A novel inverse modeling control for piezo positioning stage

This paper focuses on the application of a novel inverse nonlinear autoregressive with exogenous input (NARX) structure and a fuzzy inference system on position control of a piezo positioning stage (PPS) system. The highly relationship between input voltage and output displacement is thoroughly modeled by using the inverse fuzzy NARX model-based identification process with the experiment training data. The unknown parameters of the proposed NARX fuzzy model was obtained base on a hybridization between backtracking search algorithm and gradient descent technique. A combination between fuzzy propositional–integral–derivative controller and inverse modeling feedforward controller was then applied to control PPS with several challenged working condition. The results show efficiency of the proposed method for the PPS system in terms of high tracking precision and excellent dynamic performance.