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This paper outlines a real-time hierarchical control allocation algorithm for multi-axle land vehicles with independent hub motor wheel drives. At the top level, the driver’s input such as pedal position or steering wheel position are interpreted into desired global state responses based on a reference model. Then, a locally linearized rigid body model is used to design a linear quadratic regulator that generates the desired global control efforts, i.e., the total tire forces and moments required track the desired state responses. At the lower level, an optimal control allocation algorithm coordinates the motor torques in such a manner that the forces generated at tire-road contacts produce the desired global control efforts under some physical constraints of the actuation and the tire/wheel dynamics. The performance of the proposed control system design is verified via simulation analysis of a 3-axle heavy vehicle with independent hub-motor drives.

In intelligent surveillance and reconnaissance (ISR) missions, multiple autonomous vehicles, such as unmanned ground vehicles (UGVs) or unmanned aerial vehicles (UAVs), coordinate with each other for efficient information gathering. These vehicles are usually battery-powered and require periodic charging when deployed for continuous monitoring that spans multiple hours or days. In this paper, we consider a mobile host charging vehicle that carries distributed sources, such as a generator, solar PV and battery, and is deployed in the area where the UAVs and UGVs operate. However, due to uncertainties, the state of charge of UAV and UGV batteries, their arrival time at the charging location and the charging duration cannot be predicted accurately.