Analysis of Stability and Performance of Economic Model Predictive Control with State-Independent Costs
For control engineers dealing with systems like water distribution networks, this work provides theoretical guarantees for convergence and stability in EMPC with input-dependent costs, though the contribution is incremental.
This paper addresses economic model predictive control (EMPC) with state-independent costs, where multiple steady states can exist. It proves convergence of closed-loop trajectories to the optimal steady-state set under strict dissipativity and proposes a modified cost to ensure Lyapunov stability with minimal performance loss, validated on a water distribution network case study.
This paper studies economic model predictive Control (EMPC) schemes, where the stage cost depends only on control inputs. Such problems arise in applications like water distribution networks and differ from standard EMPC since multiple steady states can correspond to the unique optimal steady input. We show that, under a strict dissipativity assumption related to the set of optimal steady states, the closed-loop trajectories converge asymptotically to this set, ensuring convergence of the economic cost to the optimal steady state cost. To enhance Lyapunov stability, we propose a modified stage cost that preserves the optimal input while guaranteeing asymptotic stability of a specific equilibrium with a slight performance loss. The approach is further extended to EMPC of a class of linear systems with periodic costs and disturbances by lifting it to a multi-step EMPC problem for periodic operations. A case study with a water distribution network demonstrates the effectiveness of the proposed methods in achieving both asymptotic convergence and stability.