Faculty Advisor or Committee Member

Mikhail F. Dimentberg, Advisor

Faculty Advisor or Committee Member

Suzanne L. Weekes, Committee Member

Faculty Advisor or Committee Member

Zhikun Hou, Committee Member

Faculty Advisor or Committee Member

Raymond R. Hagglund, Committee Member

Faculty Advisor or Committee Member

John J. Sullivan, Committee Member

Identifier

etd-0525101-111407

Abstract

In this dissertation, certain problems of stochastic optimal control and relevant analysis of random vibrations are considered. Dynamic Programming approach is used to find an optimal control law for a linear single-degree-of-freedom system subjected to Gaussian white-noise excitation. To minimize a system's mean response energy, a bounded in magnitude control force is applied. This approach reduces the problem of finding the optimal control law to a problem of finding a solution to the Hamilton-Jacobi-Bellman (HJB) partial differential equation. A solution to this partial differential equation (PDE) is obtained by developed 'hybrid' solution method. The application of bounded in magnitude control law will always introduce a certain type of nonlinearity into the system's stochastic equation of motion. These systems may be analyzed by the Energy Balance method, which introduced and developed in this dissertation. Comparison of analytical results obtained by the Energy Balance method and by stochastic averaging method with numerical results is provided. The comparison of results indicates that the Energy Balance method is more accurate than the well-known stochastic averaging method.

Publisher

Worcester Polytechnic Institute

Degree Name

PhD

Department

Mechanical Engineering

Project Type

Dissertation

Date Accepted

2001-05-25

Accessibility

Unrestricted

Subjects

Stochastic Optimal Control, Dynamic Programming, Hamilton-Jacobi-Bellman equation, Random Vibration, Energy Balance method, Vibration, Control theory, Mathematical optimization, Stochastic control theory

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