Constrained controllability of nonlinear stochastic impulsive systems

Constrained controllability of nonlinear stochastic impulsive systemsThis paper is concerned with complete controllability of a class of nonlinear stochastic systems involving impulsive effects in a finite time interval by means of controls whose initial and final values can be assigned in advance. The result is achieved by using a fixed-point argument.

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Guaranteed Cost Control for Interval Type-2 Fuzzy Semi-Markov Switching Systems within A Finite-Time Interval

IEEE Transactions on Fuzzy Systems ◽

10.1109/tfuzz.2021.3089248 ◽

2021 ◽

pp. 1-1

Author(s):

Linchuang Zhang ◽

Yonghui Sun ◽

Hak-Keung Lam ◽

Hongyi Li ◽

Jianxi Wang ◽

...

Keyword(s):

Finite Time ◽

Cost Control ◽

Markov Switching ◽

Guaranteed Cost Control ◽

Time Interval ◽

Switching Systems ◽

Finite Time Interval ◽

Guaranteed Cost ◽

Interval Type

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A finite-time ruin probability formula for continuous claim severities

Journal of Applied Probability ◽

10.1239/jap/1082999087 ◽

2004 ◽

Vol 41 (2) ◽

pp. 570-578 ◽

Cited By ~ 25

Author(s):

Zvetan G. Ignatov ◽

Vladimir K. Kaishev

Keyword(s):

Real Function ◽

Finite Time ◽

Ruin Probability ◽

Joint Distribution ◽

Time Interval ◽

Insurance Company ◽

Finite Time Interval ◽

Appell Polynomials ◽

Premium Income ◽

Inverted Dirichlet

An explicit formula for the probability of nonruin of an insurance company in a finite time interval is derived, assuming Poisson claim arrivals, any continuous joint distribution of the claim amounts and any nonnegative, increasing real function representing its premium income. The formula is compact and expresses the nonruin probability in terms of Appell polynomials. An example, illustrating its numerical convenience, is also given in the case of inverted Dirichlet-distributed claims and a linearly increasing premium-income function.

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Some Statistical Properties of Signal Plus Narrow Band Noise Integrated over a Finite Time Interval

Journal of Applied Physics ◽

10.1063/1.1722286 ◽

1956 ◽

Vol 27 (12) ◽

pp. 1442-1448 ◽

Cited By ~ 3

Author(s):

L. C. Maximon ◽

J. P. Ruina

Keyword(s):

Finite Time ◽

Narrow Band ◽

Statistical Properties ◽

Time Interval ◽

Finite Time Interval ◽

Narrow Band Noise ◽

Band Noise

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Finite-Time Boundedness for a Class of Delayed Markovian Jumping Neural Networks with Partly Unknown Transition Probabilities

Abstract and Applied Analysis ◽

10.1155/2014/597298 ◽

2014 ◽

Vol 2014 ◽

pp. 1-8

Author(s):

Li Liang

Keyword(s):

Neural Networks ◽

Finite Time ◽

Transition Probabilities ◽

The State ◽

Time Interval ◽

Finite Time Interval ◽

Markovian Jumping ◽

Stochastic Boundedness ◽

Partly Unknown Transition Probabilities ◽

Finite Time Boundedness

This paper is concerned with the problem of finite-time boundedness for a class of delayed Markovian jumping neural networks with partly unknown transition probabilities. By introducing the appropriate stochastic Lyapunov-Krasovskii functional and the concept of stochastically finite-time stochastic boundedness for Markovian jumping neural networks, a new method is proposed to guarantee that the state trajectory remains in a bounded region of the state space over a prespecified finite-time interval. Finally, numerical examples are given to illustrate the effectiveness and reduced conservativeness of the proposed results.

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On robust controllability of uncertain non-linear jump systems with respect to the finite-time interval

Transactions of the Institute of Measurement and Control ◽

10.1177/0142331211421807 ◽

2011 ◽

Vol 34 (7) ◽

pp. 841-849 ◽

Cited By ~ 7

Author(s):

Shuping He ◽

Fei Liu

Keyword(s):

Finite Time ◽

Sufficient Conditions ◽

Linear Matrix ◽

Time Interval ◽

Finite Time Interval ◽

Markov Jump ◽

Non Linear ◽

Robust Controllability ◽

Jump Systems ◽

Takagi Sugeno

In this paper we study the robust control problems with respect to the finite-time interval of uncertain non-linear Markov jump systems. By means of Takagi–Sugeno fuzzy models, the overall closed-loop fuzzy dynamics are constructed through selected membership functions. By using the stochastic Lyapunov–Krasovskii functional approach, a sufficient condition is firstly established on the stochastic robust finite-time stabilization. Then, in terms of linear matrix inequalities techniques, the sufficient conditions on the existence of the stochastic finite-time controller are presented and proved. Finally, the design problem is formulated as an optimization one. The simulation results illustrate the effectiveness of the proposed approaches.

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