Adaptive Trajectory Tracking Controller for an Armoured Vehicle: Hardware-in-the-Ioop Simulation

This paper presents a hardware-in-the-loop (HiL) simulation study of an adaptive trajectory following strategy consists of a knowledge-based adaptive mechanism, to automatically guide an armoured vehicle along a desired path. To model the armoured vehicle, a 7 Degree-of-Freedoms (DoF) mathematical model was used. Next, a geometric controller was developed based on Stanley controller. A knowledge database was built using Particle Swarm Optimisation (PSO) algorithm to optimise set of controller parameters depending on various combinations of vehicle speed and heading error. An adaptive mechanism was developed to automatically adjust controller parameters based on this knowledge. The controller was implemented through HiL simulations and evaluated against the original Stanley Controller. Trajectory following performance was evaluated and it was proven that the adaptive controller managed to guide the armoured vehicle successfully along the roads with 87% lateral error reductions on HiL compared to the simulations. It was also shown that the proposed adaptive controller managed to produce correctional steering actions that is suitable for the steering actuator to generate.