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摘要: 针对非线性多变量系统提出一种多模型预测控制(MMPC)策略.首先给出一种多模型 辨识方法,利用模糊满意聚类算法将复杂非线性系统划分为若干子系统,并获得多个线性模型, 通过模型变换得出全局系统模型,接着对全局MIMO系统设计MMPC,并进行了系统的性能分 析,最后以pH中和过程为例,通过仿真研究验证了辨识和控制算法的有效性.
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关键词:
- MIMO系统 /
- 多模型 /
- 模型预测控制(MPC) /
- 模糊满意聚类 /
- pH中和过程
Abstract: A multi-model-based predictive control (MMPC) strategy dealing with nonlinear model-based predictive control (NMPC) for MIMO systems is developed in this paper. Firstly a multimodel identification method is given. Using fuzzy satisfactory clustering algorithm presented in this paper, the complex nonlinear system can be quickly divided into multiple fuzzy parts. A global model can be obtained by some transformation of the obtained multiple linear models. An MMPC algorithm is therefore designed for the global MIMO systems with system performance analysis. Taking a pH neutralization control system as simulation example, the simulation results verify the effectiveness of MMPC on complex nonlinear systems. -
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