A constrained model predictive controller for two cooperative tripod mobile robots

Abstract

A constrained model predictive controller for two tripod mobile robots performing cooperative transportation of an object through a pre-defined trajectory in the presence of external disturbances has been developed and validated in this paper. The robots are designed to hold an object through their end effectors while applying controlled forces to the object and transitioning along the pre-defined reference trajectory. In this collaborative transportation task, a constrained model predictive controller to control the applied forces and a sliding-mode controller to control the motion of the systems are implemented. A load-sharing algorithm allowed for decentralizing the control system to determine the share of the force applied to the object from each end effector. The system and control algorithms are modeled and simulated in a computational environment using MATLAB software. The results showed that the cooperative system’s position tracking and the force control on the object are successfully achieved using the developed algorithms with minimum deviation from the desired trajectory. In addition, robustness to a continuously increasing external disturbance exerted on the system was achieved using the proposed force control strategy.