【作者】 王楠；

【导师】 李鸿一；

【作者基本信息】 渤海大学 ， 应用数学， 2022， 硕士

【摘要】 随着科技的日益发展,系统日趋复杂化,现实生活中的控制系统大多都带有非线性动态特征和不确定因素,这对系统的建模和分析造成了很大的困扰。模糊控制由于其具有语言型控制规则的特点,可以有效地处理这些问题,并且已应用到很多工业领域。Takagi-Sugeno(T-S)模糊模型可以利用一些简单的局部线性系统近似复杂的非线性系统,这样对模糊系统进行分析与控制时就能直接利用线性系统理论知识。此外,比起不能直接处理系统中的不确定性因素的一型T-S模糊技术,利用上下界隶属度函数的区间二型模糊模型具备更强的描述不确定性的能力。另一方面,网络控制系统凭借诸多优势被广泛应用到工业控制领域中,它能实现不同用户在一定范围内的资源共享与远程操控。在带来很多便利和优势的同时,复杂的网络传输环境容易产生系统故障、通信延迟、成本过高和数据量化等问题。综上所述,本文进行如下研究:针对非线性网络控制系统,设计一个新颖的基于区间二型模糊模型的降阶故障诊断滤波器,用在简化动态模型的基础上检测系统故障。采用事件触发通信机制减少对有限网络资源的过多占用,从而降低传输负担。在定理中利用松弛矩阵降低系统保守性,给出受制于参数不确定性、通信时滞等因素的降阶故障诊断滤波器设计条件,并进一步验证所提策略的优越性。针对网络化区间二型T-S模糊系统,在稳定性分析中构造一个依赖于隶属函数及其时间导数的Lyapunov-Krasovskii泛函。设计一个基于切换方案的模糊滤波器,其前件变量与系统模型的前件变量不同,进一步提高所设计的模糊滤波器的灵活性。此外,为了减少网络通信负担,引入事件触发机制和量化机制,降低传输包大小的同时,提高网络传输速率。再通过线性矩阵不等式方法计算出模糊滤波器的增益矩阵,最后给出仿真结果以证明所提方案的有效性。更多还原

【Abstract】 With the development of science and technology,the systems become more and more complex,and most of the control systems in real life have nonlinear dynamic characteristics and uncertain factors,which cause great trouble to the modeling and analysis of the system.Because of its characteristics of language-based control rules,fuzzy control can effectively deal with these problems and has been applied to many industrial fields.Takagi-Sugeno(T-S)fuzzy models can use some simple local linear systems to approximate complex nonlinear systems,so that the analysis and synthesis of fuzzy systems can directly use the linear system theory.In addition,compared with the type-1 T-S fuzzy technology that cannot directly deal with the uncertainty factors in the system,the interval type-2 fuzzy model using the upper and lower membership functions has a stronger ability to describe the uncertainty.On the other hand,the networked control system has been widely used in the field of industrial control with many advantages,it can realize the resource sharing and remote control of different users within a certain range.While bringing many conveniences and advantages,the complex network transmission environment is prone to problems such as system failure,communication delay,high cost and data quantization.In summary,the following researches are carried out in this paper:For nonlinear networked control systems,a novel reduced-order fault detection filter based on the interval type-2 fuzzy model is designed to detect system faults on the basis of simplified the dynamic model.The event-triggered communication mechanism is used to reduce excessive occupation of limited network resources,thereby reducing the transmission burden.In the theorem,the slack matrix is used to reduce the conservatism of the system,and the design conditions of the reduced-order fault detection filter subject to the parameter uncertainty,communication delay and other factors are given,the superiority of the proposed strategy is further verified.For the networked interval type-2 T-S fuzzy system,a Lyapunov-Krasovskii functional that depends on the membership functions and their time derivatives is constructed in the stability analysis.A fuzzy filter based on the switching scheme is designed,and its premise variables are different from those of the system model,which further improves the flexibility of the designed fuzzy filter.In addition,in order to reduce the network communication burden,an event-triggered mechanism and a quantization mechanism are introduced to reduce the transmission packet size and increase the network transmission rate.Then,the gain matrices of the fuzzy filter are given by the linear matrix inequality method.Finally,the simulation results are given to prove the effectiveness of the proposed scheme.更多还原