Stability analysis of dynamic decision-making for vehicle heading control

In this paper, the problem of dynamic decision making for vehicle heading control to intercept moving targets is investigated. It is assumed that the targets arrive in the mission space sequentially. More precisely, there exist infinite number of targets that arrive the mission space one by one. The arrival times and positions of the targets are modeled using stochastic models. Furthermore, targets are assumed to move with unknown dynamics and unknown trajectories. Due to the probabilistic nature of the problem, it is desired to use a model predictive approach to control the heading of the vehicle. A reward allocation strategy is adopted for dynamic decision making and control design in order to move the vehicle toward the targets. Finite-time convergence analysis is presented for the case where the arrivals of targets occur sufficiently infrequently.