检索结果-南通市图书馆

Decomposition Based Fuzzy Model Predictive Control Approaches for Interconnected Nonlinear Systems

International Journal of Automation and computing 2019年第3期16卷 369-388页

作者： Latifa Dalhoumi mohamed Chtourou mohamed djemel Control and Energy Management Laboratory (CEM-Lab) National School of Engineering of Sfax

This paper proposes fuzzy model predictive control(FMPC)strategies for nonlinear interconnected systems based mainly on a system decomposition ***,the Takagi-Sugeno(TS)fuzzy model is formulated in such a way to describe the behavior of the nonlinear *** on that description,a fuzzy model predictive control is *** system under consideration is decomposed into several *** each subsystem,the main idea consists of the decomposition of the control action into two parts:The decentralized part contains the parameters of the subsystem and the centralized part contains the elements of other *** to such decomposition,two strategies are defined aiming to circumvent the problems caused by interconnection bet ween *** feasibility and efficiency of the proposed method are illustrated through numerical examples.

关键词： Model predictive control centralized control decentralized control Takagi-Sugeno(TS)fuzzy models·interconnected nonlinear systems fuzzy model predictive control parallel distributed compensation

来源：

维普期刊数据库

同方期刊数据库评论

在线全文

学校读者我要写书评

暂无评论

Robust Neural Control of Discrete Time Uncertain Nonlinear Systems Using Sliding Mode Backpropagation Training Algorithm

引用

International Journal of Automation and computing 2019年第2期16卷 213-225页

作者： Imen Zaidi mohamed Chtourou mohamed djemel Control & Energy Management Laboratory National School of Sfax EngineersUniversity of Sfax

This work deals with robust inverse neural control strategy for a class of single-input single-output(SISO) discrete-time nonlinear system affected by parametric uncertainties. According to the control scheme, in the first step, a direct neural model(DNM)is used to learn the behavior of the system, then, an inverse neural model(INM) is synthesized using a specialized learning technique and cascaded to the uncertain system as a controller. In previous works, the neural models are trained classically by backpropagation(BP) algorithm. In this work, the sliding mode-backpropagation(SM-BP) algorithm, presenting some important properties such as robustness and speedy learning, is investigated. Moreover, four combinations using classical BP and SM-BP are tested to determine the best configuration for the robust control of uncertain nonlinear systems. Two simulation examples are treated to illustrate the effectiveness of the proposed control strategy.

关键词： Discrete time uncertain nonlinear systems neural modelling sliding mode backpropagation (BP) algorithm robust neural control

来源：

维普期刊数据库

同方期刊数据库评论

在线全文

学校读者我要写书评

暂无评论

Two fuzzy internal model control methods for nonlinear uncertain systems

引用

International Journal of Intelligent Computing and Cybernetics 2017年第2期10卷 223-240页

作者： Amira Aydi mohamed djemel mohamed Chtourou Department of Electrical Engineering National School of Engineering of SfaxUniversity of SfaxSfaxTunisia

Purpose-The purpose of this paper is to use the internal model control to deal with nonlinear stable systems affected by parametric ***/methodology/approach-The dynamics of a considered system are approximated by a Takagi-Sugeno fuzzy *** parameters of the fuzzy rules premises are determined ***,the parameters of the fuzzy rules conclusions are updated using the descent gradient method under inequality constraints in order to ensure the stability of each local *** fact,without making these constraints the training algorithm can procure one or several unstable local models even if the desired accuracy in the training step is *** considered robust control approach is the internal *** is synthesized based on the Takagi-Sugeno fuzzy *** control strategies are *** first one is based on the parallel distribution compensation *** consists in associating an internal model control for each local ***,for the second strategy,the control law is computed based on the global Takagi-Sugeno fuzzy ***-According to the simulation results,the stability of all local models is obtained and the proposed fuzzy internal model control approaches ensure robustness against parametric ***/value-This paper introduces a method for the identification of fuzzy model parameters ensuring the stability of all local *** the resulting fuzzy model,two fuzzy internal model control designs are presented.

关键词： Robust control Uncertainties Descent gradient method Fuzzy modeling Internal model control Nonlinear systems

来源：

维普期刊数据库评论

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

欢迎您,

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

在线全文

在线全文

在线全文

请选择保存的检索档案：

请选择收藏分类：

通借通还

欢迎您,

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

在线全文

在线全文

在线全文

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：