Nonlinear Identification and Position Control of a Pneumatic System


In this work a pneumatic positioning system is studied. The system presents high nonlinearities since it is subjected to static friction, dead bands, and dead times. Firstly, the system identification is done using nonlinear identification based on the Hammerstein-Wiener model. Then, some control strategies such as Proportional-Integral-Derivative (PID) controller, Fuzzy-PID controller and Model Predictive Control (MPC) are designed to handle these nonlinearities. The main goal is to control the displacement of the pneumatic cylinder to reach any position or trajectory tracking in the shortest possible time and with the least steady state error. The results show that the Hammerstein-Wiener model identified for the system satisfactorily characterizes its nonlinear dynamics. The MPC is more efficient to control the system compared to the other controllers as it has less steady state error and stabilizes the system faster.