Practical Group Consensus of T-S Fuzzy Positive Multiagent Systems Using Compensative Control
Junfeng Zhang, Hao Ji, Tarek Raïssi, Haoyue Yang · IEEE Transactions on Artificial Intelligence · 2025
This paper investigates the practical group consensus of type-1 and type-2 T-S fuzzy positive multi-agent systems. First, a positive disturbance observer and a distributed positive compensator are proposed. A group consensus protocol is designed by integrating event-triggered mechanism, which utilizes the state information of the compensator. Some feasible conditions are addressed for practical group positive consensus in the form of linear programming. The key novelties are threefold: (i) A novel positive disturbance observer and compensator framework is constructed, (ii) A fuzzy positive group consensus protocol is established, and (iii) Linear programming is employed for describing the corresponding conditions. Finally, two examples are provided to verify the effectiveness of the theory findings.