Fuzzy robustH∞filter design for nonlinear discrete-time systems with interval time delays

2012 ◽  
Vol 43 (8) ◽  
pp. 1568-1579 ◽  
Author(s):  
Ya-Kun Su ◽  
Bing Chen ◽  
Qi Zhou ◽  
Chong Lin
Keyword(s):  
Discrete Time ◽  
Time Delays ◽  
Filter Design ◽  
Interval Time ◽  
Discrete Time Systems ◽  
Time Systems

scholarly journals Optimal Robust Fault Detection for Linear Discrete Time Systems

2008 ◽  
Vol 2008 ◽  
pp. 1-16 ◽  
Author(s):  
Nike Liu ◽  
Kemin Zhou
Keyword(s):  
Fault Detection ◽  
Discrete Time ◽  
Filter Design ◽  
Algebraic Riccati Equation ◽  
Optimization Criteria ◽  
Robust Detection ◽  
Discrete Time Systems ◽  
Robust Fault Detection ◽  
Time Systems ◽  
Detection Filter

This paper considers robust fault-detection problems for linear discrete time systems. It is shown that the optimal robust detection filters for several well-recognized robust fault-detection problems, such asℋ−/ℋ∞,ℋ2/ℋ∞, andℋ∞/ℋ∞problems, are the same and can be obtained by solving a standard algebraic Riccati equation. Optimal filters are also derived for many other optimization criteria and it is shown that some well-studied and seeming-sensible optimization criteria for fault-detection filter design could lead to (optimal) but useless fault-detection filters.

scholarly journals New Delay-Dependent Robust Stability Criterion for LPD Discrete-Time Systems with Interval Time-Varying Delays

2013 ◽  
Vol 2013 ◽  
pp. 1-10 ◽  
Author(s):  
Narongsak Yotha ◽  
Kanit Mukdasai
Keyword(s):  
Robust Stability ◽  
Discrete Time ◽  
Model Transformation ◽  
Linear Matrix ◽  
Time Varying ◽  
Interval Time ◽  
Discrete Time Systems ◽  
Delay Dependent ◽  
Parameter Dependent ◽  
Time Systems

This paper investigates the problem of robust stability for linear parameter-dependent (LPD) discrete-time systems with interval time-varying delays. Based on the combination of model transformation, utilization of zero equation, and parameter-dependent Lyapunov-Krasovskii functional, new delay-dependent robust stability conditions are obtained and formulated in terms of linear matrix inequalities (LMIs). Numerical examples are given to demonstrate the effectiveness and less conservativeness of the proposed methods.

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