Fuzzy Membership Function Dependent Switched Control for Nonlinear Systems with Memory Sampled-Data Information

Abstract In this paper, a fuzzy memory-based coupling sampled-data control (SDC) is designed for nonlinear systems through the switched approach. Compared with the usual SDC scheme, by employing the Bernoulli sequence, a more general coupling switched SDC that involving the signal transmission delay is designed. The Lyapunov-Krasovskii Functional (LKF) is presented with the available characteristics of the membership function, and a coupling sampling pattern, for the T-S fuzzy systems. Based on LKF, together with time derivative information of membership function, and the generalized N -order free-matrix-based inequality, the suitable conditions are obtained in terms of linear matrix inequalities (LMIs) for guaranteeing the asymptotic stability and stabilization of the concerned system. Then the desired fuzzy coupling SDC gain is attained from the solvable LMIs. In the end, two examples are given to validate the derived theoretical results.

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State-Feedback Sampled-Data Control Design for Nonlinear Systems via Passive Theory

Mathematical Problems in Engineering ◽

10.1155/2013/230413 ◽

2013 ◽

Vol 2013 ◽

pp. 1-12 ◽

Cited By ~ 1

Author(s):

Chengming Yang ◽

Qi Zhou ◽

H. R. Karimi ◽

Huanqing Wang

Keyword(s):

Nonlinear Systems ◽

Controller Design ◽

Linear Matrix ◽

Optimization Approach ◽

Sampled Data ◽

Control Approach ◽

Synthesis Conditions ◽

Data Control ◽

Sampled Data Control ◽

Data Controller

This paper investigates the problem of passive controller design for a class of nonlinear systems under variable sampling. The Takagi-Sugeno (T-S) fuzzy modeling method is utilized to represent the nonlinear systems. Attention is focused on the design of passive controller for the T-S fuzzy systems via sampled-data control approach. Under the concept of very-strict passivity, a novel time-dependent Lyapunov functional is constructed to develop passive analysis criteria and passive controller synthesis conditions. A new sampled-data controller is designed to guarantee that the resulting closed-loop system is very-strictly passive. These conditions are formulated in the form of linear matrix inequalities (LMIs), which can be solved by convex optimization approach. Finally, an application example is given to demonstrate the feasibility and effectiveness of the proposed results.

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TS Fuzzy Robust Sampled-Data Control for Nonlinear Systems with Bounded Disturbances

Computation ◽

10.3390/computation9120132 ◽

2021 ◽

Vol 9 (12) ◽

pp. 132

Author(s):

Thangavel Poongodi ◽

Prem Prakash Mishra ◽

Chee Peng Lim ◽

Thangavel Saravanakumar ◽

Nattakan Boonsatit ◽

...

Keyword(s):

Nonlinear Systems ◽

Fault Tolerant ◽

Sufficient Conditions ◽

Linear Matrix ◽

Sampled Data ◽

Actuator Failures ◽

Data Control ◽

Bounded Disturbances ◽

Delay Dependent ◽

Takagi Sugeno

We investigate robust fault-tolerant control pertaining to Takagi–Sugeno (TS) fuzzy nonlinear systems with bounded disturbances, actuator failures, and time delays. A new fault model based on a sampled-data scheme that is able to satisfy certain criteria in relation to actuator fault matrix is introduced. Specifically, we formulate a reliable controller with state feedback, such that the resulting closed-loop-fuzzy system is robust, asymptotically stable, and able to satisfy a prescribed H∞ performance constraint. Linear matrix inequality (LMI) together with a proper construction of the Lyapunov–Krasovskii functional is leveraged to derive delay-dependent sufficient conditions with respect to the existence of robust H∞ controller. It is straightforward to obtain the solution by using the MATLAB LMI toolbox. We demonstrate the effectiveness of the control law and less conservativeness of the results through two numerical simulations.

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