Electrical and Electronic Engineering - Research Publications

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    Stability properties of reset systems
    Nešić, D ; Zaccarian, L ; Teel, AR (Elsevier, 2005-01-01)
    Stability properties for a class of reset systems, such as systems containing a Clegg integrator, are investigated. We present Lyapunov based results for verifying L2 and exponential stability of reset systems. Our results generalize the available results in the literature and can be easily modified to cover Lp stability for arbitrary p ∈ [1;∞]. Several examples illustrate that introducing resets in a linear system may reduce the L2 gain if the reset controller parameters are carefully tuned.
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    NONLINEAR SAMPLED DATA CONTROLLER REDESIGN VIA LYAPUNOV FUNCTIONS
    Grüne, L ; Neŝić, D (Elsevier BV, 2005)
    We provide results for redesign of Lyapunov function based continuous time controllers for sampled-data implementation, using a particular form of the redesigned controller and the Taylor expansion of the sampled-data Lyapunov difference. We develop two types of redesigned controllers that (i) make the lower order terms (in T) in the series expansion of the Lyapunov difference with the redesigned controller more negative and (ii) make the terms in the Taylor expansions of the Lyapunov difference for the sampled-data system with the redesigned controller behave as close as possible to the respective values of the continuous-time system with the original controller. Simulation studies illustrate the performance of our controllers.
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    Nonlinear sampled-data observer design via approximate discrete-time models and emulation
    Arcak, M ; Nešić, D (Elsevier, 2005-01-01)
    We study observer design for sampled-data nonlinear systems using two approaches: (i) the observer is designed via an approximate discrete-time model of the plant; (ii) the observer is designed based on the continuous-time plant model and then discretized for sampled-data implementation (emulation). in each case we present Lyapunov conditions under which the observer design guarantees semiglobal practical convergence for the unknown exact discrete-time model. The semiglobal region of attraction is expanded by decreasing the sampling period. The practical convergence set is shrunk by decreasing either the sampling period, or a modelling parameter which refines the accuracy of the approximate model.
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    Networked control systems: An emulation approach to controller design
    Nešić, D (Elsevier BV, 2007-01-01)
    We overview our recent work on a design approach for networked control systems (NCS) that resembles controller emulation for sampled-data systems. In the first step, we design a controller ignoring the network and, in the second step, we implement the designed controller over the network with sufficiently fast transmissions and a given protocol. Our results have several features: (i) they apply to general nonlinear systems with disturbances; (ii) we obtain explicit (often non-conservative) bounds on the maximal allowable transmission interval that guarantee stability; (iii) and we show that this approach is valid for a wide range of network scheduling protocols. This provides a flexible framework for design of NCS that is amenable to various extensions and modifications, such as a treatment of dropouts and stochastic protocols, combined controller/protocol design for linear plants, and so on.
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    A note on input-to-state stability of sampled-data nonlinear systems
    Teel, AR ; Nesic, D ; Kokotovic, PV (IEEE, 1998)
    It is shown for nonlinear systems that sampling sufficiently fast an input-to-state stabilizing (ISS) continuous time control law results in an ISS sampled-data control law. Two main features of our approach are: we show how the nonlinear sampled-data system can be modeled by a functional differential equation (FDE); we exploit a Razumikhin type theorem for ISS of FDE that was recently proved in [14] to analyze the sampled-data system.
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    Output stabilization of nonlinear systems: Linear systems with positive outputs as a case study
    Nesic, D ; Sontag, ED (IEEE, 1998)
    The problem of stabilization of linear systems for which only the magnitudes of outputs are measured is studied. A stabilizing controller is constructed which is input to state stability (ISS)-robust with respect to observation noise. Modal analysis and theorems are presented to prove the stabilization properties of the controller.
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    Estimating the unmeasured membrane potential of neuronal populations from the EEG using a class of deterministic nonlinear filters
    Chong, M ; Postoyan, R ; Nesic, D ; Kuhlmann, L ; Varsavsky, A (IOP PUBLISHING LTD, 2012-04)
    We present a model-based estimation method to reconstruct the unmeasured membrane potential of neuronal populations from a single-channel electroencephalographic (EEG) measurement. We consider a class of neural mass models that share a general structure, specifically the models by Stam et al (1999 Clin. Neurophysiol. 110 1801-13), Jansen and Rit (1995 Biol. Cybern. 73 357-66) and Wendling et al (2005 J. Clin. Neurophysiol. 22 343). Under idealized assumptions, we prove the global exponential convergence of our filter. Then, under more realistic assumptions, we investigate the robustness of our filter against model uncertainties and disturbances. Analytic proofs are provided for all results and our analyses are further illustrated via simulations.
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    Non-linear automatic target tracking in clutter using dynamic Gaussian mixture
    Musicki, D ; Song, TL ; Kim, WC ; Nesic, D (Institution of Engineering and Technology, 2012-12-01)
    This study presents a complete algorithm for single target tracking in clutter, which addresses simultaneously: nonlinear measurements; uncertain target detections; presence of random clutter measurements; and uncertain target existence. Proposed algorithm generalises the integrated track splitting (ITS) filter by extending the ITS functionality to highly nonlinear measurements. The non-linear target tracking and estimation problems may also be solved by application of particle filters, albeit incurring a significant computational expense relative to proposed solution. In an environment without data association uncertainties proposed filter becomes a non-linear estimator.
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    Electrical probing of cortical excitability in patients with epilepsy
    Freestone, DR ; Kuhlmann, L ; Grayden, DB ; Burkitt, AN ; Lai, A ; Nelson, TS ; Vogrin, S ; Murphy, M ; D'Souza, W ; Badawy, R ; Nesic, D ; Cook, MJ (ACADEMIC PRESS INC ELSEVIER SCIENCE, 2011-12)
    Standard methods for seizure prediction involve passive monitoring of intracranial electroencephalography (iEEG) in order to track the 'state' of the brain. This paper introduces a new method for measuring cortical excitability using an electrical probing stimulus. Electrical probing enables feature extraction in a more robust and controlled manner compared to passively tracking features of iEEG signals. The probing stimuli consist of 100 bi-phasic pulses, delivered every 10 min. Features representing neural excitability are estimated from the iEEG responses to the stimuli. These features include the amplitude of the electrically evoked potential, the mean phase variance (univariate), and the phase-locking value (bivariate). In one patient, it is shown how the features vary over time in relation to the sleep-wake cycle and an epileptic seizure. For a second patient, it is demonstrated how the features vary with the rate of interictal discharges. In addition, the spatial pattern of increases and decreases in phase synchrony is explored when comparing periods of low and high interictal discharge rates, or sleep and awake states. The results demonstrate a proof-of-principle for the method to be applied in a seizure anticipation framework. This article is part of a Supplemental Special Issue entitled The Future of Automated Seizure Detection and Prediction.
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    Input-to-state stability for a class of hybrid dynamical systems via averaging
    Wang, W ; Nesic, D ; Teel, AR (Springer, 2012-02)
    Input-to-state stability (ISS) properties for a class of time-varying hybrid dynamical systems via averaging method are considered. Two definitions of averages, strong average and weak average, are used to approximate the time-varying hybrid systems with time-invariant hybrid systems. Closeness of solutions between the time-varying system and solutions of its weak or strong average on compact time domains is given under the assumption of forward completeness for the average system. We also show that ISS of the strong average implies semi-global practical (SGP)-ISS of the actual system. In a similar fashion, ISS of the weak average implies semi-global practical derivative ISS (SGP-DISS) of the actual system. Through a power converter example, we show that the main results can be used in a framework for a systematic design of hybrid feedbacks for pulse-width modulated control systems.