岩质边坡确定性块体稳定性的研究

在岩质边坡中,岩体的失稳与破坏主要受岩体内结构面的控制,它们相互之间的空间分布位置、组合关系(包括自然边坡或边坡开挖面的产状)和结构面的物理力学性质等,对边坡的稳定都起着至关重要的作用。将野外测量的结构面资料,用一定的几何图形植入三维地形模型中,可以直观显示各软弱结构面的空间展布规律和交切关系,再根据赤平投影原理进行分析统计,确定优势产状,进而对边坡在潜在不稳定块体宽度、高度、体积、失稳模式和滑动方向做出定量的判断,从而指导现场工作人员采取处理措施。

群活性与粒子群优化的稳定性分析

在探讨粒子轨迹的随机过程的基础上,用根轨迹特征值的谱半径来描述粒子群优化的PSO动态系统的稳定性区域;提出并结合实例用群活性刻画了PSO稳定区域中不同参数区间上群行为的动态特征,利用不动点技术通过数值实验描绘出PSO群活性谱及性能图,解释了先前一些文献上提出的典型参数集之所以能够取得满意性能的理由,利用PSO稳定三角中线提出保证PSO收敛性能的参数设置指导策略.

Stability analysis of time-varying systems via parameter-dependent homogeneous Lyapunov functions

This paper considers the stability analysis of linear continuous-time systems, and that the dynamic matrices are affected by uncertain time-varying parameters, which are assumed to be bounded, continuously differentiable, with bounded rates of variation. First, sufficient conditions of stability for time-varying systems are given by the commonly used parameter-dependent quadratic Lyapunov function. Moreover, the use of homogeneous polynomial Lyapunov functions for the stability analysis of the linear system subject to the time-varying parametric uncertainty is introduced. Sufficient conditions to determine the sought after Lyapunov function is derived via a suitable paramenterization of polynomial homogeneous forms. A numerical example is given to illustrate that the stability conditions are less conservative than similar tests in the literature.

Design for robust stabilization of nonlinear systems with uncertain parameters

Based on Lyapunov stability theory, a design method for the robust stabilization problem of a class of nonlinear systems with uncertain parameters is presented. The design procedure is divided into two steps: the first is to design controllers for the nominal system and make the system asymptotically stabi1ize at the expected equilibrium point; the second is to construct closed-loop nominal system based on the first step, then design robust controller to make the error of state between the origina1 system and the nominal system converge to zero, thereby a dynamic controller with the constructed closed-loop nominal system served as interior dynamic is obtained. A numerical simulation verifies the correctness of the design method.

The Robust Stabilizing Feedback for a Class of Nonlinear Uncertain Neutral Systems with Multiple Time Delays

The stabilization of a class of neutral systems with multiple time-delays is considered. To stabilize the neutral system with nonlinear uncertainty, a state feedback control law via compound memory and memoryless feedback is derived, by constructed Lyapunov functional, delay-independent stability criteria are proposed that are sufficient to ensure a uniform asymptotic stability property. Finally, two concise examples are provided to illustrate the feasibility of our results.

从“天网恢恢,疏而不漏”看法律的调整范围

从古至今,道德、宗教和法律都是调控社会的有效方式,特别是道德和法律,两者一直相伴而存。“道”与“法”虽有共性的部分,但在涵义和调节领域方面还是各有不同,对两者的关系进行梳理,以法律与道德、宗教的关系,法律的稳定性与确定性,立法者的“有限理性”,以及市场机制对社会、国家关系的影响等四个方面为支点,揭示出法律调整范围将最大限度缩小这一发展趋势,这对我国立法工作具有相当的指导意义。

Robust tracking control design for a flexible air-breathing hypersonic vehicle

A nonlinear robust controller was presented to improve the tracking control performance of a flexible air-breathing hypersonic vehicle(AHV) which is subjected to system parametric uncertainties and unknown additive time-varying disturbances.The longitudinal dynamic model for the flexible AHV was used for the control development.High-gain observers were designed to compensate for the system uncertainties and additive disturbances.Small gain theorem and Lyapunov based stability analysis were utilized to prove the stability of the closed loop system.Locally uniformly ultimately bounded tracking of the vehicle's velocity,altitude and attack angle were achieved under aeroelastic effects,system parametric uncertainties and unknown additive disturbances.Matlab/Simulink simulation results were provided to validate the robustness of the proposed control design.The simulation results demonstrate that the tracking errors stay in a small region around zero.

Synchronization of hyperchaotic Rossler system with uncertain parameters via nonlinear control

Based on the Lyapunov stability theory,a new method for synchronization of hyperchaotic Rossler system with uncertain parameters is proposed. By this method, choosing appropriate control law and adaptive update law of uncertain parameters, all the errors of system variable synchronization and of uncertain param- eter track are asymptotically stable. The theoretical analysis and the numerical simulations prove the efffectiveness of the oroDosed method.

The Chaotic Real-Exchange-Rate Growth Model

Chaos theory is used to prove that erratic and chaotic fluctuations can indeed arise in completely deterministic models. Chaos theory reveals structure in aperiodic, dynamic systems. A number of non-linear business cycle models use chaos theory to explain complex motion of the economy. Chaotic systems exhibit a sensitive dependence on initial conditions： Seemingly insignificant changes in the initial conditions produce large differences in outcomes. The basic aim of this analysis is to provide a relatively simple chaotic real-exchange-rate growth model that is capable of generating stable equilibria, cycles, or chaos.

Development of NIS Two-Temperature Humidity Generator

Abstract： This paper describes the development and characterization of a two-temperature （2-T）, constant pressure humidity generator It relies on the saturation of a stream of gas flowing over a water surface maintained at constant, well-known, temperature. It was built in order to improve the uncertainties of the dew-point temperature and humidity scales realization at the National Institute for Standard （NIS） in the dew-point range from -50 ℃ to ＋ 10 ℃. Several experiments were carried out in the above mentioned range in order to characterize the generator. Characterization comprised studies of its saturator efficiency, temperature stability and a comparison with a calibrated chilled-mirror hygrometer. The results of the efficiency tests showed good performance of the generator as described below. For uncertainty of measurements, a thorough analysis was also described representing estimations of contributions for all the sources that affecting measurements.

Robust Model Predictive Controller Design： Finite and Infinite Horizon

This paper addresses to the problem of designing, modeling and practical realization of robust model predictive control for finite and infinite prediction horizon which ensures a parameter dependent quadratic stability and guaranteed cost for linear polytopic uncertain systems. The model predictive controller design procedure based on BMI and LMI is reduced to off-line output feedback gain calculation. A numerical examples and an application to a real process is given to illustrate the effectiveness of the proposed method.

Stability control of steer by wire system based on μ synthesis robust control

The uncertainty influences may result in performance deterioration and instability to the steer by wire(SBW) system. Thus, it must make the control system keep robust stability from uncertainty, and have good robustness. In order to effectively restrain the interference and improve steering stability, this paper presents a μ synthesis robust controller based on SBW system, which considers the effect of model uncertainty and external disturbance on the system dynamics. Taking the ideal yaw rate tracking, interference suppression and excellent robustness as the control objectives, the μ synthesis robust controller is designed using linear fractional transformation theory to deal with the uncertainty. Then, it is testified through time domain and robustness simulation analysis. Simulation results show that the proposed controller can not only ensure robustness and robust stability of the system quite well, but improve handling stability of the vehicle effectively. The results of this study provide certain theoretical basis for the research and application of SBW system.

Global robust stability of complex-valued recurrent neural networks with time-delays and uncertainties

This paper focuses on the existence, uniqueness and global robust stability of equilibrium point for complex-valued recurrent neural networks with multiple time-delays and under parameter uncertainties with respect to two activation functions. Two sufficient conditions for robust stability of the considered neural networks are presented and established in two new time-independent relationships between the network parameters of the neural system, Finally, three illustrative examples are given to demonstrate the theoretical results.

ANALYSIS OF A PREDATOR-PREY MODEL WITH DISEASE IN THE PREY

In this paper, we discuss the behavior of a predator-prey model with disease in the prey with and without stochastic perturbation, respectively. First, we briefly give the dynamic of the deterministic system, by analyzing stabilities of its four equilibria. Then, we consider the asymptotic behavior of the stochastic system. By Lyapunov analysis methods, we show the stochastic stability and its long time behavior around the equi- librium of the deterministic system. We obtain there are similar properties between the stochastic system and its corresponding deterministic system, when white noise is small. But large white noise can make a unstable deterministic system to be stable.

IMPROVED STABILITY CRITERIA FOR UNCERTAIN LINEAR SYSTEMS WITH INTERVAL TIME-VARYING DELAY

This paper deals with the robust stability analysis of dynamic systems with interval time- varying delay and uncertainties. The innovation of the method includes employment of a tighter integral inequality and construction of an appropriate type of Lyapunov functional. The stability criteria derived from this method have less conservatism than some existing ones. Numerical examples are given to illustrate the effectiveness of the orooosed method.

Stability Analysis for a Kind of Hybrid Interconnected Systems

Complex large scale systems possess the characteristics of high dimensionality, large number of variables, strong nonlinearity, and parametric uncertainty. One of the effective approaches for the complex system modeling is using a hybrid interconnected model to describe the dynamics of each subsystem. Usually, some subsystems could be represented by analytic mathematical models due to their explicit mechanisms; others could only be modeled by intelligent methods because of their complicated behaviors. This paper focuses on a kind of large-scale uncertain systems with hybrid interconnected models, a part of which described by linear differential-equations and another part represented by Takagi-Sugeno fuzzy models. Through constructing a set of independent lower-dimensional linear matrix inequalities, and solving them in parallel, a novel robust stability analysis method is proposed. Thus the computational complexity is greatly reduced. Computer simulation is conducted to validate the effectiveness and efficiency of the proposed method.