Designing New Model-Based Adaptive Sliding Mode Controllers for Trajectory Tracking Control of an Unmanned Ground Vehicle

This paper proposes three new dynamic model-based adaptive sliding mode controllers (ASMC) for trajectory tracking control of unmanned ground vehicles (UGV). The controllers combine kinematic and dynamic control to achieve asymptotic stability and finite-time convergence and their stability is verified using the Lyapunov stability theory. The controllers are designed to address the challenges posed by uncertainties in vehicle dynamic parameters and outperform the sliding mode control (SMC) method in trajectory tracking control. The simulation results of the proposed controllers are also discussed in terms of performance metrics. The simulation results show that the controller proposed in rule 1 shows the better performance in terms of trajectory tracking, and then the controllers proposed in rules 2 and 3 have good performances, respectively. In addition, when the simulation results are compared, it is seen that the performance of all three proposed controllers is better than the SMC.

Automated summary

This paper proposes three new dynamic model-based adaptive sliding mode controllers for trajectory tracking control of unmanned ground vehicles. These controllers perform well in addressing the challenges posed by uncertain parameters and outperform traditional sliding mode control methods in terms of performance.