Fuzzy Predictive Controller for Trajectory Tracking of Differential-Drive Mobile Robot

Hedroug, Mohamed Elamine; Bdirina, ElKhansa; Guesmi, Kamel

doi:10.1109/ic2em59347.2023.10419477

Cited by 1 publication

(1 citation statement)

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“…In this part, we compare the results of the proposed Fuzzy Predictive Control (FPC) to those of the Model Predictive Control (MPC) established in [29] The primary goal is to direct the mobile robot along a dynamic course with varying linear and rotational velocities. This starts with a circular path given by ( 27), then a sinusoidal path defined by (28).…”

Section: Tracking Circular and Sinusoidal Trajectoriesmentioning

confidence: 99%

Fuzzy predictive controller for trajectory tracking of a wheeled mobile root

Hedroug,

Bdirina,

Guesmi

2024

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This paper presents a mobile robot control methodology that uses a fuzzy predictive control system to accurately track given paths. It is specifically designed for scenarios of two successive and distinct paths within a shared reference trajectory. Through the combination of fuzzy logic and predictive control methods, the system aims to significantly enhance tracking accuracy. Modelling the system, using a T-S fuzzy system provides a comprehensive model framework to optimize the tracking process. Furthermore, the use of a well-tuned fuzzy system facilitates dynamic adjustments of the weighting matrices of the predictive controller. The combination of fuzzy logic and predictive techniques results in a robust control system capable of handling complex tracking tasks. The simulation results describe the accuracy, robustness, and efficiency of the suggested control strategy. The system is particularly effective in scenarios with two successive paths within a shared reference trajectory, where precise tracking is essential. This approach is crucial for mobile robots or vehicles navigating complex, changing environments.

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Section: Tracking Circular and Sinusoidal Trajectoriesmentioning

confidence: 99%