The process industry has effectively used model predictive control (MPC), a potent advanced process control approach. Multi-agent systems (MASs), on the other hand, are built with various subsystems that cooperate to accomplish a particular goal. Similarly, modular plants are connections of several modules, each intended to carry out a particular task in the larger system. In this paper, first, we discuss modular plants and MASs to see if they are comparable. Then, we propose a simulation-based robust MPC strategy for n-dimensional linear MASs with uncertain and heterogeneous dynamics. The proposed control strategy consists of state space MPC and robust control. As a result, our work indicates the potential of distributed MPC for n-dimensional linear MASs with uncertain and heterogeneous dynamics in modular plants, which could help enhance the accuracy, effectiveness, and robustness of the control strategy in the process industry. The proposed control strategy can be extended to other applications in the process industry, and ongoing research is focused on using existing MAS control techniques further to improve the performance of the controller in modular plants.