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


Document Type


Student Type


Degree Name

Computer Engineering (MS)

Department, Program, or Center

Computer Engineering (KGCOE)


Juan C. Cockburn

Advisor/Committee Member

Raymond Ptucha

Advisor/Committee Member

Mark Hopkins


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


RIT – Main Campus

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