Neural Network Based Control of a Suspension Assembly with Self-Sensing Micro-Actuator for Dual-Stage HDD

摘要

This paper presents a system identification process and control system design of an artificial neural network based suspension assembly with self-sensing micro-actuator for dual-stage hard disk drive. Artificial neural networks can be used effectively for the identification and control of nonlinear dynamical systems such as a flexible micro-actuator and self-sensing system. Three neural networks are developed for the self-sensing micro-actuator, the first for system identification, the second for inverse model for control using laser sensor signal, and the third for inverse model for control using only self-sensing piezoelectric signal. And we use a neural network inverse model to control the suspension assembly which includes the micro-actuator pair. Simulation and experimental results show that good control performance can be achieved by using artificial neural networks approach.