Improved Delay-Dependent Robust Stability Criteria for a Class of Uncertain Neutral Type Lur ’ e Systems with Discrete and Distributed Delays

This paper is concerned with the problem of delay-dependent robust stability analysis for a class of uncertain neutral type Lur’e systems with mixed time-varying delays.The system has not only time-varying uncertainties and sector-bounded nonlinearity, but also discrete and distributed delays, which has never been discussed in the previous literature. Firstly, by employing one effective mathematical technique, some less conservative delay-dependent stability results are established without employing the bounding technique and the mode transformation approach. Secondly, by constructing an appropriate new type of Lyapunov-Krasovskii functional with triple terms, improved delay-dependent stability criteria in terms of linearmatrix inequalities (LMIs) derived in this paper are much brief and valid. Furthermore, both nonlinearities located in finite sector and infinite one have been also fully taken into account. Finally, three numerical examples are presented to illustrate lesser conservatism and the advantage of the proposed main results.


Introduction
Time delay arises naturally in connection with system process and information flow for different part of dynamic systems.Dynamical systems with time delays, also called dynamic systems with hereditary systems, after effect or dead time, equations with deviating argument, have been investigated extensively for the past few decades due to their wide applications in many research fields, covering nuclear reactor, manual control, engineering systems, neural networks, and other scientific areas .The main reason is that time-delay phenomenon frequently happens in various engineering systems and is also a key source of instability and oscillation.Hence, the delayed systems have been widely considered by a great quantity of research results in the recent years.To mention a few, stability analysis is carried out in [1,3,6,7,11,12,15,17,25,[32][33][34]36];  ∞ controllers and  ∞ estimation are investigated in [31,38,41]; Lur' e dynamical systems are addressed in [4][5][6][26][27][28][29]; neutral systems with discrete and distributed delays are researched in [32][33][34]; passivity analysis and reliable fuzzy control are considered, respectively, in [39,42].For the new results on time-delay systems, see the works [3,21,29,34,[38][39][40][41][42] and references cited therein.Therefore, it is of both theoretical and practical importance to study the problem of stability analysis on delayed systems.So far in the literatures, delayed systems can be classified into two types: retarded type and neutral type [1][2][3][4][5][6][7][8][9][10][11][12].The retarded type system only depends on the state delay, while the neutral type system not only defines the derivative term of the current state but also explains the derivative term of the past state.And what is more, the delayed stability criteria are also classified into two categories according to their dependence on the size of the delays, namely, delay-independent stability criteria and delay-dependent stability criteria [13][14][15][16][17][18].It is well known that delay-dependent stability criteria are less conservative than delay-independent ones when the sizes of time-delays are small.
As everyone knows, many nonlinear physical systems can be expressed as a feedback connection of a linear dynamical system and nonlinearity.One of the important classes of nonlinear systems is the Lur' e dynamical system whose nonlinear element satisfies certain sector constraints.Since the notion of absolute stability was introduced by Lur' e [19], stability analysis for the Lur' e systems has been extensively studied for several decades [20][21][22][23][24][25][26][27][28][29].Recently, various approaches have been proposed by many researchers to obtain robust stability criteria for time-delay Lur' e control systems.Therefore, many methods have been proposed in these results to reduce the conservatism of the stability criteria, such as model transformation method, the bounding technique, free-weighting matrix method, the method of constructing Lyapunov-Krasovskii functionals, delay decomposition technique, and weighting-matrix decomposition method.By using suitable Lyapunov-Krasovskii functionals and free-weighting matrices, a new delay-dependent robust stability criterion of the class of uncertain mixed neutral and Lur' e systems has been proposed in [21].Some conditions have been derived by employing Lyapunov-Krasovskii functionals and generalized convex combination in [26].Sufficient conditions for the robustly asymptotic stability have been achieved by eliminating nonlinearity and removing free-weighting matrices in [29].In addition, delayed systems often have a spatial extent because of the presence of an amount of parallel pathways of varying axon sizes and lengths.Then, there may exist either a distribution of conduction velocities along these pathways or a distribution of propagation delays over a period of time in some cases, which may cause another type of time delays, namely, distributed time delays in delayed systems.Hence, the stability problem for neutral systems with nonlinearity perturbation and time delay was thus of interest to a great number of researchers.The results in [30] are neutral-delayindependent by a method based on the equivalent equation of zero and the Leibniz-Newton formula in the derivative of the Lyapunov-Krasovskii functionals.In [32], Li and Zhu have obtained the discrete-, neutral-, and distributed-delaydependent stability conditions for uncertain neutral system with discrete and distributed delays by constructing an augmented Lyapunov-Krasovskii functional and using the freeweighting matrices combined with the bounding technique.In [34], by constructing a proper Lyapunov-Krasovskii functional, Chen et al. have derived some new delay-dependent stability criteria for uncertain neutral system with mixed constant delays by making full use of the free-weighting matrices method and without bounding technique bringing much more conservatism used to deal with these triple-integral terms in [33]; however, the research of uncertain neutral system with mixed constant delays has a lot of limitations because of the delay-dependent robust stability criteria for uncertain neutral systems often connected with time-varying delay.Since time delay and parameter uncertainty exist in Lur' e systems in practice, the robust stability analysis for uncertain Lur' e systems with time delays still requires further consideration.And theoretically, except the traditional freeweighting matrices approach, how to get rid of the rigorous constraint that the time derivatives of time-varying delays must be less than one still needs much more study.
Motivated by the above discussion, in the paper, it is the first attempt to investigate one effective mathematical technique [29] to extend for a class of uncertain neutral type Lur' e systems with mixed time-varying delays which has not only time-varying uncertainties and sector-bounded nonlinearity, but also discrete and distributed delays.The effective mathematical technique is that dividing is defined as a delay segmentation technique and supposing −ℎ() ẋ (), which plays an important role in the improvement of less conservative results.Secondly, by constructing a new type of Lyapunov-Krasovskii functional with triple terms, improved delay-dependent stability criteria in terms of linear matrix inequalities (LMIs) derived in this paper are brief and effective, which can be easily solved by using MATLAB LIM control toolbox [37].Furthermore, both nonlinearities located in a finite sector and infinite one have been also fully taken into account.Finally, three numerical examples are given to illustrate the less conservatism of the proposed method.
Notation.Notations used in this paper are fairly standard:   denotes the -dimensional Euclidean space;  × is the set of all  ×  dimensional matrices;  denotes the identity matrix of appropriate dimensions;  stands for matrix transposition; the notation  > 0 (resp.,  ≥ 0), for  ∈  × , means that the matrix is real symmetric positive definite (resp., positive semidefinite); diag{ 1 ,  2 , . . .,   } denotes block diagonal matrix with diagonal elements   ,  = 1, 2, . . ., ; the symbol * represents the elements below the main diagonal of a symmetric matrix.
The following fact and lemmas are introduced, which will be used in the proof of the main results.

Stability Analysis in the Finite
Sector  [0,  ] .In this section, we will give sufficient conditions under which the system (1) is robustly asymptotically stable.
When ℎ  = 0, we can get a delay-dependent asymptotical stability criterion for the system (1) using the same method of Theorem 4. This result is shown in Theorem 7.
Theorem 7.For a given positive integer  and scalars ℎ  , ℎ  ,   ,   , and  with 0 < ℎ  , ℎ  < 1,  D < 1, and  > 0, the system (1) with a nonlinear function (()) satisfying the finite sector condition (4) and time-varying delays ℎ() and () satisfying ( 9) is robustly asymptotically stable if there exist    =   > 0 ( = 1,3,4,5),   2 =  2 > 0, M   =   > 0 ( = 1, 2), a scalar  > 0, and diagonal matrices Λ = diag{ 1 ,  2 , . . .,   } ≥ 0 with dimensions such that the following symmetric linear matrix inequality holds: where Remark 8. Recently, Wang et al. [29] present the effective mathematical technique to improve significantly the stability criterion.Motivated by this technique, it is the first attempt of the integral partitioning method to extend to a class of uncertain neutral type Lur' e systems with discrete and distributed delays, which has never been mentioned in the previous literatures.Remark 10.Compared with those in previous methods, this method proposed in this paper has two differences: (i) the item ∫  −ℎ  ẋ  () 2 ẋ () is added into the Lyapunov functional, which will reduce the conservativeness of results; (ii) the Jensen inequality technique is used, which results in LMIs criteria with less variables than free-weighting matrix approach.
Remark 13.Table 3 shows the maximum values of ℎ  which guarantee stability of this system by applying Theorems 3 and 6 in this paper, where  1 = [0, 0.5),  2 = [0, 10), 3 = [0, 1000), and  4 = [0, ∞). where = [ −0.12 0 −0.12 0.12 ] , Remark 15.By applying Theorem 5 and solving the LMI (28) using MATLAB LMI control toolbox, we obtain the maximum allowable upper bounds which are listed in Tables 4 and 5. From Tables 4 and 5, it can be seen that our results show significant improvements over the results obtained in [15,33,34].Further, if the values of  become larger, then the upper bound of the delay will also become larger which is the advantage of the delay partitioning approach used in this paper.Figures 5-8 show clearly that the state vector () stabilizes to zero asymptotically.
Example 16.Consider the system (1) with the following parameters [7]: x 1 (t) Remark 17.When ℎ  = 0, the maximum upper bounds ℎ  of the delay ℎ() for different ℎ  and   obtained from [7] and Theorem 3 of this paper are listed in Tables 6, 7, and 8. From the tables, we can see that the proposed result in this paper is less conservative than the one in [7].Besides,   x 1 (t) x 1 (t) x 2 (t) x 2 (t)    var2, var3, and var4 is plotted as var2 versus var1, var4 versus var3, and so on.Both variables in associated pairs must contain the same number of elements.
Figures 2, 6, and 10 are 3D mesh plot displaying a matrix as a wireframe surface.Plotted variables are as follows: (1) single variable (): plot matrix values as heights above the - plane and map data values to colormap; (2) three variables (, , ):  and  are vectors or matrices defining the  and  components of a surface.
Figures 3, 7, and 11 are 3D stem graph (display lines extending from the --plane, terminating in circular markers).Plotted variables are as follows: (1) single variable (): when  is a row vector, plot all elements at equally spaced -values against the same x 1 (t) x 1 (t) x 2 (t) x 2 (t)  (1) two rho): polar coordinate plot of angle theta (radians) versus radius rho (data units).

)
Remark 12.For Example 11, our results of the maximum allowable delay bound (MADB) ℎ  for different values of ℎ  and   are listed in Tables1 and 2. It is clear to show that the maximum allowable delay bound (MADB) ℎ  is dependent on different values of ℎ  and   .The values of ℎ  and   increase, respectively, as the maximum allowable delay bound (MADB) ℎ

Table 4 :
Maximum allowable delay bound (MADB)  for  = 0.1 and different values of ℎ in Example 14.

Table 5 :
Maximum allowable delay bound (MADB) ℎ for  = 0.1 and different values of  in Example 14.

Table 6 :
Maximum allowable delay bound (MADB) ℎ  for different values of ℎ  in Example 16.
(2)  variable pairs: plot each pair of variables the selected sequence.For example, the sequence var1,

Table 8 :
Maximum allowable delay bound (MADB) ℎ  for different values of ℎ  in Example 16. type Lur' e systems with discrete and distributed delays.In the first place, by using one effective mathematical technique, some less conservative delay-dependent stability results are established without employing the bounding technique and the mode transformation approach.In the second place, by constructing an appropriate Lyapunov-Krasovskii functional with triple terms playing an important role in reducing the conservatism of our results, improved delay-dependent stability criteria in terms of linear matrix inequalities (LMIs) derived in this paper are much simple and valid.What is more, both nonlinearities located in a finite sector and infinite one have been also fully taken into account.Finally, three numerical examples are given to illustrate the less conservatism of the proposed main results. neutral