Model Predictive Control of a Differential-Drive Mobile Robot

Samir Bouzoualegh; El-Hadi Guechi; Ridha Kelaiaia

doi:10.2478/auseme-2018-0002

Abstract

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.

References

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Model Predictive Control of a Differential-Drive Mobile Robot

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