A Behavioral Adaptive Fuzzy controller of multi robots in a cluster space

• Novel cluster-space controller for non-holonomic systems based Behavioral Adaptive Fuzzy tuning algorithm (BAFC).
• Controller is easy to implement and performs tasks based on their importance.
• Fuzzy tuned controller uses position error and its rate of change as inputs.
• Implementation using SIMULINK on Lego EV3 WMRs wheeled robot is presented.
• Wi-Fi link establishes communication between agents and controller.

Cooperation between autonomous robot vehicles holds several promising advantages like robustness, adaptability, configurability, and scalability. Coordination between the different robots and the individual relative motion represent both the main challenges especially when dealing with formation control and maintenance. Cluster space control provides a simple concept for controlling multi-agent formation. In the classical approach, formation control is the unique task for the multi-agent system. In this paper, the development and application of a novel Behavioral Adaptive Fuzzy-based Cluster Space Control (BAFC) to non-holonomic robots is presented. By applying a fuzzy priority control approach, BAFC deals with two conflicting tasks: formation maintenance and target following. Using priority rules, the fuzzy approach is used to adapt the controller and therefore the behavior of the system, taking into accounts the errors in the formation states and the target following states. The control approach is easy to implement and has been implemented in this paper using SIMULINK real-time platform. The communication between the different agents and the controller is established through Wi-Fi link. Both simulation and experimental results demonstrate the behavioral response where the robot performs the higher priority tasks first. This new approach shows a great performance with a lower control signal when benchmarked with previously known results in the literature.

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