Statistical parameter estimation and uncertainty quantification for macro fiber composite actuators operating in nonlinear and hysteretic regimes

Macro Fiber Composites (MFC) are planar actuators comprised of PZT fibers embedded in an epoxy matrix that is sandwiched between electrodes. Due to their construction, they exhibit significant durability and flexibility in addition to being lightweight and providing broadband inputs. They are presently being considered for a range of applications including positioning and control of membrane mirrors and configurable aerospace structures. However, due to the noncentrosymmetric nature of PZT, MFC also exhibit hysteresis and constitutive nonlinearities that must be incorporated in models and control designs to achieve their full potential. In this paper, we discuss issues associated with the estimation of parameters and uncertainty quantification (UQ) for a distributed model that quantifies the hysteretic dynamics of the devices. Statistical parameter estimation techniques are used to construct densities for model parameters. These uncertainties are subsequently propagated though the model to construct error bounds.