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Self-stabilizing economic nonlinear model predictive control applied to modular systems
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DOI：10.1016/j.compchemeng.2024.108825.png)
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Abstract
En 中文
Recent advances have been made in self-stabilizing Economic Nonlinear Model Predictive Control (eNMPC) formulation without pre-calculated setpoints, which leverages norm-based steady-state optimality conditions to enhance system robustness. To enable practical implementation, a generalized time-domain formulation is proposed, accommodating the discrete-time nature of control instrumentation and the continuous-time nature of first-principles models. A case study involving a modular membrane reactor illustrates the applicability of self-stabilizing eNMPC in real-world industrial scenarios.
Keywords:
Process control
Model predictive control
Economic model predictive control
Lyapunov stability
Modular membrane reactor
Journal
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Citations:
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