Date of Award
Summer 8-2010
Document Type
Thesis
Degree Name
Master of Science (MS)
Department
Electrical and Computer Engineering
First Advisor
Schneider, Susan
Second Advisor
Yaz, Edwin
Third Advisor
Jeong, Chung Seop
Abstract
Control theory has generally been divided into two categories, modern control and classical control. Modern control uses state feedback to alter the pole locations of a given system. Classical control uses pre-compensation to alter the zeroes of the system and uses output feedback to adjust the poles to bring stability to the system. The drawback is that the application of classical control techniques can be a lengthy, complicated and iterative design process and in the end, classical control techniques still do not give information about the state of the system. Neoclassical control combines classical control techniques with the state feedback approach of modern control to stabilize the system, eliminate the steady state error, provide relevant internal state information, and reduce the time it takes to design the controller.
This thesis explores the application of neoclassical control to discrete-time systems. The mass-spring-damper, magnetic levitation, and ball and beam systems are discretized using the zero-order-hold or the Euler approximation. State-feedback control is used to modify the pole locations for these systems. A discrete-time integrator is put in series to eliminate the steady-state error for a step input. The pre-compensator is also put in series to replace the numerator of the open-loop system with a desired numerator. The unit output-feedback is then used to close the loop. The closed-loop system will have a step response which matches the discrete-time optimal ITAE, Bessel, or Butterworth transfer functions.
An observer is added to estimate the state of the plant in this work. The observer is applied to the discrete-time mass-spring-damper, the magnetic levitation, and the ball and beam systems in such a way that the error in the state estimate will be driven to zero within the desired period of time. This will allow the application of this controller to systems when the state is not known or measurable.