The Glansdorff–Prigogine stability criterion for biochemical reaction networks

Local stability analysis of steady states in mathematical models of biochemical reaction networks is an important tool for systems biology. The second variation of the Gibbs energy around a steady state is a positive definite function and a candidate for a Lyapunov function. A sufficient condition for the local stability is the local negative definiteness of the time derivative of this function. This is expressed by the Glansdorff–Prigogine stability criterion. Previously, the criterion was criticized to be overly conservative and difficult to check. Here, we derive an easily testable form of the criterion for models of biochemical networks. The criterion can be evaluated with incomplete knowledge of the parameters. For ideal mass-action kinetics, it depends only on the steady state fluxes. For reaction systems in ideal solutions, the Glansdorff–Prigogine criterion is overly conservative and we give a tighter criterion that depends on the same subset of the parameters as the Glansdorff–Prigogine criterion. Whenever these criteria are indefinite, there exist parameter values such that the steady state is unstable. By means of simple example systems we explore these aspects and discuss the possible uses of the criteria for systems biology.     

Cyclic elastic-plastic creep steady-state analysis by the finite element method

In this paper, a definition of generalized cyclic steady state and convergence criterion of cyclic steady state for numerical calculation are introduced. An incremental-iterative finite element analysis based on the modified Newton-Raphson method is used for the steady state analysis. The material model used for numerical computation is an extension of classical plasticity theory which accounts for nonisothermal effect and creep behavior. In addition, two numerical examples are presented to demonstrate different types of cyclic steady states.     

Design and study of a risk management criterion for an unstable anaerobic wastewater treatment process

In this paper, we consider an unstable biological process used for wastewater treatment. This anaerobic digestion ecosystem can have two locally stable steady states and one unstable steady state. We first study the model and characterise the attraction basin associated to the normal operating mode. In the second step, we estimate the size of this attraction basin by using a simplified criterion that turns out to be a good approximation. Finally, we apply the approach on a real anaerobic digestion plant, and we show that the proposed criterion allows to rapidly detect the conditions of a destabilisation.     

Shape Restoration via a Regularized Curvature Flow

Any image filtering operator designed for automatic shape restoration should satisfy robustness (whatever the nature and degree of noise is) as well as non-trivial smooth asymptotic behavior. Moreover, a stopping criterion should be determined by characteristics of the evolved image rather than dependent on the number of iterations. Among the several PDE based techniques, curvature flows appear to be highly reliable for strongly noisy images compared to image diffusion processes.In the present paper, we introduce a regularized curvature flow (RCF) that admits non-trivial steady states. It is based on a measure of the local curve smoothness that takes into account regularity of the curve curvature and serves as stopping term in the mean curvature flow. We prove that this measure decreases over the orbits of RCF, which endows the method with a natural stop criterion in terms of the magnitude of this measure. Further, in its discrete version it produces steady states consisting of piece-wise regular curves. Numerical experiments made on synthetic shapes corrupted with different kinds of noise show the abilities and limitations of each of the current geometric flows and the benefits of RCF. Finally, we present results on real images that illustrate the usefulness of the present approach in practical applications.     

Robust stability analysis of systems with real parametric uncertainty: A global optimization approach

This paper presents an optimization framework for the robustness analysis of linear and nonlinear systems with real parameter uncertainty. For linear systems, a nonlinear programming formulation for the exact calculation of the stability margin is presented. The potential of decomposition-based global optimization methods for the solution of this nonconvex problem is discussed. Next the concept of the stability margin is extended to a class of nonlinear systems. A nonlinear stability margin and a uniqueness margin are defined to address the effect of parametric uncertainty on the stability of a particular steady state, as well as on the number of steady states of the system. This analysis allows for the derivation of necessary and sufficient conditions for robust stability and robust uniqueness of the steady state of the system in the presence of parametric uncertainty.     

多传感器标量加权最优信息融合稳态Ka lman 滤波器

提出一种新的标量加权多传感器线性最小方差意义下的最优信息融合准则．该准则考虑了局部估计误差之间的相关性，只需计算加权标量系数，避免了加权矩阵的计算，明显减小了计算量，便于实时应用．运用稳态Kalman滤波理论，基于该融合准则，给出了多传感器最优信息融合稳态Kalman滤波器．在所有局部滤波器达到稳态时，只需一次融合便可获得信息融合稳态滤波器，算法简单．仿真例子验证了其有效性．     

Sum‐of‐squares–based consensus verification for directed networks with nonlinear protocols

In this paper, we investigate the consensus verification problem of nonlinear agents in a fixed directed network with a nonlinear protocol. Inspired by the classical Lipschitz‐like condition, we introduce a more relax condition for the dynamics of the nonlinear agents. This condition is motivated via the construction of general Lyapunov functions for achieving asymptotic consensus. Especially, for agents where dynamics are described by polynomial function of the states, our consensus criterion can be converted to a sum of squares (SOS) programming problem, solvable via semidefinite programming tools. Of interest is that the scale of the resulting SOS programming problem does not increase as the size of the network increases, and thus, the applicability to analyze consensus of large‐scale networks is promising. Finally, an example is given to illustrate the effectiveness of our theoretical results.     

Further Results on the Cross Norm Criterion for Separability

In the present paper we develop and investigate a novel approach that aims to characterize quantum entanglement by using cross norms. In the first part of the paper we further develop the mathematical theory by determining the value of the greatest cross norm for Werner states, for isotropic states and for Bell diagonal states. In the second part we show that our techniques induce a novel powerful analytical and computable separability criterion for bipartite systems. This new criterion complements the well-known Peres positive partial transpose criterion in several aspects. It is a necessary but in general not a sufficient criterion for separability. We demonstrate the power of the new criterion by evaluating the criterion for a number of important examples. We also demonstrate that the new criterion is able to detect bound entangled states.     

一类非线性不确定性系统基于状态观测器的输出反馈镇定控制设计

The output-feedback stabilization control problem is investigated for a class of nonlinear uncertain systems. Based on the multivariable analog of circle criterion, an observer is designed to estimate the system states and hence the dynamical equations that the estimation error satisfies are derived first. Then, by using integral backstepping approach together with completing square technique, the output-feedback stabilization control is constructively designed such that the closedloop system is asymptotically stable. Finally, an example is given to illustrate the main results of this paper.     

Finite-time stability analysis of a class of nonlinear time-varying systems: a numerical algorithm

The paper investigates the finite-time stability (FTS) analysis of a very general class of nonlinear time-varying systems. The FTS of the considered system, whose vector field consists of a nonlinear part which can be sublinear or superlinear, and a linear part which can be time-varying, has not been fully studied before. By estimating the bound of the norm of the considered system's states with the generalised Gronwall–Bellman inequality, a sufficient criterion is established to guarantee the FTS of the considered system. To facilitate checking the criterion in practice, a novel numerical algorithm is proposed by numerically solving certain differential equations. Therefore, the FTS of the considered class of nonlinear time-varying systems can be easily analysed by the numerical algorithm. Further considering the numerical errors in the practical numerical computation, we strictly prove the credibility and programmability of the numerical algorithm in theory. Finally, three numerical examples are provided to illustrate the effectiveness the proposed results.     

Graph-theoretic characterisations of the steady states for containment control

Containment control is a consensus-like protocol whose objective is to drive all the followers into the convex hull formed by the leaders. The steady states of the followers have great effect on system performance. Two kinds of cell partitions from graph theory are employed to investigate the reflections of the information topology on the steady states of the followers. It is proved that agents that belong to the same cell have the same steady states.     

Realignment entanglement criterion of phase damped Gaussian states

We derive the realignment entanglement criterion for non-Gaussian states prepared by two mode symmetric Gaussian states undergoing phase damping. The entanglement detecting ability is compared with that of second moment criterion and Fock space criterion of positive partial transpose. New non-Gaussian entangled states are detected.     

基于扩展BP神经网络的一类非线性系统自适应控制设计

针对单输入单输出非线性系统的不确定性问题,提出了一种新型的基于扩展反向传播（BP）神经网络的自适应控制方法。首先,采用离线数据来训练BP神经网络的权值向量;然后,通过在线调节伸缩因子和逼近精度估计值的更新律,从而来达到控制整个系统的目的。在控制器的设计过程中,利用李亚普诺夫稳定性分析原理,保证了闭环系统的所有状态一致终极有界（UUB）。相比传统的BP神经网络自适应控制,所提方法能有效地减少在线调节的参数数目、减轻计算负担。仿真结果表明,该方法能够使闭环系统的所有状态都趋于零,即系统达到稳定状态。     

Adaptive prescribed performance tracking control for strict‐feedback nonlinear systems with zero dynamics

This paper focuses on the adaptive tracking control problem for strict‐feedback nonlinear systems with zero dynamics via prescribed performance. Based on polynomial fitting, an adjustable performance function is firstly proposed, whose parameters can be adjusted in real time according to the tracking error. Furthermore, an adaptive prescribed performance tracking controller is constructed via the backstepping method, which guarantees that all the states in the closed‐loop system are bounded. Meanwhile, the output tracking error falls within an adjustable performance boundary and asymptotically converges to zero. Simulation comparison demonstrates the advantages of the developed controller as follows: (1) the parameters of the adjustable performance function are adjusted online according to the tracking errors for a faster convergent performance boundary; (2) the steady‐state performance of the system is further optimized simultaneously.     

Construction of bound entangled states based on permutation operators

We present a construction of new bound entangled states from given bound entangled states for arbitrary dimensional bipartite systems. One way to construct bound entangled states is to show that these states are positive partial transpose (PPT) and violate the range criterion at the same time. By applying certain operators to given bound entangled states or to one of the subsystems of the given bound entangled states, we obtain a set of new states which are both PPT and violate the range criterion. We show that the derived bound entangled states are not local unitary equivalent to the original bound entangled states by detail examples.     

Guaranteed steady state bounds for uncertain (bio-)chemical processes using infeasibility certificates

Analysis and safety considerations of chemical and biological processes require complete knowledge of the set of all feasible steady states. Nonlinearities, uncertain parameters, and discrete variables complicate the task of obtaining this set. In this paper, the problem of outer-approximating the region of feasible steady states, for processes described by uncertain nonlinear differential algebraic equations including discrete variables and discrete changes in the dynamics, is addressed.The calculation of the outer bounds is based on a relaxed version of the corresponding feasibility problem. It uses the Lagrange dual problem to obtain certificates for regions in state space not containing steady states. These infeasibility certificates can be computed efficiently by solving a semidefinite program, rendering the calculation of an outer bounding set computationally feasible. The derived method guarantees globally valid outer bounds for the feasible steady states.The method is exemplified by the analysis of a simple chemical reactor showing parametric uncertainties and large variability due to the appearance of bifurcations characterising the ignition and extinction of a reaction.     

Nonlinear entanglement witnesses based on continuous-variable local orthogonal observables for bipartite systems

In this paper, a nonlinear entanglement witness criterion based on continuous-variable local orthogonal observables for bipartite states is established, which is strictly stronger than the the linear entanglement witnesses criterion introduced by Zhang et al. (Phys. Rev. Lett. 111:190501, 2013). This criterion is particularly applied to two-mode Gaussian states yielding a criterion in terms of the covariance matrix. Comparison with CCNR criterion is discussed.     

对一类不确定系统的推广波波关判据

本文将对一类不确定系统提出推广的波波夫判据,这类系统的线性部分乃诸顶点模型的凸组合,而非线性函数是处于某扇区内。判据说:不确定系统是某扇区绝对稳定的如果存在一条公共的波波夫直线使所有顶点系统的修正奈氏曲线位于这直线右侧。     

一类双线性Hammerstein模型的集成辨识方法

对于一类静态非线性增益具有原点对称特性的双线性Ｈａｍｍｅｒｓｔｅｉｎ模型,提出了一种稳态与动态辨识相结合的集成辨识方法。该方法利用稳态信号获得稳态模型的强一致性估计,并通过稳态模型获得非线性增益的估计,再利用动态信息辨识获得双线性Ｈａｍｍｅｒｉｓｔｅｉｎ模型的双线性系统未知参数的一致性估计。仿真结果表明了该方法的有效性和实用性。     

Optimal control for a polynomial system with a quadratic criterion over infinite horizon

This paper proposes an optimal control algorithm for a polynomial system with a quadratic criterion over infinite horizon. The designed regulator gives a closed-form solution to the infinite horizon optimal control problem for a polynomial system with a quadratic criterion. The obtained solution consists of a feedback control law obtained by solving a Riccati algebraic equation dependent on the state. Numerical simulations in the example show advantages of the developed algorithm.