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  • About
  • The Global ETD Search service is a free service for researchers to find electronic theses and dissertations. This service is provided by the Networked Digital Library of Theses and Dissertations.
    Our metadata is collected from universities around the world. If you manage a university/consortium/country archive and want to be added, details can be found on the NDLTD website.
1

Learning to control

Potts, Duncan, Computer Science & Engineering, Faculty of Engineering, UNSW January 2007 (has links)
This thesis examines whether it is possible for a machine to incrementally build a complex model of its environment, and then use this model for control purposes. Given a sequence of noisy observations, the machine forms a piecewise linear approximation to the nonlinear dynamic equations that are assumed to describe the real world. A number of existing online system identification techniques are examined, but it is found that they all either scale poorly with dimensionality, have a number of parameters that make them difficult to apply, or do not learn sufficiently accurate approximations. Therefore a novel framework is developed for learning linear model trees in both batch and online settings. The algorithms are evaluated empirically on a number of commonly used benchmark datasets, a simple test function, and three dynamic domains ranging from a simple pendulum to a complex flight simulator. The new batch algorithm is compared with three state-of-the-art algorithms and is seen to perform favourably overall. The new incremental model tree learner also compares well with a recent online function approximator from the literature. Armed with a tool for effectively constructing piecewise linear models of the environment, a control framework is developed that learns trajectories from a demonstrator and attempts to follow these trajectories within each linear region usinglinear quadratic control. The induced controllers are able to swing up and balance a simple forced pendulum both in simulation and in the real world. They can also swing up and balance a real double pendulum. The induced controllers are empirically shown to perform better than the original demonstrator, and could therefore be used to either replace a human operator or improve upon an existing automatic controller. In addition an ability to generalise the learnt trajectories enables the system to perform novel tasks. This is demonstrated on a flight simulator where, having observed an aircraft flying several times around a circuit, the controller is able to copy the take-off procedure, fly a completely new circuit that includes new manoeuvres, and successfully land the plane.
2

A comparison of methods for multivariable control synthesis

White, Robert Lee, 1940- January 1964 (has links)
No description available.
3

On a problem of parameter identification in a distributed system

Aziz, Sajid. January 1978 (has links)
No description available.
4

An investigation of singular optimal control problems

Scardina, John Anthony 05 1900 (has links)
No description available.
5

A design procedure based on the quadratic performance index and linear least squares approximations

Peterson, David Eric 05 1900 (has links)
No description available.
6

A study of the characteristics of control systems designed using the quadratic index of performance

Bell, Charles James 08 1900 (has links)
No description available.
7

Learning to control

Potts, Duncan, Computer Science & Engineering, Faculty of Engineering, UNSW January 2007 (has links)
This thesis examines whether it is possible for a machine to incrementally build a complex model of its environment, and then use this model for control purposes. Given a sequence of noisy observations, the machine forms a piecewise linear approximation to the nonlinear dynamic equations that are assumed to describe the real world. A number of existing online system identification techniques are examined, but it is found that they all either scale poorly with dimensionality, have a number of parameters that make them difficult to apply, or do not learn sufficiently accurate approximations. Therefore a novel framework is developed for learning linear model trees in both batch and online settings. The algorithms are evaluated empirically on a number of commonly used benchmark datasets, a simple test function, and three dynamic domains ranging from a simple pendulum to a complex flight simulator. The new batch algorithm is compared with three state-of-the-art algorithms and is seen to perform favourably overall. The new incremental model tree learner also compares well with a recent online function approximator from the literature. Armed with a tool for effectively constructing piecewise linear models of the environment, a control framework is developed that learns trajectories from a demonstrator and attempts to follow these trajectories within each linear region usinglinear quadratic control. The induced controllers are able to swing up and balance a simple forced pendulum both in simulation and in the real world. They can also swing up and balance a real double pendulum. The induced controllers are empirically shown to perform better than the original demonstrator, and could therefore be used to either replace a human operator or improve upon an existing automatic controller. In addition an ability to generalise the learnt trajectories enables the system to perform novel tasks. This is demonstrated on a flight simulator where, having observed an aircraft flying several times around a circuit, the controller is able to copy the take-off procedure, fly a completely new circuit that includes new manoeuvres, and successfully land the plane.
8

Sensitivity analysis of cam-and-follower mechanism at high speeds

Yang, Shyuan-Bai. January 1981 (has links)
Thesis (M.S.)--Ohio University, June, 1981. / Title from PDF t.p.
9

Robust control via higher order trajectory sensitivity minimization

Chopra, Avnish. January 1994 (has links)
Thesis (M.S.)--Ohio University, March, 1994. / Title from PDF t.p.
10

Controller performance monitoring for constrained systems /

Huang, Lilong, January 2004 (has links)
Thesis (Ph. D.)--Lehigh University, 2005. / Includes vita. Includes bibliographical references (leaves 187-194).

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