medical control systems switched manual pursuit tracking neuro-degenerative disorder cerebellar structure control theoretic measure Self-adjusting control systems Biological and medical control systems multiple model adaptive estimation motor performance

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Fundamental Issues in Manual Control Cybernetics

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IFAC-PapersOnLine 2016年第19期49卷 1-6页

作者： Mulder, M. Pool, D.M. Abbink, D.A. Boer, E.R. van Paassen, M.M. Control and Simulation Faculty of Aerospace Engineering TU Delft DelftHS2629 Netherlands Biomechanical Engineering Faculty of 3ME TU Delft DelftCD2628 Netherlands

Manual control cybernetics aims to understand and describe how humans control vehicles and devices, such that more effective human-machine interfaces can be designed. Current cybernetics theory is primarily based on technology and analysis methods developed in the 1960s and has shown to be limited in its capability to capture the full breadth of human cognition and control. This paper summarizes some of the main fundamental limitations in cybernetics and provides a possible road-map to advance the theory and its applications. Central in this agenda will be a shift from the current linear time-invariant modeling approach, to the use of linear parameter-varying system models. Recent progress in identification methods of these latter models may allow us, for the first time, to mathematically model and identify time-varying, adaptive human control, opening up many opportunities to systematically optimize our human control interfaces and training. New foundations for cybernetics will impact all domains that involve humans in manual and semi-automatic control. © 2016

关键词： Cybernetics Automation linear systems Manual control models Control vehicles Dynamic behaviours Fundamental limitations Human Machine Interface Identification method linear parameter varying systems linear time invariant model Semi automatic control

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Application of Input and State Multiple model Adaptive Estimator for Aircraft Airspeed Approximation

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IFAC-PapersOnLine 2016年第17期49卷 76-81页

作者： Bauer, Péter Baár, Tamás Péni, Tamás Vanek, Bálint Bokor, József MTA SZTAKI Systems and Control Lab Budapest1111 Hungary

This paper addresses the problem of state estimation in the presence of unknown inputs if the system is dependent on an uncertain parameter. Multiple model Adaptive Estimation is applied to state and unknown input observers. The theory is evaluated on an aircraft airspeed estimator algorithm. The developed algorithm is based-on linear time invariant (LTI) models of an aircraft linearized at distinct airspeed values. Separate Kalman Filters are designed for aircraft LTI models, run parallel, and the airspeed estimate is the weighted sum of the airspeed estimates provided by the Kalman Filters. linear and nonlinear test simulations without and with measurement noise proved that the developed algorithm is able to provide accurate airspeed estimates. © 2016

关键词： Kalman filters State estimation Uncertainty analysis Adaptive estimators Estimator algorithms linear time invariant model Multiple model adaptive estimation State Uncertain parameters Unknown input estimation Unknown input observer

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LPV System Local model Interpolation Based on Combined model Reduction

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IFAC-PapersOnLine 2018年第15期51卷 1104-1109页

作者： Zhang, Qinghua Inria IFSTTAR Université de Rennes Campus de Beaulieu Rennes Cedex35042 France

The local approach to linear parameter varying (LPV) system identification consists in interpolating a collection of linear time invariant (LTI) models, which have been estimated from data acquired at different working points of a nonlinear system. Interpolation is essential in this approach. When the local LTI models are in state-space form, as each local model can be estimated with an arbitrary state basis, it is widely acknowledged that the local models should be made coherent before their interpolation. In order to avoid the delicate task of making local state-space models coherent, a new interpolation method of local state-space models is proposed in this paper, which does not require coherent local models. This method is based on the reduction of the large state-space model built by combining the local models. Numerical examples are presented to illustrate the effectiveness of this method. © 2018

关键词： Interpolation Numerical methods Religious buildings State space methods Interpolation method linear parameter varying systems linear time invariant model Local model Local state space LPV systems State space models State space form

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The effects of uncertainties on the control performance of sewer networks

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WATER SCIENCE AND TECHNOLOGY 1997年第5期36卷 309-315页

作者： Methot, JF Pleau, M ASSEAU INC QUEBEC CITYPQ G1P 2J7CANADA

The effects of uncertainties on the performance of a Certainty Equivalent Open Loop Feedback Control approach is investigated throughout simulations of the Quebec Urban Community Sewer Network. The optimization algorithm is based on nonlinear programming with the peculiarity that all the constraints are linear. The hydraulic routine is a linear time invariant (LTI) model associated to a Kalman filter. Preliminary results show the benefit of adding a filtering action to guarantee robust performance in the presence of measurement errors and model mismatch. The selected control scheme seems to be a good compromise between the short computational time required for Real time Control applications and the high performance expected in the presence of uncertainties. (C) 1997 IAWQ. Published by Elsevier Science Ltd.

关键词： Kalman filter linear time invariant model minimization of CSO nonlinear programming overflow volume real time control sewer network

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