For the fourth-order scheme, the dominant first-order error component is reduced by the grid adaptation, while the design-order error component drastically increases because of the grid nonuniformity.
We first present a controller design for biaxial feed drive systems that enables assignment of controller gains, for reducing the error component orthogonal to the desired contour curve, independent of the tangential error component.
An additive time series method divides the analysis into three parts: a trend, a cyclic, and a random error component.
The turbulence closure model is the dominant source of error in most Reynolds-Averaged Navier Stokes simulations, yet no reliable estimators for this error component currently exist.
The contour error, which is defined as the error component orthogonal to the desired contour curve, is a good indicator of machining precision.
Each error component can be afforded a separate weighting such that a cost or value of the forecast can be calculated that accounts for different error types.
Because the contour error is more important than the tracking error with respect to each feed drive, the contour error component is included in the proposed sliding surface.
Mixed logit, error component models show that reference-dependent models best describe the choice data, and we find that consumer choice is significantly affected by the experiment manipulations.
The results show that the wavelength of each profile error component is a main affecting factor on the error averaging effect.
Fluid films usually show obvious error averaging effect on each profile error component when the wavelength λ is shorter than twice of the pad length 2lu.
This method not only increases the stiffness of the sensitive error component, but also changes the layout of the machine tool based on dynamic sensitivity analysis results.
