Nonlinear identification and optimal feedforward friction compensation for a motion platform

Abstract

We present a method of nonlinear identification and optimal feedforward friction compensation procedure for an industrial single degree of freedom motion platform. The platform suffers from nonlinear dynamic effects, such as friction and backlash in the driveline, along with precise reference tracking requirements. In order to eliminate the nonlinear dynamic effects and obtain precise reference tracking, we first identified the system using nonparametric identification with Best Linear Approximation (BLA). Next, the feedback controller is implemented as a classical PI controller and it is designed using loop shaping techniques so that the system meets the linear system requirements. Then, we identified the nonlinear dynamics of the platform using Higher Order Sinusoidal Input Describing Function (HOSIDF) based system identification and we present optimal feedforward compensation design to improve reference tracking performance. We modeled the friction characteristics using the Stribeck friction model and identified through a procedure with a special reference signal and the Nelder-Mead algorithm. Results indicate that the RMS trajectory error decreased from 0.0431 deg/s to 0.0117 deg/s, and standart deviation of speed reference error integral decreased from 0.0382 deg to 0.0051 deg, when the proposed nonlinear identification and friction compensation method is used.