Abstract
An adaptive control method is proposed to suppress vibration of smart structures by using a self-organizing map (SOM), one type of neural networks. The SOM learns characteristics of given data without supervising, and categorizes high dimensional data into low dimensional maps with keeping complex relationships among data. The present method employs the SOM to estimate states of the controlled object and makes a lookup table of control input. Each node of the state estimation SOM consists of vectors including controlled responses and control input. The SOM and lookup table learn and are updated only when the effective control input is applied to the controlled object where the evaluation function of control system is defined by difference between the desired state and current state. The present method just requires information about the control response and input, resulting in implementation of the vibration control without numerical models. Numerical and experimental results are given for the smart structure fabricated by an aluminum plate and piezoelectric actuators, and effectiveness of the present method is confirmed from both results.
