Control-Theoretic Liquidity Optimization in Decentralized Finance: The Aeon Protocol

Abstract

Decentralized finance (DeFi) systems currently rely on static parameters and reactive mechanisms that fail to adapt to rapidly changing market conditions. These limitations contribute to systemic inefficiencies including yield instability, capital fragmentation, and the extraction of value through adversarial mechanisms such as maximal extractable value (MEV). This paper introduces The Aeon Protocol, a control-theoretic framework for adaptive financial infrastructure. The protocol models decentralized liquidity management as a closed-loop control system in which economic variables are continuously monitored, predicted, and regulated through feedback mechanisms derived from classical control theory. The Aeon architecture integrates four primary system layers: • KENDRA — predictive forecasting and regime detection from on-chain data streams• NOEMA — model predictive control for economic orchestration• AURA — ethical routing layer that captures and redistributes MEV through sealed-bid auctions• LEIA — liquidity management engine governing protocol-owned liquidity across decentralized markets At the core of the system is a PID-controlled adaptive yield mechanism designed to regulate total value locked (TVL) and stabilize protocol yield within bounded ranges. A complementary Burn-and-Mint Equilibrium (BME) mechanism dynamically adjusts token supply to maintain long-term economic balance. A central implication of the Aeon architecture is the emergence of a self-reinforcing liquidity ecosystem. By integrating predictive forecasting, control optimization, and ethical MEV capture into a closed-loop economic system, the protocol continuously identifies inefficiencies in decentralized markets and redirects the associated value back into the protocol’s liquidity layer. This process transforms otherwise extractive market dynamics into a productive feedback cycle, where captured value is redistributed through liquidity provisioning, treasury reserves, and reflection mechanisms. Empirical simulations and historical replay experiments demonstrate that this feedback architecture materially increases capital utilization across the system. In controlled Monte Carlo simulations spanning 10,000 market scenarios, the protocol achieved improvements of 50–180% in capital efficiency, while redirecting approximately 68% of extractable value to protocol participants rather than external arbitrage actors. These results suggest that adaptive control systems can convert structural market inefficiencies into a persistent source of liquidity and yield generation, enabling decentralized financial networks to operate as self-regulating economic environments rather than static rule-based infrastructures. Formal analysis establishes asymptotic stability conditions for the controller using the Routh–Hurwitz criterion and Lyapunov stability methods, providing theoretical guarantees that the system converges toward equilibrium under defined parameter constraints. Collectively, the results demonstrate that control-theoretic economic architectures can provide a principled foundation for designing stable, transparent, and adaptive decentralized financial infrastructure. The Aeon Protocol represents a broader research direction toward autonomous economic systems, where financial networks operate as self-regulating feedback environments capable of maintaining equilibrium under dynamic market conditions.