Convex Optimization Approach to Observer-Based Stabilization of Uncertain Linear Systems

2005 ◽  
Vol 128 (4) ◽  
pp. 989-994 ◽  
Author(s):  
Salim Ibrir
Keyword(s):  
Linear Systems ◽  
State Feedback ◽  
Observer Design ◽  
Linear Matrix ◽  
Computational Algorithms ◽  
Optimization Approach ◽  
Matrix Inequality ◽  
Matrix Inequalities ◽  
The Stability ◽  
Uncertain Linear Systems

New sufficient linear matrix inequality conditions guaranteeing the stability of uncertain linear systems by means of dynamic output feedbacks are presented. It is shown that the search of an observer-based controller for this class of systems is fundamentally decomposed into two main problems: robust stability with a memoryless state feedback and observer design with measured uncertainties. Under the fulfilment of the developed linear matrix inequalities conditions, we show that the observer-based problem is solvable without any need for some equality constraints or iterative computational algorithms. Examples showing the potential of the results are presented.

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.

Mixed H2/H∞ Control for State-Delayed Linear Systems and a LMI Approach to the Solution of Coupled AREs

2003 ◽  
Vol 125 (2) ◽  
pp. 249-253 ◽  
Author(s):  
M. D. S. Aliyu
Keyword(s):  
Control Problem ◽  
Linear Systems ◽  
Linear Matrix Inequalities ◽  
State Feedback ◽  
Sufficient Conditions ◽  
Riccati Equations ◽  
Linear Matrix ◽  
Matrix Inequalities ◽  
Lmi Approach ◽  
Alternative Approach

In this paper, the state-feedback mixed H2/H∞ control problem for state-delayed linear systems is considered. Sufficient conditions for the solvability of this problem are given in terms of the solution to a pair of algebraic Riccati equations similar to the nondelayed case. However, these Riccati equations are more difficult to solve than those arising in the pure H2,H∞ problems, and an alternative approach is to solve a pair of linear matrix inequalities (LMIs).

scholarly journals Less Conservative Control Design for Linear Systems with Polytopic Uncertainties via State-Derivative Feedback

2012 ◽  
Vol 2012 ◽  
pp. 1-21 ◽  
Author(s):  
Emerson R. P. da Silva ◽  
Edvaldo Assunção ◽  
Marcelo C. M. Teixeira ◽  
Luiz Francisco S. Buzachero
Keyword(s):  
Linear Systems ◽  
Lyapunov Functions ◽  
State Feedback ◽  
Controller Design ◽  
Linear Matrix ◽  
Matrix Inequalities ◽  
Polytopic Uncertainties ◽  
Parameter Dependent ◽  
Finsler’S Lemma ◽  
Time Linear

The motivation for the use of state-derivative feedback instead of conventional state feedback is due to its easy implementation in some mechanical applications, for example, in vibration control of mechanical systems, where accelerometers have been used to measure the system state. Using linear matrix inequalities (LMIs) and a parameter-dependent Lyapunov functions (PDLF) allowed by Finsler’s lemma, a less conservative approach to the controller design via state-derivative feedback, is proposed in this work, with and without decay rate restriction, for continuous-time linear systems subject to polytopic uncertainties. Finally, numerical examples illustrate the efficiency of the proposed method.

scholarly journals A comparative study of nonlinear circle criterion based observer and H∞ observer for induction motor drive

2019 ◽  
Vol 10 (3) ◽  
pp. 1229
Author(s):  
Farid Berrezzek ◽  
Wafa Bourbia ◽  
Bachir Bensaker
Keyword(s):  
Comparative Study ◽  
Induction Motor ◽  
Observer Design ◽  
Nonlinear Observer ◽  
Linear Matrix ◽  
Optimization Approach ◽  
Lmi Optimization ◽  
Circle Criterion ◽  
True State ◽  
The Stability

<span lang="EN-US">This paper deals with a comparative study of circle criterion based nonlinear observer<em> </em>and <em>H<sub>∞</sub></em> observer for induction motor (IM) drive. The  advantage of the circle criterion approach for nonlinear observer design is that it directly handles the nonlinearities of the system with less restriction  conditions in contrast of the other methods which attempt to eliminate them. However the <em>H<sub>∞</sub></em> observer guaranteed the stability taking into account disturbance and noise attenuation. Linear matrix inequality (LMI) optimization approach is used to compute the gains matrices for the two observers. The simulation results show the superiority of <em>H<sub>∞</sub></em> observer in the sense that it can achieve convergence to the true state, despite the nonlinearity of model and the presence of disturbance.</span>

scholarly journals State Estimators for Uncertain Linear Systems with Different Disturbance/Noise Using Quadratic Boundedness

2012 ◽  
Vol 2012 ◽  
pp. 1-10 ◽  
Author(s):  
Longge Zhang ◽  
Xiangjie Liu ◽  
Xiaobing Kong
Keyword(s):  
Linear Systems ◽  
Estimation Error ◽  
Measurement Noise ◽  
Linear Matrix ◽  
Matrix Inequalities ◽  
State Estimators ◽  
Sufficient Stability ◽  
Necessary And Sufficient ◽  
Uncertain Linear Systems ◽  
Sufficient Stability Conditions

This paper designs state estimators for uncertain linear systems with polytopic description, different state disturbance, and measurement noise. Necessary and sufficient stability conditions are derived followed with the upper bounding sequences on the estimation error. All the conditions can be expressed in the form of linear matrix inequalities. A numerical example is given to illustrate the effectiveness of the approach.

scholarly journals Robust H∞ Control For Uncertain Singular Neutral Time-Delay Systems

Mathematics ◽  
2019 ◽  
Vol 7 (3) ◽  
pp. 217 ◽  
Author(s):  
Yuhong Huo ◽  
Jia-Bao Liu
Keyword(s):  
Time Delay ◽  
Stability Condition ◽  
State Feedback ◽  
State Feedback Control ◽  
Delay Systems ◽  
Linear Matrix ◽  
Control Law ◽  
Matrix Inequality ◽  
Time Delay Systems ◽  
Matrix Inequalities

The present paper attempts to investigate the problem of robust H ∞ control for a class of uncertain singular neutral time-delay systems. First, a linear matrix inequality (LMI) is proposed to give a generalized asymptotically stability condition and an H ∞ norm condition for singular neutral time-delay systems. Second, the LMI is utilized to solve the robust H ∞ problem for singular neutral time-delay systems, and a state feedback control law verifies the solution. Finally, four theorems are formulated in terms of a matrix equation and linear matrix inequalities.

scholarly journals LMI-Observer-Based Stabilizer for Chaotic Systems in the Existence of a Nonlinear Function and Perturbation

Mathematics ◽  
2021 ◽  
Vol 9 (10) ◽  
pp. 1128
Author(s):  
Hamede Karami ◽  
Saleh Mobayen ◽  
Marzieh Lashkari ◽  
Farhad Bayat ◽  
Arthur Chang
Keyword(s):  
Linear Matrix Inequality ◽  
State Feedback ◽  
Chaotic Systems ◽  
Nonlinear Function ◽  
Observer Design ◽  
System Stability ◽  
Linear Matrix ◽  
Matrix Inequality ◽  
Estimation Errors ◽  
Suggested Approach

In this study, the observer-based state feedback stabilizer design for a class of chaotic systems in the existence of external perturbations and Lipchitz nonlinearities is presented. This manuscript aims to design a state feedback controller based on a state observer by the linear matrix inequality method. The conditions of linear matrix inequality guarantee the asymptotical stability of the system based on the Lyapunov theorem. The stabilizer and observer parameters are obtained using linear matrix inequalities, which make the state errors converge to the origin. The effects of the nonlinear Lipschitz perturbation and external disturbances on the system stability are then reduced. Moreover, the stabilizer and observer design techniques are investigated for the nonlinear systems with an output nonlinear function. The main advantages of the suggested approach are the convergence of estimation errors to zero, the Lyapunov stability of the closed-loop system and the elimination of the effects of perturbation and nonlinearities. Furthermore, numerical examples are used to illustrate the accuracy and reliability of the proposed approaches.

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