The asymptotic properties of the suppressed functional differential system by Brownian noise under regime switching

In the previous work by Wu et al., it was shown that the polynomial Brownian noise may suppress the potential explosion of the nonlinear system without the linear growth condition or the one-sided linear growth condition and the linear Brownian noise may stabilise this suppressed system. This paper is a continuation of our previous article and considers the asymptotic properties of the suppressed functional differential system under regime switching. These asymptotic properties show that the suppressed functional differential system by polynomial Brownian noise will grow with at most polynomial speed.     

New criteria for stochastic suppression and stabilization of hybrid functional differential systems

This paper establishes new criteria for stochastic suppression and stabilization of hybrid functional differential systems with general 1‐sided polynomial growth condition. For an unstable nonlinear hybrid functional differential system with general 1‐sided polynomial growth condition, 2 independent Brownian noise processes are used to perturb the system into the stochastic hybrid differential system. Theoretical analysis shows that one of the nonlinear diffusion terms may suppress the explosive solution of deterministic system, and the other one can make the perturbed hybrid system almost surely stable with general decay rate.     

A note on explosion suppression for nonlinear delay differential systems by polynomial noise

Liu and Shen discussed the role of stochastic suppression on the explosive solution by a polynomial noise for a deterministic differential system satisfying a general polynomial growth condition. They further showed that the global solution of the corresponding perturbed system grows at most polynomially. However, the estimation of the asymptotic property of polynomial growth is rough, and we see the necessity to develop a more accurate estimation which is the main motivation of the present paper. As to the existence of time delays, we aim to discuss the stochastic roles of the polynomial noise for a deterministic delay differential system with the general polynomial growth condition. We show that a properly chosen polynomial stochastic noise not only can guarantee the existence and uniqueness of the global solution of the stochastically perturbed delay differential system, but also can make almost every sample path of the global solution grow at most with polynomial rate and even decay to the zero solution exponentially.     

Algebraic approach to stochastic optimal digital controller design

A new approach to the design of an optimal controller for a system described by its transfer function (SISO case) is presented. The stochastic or deterministic disturbances as well as the noise contaminating measured output are described by the spectral density. The objective is the minimization of a linear combination of quadratic measures of system input and output on an infinite time range. The basic idea is the determination of a new optimization domain inside which asymptotic stability of the system, considering its closed-loop structure, is guaranteed. The solution uses polynomial algebraic techniques and requires only the solution of the system of two polynomial equations, the coefficients of which are obtained from spectral factorization. The system may be unstable and/or non-minimal phase and possible measurement noise may be coloured.     

Error feedback and a servomechanism problem for uncertain nonlinear systems

The robust servomechanism problem, also known as the problem of robust output regulation, is considered for a family of uncertain triangular systems. In contrast to the previous work where the uncertain vector field of the controlled plant was assumed to be bounded by a linear growth of the unmeasurable states multiplied by a polynomial function of the system output, we show that the polynomial growth condition can be relaxed and robust output regulation by error feedback is still possible, as long as the uncertain system is dominated by a continuous function of the system output multiplied by a linear growth of the unmeasurable states.     

Global asymptotic stabilisation of rational dynamical systems based on solving BMI

In this paper, the global asymptotic stabiliser design of rational systems is studied in detail. To develop the idea, the state equations of the system are transformed to a new coordinate via polynomial transformation and the state feedback control law. This in turn is followed by the satisfaction of the linear growth condition (i.e. Lipschitz at zero). Based on a linear matrix inequality solution, the system in the new coordinate is globally asymptotically stabilised and then, leading to the global asymptotic stabilisation of the primary system. The polynomial transformation coefficients are derived by solving the bilinear matrix inequality problem. To confirm the capability of this method, three examples are highlighted.     

Robust output feedback control of polynomial growth nonlinear systems with measurement uncertainty

Even in the presence of uncertainty in both state and output equations, we prove that global asymptotic stabilization is still possible by output feedback for a family of uncertain nonlinear systems dominated by a triangular system with a polynomial output‐dependent growth rate. In contrast to the linear growth requirement in the recent work the nonlinear perturbations in this paper are allowed to satisfy a linear growth condition with a polynomial output‐dependent rate. To handle simultaneously the polynomial nonlinearities and unknown parameter in the system output, we propose a high‐gain estimator with a dynamic gain that is updated online through a Riccati‐type dynamic equation. Then, an estimator‐based controller is designed by a recursive algorithm that makes it possible to assign the controller gains step by step. The globally stabilizing output‐feedback controller developed in this paper is robust with respect to uncertainties in the system dynamics and output equations.     

The Multidimensional Asymptotic Stability Domain of Linear Discrete Systems: Its Symmetry and Other Properties

The properties of the closed asymptotic stability domain of a linear discrete system in the space of coefficients of its characteristic polynomial are investigated. An example is given.     

Stochastic suppression and stabilization of delay differential systems

In this paper, we investigate stochastic suppression and stabilization for nonlinear delay differential system ${\dot{x}}(t)=f(x(t),x(t-\delta(t)),t)In this paper, we investigate stochastic suppression and stabilization for nonlinear delay differential system ${\dot{x}}(t)=f(x(t),x(t-\delta(t)),t)$, where δ(t) is the variable delay and f satisfies the one‐sided polynomial growth condition. Since f may defy the linear growth condition or the one‐sided linear growth condition, this system may explode in a finite time. To stabilize this system by Brownian noises, we stochastically perturb this system into the nonlinear stochastic differential system dx(t)=f(x(t), x(t?δ(t)), t)dt+qx(t)dw₁(t)+σ|x(t)|^βx(t)dw₂(t) by introducing two independent Brownian motions w₁(t) and w₂(t). This paper shows that the Brownian motion w₂(t) may suppress the potential explosion of the solution of this stochastic system for appropriate choice of β under the condition σ≠0. Moreover, for sufficiently large q, the Brownian motion w₁(t) may exponentially stabilize this system. Copyright © 2010 John Wiley & Sons, Ltd.     

Frequency sweeping tests for stability independent of delay

In this paper we study the stability properties of linear time-invariant delay systems given in a state space form. We consider specifically the notion of asymptotic stability independent of delay. Systems with both commensurate and noncommensurate delays are investigated. We present for each class of systems a necessary and sufficient condition in terms of structured singular values, and further we demonstrate how these conditions may be extended to study stability independent of delay for uncertain systems. Our results consist of several frequency sweeping tests that can be systematically implemented and that should complement the previous work     

Linearity of the coefficients of the closed-loop characteristic polynomial

This note examines the condition given by Kolka for linearity of the coefficients of the closed-loop characteristic polynomial. An alternative necessary and sufficient condition is given for v coefficients of the characteristic polynomial to be linear in the elements of the output-feedback matrix. It is shown that this condition is applicable to a wider class of systems and provides more information about the system properties.     

Singularly perturbed implicit control law for linear time‐varying delay MIMO systems

This paper proposes a control scheme for the problem of stabilizing partly unknown multiple‐input multiple‐output linear time‐varying retarded systems. The control scheme is composed by a singularly perturbed controller and a reference model. We assume the knowledge of a number of structural characteristics of the system as the boundedness and the knowledge of the bounds for the unknown parameters (and their derivatives) that define the system matrices, as well as the structure of these matrices. The results presented here are a generalization of previous results on linear time‐varying Single‐Input Single‐Output (SISO) and multiple‐input multiple‐output systems without delays and linear time‐varying retarded SISO systems. The closed‐loop system is a linear singularly perturbed retarded system with uniform asymptotic stability behavior. The uniform asymptotic stability of the singularly perturbed retarded system is guaranteed. We show how to design a control law such that the system dynamics for each output is given by a Hurwitz polynomial with constant coefficients. Copyright © 2015 John Wiley & Sons, Ltd.     

多组时滞大型控制系统的镇定

给出了由无时滞线性定常闭孤立控制子系统的渐近稳定性推出多组时滞线性定常闭环大型控制系统的渐近稳定性的充分条件，并说明了所得结果可以推广到多组时滞线性时变闭环大型控制系统与多组时滞线中立型定常（或时变）闭环大型控制系统，所得结果改进了前人的结果，通过参数镇定域的比较知，可使参数镇定域扩大为原来的６倍。     

A Lyapunov function of two-dimensional linear systems

In this note a Lyapunov function for a 2-D time invariant discrete linear system is introduced, using the 2-D system model given by Roesser [1]. The Lyapunov function may be used to investigate the asymptotic stability of the 2-D system. Previous work dealing with asymptotic stability of 2-D systems [3]-[5] is based upon the location of roots of the characteristic polynomial in the closed polydiskoverline{U}^{2}.     

Robust estimation without positive real condition

The strictly positive real (SPR) condition on the noise model is necessary for a discrete-time linear stochastic control system with unmodeled dynamics, even so for a time-invariant ARMAX system, in the past robust analysis of parameter estimation. However, this condition is hardly satisfied for a high-order and/or multidimensional system with correlated noise. The main work in this paper is to show that for robust parameter estimation and adaptive tracking, as well as closed-loop system stabilization, the SPR condition is replaced by a stable matrix polynomial. The main method is to design a “two-step” recursive least squares algorithm with or without a weighted factor and with a fixed lag regressive vector and to define an adaptive control with bounded external excitation and with randomly varying truncation     

Optimal filtering for polynomial system states with polynomial multiplicative noise

In this paper, the optimal filtering problem for polynomial system states with polynomial multiplicative noise over linear observations is treated proceeding from the general expression for the stochastic Ito differential of the optimal estimate and the error variance. As a result, the Ito differentials for the optimal estimate and error variance corresponding to the stated filtering problem are first derived. The procedure for obtaining a closed system of the filtering equations for any polynomial state with polynomial multiplicative noise over linear observations is then established, which yields the explicit closed form of the filtering equations in the particular cases of a linear state equation with linear multiplicative noise and a bilinear state equation with bilinear multiplicative noise. In the example, performance of the designed optimal filter is verified for a quadratic state with a quadratic multiplicative noise over linear observations against the optimal filter for a quadratic state with a state‐independent noise and a conventional extended Kalman–Bucy filter. Copyright © 2006 John Wiley & Sons, Ltd.     

Mean square exponential stability of stochastic nonlinear delay systems

In this paper, we are concerned with the stability of stochastic nonlinear delay systems. Different from the previous literature, we aim to show that when the determinate nonlinear delay system is globally exponentially stable, the corresponding stochastic nonlinear delay system can be mean square globally exponentially stable. In particular, we remove the linear growth condition and introduce a new polynomial growth condition for g(x(t), x(t ? τ(t))), which overcomes the limitation of application scope and the boundedness of diffusion term form. Finally, we provide an example to illustrate our results.     

A novel narrow band digital filter and its application to multivariable system identification

A novel narrow band time-varying digital filter is proposed, which has desirable properties such as global asymptotic stability, asymptotic noise annihilation and asymptotic signal tracking. It is shown that the proposed filter is comparable to the Kalman filter in performance, but with substantial computational simplicity; no Ricatti equation is involved. It is basically a Fourier analysis method but the Fourier coefficients are found recursively. The application of the proposed filter for on-line identification of a linear multivariable system subject to both deterministic and stochastic disturbances is presented; simulation results are given.     

On the componentwise stability of linear systems

The componentwise asymptotic stability (CWAS) and componentwise exponential asymptotic stability (CWEAS) represent stronger types of asymptotic stability, which were first defined for symmetrical bounds constraining the flow of the state‐space trajectories, and then, were generalized for arbitrary bounds, not necessarily symmetrical. Our paper explores the links between the symmetrical and the general case, proving that the former contains all the information requested by the characterization of the CWAS/CWEAS as qualitative properties. Complementary to the previous approaches to CWAS/CWEAS that were based on the construction of special operators, we incorporate the flow‐invariance condition into the classical framework of stability analysis. Consequently, we show that the componentwise stability can be investigated by using the operator defining the system dynamics, as well as the standard ε?δ formalism. Although this paper explicitly refers only to continuous‐time linear systems, the key elements of our work also apply, mutatis mutandis, to discrete‐time linear systems. Copyright © 2004 John Wiley & Sons, Ltd.