Min-max MPC algorithm for LPV systems subject to input saturation

Min-max MPC algorithm for LPV systems subject to input saturation
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DOI：
10.1049/ip-cta:20041314
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发表时间：
2005-07
期刊：
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影响因子：
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通讯作者：
Yong-Yan Cao;Zongli Lin
Yong-Yan Cao;Zongli Lin
中科院分区：
其他
文献类型：
--
作者：
Yong-Yan Cao;Zongli Lin

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针对输入饱和的多面体线性变参数系统，提出了一种新的模型预测控制(MPC)算法。给出了具有输入饱和的离散LPV系统的集不变性条件，并通过求解直接包含输入饱和的LMI优化问题来确定不变集。基于这一集不变性条件，针对具有输入饱和的LPV系统，提出了一种最小-最大预测控制算法。针对参数依赖控制器的设计，提出了一种基于增益调度的MPC算法。数值算例验证了算法的有效性。
In this paper, a new model predictive control (MPC) algorithm is developed for polytopic linear parameter-varying (LPV) systems subject to input saturation. A set invariance condition for discrete-time LPV systems with input saturation is identified and the invariant set is determined by solving an LMI optimisation problem, which directly incorporates input saturation. Based on this set invariance condition, a min-max MPC algorithm is proposed for the LPV systems with input saturation. A gain-scheduling MPC algorithm is also proposed for the design of a parameter-dependent controller. Numerical examples demonstrate the effectiveness of the algorithms.