Sampled-data MPC for LPV systems with input saturation

Sampled-data MPC for LPV systems with input saturation
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用于具有输入饱和的 LPV 系统的采样数据 MPC

DOI:
10.1049/iet-cta.2014.0205
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发表时间:
2014-08
影响因子:
2.6
通讯作者:
Hongye Su
Hongye Su
中科院分区:
计算机科学4区
文献类型:
--
作者:
Ting Shi;Hongye Su

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针对连续时间线性变参数(LPV)系统,提出了一种采样数据模型预测控制(MPC)设计方法。同时考虑了输入饱和和参数不确定性。采用一种执行器饱和处理方法,允许MPC控制器饱和。使用可测量的参数向量,预定的状态反馈MPC控制器计算在每个时刻,充分利用的植物特性的变化的实时信息。通过将具有分段常数采样控制输入的连续时间LPV系统的闭环系统建模为线性脉冲系统,研究了所提出的MPC的稳定性。本工作中的采样间隔不要求是周期性的。提出的MPC设计方法有望进一步降低保守性。对所提出的采样数据MPC方法进行了改进。通过示例来演示其它现有MPC技术。
In this work, a sampled-data model predictive control (MPC) design method is proposed for continuous-time linear parameter varying (LPV) systems. The input saturation and parameter uncertainties are both considered. Using a method to deal with actuator saturation, the MPC controller is permitted to saturate. Using the measurable parameter vector, a scheduled state-feedback MPC controller is computed at each time instant which fully exploits the real-time information on the variations of the plant characteristics. By modelling the closed-loop systems of the continuous-time LPV systems with a piecewise constant sampled-data control input as linear impulsive systems, the stability properties of the proposed MPC are studied. The sampling interval in this work is not required to be periodic. The proposed MPC design method is expected to further reduce the conservativeness. The improvements of the proposed sampled-data MPC method w.r.t. other existing MPC techniques are demonstrated by an example.
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