Optimal Path Tracking Controller of Multiple Unmanned Tracked Vehicles: A Distributed Model Predictive Control Approach

In this paper, we propose a novel distributed model predictive control (DMPC) approach for optimal path tracking (OPT) in multiple unmanned tracked vehicles (UTVs). The novelty of this work lies in the integration of longitudinal and lateral motion control by minimizing the cost function and formulating a standard multi-objective DMPC optimization problem. Firstly, a longitudinal and lateral coupled kinematic model of the tracked vehicle is established. And then a DMPC approach considering multi-objective optimization is formulated to deal with multiple tracked vehicle path tracking control and distributed computing problems. Some challenging scenarios including S-bend and rectangle are tested and validated in simulation and real tracked vehicle for the proposed OPT strategy. A comparison is made between distributed and centralized methods, and the comparison result shows the rapidity of DMPC approach.