Optimal torque distribution of distributed driving AGV under the condition of centroid change

The torque distribution is researched under the condition of the centroid position of distributed drive automatic guided vehicle (AGV) with load platform and is uncertain due to the unknown movable load. The whole vehicle model under centroid variation, the efficiency model of the hub motor and the torque distribution control strategy based on a PID neural network are established. A hierarchical controller is designed to accurately ensure the economy and stability of the vehicle. Simulations of the proposed control strategy are conducted, the results show that the total power and lateral deviation distance of the driving wheels are reduced by 17.63% and 61.54% under low load conditions and 15.54% and 61.39% under high load conditions, respectively, compared with those of the driving wheels under the average torque distribution, and the goal of close slip rates of the driving wheels is achieved. A system prototype is developed and tested, and the experimental results agree with the simulation within error permissibility. The margin of error is less than 5.8%, the results demonstrate that the proposed control strategy is effective. This research can provide a theoretical and experimental basis for the torque optimization distribution of distributed drive AGVs under centroid variation conditions.

Research on PID Neural Network Decoupling Control Among Joints of Hydraulic Quadruped Robot

Background: Hydraulic quadruped robot is a representative of the redundant transmission. This is a great challenge for multi-joints coordinated movement of the robot, because of the movement coupling with several freedom degrees among kinematic chains. Therefore, there is an urgent need to realize the decoupling among the joints of the hydraulic quadruped robot. Objective: The purpose of this study is to provide an overview of controller design from many studies and patents, and propose a novel controller to realize the decoupling control among joints of a hydraulic quadruped robot. Methods: For the coupling problems between the thigh and calf of a hydraulic quadruped robot, based on the Lagrangian method, dynamics model of the robot’s leg is established. The influence of driven system is considered. The model of the hydraulic servo driven system is built, so as to obtain the coupling relationship between thigh and calf of hydraulic quadruped robot. Based on the multivariable decoupling theory, a PID neural network decoupling controller is designed. Results: The researches on experiments are executed. The PID neural network decoupling control method is compared with the control that does not use any decoupling method. The decoupling effect of the proposed algorithm is verified on the thigh and the calf of the hydraulic quadruped robot. Conclusion: The designed PID neural network decoupling control method reduces the crosscoupling between thigh and calf of the hydraulic quadruped robot, and has obvious effect to improve the dynamic characteristics of single joint of robot's leg.