A Novel Tuning approach for MPC parameters based on Artificial Neural Network

The appropriately tuned parameters allow a successful implementation of Model Predictive Control (MPC). In this paper an Artificial-Neural-Network (ANN) based approach is presented and detailed in the case of second order Single-Input-Single-output (SISO) system with active constraints. The benefits of our novel proposed approach lie in its capability to reach closed-loop stability and tune online the MPC parameters using Particle- Swarm-optimization (PSO), and Online-Sequential- Extreme-Learning-Machine(OS-ELM). Finally, the effectiveness of our approach has been emphasized by comparing the obtained performances to other existing methods.