Fixed Structure Feedforward Controller Tuning Exploiting Iterative Trials, Applied to a High-Precision Electromechanical Servo System

Abstract

In this paper, the feedforward controller design problem for high-precision electromechanical servo systems that execute finite time tasks is addressed. The presented procedure combines the selection of the fixed structure of the feedforward controller and the optimization of the controller parameters on the basis of measurement data from iterative trials. A linear parameterization of the feedforward controller in a two-degree- of-freedom control architecture is chosen, which for a linear time-invariant (LTI) plant results in a feedforward controller that is applicable to a class of motion profiles as well as in a convex optimization problem with the objective function being a quadratic function of the tracking error. Optimization by iterative trials results in the controller parameter values that are optimal with respect to the actual plant, which leads to a high tracking performance. The use of iterative trials in general outperforms techniques that are based on a detailed a priori plant model only, whereas the fixed structure of the feedforward controller, i.e., the approximative inverse plant model, guarantees a high tracking performance for a class of motion profiles, unlike for example iterative learning control (ILC). Experimental results on a high-precision wafer stage illustrate the procedure.