Robust Model Predictive Control With Bi-Level Optimization for Boiler-Turbine System
| Autor: | Li Wang, Baocang Ding, Yuanli Cai |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2021 |
| Předmět: |
Dynamic control policy
0209 industrial biotechnology General Computer Science Exponential weighting Computer science model predictive control Load modeling Control (management) General Engineering Boiler turbine 02 engineering and technology nonlinear system linear parameter varying model Model predictive control Nonlinear system 020901 industrial engineering & automation 020401 chemical engineering Control theory General Materials Science lcsh:Electrical engineering. Electronics. Nuclear engineering 0204 chemical engineering Actuator lcsh:TK1-9971 |
| Zdroj: | IEEE Access, Vol 9, Pp 48244-48253 (2021) |
| ISSN: | 2169-3536 |
| Popis: | A robust model predictive control (MPC) with bi-level optimization is proposed for nonlinear boiler-turbine system. The nonlinear dynamics are described by multiple local models linearized at distinct operating points. A global linear parameter varying (LPV) model is constructed by combining the linearized local models. In order to combine the local models smoothly, an exponential weighting coefficient determined by the system states is applied. The bi-level optimization is proposed to optimize the control moves and control policy respectively. A controller model is designed as the inner optimization to calculate the suitable control policy under different operating conditions. The closed-loop robust MPC is designed to optimize the control moves to improve economic performance. Simulations under wide operating conditions have demonstrated the effectiveness of the proposed robust MPC method, by applying which the economic performance of the nonlinear boiler-turbine system is improved. |
| Databáze: | OpenAIRE |
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