T-S模糊系统动态量化输出反馈控制与弹性滤波

The T-S fuzzy model approach is one of the hot topics on nonlinear systems analysis and design. With the development of networked techniques, the problem of dynamic quantization for transmission signal has received more and more attention. This project focuses on an innovative investigation of dynamic quantization control and state estimation problems for T-S fuzzy systems: (1) A novel dynamic quantization strategy is proposed, and the effects of quantization on closed-loop control systems (filtering error systems) performance are taken into account to achieve dynamic quantization design for T-S fuzzy systems; (2) A new decoupling method of nonlinear coupling is presented, and output feedback control design for general T-S fuzzy systems is given; (3) A new method is provided to deal with uncertain product items, and the resilient filtering design for T-S fuzzy systems is studied accordingly. The whole team has achieved valuable results on the mentioned topic, and the investigated problems are innovative. This project is a perfect combination of transmission signal quantization, feedback control, and state estimation. Then, this project is valuable in the sense of both scientific research and industrial applications.

T-S模糊模型方法是当今国际上非线性系统分析与设计领域研究的热点问题之一，而随着网络化技术的不断发展，传输信号的动态量化问题也已经受到高度关注。本项目拟对T-S模糊系统动态量化控制与状态估计问题开展创新性的研究：(1)提出新的动态量化策略，充分考虑量化对闭环控制系统（滤波误差系统）性能的影响，给出T-S模糊系统动态量化设计；(2)提出新的非线性耦合解耦方法，给出一般性T-S模糊系统输出反馈控制设计；(3)提出新的不确定乘积项处理方法，给出T-S模糊系统弹性滤波设计。项目组在相关问题上已有丰富的研究积累，拟研究的问题创新性强，融合了传输信号量化、反馈控制、状态估计等领域，既有重要的科学意义，也有广阔的应用前景。

非线性系统的操控和状态检测一直是控制领域中的关键问题。近些年来，随着现代系统非线性程度越来越高，对系统控制与状态估计变得更加困难。而对于实际的系统而言，系统状态往往是不能直接测量的，利用系统的测量输出对系统进行控制和状态估计已经成为现代工业复杂系统分析与设计的主流方法之一。本项目主要针对非线性模糊系统在输出反馈控制与滤波、弹性设计以及信号传输量化和数据丢包等问题上开展深入的研究，取得了创新性的研究成果。本项目的研究融合了非线性系统、模糊系统、鲁棒控制和滤波以及网络化系统等领域，它的开展丰富和完善了复杂系统理论，具有重要的科学意义。