Robust Model Predictive Control Algorithm with Variable Feedback Gains for Output Tracking
Robust Model Predictive Control Algorithm with Variable Feedback Gains for Output Tracking
复制标题
具有用于输出跟踪的可变反馈增益的鲁棒模型预测控制算法
DOI：
10.1109/tie.2020.2984440
复制
发表时间：
2021
影响因子：
7.7
通讯作者：
C.L.Philip Chen
中科院分区：
文献类型：
--
作者：
Feng Zhou;Min Gan;C.L.Philip Chen
具有外生输入的变系数状态相关自回归模型在非线性系统建模和控制中有着重要的应用。考虑到具有一系列可变反馈增益的状态反馈控制策略为鲁棒预测控制器的设计提供了比恒定反馈增益更大的自由度，提出了一种用于输出跟踪的可变反馈增益鲁棒模型预测控制（RPC）算法。该方法通过定义系统的输入和输出增量序列，构造了两个包含系统动态行为的多面体状态空间模型。然后，基于多面体状态空间模型，设计了一种用于输出跟踪的变反馈增益RPC。为了进一步降低保守性，参数依赖的李雅普诺夫函数的设计中的控制策略的可变反馈增益的构造。提出的RPC可以扩大鲁棒控制器的可行域，提高控制性能。对连续搅拌釜式反应器的仿真验证了该方法的可行性和有效性。
The varying-coefficient state-dependent autoregressive with exogenous inputs models are very useful in nonlinear system modeling and control. Considering that state feedback control strategy with a series of variable feedback gains provides more freedom than a constant feedback gain for the robust predictive controller design, this article proposes a robust model predictive control (RPC) algorithm with variable feedback gains for output tracking. In the proposed method, by defining input and output increment sequences of the system, two polytopic state-space models, in which the dynamic behavior of the system is wrapped, are constructed. Then, based on the polytopic state-space models, an RPC with variable feedback gains for output tracking is designed. To further reduce the conservatism, the parameter-dependent Lyapunov functions are constructed for the design of the variable feedback gains in the control strategy. The proposed RPC can expand the feasible region of the robust controller and improve the control performance. The simulation on a continuous stirred tank reactor verified the feasibility and efficacy of the proposed method.