Model-Free H_∞Optimal Control of Multi-Agent Systems with Intermittent Exploration Noise via Adaptive Dynamic Programming

In this paper, the <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$H$</tex><inf xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">∞</inf>optimal control problem for linear multi-agent systems is studied, and a hierarchical control scheme is designed to reduce the computational complexity. By introducing an additional compensating input indicator, the expected performance indicators are met. The designed output feedback control protocol introduces relaxation parameters, which relax the design requirements of the performance indicators. In addition, by using the idea of adaptive dynamic programming (ADP) at the local level and designing the data set at the collaborative level, the model-free control of the multi-agent system is realized. In the data acquisition phase, intermittent noise detection is used to suppress the system oscillation caused by the introduced external noise. Finally, the effectiveness of the proposed control protocol and algorithm is verified by simulation on the F-16 aircraft model.