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Polynomial Chaos Based Design of Robust Input Shapers
Authors
Singh, T., Singla, P. and Konda, U.
Source
ASME Journal of Dynamic Systems, Measurement and Control,
132(5).
Abstract
A probabilistic approach, which exploits the domain and distribution of the uncertain
model parameters, has been developed for the design of robust input shapers. Polynomial
chaos expansions are used to approximate uncertain system states and cost functions in
the stochastic space. Residual energy of the system is used as the cost function to design
robust input shapers for precise rest-to-rest maneuvers. An optimization problem, which
minimizes any moment or combination of moments of the distribution function of the
residual energy is formulated. Numerical examples are used to illustrate the benefit of
using the polynomial chaos based probabilistic approach for the determination of robust
input shapers for uncertain linear systems. The solution of polynomial chaos based
approach is compared with the minimax optimization based robust input shaper design
approach, which emulates a Monte Carlo process.
@article{Singh10_DSMC2,
Author = {T. Singh, P. Singla and U. Konda},
Journal = {ASME Journal for Dynamic Systems, Measurement and Control},
Month = {March},
Title = {Polynomial Chaos Based Design of Robust Input Shapers},
Volume = {132},
Number = {5},
Year = {2010}
}
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