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.

Browse

Author: search.filters.author.Blankenehip, Gilmer L.

Search Results

Now showing 1 - 10 of 23
  • Thumbnail Image
    Item
    Adaptive Control of Nonlinear Systems via Approximate Linearization
    (1993) Ghanadan, Reza; Blankenehip, Gilmer L.; ISR
    We present a direct adaptive tracking control scheme for nonlinear systems that do not have a well defined (vector) relative degree and hence are not feedback linearizable. This techniques uses feedback and coordinate changes to transform a nonlinear system with parameter uncertainty into an approximate input-output linearized one. Our result is also applicable to slightly non-minimum phase nonlinear systems with unknown parameters. We prove that the presented adaptive design scheme results in an asymptotically stable closed loop system and show that the controller can achieve adaptive tracking of reasonable trajectories with bounds on the tracking error. We also present a state regulation scheme based on state approximate linearization. We demonstrate the adaptive approximate tracking results using a simplified model of an aircraft which is slightly non-minimum phase. The usefulness of our approach is also illustrated on a "benchmark" example that is not feedback linearizable.
  • Thumbnail Image
    Item
    Reactive Operations Scheduling for Flexible Manufacturing Systems
    (1993) Dhingra, Jastej S.; Musser, K.L.; Blankenehip, Gilmer L.; ISR
    In this paper we present a reactive operations scheduling methodology for online control of manufacturing systems. We present description of the Texas Instruments electronic circuit board assembly unit at Johnson City, TN, which was used as a model for the development of the reactive operations scheduling scheme. Based on the manufacturing system model, we present the operations scheduling problem as a combinatorial optimization problem. We present a simulated annealing based predictive scheduling algorithm for feed-forward control of the manufacturing system. For reactive operations scheduling, the closed loop configuration consists of the simulated annealing based predictive scheduler and the manufacturing system model in the feed forward path, and a reactive re-scheduler in the feedback path. Deviations of the observed sequenced operation timings from the scheduled timings, quantified by a cost functional, are used to trigger the re-scheduling loop. The capabilities of the scheme are demonstrated using a discrete event simulation of the Texas Instruments manufacturing unit.
  • Thumbnail Image
    Item
    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.
  • Thumbnail Image
    Item
    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.
  • Thumbnail Image
    Item
    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.
  • Thumbnail Image
    Item
    Annealing Based Experiment in Scheduling
    (1991) Dhingra, Jastej S.; Musser, K.L.; Blankenehip, Gilmer L.; Ferguson, L.; ISR
    A scheduling software was developed for general job shop scheduling. It was implemented at a Texas Instruments electronic circuit board assembly facility. The assembly line scheduling problem is presented as an optimization problem. A variation of simulated annealing technique was used to find a solution to the optimization problem. A detailed description of the software is presented and various assembly line features which were incorporated in the software are discussed. Finally, an onsite evaluation is presented.
  • Thumbnail Image
    Item
    Optimization Based Job Shop Scheduling
    (1991) Musser, K.L.; Dhingra, Jastej S.; Blankenehip, Gilmer L.; ISR
    A generalized job shop scheduling problem is defined in detail. The proposed factory description is sufficiently realistic to model the routing and sequencing decisions made in a real manufacturing plant. An optimization problem is posed, permitting the use of very general cost functions. A variation of the method of simulated annealing is proposed as a tool for the solution of the optimization problem. A novel technique for embedding the space of feasible schedules into a permutation group is used to define a neighborhood structure for the simulated annealing process. This technique has algorithmic advantages over working directly in the space of schedules. These ideas were used to construct a scheduling software system which is in use at a Texas Instruments Custom Manufacturing Unit. We give a brief description of the software system, called ABES for Annealing Based Experiment in Scheduling, and comment on its effectiveness.
  • Thumbnail Image
    Item
    A Bound Approach to Asymptotic Optimality in Nonlinear Filtering of DifFusion Processes.
    (1987) Saydy, L.; Blankenehip, Gilmer L.; ISR
    The asymptotic behavior as a small parameter EPSILON --> 0 is investigated for one dimensional nonlinear filtering problems. Both weakly nonlinear systems (WNL) and systems measured through a low noise channel are considered. Upper and lower bounds on the optimal mean square error combined with perturbation methods are used to show that, in the case of WNL, the Kalman filter formally designed for the underlying linear systems is asymptotically optimal in some sense. In the case of systems with low measurement noise, three asymptotically optimal filters are provided, one of which is linear. Examples with simulation results are provided.
  • Thumbnail Image
    Item
    Optimal Stationary Behavior in Some Stochastic Nonlinear Filtering Problems- A Bound Approach.
    (1987) Saydy, L.; Blankenehip, Gilmer L.; ISR
    A lower and upper bound on the a priori optimal mean square error is used to study the stationary behavior of one dimensional nonlinear filters. The long time behavior as t--> INFINITY for asymptotically linear systems is investigated. Lower and upper bounds of the Riccati type are derived and it is shown that for nonlinear systems with linear limiting ones, the Kalman filter (KF) formally designed for the limiting systems is asymptotically optimal in some sense. Examples with simulation results are provided.
  • Thumbnail Image
    Item
    Asymptotic Behavior in Nonlinear Stochastic Filtering.
    (1987) Saydy, L.; Blankenehip, Gilmer L.; ISR
    A lower and upper bound approach on the optimal mean square error is used to study the asymptotic behavior of one dimensional nonlinear filters. Two aspects are treated: (1) The long time behavior (t --> INFINITY). (2) The asymptotic behavior as a small parameter EPSILON-->0. Lower and upper bounds that satisfy Riccati equations are derived and it is shown that for nonlinear systems with linear limiting systems, the Kalman filter designed for the limiting systems is asymptotically optimal in a reasonable sense. In the case of nonlinear systems with low measurement noise level, three asymptotically optimal filters are provided one of which is linear. In chapter 4, the stationary behavior of the Benes filter is investigated.