scholarly journals Robust Observer Design for Discrete Descriptor Systems with Packet Losses

Complexity ◽  
2021 ◽  
Vol 2021 ◽  
pp. 1-11
Author(s):  
Yan Liu ◽  
Weifeng Zhong ◽  
Qiang Fan ◽  
Bo You ◽  
Jiazhong Xu
Keyword(s):  
Sufficient Conditions ◽  
Switched System ◽  
Observer Design ◽  
Descriptor Systems ◽  
Linear Matrix ◽  
Matrix Inequalities ◽  
Robust Performance ◽  
Packet Losses ◽  
Robust Observer ◽  
Error Dynamic

This paper considers observer design for discrete-time descriptor systems with packet losses. By taking packet loss into consideration, the error dynamic of the proposed observer becomes a stochastic switched system. Consequently, the proposed observer is synthesized in a stochastic switched system framework. Sufficient conditions for the stochastic stability with a prescribed robust performance of the error dynamic system are derived and converted into linear matrix inequalities. Not only can the proposed observer deal with packet losses, but it also attenuates the effect of process disturbance and measurement noise. A numerical simulation of a truck-trailer is given to demonstrate the effectiveness of the proposed method.

scholarly journals Robust Observer Design for Switched Positive Linear System with Uncertainties

2014 ◽  
Vol 2014 ◽  
pp. 1-9 ◽  
Author(s):  
Yanke Zhong ◽  
Tefang Chen
Keyword(s):  
Linear System ◽  
Linear Matrix Inequality ◽  
Dwell Time ◽  
Sufficient Conditions ◽  
Average Dwell Time ◽  
Observer Design ◽  
Linear Matrix ◽  
Matrix Inequality ◽  
Robust Observer ◽  
Slack Variable

This paper is concerned with the design of a robust observer for the switched positive linear system with uncertainties. Sufficient conditions of building a robust observer are established by using the multiple copositive Lyapunov-krasovskii function and the average dwell time approach. By introducing an auxiliary slack variable, these sufficient conditions are transformed into LMI (linear matrix inequality). A numerical example is given to illustrate the validities of obtained results.

Design the finite-time H∞ resilient filter of a class of switched systems with uncertain parameters

2017 ◽  
Vol 40 (9) ◽  
pp. 2756-2764 ◽  
Author(s):  
Qilong Ai ◽  
Chengcheng Ren ◽  
Jun Dong ◽  
Shuping He
Keyword(s):  
Dynamic Systems ◽  
Finite Time ◽  
Estimation Error ◽  
Sufficient Conditions ◽  
Average Dwell Time ◽  
Linear Matrix ◽  
Matrix Inequalities ◽  
Error Dynamic ◽  
Finite Time Boundedness ◽  
Error Dynamics

This paper is concerned with the problem of finite-time H∞ resilient filtering for a class of switch systems. The filtering error dynamics is constructed based on the H∞ resilient filter. The objective is to design a filter such that the finite-time H∞ gain from the unknown input to an estimation error is minimized or guaranteed to be less than or equal to a prescribed value. By selecting the proper multiple Lyapunov function and using the average dwell-time approach, sufficient conditions are obtained for the existence of the desired H∞ resilient filter, which also guarantee the finite-time boundedness of the filtering error dynamic systems. The design criteria are proposed in the form of linear matrix inequalities and then described as an optimization algorithm. Finally, a numerical example is employed to illustrate the effectiveness of the developed techniques.

scholarly journals Unbiased H∞ Infinite Filtering for Stochastic Systems with Data Packet Losses

2011 ◽  
Vol 204-210 ◽  
pp. 400-405
Author(s):  
Yu Mei Li ◽  
Bin Zhao ◽  
Xin Ping Guan
Keyword(s):  
Linear Matrix Inequalities ◽  
Stochastic Systems ◽  
Filter Design ◽  
Sufficient Conditions ◽  
Data Packet ◽  
Linear Matrix ◽  
Matrix Inequalities ◽  
Packet Losses ◽  
Computational Burden ◽  
Delay Dependent

This paper presents the unbiased H∞ filter design for stochastic systems with data packet losses. By constructing unbiased filter, the complexity and computational burden of the real-time filtering process are reduced greatly. Delay-dependent sufficient conditions for stochastic system with data packet losses are proposed in terms of linear matrix inequalities (LMIs). Numerical example demonstrates the proposed approaches are effective.

scholarly journals NonfragileH∞Control for Stochastic Systems with Markovian Jumping Parameters and Random Packet Losses

2014 ◽  
Vol 2014 ◽  
pp. 1-8 ◽  
Author(s):  
Jing Wang ◽  
Ke Zhang
Keyword(s):  
Closed Loop ◽  
Stochastic Systems ◽  
Sufficient Conditions ◽  
Linear Matrix ◽  
Markovian Jumping Parameters ◽  
Matrix Inequalities ◽  
Closed Loop System ◽  
Packet Losses ◽  
Markovian Jumping ◽  
Physical Plant

This paper is concerned with the nonfragileH∞control problem for stochastic systems with Markovian jumping parameters and random packet losses. The communication between the physical plant and controller is assumed to be imperfect, where random packet losses phenomenon occurs in a random way. Such a phenomenon is represented by a stochastic variable satisfying the Bernoulli distribution. The purpose is to design a nonfragile controller such that the resulting closed-loop system is stochastically mean square stable with a guaranteedH∞performance levelγ. By using the Lyapunov function approach, some sufficient conditions for the solvability of the previous problem are proposed in terms of linear matrix inequalities (LMIs), and a corresponding explicit parametrization of the desired controller is given. Finally, an example illustrating the effectiveness of the proposed approach is presented.

State and Input Observer Design for Nonlinear Impulsive Systems via LMI Approach

2014 ◽  
Vol 950 ◽  
pp. 119-124
Author(s):  
Tian Shao ◽  
Ke Peng ◽  
Zhi Sheng Chen ◽  
Yan Jun Liu
Keyword(s):  
Linear Matrix Inequalities ◽  
Sufficient Conditions ◽  
The State ◽  
Lyapunov Theory ◽  
Observer Design ◽  
Linear Matrix ◽  
Matrix Inequalities ◽  
Impulsive Systems ◽  
Lmi Approach ◽  
Quadratic Constraint

This paper addresses the observer design for simultaneously estimating the state and input of a class of impulsive systems whose nonlinear terms satisfy an incremental quadratic constraint. By employing Lyapunov theory, sufficient conditions for asymptotical and exponential estimation convergence are derived. Gain matrices of the proposed observer can be obtained by solving linear matrix inequalities (LMIs).

scholarly journals Robust Observer Design for Takagi-Sugeno Fuzzy Systems with Mixed Neutral and Discrete Delays and Unknown Inputs

2012 ◽  
Vol 2012 ◽  
pp. 1-13 ◽  
Author(s):  
Hamid Reza Karimi ◽  
Mohammed Chadli
Keyword(s):  
Sufficient Conditions ◽  
Observer Design ◽  
Linear Matrix ◽  
Robust Observer ◽  
Unknown Inputs ◽  
Discrete Delays ◽  
Neutral Models ◽  
Intermediate Variables ◽  
Delay Dependent ◽  
Takagi Sugeno

A robust observer design is proposed for Takagi-Sugeno fuzzy neutral models with unknown inputs. The model consists of a mixed neutral and discrete delay, and the disturbances are imposed on both state and output signals. Delay-dependent sufficient conditions for the design of an unknown input T-S observer with time delays are given in terms of linear matrix inequalities. Some relaxations are introduced by using intermediate variables. A numerical example is given to illustrate the effectiveness of the given results.

Exponential stability and periodicity of memristor-based recurrent neural networks with time-varying delays

2017 ◽  
Vol 10 (02) ◽  
pp. 1750027 ◽  
Author(s):  
Wei Zhang ◽  
Chuandong Li ◽  
Tingwen Huang
Keyword(s):  
Neural Networks ◽  
Exponential Stability ◽  
Sufficient Conditions ◽  
Functional Approach ◽  
Linear Matrix ◽  
Time Varying ◽  
Matrix Inequality ◽  
Matrix Inequalities ◽  
Inclusion Theory ◽  
The Stability

In this paper, the stability and periodicity of memristor-based neural networks with time-varying delays are studied. Based on linear matrix inequalities, differential inclusion theory and by constructing proper Lyapunov functional approach and using linear matrix inequality, some sufficient conditions are obtained for the global exponential stability and periodic solutions of memristor-based neural networks. Finally, two illustrative examples are given to demonstrate the results.

Exponential Stability for Stochastic Neural Networks with Time-Varying Delay and Leakage Delay

2015 ◽  
Vol 742 ◽  
pp. 399-403
Author(s):  
Ya Jun Li ◽  
Jing Zhao Li
Keyword(s):  
Neural Networks ◽  
Exponential Stability ◽  
Sufficient Conditions ◽  
Leakage Delay ◽  
Linear Matrix ◽  
Stochastic Neural Networks ◽  
Time Varying ◽  
Matrix Inequalities ◽  
Time Varying Delay ◽  
Varying Delay

This paper investigates the exponential stability problem for a class of stochastic neural networks with leakage delay. By employing a suitable Lyapunov functional and stochastic stability theory technic, the sufficient conditions which make the stochastic neural networks system exponential mean square stable are proposed and proved. All results are expressed in terms of linear matrix inequalities (LMIs). Example and simulation are presented to show the effectiveness of the proposed method.

scholarly journals Finite-Time Stabilization for Stochastic Inertial Neural Networks with Time-Delay via Nonlinear Delay Controller

2018 ◽  
Vol 2018 ◽  
pp. 1-11
Author(s):  
Deyi Li ◽  
Yuanyuan Wang ◽  
Guici Chen ◽  
Shasha Zhu
Keyword(s):  
Neural Networks ◽  
Time Delay ◽  
Finite Time ◽  
Design Method ◽  
Sufficient Conditions ◽  
Linear Matrix ◽  
Matrix Inequalities ◽  
Nonlinear Feedback ◽  
Inertial Neural Networks ◽  
Finite Time Stabilization

This paper pays close attention to the problem of finite-time stabilization related to stochastic inertial neural networks with or without time-delay. By establishing proper Lyapunov-Krasovskii functional and making use of matrix inequalities, some sufficient conditions on finite-time stabilization are obtained and the stochastic settling-time function is also estimated. Furthermore, in order to achieve the finite-time stabilization, both delayed and nondelayed nonlinear feedback controllers are designed, respectively, in terms of solutions to a set of linear matrix inequalities (LMIs). Finally, a numerical example is provided to demonstrate the correction of the theoretical results and the effectiveness of the proposed control design method.

Global dissipativity of stochastic Lotka–Volterra system with feedback controls

2017 ◽  
Vol 10 (02) ◽  
pp. 1750022 ◽  
Author(s):  
Qimin Zhang ◽  
Xinjing Zhang ◽  
Hongfu Yang
Keyword(s):  
Linear Matrix Inequalities ◽  
Lyapunov Functions ◽  
Sufficient Conditions ◽  
Jensen Inequality ◽  
Linear Matrix ◽  
Mean Square ◽  
Matrix Inequalities ◽  
Volterra System ◽  
Feedback Controls ◽  
The Mean

In this paper, a class of stochastic Lotka–Volterra system with feedback controls is considered. The purpose is to establish some criteria to ensure the system is globally dissipative in the mean square. By constructing suitable Lyapunov functions as well as combining with Jensen inequality and It[Formula: see text] formula, the sufficient conditions are established and they are expressed in terms of the feasibility to a couple linear matrix inequalities (LMIs). Finally, the main results are illustrated by examples.

Sign in / Sign up

Export Citation Format

Share Document