This work proposes an adaptive Multi-Input and Single-Output fuzzy controller which is designed in a supervisory manner for a multi-agent system. This paper mainly aims to control the frequency oscillation of each agent and minimize the production cost of the whole interconnected system. In the proposed controller, the load frequency control and management controller loops are integrated into the designing phase. In many parallel works, designing a load frequency controller and managing unit have been carried out separately which leads to disturbance in both outputs. In the present work, the disruption is eliminated by the implementation of the proposed controlling method. To improve the performance of the proposed controller, the key parameters of the controller are tuned using the modified particle swarm optimization algorithm. The designed control system namely "distributed control method" is applied for several independent units (agents). The controller parameters are tuned in a supervisory manner for the considered multi-agent system, where each agent is connected to the adjacent agents. A wide range of operation points is regarded in the designing phase to adjust the parameters in a way that the controller can effectively control the system in the whole of this range. (C) 2019 Elsevier Ltd. All rights reserved.