Adaptive Continuous Predictive Control of Wheeled Robots based on Extended State Observer

This study emphasizes a continuous predictive control approach based on the extended state observer, aiming to accurately control and track the path of a wheeled robot. The extended state observer is designed to compensate for the model uncertainties and unknown external disturbances applied to the robot from the environment which has a detrimental effect on its performance. The proposed approach utilizes measured angular and linear velocities to estimate unknown external disturbances and model uncertainties of the system, in addition to other states. Mathematical analyses are given to illustrate the stability of the proposed approach. The continuous predictive controller, formulated from the model, possesses the capability to adapt itself with real-world conditions by effectively using the information of disturbances and uncertainties from the extended state observer. The comparative results indicate high accuracy for the proposed observer-based predictive controller in rejecting the disturbance and compensating for the uncertainties under different trajectories.