Integrating Damping Control with Iterative Learning Control for Fast and Precise Scanning of Nanopositioners: A TITO Design

Fixed-structure low-order feedback control is a simple and effective damping approach for piezo nanopositioning thanks to the merits of ease of implementation and low computational complexity. However, the tracking performance of scanning motions for nanopositioners is weaken due to the unexpected phase lag and residual periodic errors caused by feedback control alone. In this paper, a feedback integral resonant control (IRC) integrated with a feedforward PID type iterative learning control (ILC) is proposed for vibration damping and precision scanning simultaneously. For a two-input-two-output (TITO) system with cross coupling around the first resonance, a static decoupling matrix is designed to obtain decoupled dynamics. A standard IRC along with ILC is then applied. The parameters in the composite controller are determined to satisfy the convergence condition based on lifted matrix computation. For evaluations, simulations are conducted to check the effectiveness of the parameters. Compared with feedback IRC alone, experimental results demonstrate the superiority of the composite design with more than 85% improvements in RMS errors for both raster and spiral scanning at 20 and 40 Hz.