 Electrical and Electronic Engineering  Research Publications
Electrical and Electronic Engineering  Research Publications
Permanent URI for this collection
Search Results
Now showing
1  10 of 227

ItemElectrical Stimulation of Neural Tissue Modeled as a Cellular Composite: Point Source Electrode in an Isotropic TissueMonfared, O ; Nesic, D ; Freestone, DR ; Grayden, DB ; Tahayori, B ; Meffin, H (IEEE, 20140101)Standard volume conductor models of neural electrical stimulation assume that the electrical properties of the tissue are well described by a conductivity that is smooth and homogeneous at a microscopic scale. However, neural tissue is composed of tightly packed cells whose membranes have markedly different electrical properties to either the intra or extracellular space. Consequently, the electrical properties of tissue are highly heterogeneous at the microscopic scale: a fact not accounted for in standard volume conductor models. Here we apply a recently developed framework for volume conductor models that accounts for the cellular composition of tissue. We consider the case of a point source electrode in tissue comprised of neural fibers crossing each other equally in all directions. We derive the tissue admittivity (that replaces the standard tissue conductivity) from single cell properties, and then calculate the extracellular potential. Our findings indicate that the cellular composition of tissue affects the spatiotemporal profile of the extracellular potential. In particular, the full solution asymptotically approaches a nearfield limit close to the electrode and a farfield limit far from the electrode. The nearfield and farfield approximations are solutions to standard volume conductor models, but differ from each other by nearly an order or magnitude. Consequently the full solution is expected to provide a more accurate estimate of electrical potentials over the full range of electrodeneurite separations.

ItemAveraging for nonlinear systems on Riemannian manifoldsTaringoo, F ; Nesic, D ; Tan, Y ; Dower, PM (IEEE, 2013)This paper provides a derivation of the averaging methods for nonlinear timevarying dynamical systems defined on Riemannian manifolds. We extend the results on ℝ n to Riemannian manifolds by employing the language of differential geometry.

ItemPWM hybrid control systems: averaging tools for analysis and designTeel, AR ; Nesic, D (IEEE, 2010)We consider averaging for a class of hybrid systems that are motivated by Pulse Width Modulated (PWM) implementation of hybrid control laws for general nonlinear plants. Rapid time variations in the flow map of a hybrid system generate solutions that are also solutions of a timeinvariant average hybrid system that is slightly perturbed. Results relating solutions of the timevarying system to solutions of the average system ensue. In the absence of finite escape times for the average system, on compact time domains each solution of the timevarying system is close to a solution of the average system. In the presence of asymptotic stability for the average system, the timevarying system exhibits semiglobal, practical asymptotic stability. These results rely on mild regularity properties for the average system. In particular, the average system is not required to exhibit unique solutions. Both periodic and nonperiodic flow maps are considered.

ItemLyapunov functions for L2 and inputtostate stability in a class of quantized control systemsTeel, AR ; Nesic, D (IEEE, 20110101)ℒ 2 and inputtostate stability (ISS) properties of a class of linear quantized control systems are considered. The quantized control system differs slightly from the ones considered in the literature previously. A recently proposed hybrid modeling framework and corresponding Lyapunov analysis tools are used to calculate the finite gains of the closed loop system.

ItemIdle speed control using linear time varying model predictive control and discrete time approximationsSharma, R ; Nesic, D ; Manzie, C (IEEE, 20100101)This paper addresses the problem of idle speed control of hydrogen fueled internal combustion engine (H2ICE) using model predictive control (MPC) and sampled data control (SDC) theories. In the first step, results from SDC theory and a version of MPC are collectively employed to obtain a rigorously developed new generic control strategy. Here, a controller, based on a family of approximate discrete time models, is designed within a previously proposed framework to have guaranteed practical asymptotic stability of the exact (unknown) discrete time model. Controller design, accomplished using MPC theory, is facilitated by successive online linearizations of the nonlinear discrete time model at each sampling instant. In the second step, the technique is implemented in the idle speed control of hydrogen internal combustion engine (H2ICE). Various conditions under which this theory can be implemented are presented and their validity for idle speed control problem are discussed. Simulations are presented to illustrate the effectiveness of the control scheme.

ItemReal time model predictive idle speed control of ultralean burn engines: Experimental resultsSharma, R ; Dennis, P ; Manzie, C ; Nešić, D ; Brear, MJ (IEEE, 20110101)

ItemNew Stability Criteria for Switched TimeVarying Systems: OutputPersistently Exciting ConditionsLee, TC ; Tan, Y ; Nesic, D (IEEE, 20110101)This paper proposes three tools to facilitate the verification of the outputpersistently exciting (OPE) condition and simultaneously, provides new asymptotic stability criteria for uniformly globally stable switched systems. By introducing some related reference systems, the OPE condition of the original system can be reduced or simplified. Both the ideas of classic LaSalle invariance principle and nested Matrosov theorem are used to generate such reference systems. The effectiveness and flexibility of the proposed methods are demonstrated by two applications. From these applications, it can be seen that the flexibility of the proposed method produces a novel set of tools for checking uniform asymptotic stability of switched timevarying systems.

ItemExtremum seeking control for nonlinear systems on compact Riemannian manifoldsTaringoo, F ; Nesic, D ; Tan, Y ; DOWER, PM (IEEE Press, 2014)This paper formulates the extremum seeking control problem for nonlinear dynamical systems which evolve on Riemannian manifolds and presents stability results for a class of numerical algorithms defined in this context. The results are obtained based upon an extension of extremum seeking algorithms in Euclidean spaces and a generalization of Lyapunov stability theory for dynamical systems defined on Rimannian manifolds. We employ local properties of Lyapunov functions to extend the singular perturbation analysis on Riemannian manifolds. Consequently, the results of the singular perturbation on manifolds are used to obtain the convergence of extremum seeking algorithms for dynamical systems on Riemannian manifolds.

ItemExtremum Seeking From 1922 To 2010Tan, Y ; Moase, WH ; Manzie, C ; Nesic, D ; Mareels, IMY ; Chen, J (IEEE, 20100101)Extremum seeking is a form of adaptive control where the steadystate inputoutput characteristic is optimized, without requiring any explicit knowledge about this inputoutput characteristic other than that it exists and that it has an extremum. Because extremum seeking is model free, it has proven to be both robust and effective in many different application domains. Equally being model free, there are clear limitations to what can be achieved. Perhaps paradoxically, although being model free, extremum seeking is a gradient based optimization technique. Extremum seeking relies on an appropriate exploration of the process to be optimized to provide the user with an approximate gradient, and hence the means to locate an extremum. These observations are elucidated in the paper. Using averaging and timescale separation ideas more generally, the main behavioral characteristics of the simplest (model free) extremum seeking algorithm are established.

ItemCoordination of blind agents on Lie groupsTaringoo, F ; Nesic, D ; DOWER, P ; Tan, Y (IEEE, 2015)This paper presents an algorithm for the synchronization of blind agents evolving on a connected Lie group. We employ the method of extremum seeking control for nonlinear dynamical systems defined on connected Riemannian manifolds to achieve the synchronization among the agents. This approach is independent of the underlying graph of the system and each agent updates its position on the connected Lie group by only receiving the synchronization cost function.