Dynamic Output Feedback-Predictive Control of a Takagi–Sugeno Model With Bounded Disturbance
Dynamic Output Feedback-Predictive Control of a Takagi–Sugeno Model With Bounded Disturbance
复制标题
DOI：
10.1109/tfuzz.2016.2574907
复制
发表时间：
2017-06
影响因子：
11.9
通讯作者：
B. Ding;Hongguang Pan
中科院分区：
文献类型：
--
作者：
B. Ding;Hongguang Pan
研究了严格满足输入和状态约束的具有有界扰动的Takagi-Sugeno模糊模型的预测控制问题。与以前的工作一样，利用了隶属度函数相关的动态输出反馈律。其新颖性在于以下技术改进。对于二次有界性的概念，它描述了闭环系统的稳定性和不变性，使用了完整的Lyapunov矩阵。通过调用S程序递归优化真实状态的实时椭球界。为了更好地处理输入约束和状态约束，引入了一些松弛标量，并通过范数定界技术进行了优化。给出了多步法，即在每个采样时刻优化一系列动态输出反馈规律，以改进单步法。数值算例说明了所提出的控制器的有效性。
This paper considers predictive control of a Takagi–Sugeno fuzzy model with bounded disturbance, strictly satisfying the input and state constraints. The membership-function-dependent dynamic output feedback law, as in a previous work, is utilized. The novelty lies in the following technical improvements. For the notion of quadratic boundedness, which specifies closed-loop stability and invariance properties, the full Lyapunov matrix is utilized. The real-time ellipsoidal bound of true state is recursively optimized by invoking the S-procedure. Some relaxation scalars, being optimized by the norm-bounding technique, are introduced for better handling the input and state constraints. The multistep approach, where a sequence of dynamic output feedback laws are optimized at each sampling instant, is given to improve the single-step approach. Numerical examples are given to illustrate the effectiveness of the proposed controllers.