This paper presents a model predictive control (MPC) for a differential-drive mobile robot (DDMR) based on the dynamic model. The robot’s mathematical model is nonlinear, which is why an input–output linearization technique is used, and, based on the obtained linear model, an MPC was developed. The predictive control law gains were acquired by minimizing a quadratic criterion. In addition, to enable better tuning of the obtained predictive controller gains, torques and settling time graphs were used. To show the efficiency of the proposed approach, some simulation results are provided.
 Guechi, E.H., Abellard, A., and Abellard, P. “TS-Fuzzy Predictor Observer Design for TrajectoryTracking of Wheeled Mobile Robot”, IECON 2011-37th annual Conf. of IEEE Industrial Electronic Society, pp. 319–324, 2011.
 Guechi, E. H., Bouzoualegh, S., Messikh, L. and Blažic, S. “Model Predictive Control of a two-link robot arm”, 2018 Int. Conf. on Advanced Sys. and Electric Tech. (IC_ASET), Tunisia, pp. 409–414, March 2018.
 Belda, K. and Rovný, O. “Predictive Control of 5 DOF Robot Arm of Autonomous Mobile Robotic System”, In Proc. Process Control (PC), 2017 21st International Conference on IEEE, 2017.
 Kamel, M. and Zhang, Y. “Linear Model Predictive Control via Feedback Linearization for Formation Control of Multiple Wheeled Mobile Robots”, Information and Automation, 2015 IEEE International Conference on. IEEE, pp. 1283–1288, Aug. 2015.
 Guechi, E. H., Bouzoualegh, S., Zennir, Y. and Blažic, S. “MPC Control Study and LQ Optimal Control of A Two-Link Robot Arm:A Comparative Study”, Machines 2018, vol. 6, no. 3, pp. 37.
 Elkhateeb, N. A. and Badr, R. I. “Novel PID Tracking Controller for 2DOF Robotic Manipulator System Based on Artificial Bee Colony Algorithm”, Electrical, Control and Communication Engineering, vol. 13, no.1 pp. 55–62, Dec. 2017.
 Mendili, M. and Bouani, F. “Predictive Control Based on Dynamic Modeling of OmniDir Mobile”, Engineering & MIS (ICEMIS), 2017 International Conference on IEEE, pp. 1–6, May 2017.
 Mendili, M. and Bouani, F. “Predictive Control of Mobile Robot Using Kinematic and Dynamic Models”, Hindawi, Journal of Control Science and Eng., vol. 2017.
 Maniatopoulos, S., Panagou, D. and Kyriakopoulos, K. J. “Model Predictive Control for the Navigation of a Nonholonomic Vehicle with Field-of-View Constraints”, American Control Conference (ACC), 2013. IEEE, pp. 3967–3972, June 2013.
 Sinaeefar, Z. and Farrokhi, M. “Adaptive Fuzzy Model Based Predictive Control of Nonholonomic Wheeled Mobile Robots Including Actuators Dynamics”, Int. Journal of Scientific & Eng. Research, vol. 3, no. 9, Sep. 2012.
 Mazur, A. “Hybrid adaptive control laws solving a path following problem for Non-Holonomic mobile manipulators”, International Journal of Control, vol. 77, no. 15, pp. 1297–1306, Feb. 2007.
 Ostafew, C. J., Schoellig, A. P. and Barfoot, T. D. “Learning-Based Nonlinear MPC to Improve Vision-Based Mobile Robot Path Tracking”, Journal of Field Robotics, vol. 33, no 1, pp. 133–152, 2016.
 Mitrovic, S. T., & Djurovic, Z. M. “Fuzzy-Based Controller for Differential Drive Mobile Robot Obstacle Avoidance”, IFAC Proceedings, vol. 43, no. 16, pp. 67–72, 2010.
 Dhaouadi, R., & Hatab, A. A. “Dynamic modelling of differential drive mobile robots, a unified framework”, Advances in Robotics & Automation, vol. 2, no. 2, pp. 1–7, 2013.
 Yamamoto, Y. and Yun, X. “Coordinating Locomotion and Manipulation of a Mobile Manipulator”, Decision and Control, Proceedings of the 31st IEEE Conference, pp. 2643–2648, 1992.
 Magni, L., Scattolini, R. and Aström, K. J. “Global stabilization of the inverted pendulum using model predictive control”, Proceedings of the 15th IFAC World Congress, vol. 1554, 2002.
 Gawthrop, P. J. and Wang, L. “Intermittent predictive control of an inverted pendulum”, Control Engineering Practice, vol. 14, no. 11, pp. 1347–1356, 2006.
 Mills, A., Wills, A. and Ninness, B. “Nonlinear model predictive control of an inverted pendulum”, Proceedings of the American Control Conference, pp. 2335–2340, 2009.
 MIT Open Course Ware,”Dynamics and Control”, Spring 2008.