Convergence Filters for Efficient Economic MPC of Non-dissipative Systems
Abstract
This note presents a novel, efficient economic model predictive control (EMPC) scheme for non-dissipative systems subject to state and input constraints. A new conception of convergence filters is defined to address the stability issue of EMPC for constrained non-dissipative systems. Three convergence filters are designed accordingly to be imposed into the receding horizon optimization problem of EMPC. To improve online computational efficiency, the variable horizon idea without terminal constraints is adopted to compromise the convergence speed, economic performance, and computational burden of EMPC. Moreover, sufficient conditions are derived to guarantee the recursive feasibility and stability of the EMPC. The advantages of the proposed EMPC are validated by a classical non-dissipative continuous stirred-tank reactor.