基于状态扩展的双反馈模型预测控制技术研究  

Research on Model Predictive Control with Dual Feedback Based on State Extension

作　　者：赵熙临[1] 殷丽娟[1] 

机构地区：[1]湖北工业大学电气与电子工程学院,武汉430068

出　　处：《系统仿真学报》2015年第3期591-597,共7页Journal of System Simulation

基　　金：湖北省自然科学基金(2011CHB003);湖北省教育厅科学技术研究重点项目(D20111410)

摘　　要：针对模型预测控制在线滚动的实施要求,提出了基于状态扩展的双反馈预测控制策略,旨在不改变系统信息描述的前提下,提高其在线计算能力。在模型预测控制滚动时域特征分析及其数学模型演化讨论基础上,根据系统变量及其差值与系统方程的关联关系进行状态变量的扩展与转换,使变量转换后的系统在预测控制模式下表现为状态与输出双反馈的结构形式,从而通过输出反馈的引入,在系统控制信息无任何约束及处理的基础上有效缩减控制域,降低系统在线计算量。光伏系统最大功率点跟踪(MPPT)控制仿真示例验证了设计的可行性与有效性。Depending on the online implementation demand of Model Predictive Control(MPC) for the receding horizon control characteristic, a control strategy of dual feedback structure based on state extension was proposed. The control strategy was aimed to improve the online computational capability about the control system to achieve the control target without any change of the system information. Based on the analysis of the characteristic of MPC, the extension and conversion method of state variable was proposed according to the relationship between state variable, control variable, output variable and system model. And the structure of the control system after state extension was manifested as a dual feedback style. Thus, the control horizon of MPC system was decreased because of the introduction of the output feedback without any constraint and treatment to the system information. The decrease of the control horizon will conducive to improve the online computational capability of the control system remarkably. The feasibility and validity of the proposed method was verified by an example of maximum power point tracking(MPPT) control of photovoltaic system.

关 键 词：模型预测控制 状态扩展 双反馈 滚动时域 

分 类 号：TP273[自动化与计算机技术—检测技术与自动化装置]