Active vortex induced vibration controller and Neuro identification for marine risers

Abstract

In this work, a vortex induced vibration controller within discrete time has been investigated on marine cylinder pipe risers which represented by using nonlinear neuron identification models namely NARX and NAR. Input-output data have been extracted from the experimental rig of vortex induced vibration marine riser. A proposed work in this paper is to create the nonlinear system identification model undergoing for vortex induced vibration of marine riser depends on Neural Network which didn’t represented before this time in this application and using PID controller to suppress the vibration. Two nonlinear system identification methods used to represent the models which are: Neural Network based on Nonlinear Auto-Regressive External (Exogenous) Input (NARX) and Neural Network based on Nonlinear Auto-Regressive (NAR). Also, the best model has been chosen based on the lowest value of Mean Square Error (MSE) between actual and predicted response. While, PID controller has been used to suppress the oscillation of pipe cylinder for all models and the comparison of the controller’s performance on each model by tuning the controller parameter (KP, KI and KD) using heuristic method. Finally, the outcomes show that the NARX model performed better than the NAR model to predict the dynamic response of the system. On the other hand, PID controller has been managed to reduce the pipe cylinder fluctuation for all models specially the NARX model. Using particle swarm optimization (PSO) to improve the stability for marine riser on the parameters of PID controller are planned for future work