Model Reference Adaptive Control of Advertising Systems

Internet advertising is a relatively new area where feedback control has become critically important for scalable optimization. But using feedback control in this space is challenging due to nonlinear, time-varying, and uncertain plants. In this paper we propose a high-fidelity model reference adaptive controller for reference tracking of budget-constrained advertisement campaigns.