Robust Fixed Point Transformations Based Adaptive Control of an Electrostatic Microactuator

In this paper a potential application of a novel adaptive controller based on robust fixed point transformations of local basin of attraction in iterative learning is suggested on the basis of numerical simulation results. Its main advantage is its simplicity in comparison with the more sophisticated adaptive approaches in nonlinear control that normally are based on the application of Lyapunovfunctions. While the Lyapunov function based parameter tuning normally is complicated, is restricted to special models and typically is sensitive to unknown external disturbances, the here resented method needs only approximate setting of actually only two adaptive parameters and it efficiently can compensate the effects of the external perturbations. The electrostatic micro-actuators (E$upmu$As) seem to be typical application area for this control that needs simple and fast calculations on the basis of quite approximate available model.