Electrical and Electronic Engineering - Research Publications

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    TRACKING AND REGRET BOUNDS FOR ONLINE ZEROTH-ORDER EUCLIDEAN AND RIEMANNIAN OPTIMIZATION
    Maass, A ; Manzie, C ; Nesic, D ; Manton, JH ; Shames, I (SIAM PUBLICATIONS, 2022)
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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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    Online optimization of spark advance in alternative fueled engines using extremum seeking control
    Mohammadi, A ; Manzie, C ; Nesic, D (Elsevier, 2014-08-01)
    Alternative fueled engines offer greater challenges for engine control courtesy of uncertain fuel composition. This makes optimal tuning of input parameters like spark advance extremely difficult in most existing ECU architectures. This paper proposes the use of grey-box extremum seeking techniques to provide real-time optimization of the spark advance in alternative fueled engines. Since practical implementation of grey-box extremum seeking methods is typically done using digital technology, this paper takes advantage of emulation design methods to port the existing continuous-time grey-box extremum seeking methods to discrete-time frameworks. The ability and flexibility of the proposed discrete-time framework is demonstrated through simulations and in practical situation using a natural gas fueled engine.
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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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    Sampled Data Model Predictive Idle Speed Control of Ultra-Lean Burn Hydrogen Engines
    Sharma, R ; Nesic, D ; Manzie, C (Institute of Electrical and Electronics Engineers, 2013-03-01)
    A model-based approach for the idle speed control of ultra-lean burn engines is presented. The results from model predictive control (MPC) are extended and collectively used with the existing sampled data control theory to obtain a rigorously developed idle speed control strategy. Controller is designed using MPC theory and facilitated by successive online linearizations of the nonlinear discrete-time model at each sampling instant. Simultaneously, the approximations due to the discretization of the nonlinear engine model are explicitly considered by designing the control within a previously proposed control design framework to obtain appropriate stability guarantees of an exact (unknown) discrete-time engine model. The proposed idle speed control method is experimentally validated on a prototype 6-cylinder hydrogen engine.