Title page for ETD etd-04302008-110230

Type of Document Master's Thesis
Author Shimp III, Samuel Kline
Author's Email Address sshimp@vt.edu
URN etd-04302008-110230
Title Vehicle Sprung Mass Parameter Estimation Using an Adaptive Polynomial-Chaos Method
Degree Master of Science
Department Mechanical Engineering
Advisory Committee
Advisor Name Title
Southward, Steve C. Committee Chair
Ahmadian, Mehdi Committee Member
Sandu, Corina Committee Member
  • Polynomial-Chaos
  • adaptive parameter estimation
  • adaptive control
  • uncertainty propagation
  • stochastic modeling
Date of Defense 2008-04-18
Availability unrestricted
The polynomial-chaos expansion (PCE) approach to modeling provides an estimate of the probabilistic response of a dynamic system with uncertainty in the system parameters. A novel adaptive parameter estimation method exploiting the polynomial-chaos representation of a general quarter-car model is presented. Because the uncertainty was assumed to be concentrated in the sprung mass parameter, a novel pseudo mass matrix was developed for generating the state-space PCE model. In order to implement the PCE model in a real-time adaptation routine, a novel technique for representing PCE output equations was also developed. A simple parameter estimation law based on the output error between measured accelerations and PCE acceleration estimates was developed and evaluated through simulation and experiment. Simulation results of the novel adaptation algorithm demonstrate the estimation convergence properties as well as its limitations. The simulation results are further verified by a real-time experimental implementation on a quarter-car test rig. This work presents the first truly real-time implementation of a PCE model. The experimental real-time implementation of the novel adaptive PCE estimation method shows promising results by its ability to converge and maintain a stable estimate of the unknown parameter.
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