Abstract
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.
Highlights
The dynamics of boiler-turbine system are typically multi-variable, constrained and highly nonlinear [1]–[5]
Wang et al.: Robust Model Predictive Control With Bi-Level Optimization for Boiler-Turbine System of multiple local models linearized at different operating points
We develop the closed-loop robust model predictive control (MPC) with bi-level optimization for the nonlinear boiler-turbine system
Summary
The dynamics of boiler-turbine system are typically multi-variable, constrained and highly nonlinear [1]–[5]. L. Wang et al.: Robust Model Predictive Control With Bi-Level Optimization for Boiler-Turbine System of multiple local models linearized at different operating points. A new coordinated control strategy by combining min-max MPC with moving horizon estimation (MHE-MPC) was proposed in [28] to deal with the unmeasured disturbance for boiler-turbine system, in which the bounded stochastic disturbance and dead characteristics of inputs have been effectively suppressed All of these methods applied to linear time-invariant system have achieved good tracking performance. A more sophisticated strategy is expected to optimize both the control policy and control moves at each iteration Motivated by these considerations, we develop the closed-loop robust MPC with bi-level optimization for the nonlinear boiler-turbine system. Causes main dynamic characteristics, such as drum pressure, power output and water level deviation to vary significantly. By combining the local linearized models, a global LPV model is constructed
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