Date of Award

12-2010

Degree Name

Master of Science in Engineering

Department

Mechanical and Aeronautical Engineering (to 2013)

First Advisor

Dr. James W. Kamman

Second Advisor

Dr. Rameshwar P. Sharma

Third Advisor

Dr. Kapseong Ro

Access Setting

Masters Thesis-Campus Only

Abstract

General technologies in engineering fields currently involve control processes. Present control theories and process optimizations are able to exploit system models to reduce input of resources and increase productivity. This work explores mainstream modeling techniques for the development of dynamic models. Black-box modeling is used to develop data-based models. The first principles of physics are used to model dynamic relationships during white-box modeling. Signal optimization techniques are used to tune simulated process responses and model parameters. The developed models use gain scheduling for the dynamic tuning of the model parameters with lookup tables. Furthermore, models are demonstrated to be suitable for controller development and model based control. Controllers developed using linear control theory is compared to nonlinear controller based on Lyapunov stability.

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