How Model Predictive Control Stabilizes Token Prices

This article evaluates blockchain tokenomics through the lens of control theory, comparing Model Predictive Control (MPC), PID controllers, and no-control scenarios. Using both synthetic growth models and Helium DeWi real-world data, results show that MPC consistently stabilizes token prices and minimizes control costs better than reactive benchmarks. The study highlights the importance of programmable, adaptive tokenomics for achieving stable network growth and sustainable economies.