New condition of stabilization for continuous Takagi-Sugeno fuzzy system based on fuzzy Lyapunov function

Bouyahya, Ali; Manai, Yassine; Haggège, Joseph

doi:10.1109/iceesa.2013.6578391

Cited by 9 publications

(3 citation statements)

References 16 publications

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“…However, most systems are complex and nonlinear in actual industrial production; hence, more attention should be paid to the design of nonlinear networked controllers and it is urgently necessary to study the relevant results further. In the field of nonlinear control systems, fuzzy control has aroused great attention, especially for the T–S fuzzy model, which is an effective solution to narrow the gap between the fruitful linear control systems and complex nonlinear fuzzy control ones (Bouyahya et al, 2013; Lu and Shih, 2010; Ren et al, 2014).…”

Section: Introductionmentioning

confidence: 99%

Constrained model predictive control for T–S fuzzy system with randomly occurring actuator saturation and packet losses via PDC and non-PDC strategies

Liu

Tang

Deng

2018

Transactions of the Institute of Measurement and Control

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This paper studies model predictive control for a Takagi–Sugeno (T–S) fuzzy system with randomly occurring actuator saturation and packet losses. The nonlinearity of the actuator saturation is transformed into a set of convex hulls, while the packet losses are assumed to obey the rules of Bernoulli distribution. Both parallel-distributed-compensation (PDC) and non-parallel-distributed-compensation (non-PDC) strategies are adopted to design the controller for the system. In addition, sufficient conditions of the stability for the closed-loop system are given in terms of linear matrix inequalities. It is shown that the non-PDC strategy behaves less conservatively than the PDC strategy in controlling the considered T–S fuzzy system, when the input and output constraints are explicitly considered. Two simulation examples are provided to illustrate the effectiveness of the proposed design techniques.

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Section: Introductionmentioning

confidence: 99%

Constrained model predictive control for T–S fuzzy system with randomly occurring actuator saturation and packet losses via PDC and non-PDC strategies

Liu

Tang

Deng

2018

Transactions of the Institute of Measurement and Control

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“…The second class of function is less conservative than the first. Many researches have investigated nonquadratic Lyapunov functions [11,12,13,14,15,16].…”

Section: Introductionmentioning

confidence: 99%

Nonquadratic Lyapunov Functions for Nonlinear Takagi-Sugeno Discrete Time Uncertain Systems Analysis and Control

Bouyahya¹,

Manai²,

Haggège³

2016

ijacsa

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“…The PDC control law is written is the next equation For the modelisation and conception details for the PDC controller, see [23].…”

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confidence: 99%

Application of New Approach of design flow for Hardware/Software Embedded System with the Use of Design Patterns in Fuzzy control system

Bouyahya

Manai

Haggège

2015

IJRES

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<p>This paper present a new method of conception of hardware/software embedded system design methodology based on use of design pattern approach called Abstract_factory. We called this new design tool “smart cell”. The main idea of the conception of embedded systems design is based on the used of object-oriented design ULM2.0. When the smart-cell is implemented, we justify their uses as a design tool that allows, first, to develop a specified application of fuzzy controller called PDC (parallel distributed conpensation). Second, the specification of the generation phases of the system architecture design, and eventually partitioning the application on heterogeneous platform based on hardware resource DSP and FPGA software to illustrate the proposed approach.</p>

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New condition of stabilization for continuous Takagi-Sugeno fuzzy system based on fuzzy Lyapunov function

Cited by 9 publications

References 16 publications

Constrained model predictive control for T–S fuzzy system with randomly occurring actuator saturation and packet losses via PDC and non-PDC strategies

Constrained model predictive control for T–S fuzzy system with randomly occurring actuator saturation and packet losses via PDC and non-PDC strategies

Nonquadratic Lyapunov Functions for Nonlinear Takagi-Sugeno Discrete Time Uncertain Systems Analysis and Control

Application of New Approach of design flow for Hardware/Software Embedded System with the Use of Design Patterns in Fuzzy control system

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