Abstract

Reduced cost of sensors and increased computing power is enabling

the development and implementation of control systems that can

simultaneously regulate multiple variables and handle conflicting

objectives while maintaining stringent performance objectives. To

make this a reality, practical analysis and design tools must be developed

that allow the designer to trade-off conflicting objectives and

guarantee performance in the presence of uncertain system dynamics,

an uncertain environment, and over a wide range of operating

conditions. As a first step towards this goal, we organize and streamline

a promising robust control approach, Robust Linear Parameter

Varying control, which integrates three fields of control theory: Integral

Quadratic Constraints (IQC) to characterize uncertainty and

nonlinearities, Linear Parameter Varying systems (LPV) that formalizes

gain-scheduling, and convex optimization to solve the resulting

robust control Linear Matrix Inequalities (LMI).

To demonstrate the potential of this approach, it was applied to

the design of a robust linear parametrically varying controller for an

ecosystem with nonlinear predator-prey-hunter dynamics.

Library of Congress Subject Headings

Programmable controllers--Design; Linear systems--Design

Publication Date

2-2014

Document Type

Thesis

Student Type

Graduate

Degree Name

Computer Engineering (MS)

Department, Program, or Center

Computer Engineering (KGCOE)

Advisor

Juan C. Cockburn

Advisor/Committee Member

Raymond Ptucha

Advisor/Committee Member

Mark Hopkins

Comments

Physical copy available from RIT's Wallace Library at TJ223.P76 K46 2014

Campus

RIT – Main Campus

Plan Codes

CMPE-MS

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