Robust passivity analysis of Markov‐type Lotka–Volterra model with time‐varying delay and uncertain mode transition rates

2020 ◽  
Vol 43 (11) ◽  
pp. 6976-6984
Author(s):  
Lan Wang ◽  
Yiping Dong ◽  
Da Xie ◽  
Jinde Cao
Keyword(s):  
Volterra Model ◽  
Time Varying ◽  
Mode Transition ◽  
Transition Rates ◽  
Markov Type ◽  
Time Varying Delay ◽  
Passivity Analysis ◽  
Varying Delay

Positive L1-gain filter design for positive Markovian jump systems with time-varying delay and incomplete transition rates

2016 ◽  
Vol 94 (9) ◽  
pp. 877-883
Author(s):  
Wenhai Qi ◽  
Xianwen Gao ◽  
Yonggui Kao
Keyword(s):  
Filter Design ◽  
Markovian Jump Systems ◽  
Time Varying ◽  
Transition Rates ◽  
Markovian Jump ◽  
Time Varying Delay ◽  
Positive Markovian Jump Systems ◽  
Error System ◽  
Jump Systems ◽  
Varying Delay

This paper deals with the problem of positive L1-gain filter design for positive Markovian jump systems with time-varying delay and incomplete transition rates. By implying an appropriate co-positive type Lyapunov function and free-connection weighting vectors, sufficient conditions for stochastic stability of the filtering error system are established. Then, the L1-gain performance is analyzed. Based on the obtained results, a positive full-order filter is designed to ensure that the corresponding filtering error system is positive and stochastically stable with L1-gain performance. All the conditions are derived in linear programming. Finally, the obtained theoretical results are demonstrated by a numerical example.

A Delay-Dependent Approach to Passivity Analysis for Uncertain Neural Networks with Time-varying Delay

2008 ◽  
Vol 27 (3) ◽  
pp. 237-246 ◽  
Author(s):  
Chien-Yu Lu ◽  
Hsun-Heng Tsai ◽  
Te-Jen Su ◽  
Jason Sheng-Hong Tsai ◽  
Chin-Wen Liao
Keyword(s):  
Neural Networks ◽  
Time Varying ◽  
Time Varying Delay ◽  
Passivity Analysis ◽  
Uncertain Neural Networks ◽  
Delay Dependent ◽  
Varying Delay
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