Institute for Systems Research Technical Reports

Permanent URI for this collectionhttp://hdl.handle.net/1903/4376

This archive contains a collection of reports generated by the faculty and students of the Institute for Systems Research (ISR), a permanent, interdisciplinary research unit in the A. James Clark School of Engineering at the University of Maryland. ISR-based projects are conducted through partnerships with industry and government, bringing together faculty and students from multiple academic departments and colleges across the university.

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Author: search.filters.author.Blankenehip, Gilmer L.Subject: search.filters.subject.algorithms

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    On Adaptive Control of Non-Minimum Phase Nonlinear Systems
    (1992) Ghanadan, Reza; Blankenehip, Gilmer L.; ISR
    We present a technique of indirect adaptive control for approximate linearization of nonlinear systems based on approximate input-output linearization scheme recently proposed in [HSK92]. The controller can achieve adaptive tracking of reasonable trajectories with small error for slightly non-minimum phase systems. It can also be applied to nonlinear systems where the relative degree is not well defined. Simulation results are provided for the familiar ball and beam experiment under some parameter uncertainty.
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    Adaptive Output Tracking of Invertible MIMO Nonlinear Systems
    (1992) Ghanadan, Reza; Blankenehip, Gilmer L.; ISR
    In this paper we discuss some initial results on the adaptive tracking of MIMO nonlinear systems which do not have a well defined vector relative degree. First, we consider systems that are right-invertible with linear parametric uncertainty in their dynamics. Second, we consider the case where the system is not necessarily invertible. Simulation results for both schemes are presented.
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    Online Parameter Optimization for a Multi-Product, Multi-Machine Manufacturing System
    (1992) Dhingra, Jastej S.; Blankenehip, Gilmer L.; ISR
    We develop an algorithm based on Infinitesimal Perturbation Analysis for online optimization of a multi-product service facility composed of a network of multi-server machines, modeled using multi-class M/M/m queues. starting from the Robbins-Monro stochastic approximation method, we first develop an online, local optimization algorithm for a single multi-server machine. for the special case of Poisson arrivals and exponentially distributed service time in a multi-machine network, local optimization at individual machines leads to global optimization of the overall network. Simulation results for a single machine are compared to the exact analytical results. Application of the methodology for the optimization of a simple flexible manufacturing system is also presented.