Amirkabir University of Technology AUT Journal of Electrical Engineering 2588-2910 46 2 2015 09 23 Adaptive Simplified Model Predictive Control with Tuning Considerations Adaptive Simplified Model Predictive Control with Tuning Considerations 57 63 514 10.22060/eej.2015.514 EN A.S. Ashtari MSc. Student, APAC Research Group, Industrial Control Center of Excellence, K.N.Toosi University of Technology, Tehran, Iran A. Khaki Sedigh Professor, APAC Research Group, Industrial Control Center of Excellence, K.N.Toosi University of Technology, Tehran, Iran Journal Article 2015 11 29 Model predictive controller is widely used in industrial plants. Uncertainty is one of the critical issues in real systems. In this paper, the direct adaptive Simplified Model Predictive Control (SMPC) is proposed for unknown or time varying plants with uncertainties. By estimating the plant step response in each sample, the controller is designed and the controller coefficients are directly calculated. The proposed method is validated via simulations for both slow and fast time varying systems. Simulation results indicate the controller ability for tracking references in the presence of plant’s time varying parameters. In addition, an analytical tuning method for adjusting prediction horizon is proposed based on optimization of the objective function. It leads to a simple formula including the model parameters, and an indirect adaptive controller can be designed based on the analytical formula. Simulation results indicate a better performance for the tuned controller. Finally, experimental tests are performed to show the effectiveness of the proposed methodologies. https://eej.aut.ac.ir/article_514_59b90e1005a220e2ebc542eb9d950b1e.pdf