Nonlinear Predictive Control for a Boiler–Turbine Unit Based on a Local Model Network and Immune Genetic Algorithm
作者： Hongxia Zhu , Gang Zhao , Li Sun , Kwang Y. Lee
DOI: 10.3390/SU11185102
关键词:
摘要: This paper proposes a nonlinear model predictive control (NMPC) strategy based on local network (LMN) and heuristic optimization method to solve the problem for boiler–turbine unit. First, LMN of unit is identified by using data-driven modeling converted into time-varying global predictor. Then, constrained solved online specially designed immune genetic algorithm (IGA), which calculates optimal law at each sampling instant. By introducing an adaptive terminal cost in objective function utilizing fictitious controllers improve initial population IGA, proposed NMPC can guarantee system stability while computational complexity reduced since shorter prediction horizon be adopted. The effectiveness validated simulations 500 MW coal-fired
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