In a multirobot system, cooperation among the robots is important to successfully achieve mission objectives which requires the robots to work together. Under such circumstances, the cooperation between the robots is akin to the cooperation between humans where trust among each other plays a vital role in ensuring the effectiveness for achieving given objectives. This paper presents the development of a trust based control system for a multirobot framework aimed to improve the cooperation efficiency of the robots by identifying and collaborating only with trustworthy robots in the system. The developed control system is embedded with a trust evaluation model, designed using a novel adaptation of Markov Games concept into temporal difference learning to compute the direct trust and using a novel heuristic method to integrate the indirect trust. Simulation and real world experiments are carried out to compare and evaluate the performance of the developed model. Evidence from the experiments strongly suggest that the developed trust based control system can effectively distinguish between trustworthy and untrustworthy robots leading a more efficient task completion. © 2017 Elsevier Ltd