Linear Time-Varying Robust Model Predictive Control for Discrete-Time Nonlinear Systems*
Linear Time-Varying Robust Model Predictive Control for Discrete-Time Nonlinear Systems*
复制标题
离散时间非线性系统的线性时变鲁棒模型预测控制*
DOI：
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发表时间：
2018
期刊：
影响因子：
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通讯作者：
J. Mårtensson
中科院分区：
文献类型：
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作者：
Gonçalo Collares Pereira;P. Lima;B. Wahlberg;Henrik Pettersson;J. Mårtensson
针对状态和输入约束以及未知但有界的输入扰动的离散非线性系统，提出了一种鲁棒模型预测控制器。该预测模型使用了原始离散时间系统的线性化时变版本。所提出的优化问题包括作为优化变量的系统的当前标称模型的初始状态，这允许保证离散时间非线性系统的扰动不变集的鲁棒指数稳定性。从模拟，它是可能的，以验证所提出的算法是实时的能力，因为问题是凸的，并提出了作为一个二次规划。
This paper presents a robust model predictive controller for discrete-time nonlinear systems, subject to state and input constraints and unknown but bounded input disturbances. The prediction model uses a linearized time-varying version of the original discrete-time system. The proposed optimization problem includes the initial state of the current nominal model of the system as an optimization variable, which allows to guarantee robust exponential stability of a disturbance invariant set for the discrete-time nonlinear system. From simulations, it is possible to verify the proposed algorithm is real-time capable, since the problem is convex and posed as a quadratic program.