Design of computer experiments applied to modeling of compliant mechanisms for real-time control
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2013-07-01
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SPRINGER
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This article discusses the use of design of computer experiments (DOCE) (i.e., experiments run with a computer model to find how a set of inputs affects a set of outputs) to obtain a force-displacement meta-model (i.e., a mathematical equation that summarizes and aids in analyzing the input-output data of a DOCE) of compliant mechanisms (CMs). The procedure discussed produces a force-displacement meta-model, or closed analytic vector function, that aims to control CMs in real-time. In our work, the factorial and space-filling DOCE meta-model of CMs is supported by finite element analysis (FEA). The protocol discussed is used to model the HexFlex mechanism functioning under quasi-static conditions. The HexFlex is a parallel CM for nano-manipulation that allows six degrees of freedom (x, y, z, ? x, ? y, ? z ) of its moving platform. In the multi-linear model fit of the HexFlex, the products or interactions proved to be negligible, yielding a linear model (i.e., linear in the inputs) for the operating range. The accuracy of the meta-model was calculated by conducting a set of computer experiments with random uniform distribution of the input forces. Three error criteria were recorded comparing the meta-model prediction with respect to the results of the FEA experiments by determining: (1) maximum of the absolute value of the error, (2) relative error, and (3) root mean square error. The maximum errors of our model are lower than high-precision manufacturing tolerances and are also lower than those reported by other researchers who have tried to fit meta-models to the HexFlex mechanism. © 2012 Springer-Verlag London Limited.
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Design of computer experiments, High-precision manufacturing, Metamodeling, Plackett-Burman designs, Quasi-static conditions, Root mean square errors, Six degrees of freedom, Uniform design, Compliant mechanisms, Design of experiments, Experiments, Finite element method, Knowledge management, Mean square error, Mechanical engineering, Mechanisms, Real time control, Mathematical models