Adaptive trajectory tracking control algorithm for cross-domain robots in ground environment based on adaptive sliding mode observer

This paper proposes an adaptive control framework for cross-domain robots (CDRs) in ground environments. The framework integrates an adaptive trajectory tracking algorithm and an adaptive finite-time convergent sliding mode observer (AFSMO) to address trajectory tracking control issues under model parameter uncertainty and external disturbances. Based on the traditional dual-loop control structure, the framework introduces adaptive parameters into the position loop to estimate the side-slipping angle caused by environmental disturbances and re-plan the robot's desired linear velocity and angular velocity based on the side-slipping angle. In the velocity loop, an adaptive sliding mode observer is used to estimate the unknown lumped disturbances caused by parameter uncertainties and external disturbances, and velocity and angular velocity controllers are designed based on this estimation value. Additionally, the gains of the sliding mode observer are dynamically adjusted by the adaptive law. Based on finite-time convergence theory, it is proven that the trajectory tracking error and observation error can converge within a finite time. Finally, the effectiveness of the algorithm is validated through simulation and experimental results.