Internal-Stably Energy-Saving Cooperative Control of Articulated Wheeled Robot with Distributed Drive Units

Abstract

Articulated wheeled robots play a crucial role in the logistics industry. However, conventional tractor-driven articulated wheeled robots exhibit poor internal stability and are prone to jackknifing, while also consuming a significant amount of energy. By deploying distributed drives and coordinating control among multiple drives, these issues can be effectively addressed. However, the flexible connections between the bodies of articulated vehicles pose significant challenges to the coordinated control of distributed drives. This paper proposes a multi-drive unit coordinated control algorithm based on driving force equivalence and allocation. A neural network is used to predict the driving force, and through non-linear driving force equivalence, a feedforward driving force is obtained. This is combined with a closed-loop feedback compensation controller to form a control architecture that integrates feedforward and feedback, resulting in the equivalent total driving force for the vehicle queue. Subsequently, an equivalent distribution strategy allocates the required driving force to each drive, enabling the vehicle bodies to achieve accurate and stable speed tracking while allowing each drive to operate near its efficient operating point, thereby reducing total energy consumption. Experiments demonstrate that our algorithm significantly lowers the total energy consumption of the vehicle queue under standard operating conditions while ensuring speed-tracking accuracy and improving internal stability.