Input nonlinearities, or actuator nonlinearities, can be seen in a lot of systems and have significant effects on the system performance. From the controller design point of view, accurate yet simple model of input nonlinearities is essential to compensate their effects and to achieve high level control performance. Unfortunately, most input nonlinearities are neither known nor easy to characterize, especially when the input nonlinearities and unknown system parameters are present simultaneously in the system dynamics. Off-board calibration may be possible yet it is very time consuming and requires additional calibration systems. This paper focuses on a class of systems with unknown input nonlinearities and system parameters and proposes an on-board system identification process to model the unknown nonlinearities. The input nonlinearities are decomposed into localized orthogonal basis and then estimated together with the system parameters. The proposed method is applied to model the nonlinear flow mapping of cartridge valves. Simulation and experimental results are obtained to illustrate the effectiveness and practicality of the proposed method.
Hammerstein Models and Real-Time System Identification of Load Dynamics for Voltage Management