Online Tracking of Varying Inertia using a SDFT Approach

The mechanical dynamics of modern machines very often depend on the angular position of the driven axis. To obtain optimal control, such applications typically require an advanced control structure such as an adaptive controller. Moreover, the variation in the dynamics like changing inertia, load torque, and viscous friction limits the performance and reduces the energy efficiency. Energy savings can be obtained by using so-called trajectory optimization techniques combined with feedforward control. However, both optimization and adaptive control require the knowledge of the position dependency of the mechanical parameters. In the case of reciprocating mechanisms, for instance, this position dependency is significant. Consequently, the mechanical parameters change rapidly at high operating speed of the machine. This paper thus contributes towards fast and accurate estimation of rapidly varying mechanical parameters. A sliding discrete Fourier transform (SDFT) approach is proposed to track the inertia variation of a reciprocating mechanism online. The feasibility is verified with experiments on an industrial pick and place unit. Both the results on the real machine and its CAD equivalent, modelled in a multibody dynamics software package, are considered. In addition, the developed inertia tracking algorithm is proven to be implementable in standard commercial drive components.