Multiagent Distributed Source Seeking Under Globally Coupled Constraints: Algorithms and Experiments

The distributed source seeking complication for nonlinear multiagent systems subject to globally coupled constraints is investigated in this article. By the local optimization function measurement, the main objective is to drive all agents' output signals to the optimal value point of a coherent global optimization function with globally coupled constraints. To attain this purpose, projection-operators-based distributed optimal coordinators and reference-tracking controllers are constructed separately. Through the actual outputs of the agents, the distributed optimal coordinators generate the desired output to converge the optimal value point to the local optimization functions satisfying these constraints. In contrast, the reference-tracking controllers are proposed to drive all agents' output signals to track the optimal value point. The singular perturbation approach is applied for the interconnection feature and the system stability analysis. It is demonstrated that the distributed source-seeking problem for nonlinear multiagent systems with globally coupled constraints can be solved. In the end, experimental results on the four-wheeled omni-directional mobile robots platform demonstrate the efficacy and superiority of the proposed technique.