IMPROVING THE BOTTLE CAPPING SYSTEM WITH AN ADAPTIVE MODEL PREDICTIVE CONTROLLER

Subject Area: Control system engineering

This work is aimed at improving the bottle capping system with an adaptive model predictive controller. To achieve this, first, a robust pneumatic frictional force model was developed considering damping and stiffness coefficients of microscopic deformations of the piston surfaces which was mainly responsible for object positioning inaccuracies. To deal with this, an Adaptive Model Predictive Controller (AMPC) model was developed and used to control the linear time-invariant behavior of the pneumatic actuator and then updated the control response with the Kalman filter. This was guided by qualitative methodology and the system implementation was achieved with Simulink. The result showed that the response time to friction was 4.02ms. The AMPC was integrated into the plant model and tested using a tenfold cross-validation technique. The result showed that static friction was 33.32N and coulomb friction 2.71N. To improve the validity of the work, the AMPC was compared with data on friction collected from a conventional pneumatic system. The result showed that 24.57% of static friction was reduced and 29.9% of coulomb friction was reduced, and this is the improvement achieved in the control of both static and coulomb friction of the pneumatic system.