切换多项式非线性系统的输入-状态稳定性

利用耗散不等式研究了切换多项式非线性系统的输入-状态稳定性分析问题,在任意切换信号下,给出了使得切换多项式非线性系统输入-状态稳定的充分条件.采用平方和分解方法来寻找切换多项式非线性系统的输入-状态稳定共同Lyapunov函数.数值算例验证了所提方法的可行性.     

基于符号数值混合计算的混成系统Lyapunov函数构造

基于平方和松弛和有理向量恢复,提出了一种符号数值混合计算方法来构造多项式Lyapunov函数以判定非线性混成系统的稳定性,首先,为Lyapunov函数预定一个给定次数的多项式模板,则Lyapunov函数构造问题可转化为相应的带参数的多项式优化问题,然后运用平方和松弛方法求得一个近似的数值多项式Lyapunov函数,再应用高斯-牛顿精化和有理向量恢复将数值多项式转化为验证的有理多项式Lyapunov函数.     

Synchronization of a class of chaotic dynamic systems with controller gain variations

In this paper, the nonfragile control problem for synchronization of a class of chaotic dynamical systems with controller gain variations is studied. Using the Lyapunov method and LMI (linear matrix inequality) technique, a criterion for the existence of the nonfragile controller for synchronization is derived in terms of LMI. To show the effectiveness of the proposed method, the control problem is applied to Genesio chaotic system.     

Monitoring change point for diffusion parameter based on discretely observed sample from stochastic differential equation models

Stochastic differential equation (SDE) models are useful in describing complex dynamical systems in science and engineering. In this study, we consider a monitoring procedure for an early detection of dispersion parameter change in SDE models. The proposed scheme provides a useful diagnostic analysis for phase I retrospective study and develops a flexible and effective control chart for phase II prospective monitoring. A standardized control chart is constructed, and a bootstrap method is used to estimate the mean and variance of the monitoring statistic. The control limit is obtained as an upper percentile of the maximum value of a standard Wiener process. The proposed procedure appears to have a manageable computational complexity for online implementation and also to be effective in detecting changes. We also investigate the performance of the exponentially weighted mean squared control charts for the continuous SDE processes. A simulation method is used to study the empirical sizes and the average run length characteristics of the proposed scheme, which also demonstrates the effectiveness of our method. Finally, we provide an empirical example for illustration. Copyright © 2014 John Wiley & Sons, Ltd.     

Adaptive scheme for time-varying anticipating synchronization of certain or uncertain chaotic dynamical systems

In this paper, a new type of anticipating synchronization, called time-varying anticipating synchronization, is defined firstly. Then novel adaptive schemes for time-varying anticipating synchronization of certain or uncertain chaotic dynamical systems are designed based on the Lyapunov function and invariance principle. The update gain of coupling strength can be automatically adapted to a suitable strength depending on the initial values and can be properly chosen to adjust the speed of achieving synchronization, so these schemes are analytical and simple to implement in practice. A classical chaotic dynamical system is used to demonstrate the effectiveness of the proposed adaptive schemes with or without parameter uncertainties.     

The design of a linear regulator based on an integral-equation representation

This paper presents an alternative on-line algorithm for calculating regulators of linear deterministic dynamical systems which minimize quadratic cost functions employing the invariant-imbedding method. The design scheme used for the optimum linear regulator is based on the integral-equation representation, which enables one to obtain the solution to the corresponding two-point boundary-value problem. The algorithm can be implemented in forward time without memory, unlike the conventional one which uses the Kalman gain function to calculate the feedback gain.     

Stabilization of unknown nonlinear systems using a cognition-based framework

This paper considers an adaptive control method based on a cognition-based framework to stabilize unknown nonlinear systems. In order to fulfill the task of stabilization, neither the information about the systems dynamical structure nor the knowledge about system physical behaviors, but the system states, which are assumed as measurable, are required. The structure of the proposed controller consists of three parts. The first part is based on a recurrent neural network (RNN) to be used for local identification of the unknown nonlinear system in real time. The network can be utilized as system characteristics, which is further used to design the controller within the third part. In the second part, the set of the given input values leading to stable behavior of the closed-loop system will be calculated numerically with a geometrical criterion based on a suitable definition of quadratic stability. In the third part, a suitable control input value is chosen accordingly to a time-relevant criteria from the set of input values generated in the second part of the controller. These three parts and their internal connections are arranged within a so-called cognition framework. The proposed cognitive controller is able to gain useful knowledge (with local validity) and define autonomously a suitable control input with respect to the requirements of the time-relevant criteria. Numerical examples are shown to demonstrate the successful application and performance of the method. (© 2011 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim)     

Adaptive synchronization in tree-like dynamical networks

Synchronization in an array of coupled identical nonlinear dynamical systems have attracted increasing attention from various fields of science and engineering. In this paper, we investigate the synchronization phenomenon in tree-like dynamical networks. Based on the LaSalle invariant principle, a simple and systematic adaptive control scheme with variable coupling strength is proposed for the synchronization of tree-like dynamical networks without any knowledge of the concrete structure of isolate system. This result indicates that synchronization can be achieved for strong enough coupling if there exists a system (located at the root of the tree) which directly or indirectly influences all other systems. Furthermore, the main result is applied to several Lorenz chaotic systems coupled by a tree. And numerical simulations are also given to show the effectiveness of the proposed synchronization method.     

Pitfalls in the frequency response represented onto Polynomial Chaos for random SDOF mechanical systems

Uncertainties are present in the modeling of dynamical systems and they must be taken into account to improve the prediction of the models. It is very important to understand how they propagate and how random systems behave. This study aims at pointing out the somehow complex behavior of the structural response of stochastic dynamical systems and consequently the difficulty to represent this behavior using spectral approaches. The main objective is to find numerically the probability density function (PDF) of the response of a random linear mechanical systems. Since it is found that difficulties can occur even for a single-degree-of-freedom system when only the stiffness is random, this work focuses on this application to test several methods. Polynomial Chaos performance is first investigated for the propagation of uncertainties in several situations of stiffness variances for a damped single-degree-of-freedom system. For some specific conditions of damping and stiffness variances, it is found that numerical difficulties occur for the standard polynomial bases near the resonant frequency, where it is generally observed that the shape of the system response PDFs presents multimodality. Strategies to build enhanced bases are then proposed and investigated with varying degrees of success. Finally, a multi-element approach is used in order to gain robustness.     

On recent results of ergodic property for p-adic dynamical systems

Theory of dynamical systems in fields of p-adic numbers is an important part of algebraic and arithmetic dynamics. The study of p-adic dynamical systems is motivated by their applications in various areas of mathematics, physics, genetics, biology, cognitive science, neurophysiology, computer science, cryptology, etc. In particular, p-adic dynamical systems found applications in cryptography, which stimulated the interest to nonsmooth dynamical maps. An important class of (in general) nonsmooth maps is given by 1-Lipschitz functions. In this paper we present a recent summary of results about the class of 1-Lipschitz functions and describe measure-preserving (for the Haar measure on the ring of p-adic integers) and ergodic functions. The main mathematical tool used in this work is the representation of the function by the van der Put series which is actively used in p-adic analysis. The van der Put basis differs fundamentally from previously used ones (for example, the monomial and Mahler basis) which are related to the algebraic structure of p-adic fields. The basic point in the construction of van der Put basis is the continuity of the characteristic function of a p-adic ball. Also we use an algebraic structure (permutations) induced by coordinate functions with partially frozen variables.     

A dynamic parameter estimator to control chaos with distinct feedback schemes

A dynamic strategy is proposed to estimate parameters of chaotic systems. The dynamic estimator of parameters can be used with diverse control functions; for example, those based on: (i) Lie algebra, (ii) backstepping, or (iii) variable feedback structure (sliding-mode). The proposal has adaptive structure because of interaction between dynamic estimation of parameters and a feedback control function. Without lost of generality, a class of dynamical systems with chaotic behavior is considered as benchmark. The proposed scheme is compared with a previous low-parameterized robust adaptive feedback in terms of execution and performance. The comparison is motivated to ask: What is the suitable adaptive scheme to suppress chaos in an specific implementation? Experimental results of proposed scheme are discussed in terms of control execution and performance and are relevant in specific implementations; for example, in order to induce synchrony in complex networks.     

On the fuzzy minimum entropy control to stabilize the unstable fixed points of chaotic maps

This paper presents a fuzzy algorithm for controlling chaos in nonlinear systems via minimum entropy approach. The proposed fuzzy logic algorithm is used to minimize the Shannon entropy of a chaotic dynamics. The fuzzy laws are determined in such a way that the entropy function descends until the chaotic trajectory of the system is replaced by a regular one. The Logistic and the Henon maps as two discrete chaotic systems, and the Duffing equation as a continuous one are used to validate the proposed scheme and show the effectiveness of the control method in chaotic dynamical systems.     

Boundary control and canonical realizations of a two-velocity dynamical system

The paper is devoted to the problems of controllability and realization for dynamical systems with various types of interacting waves that propagate with different velocities. One-velocity and a two-velocity dynamical systems are significantly different from the physical point of view. One can reconstruct a one-velocity system by its transfer function. For a two-velocity system a unique reconstruction is impossible. A procedure is proposed that allows us to construct by a transfer function of a two-velocity system a one-velocity system (a model) with the same transfer function. We give a “dynamical” interpretation for the triangular Krein factorization and for the corresponding construction of a triangular integral. For a transformation operator that connects a two-velocity system and its one-velocity model, a representation is given in terms of projectors on the accessible sets. Bibliography: 7 titles. Translated fromZapiski Nauchnykh Seminarov POMI, Vol. 222, 1994, pp. 18–44.     

Finite dimensional Markov process approximation for stochastic time-delayed dynamical systems

This paper presents a method of finite dimensional Markov process (FDMP) approximation for stochastic dynamical systems with time delay. The FDMP method preserves the standard state space format of the system, and allows us to apply all the existing methods and theories for analysis and control of stochastic dynamical systems. The paper presents the theoretical framework for stochastic dynamical systems with time delay based on the FDMP method, including the FPK equation, backward Kolmogorov equation, and reliability formulation. A simple one-dimensional stochastic system is used to demonstrate the method and the theory. The work of this paper opens a door to various studies of stochastic dynamical systems with time delay.     

Synchronizing chaotic systems using control based on tridiagonal structure

The direct design approach based on tridiagonal structure combines the structure analysis with the design of stabilizing controller and the original nonlinear affine systems is transformed into a stable system with special tridiagonal structure using the method. In this study, the direct method is proposed for synchronizing chaotic systems. There are several advantages in this method for synchronizing chaotic systems: (a) it presents an easy procedure for selecting proper controllers in chaos synchronization; (b) it constructs simple controllers easy to implement. Examples of Lorenz system, Chua’s circuit and Duffing system are presented.     

Modelling,simulation and control of a redundant parallel robotic manipulator based on invariant manifolds

In this article a systematic approach of modelling and control for a parallel robotic manipulator is presented. Regarding the framework of structured analysis of dynamical systems the derivation of a differential-algebraic model of the mechanical system is straightforward. Using some differential-geometric considerations based on invariant manifolds and the definition of fictitious additional input and output variables a suitable state feedback can be constructed which transforms the differential-algebraic representation into a state-space model for the robotic manipulator. On this basis a classical two-degree-of-freedom (2-DOF) control structure has been designed using the well-known input–output linearization and a linear time-variant Kalman filter-based output feedback. Finally, the control structure including a friction compensation is applied to the robotic system in the laboratory which shows the practical applicability of the proposed procedure.     

Discretization of nonlinear input-driven dynamical systems using the Adomian Decomposition Method

A numerical decomposition method proposed by Adomian provides solutions to nonlinear, or stochastic, continuous time systems without the usual restrictive restraints. It is applicable to differential, delay differential, integro-differential, and partial differential equations without the need for linearization or other restrictions. It also works through both uncoupled boundary conditions as well as delay systems. In the following paper, a new time discretization method for the development of a sample-data representation of a nonlinear continuous-time input-driven dynamical system is proposed. The proposed method is based on both the zero-order hold (ZOH) assumption as well as the Adomian Decomposition Method which exhibit unique algorithmic and computational advantages. To take advantage of this method, the following steps must be followed. First, the method is applied to a linear input-driven dynamical system to explicitly derive an exact sample-data representation, producing proper results. Second, the method is then applied to a nonlinear input-driven dynamical system, which thereby derives exact and approximate sample-data representations, the latter being most suited for practical applications. To evaluate the performance, the proposed discretization procedure was tested using simulations in a case study which involved an illustrative two-degree-of-freedom mechanical system that exhibited nonlinear behavior considering various control and input variable profiles. In conclusion, the suggested algorithm, in comparison to the results of a Taylor-Lie series expansion method, demonstrated increased performance and efficiency.     

Structural damage detection using an efficient correlation-based index and a modified genetic algorithm

An efficient optimization procedure is proposed to detect multiple damage in structural systems. Natural frequency changes of a structure are considered as a criterion for damage presence. In order to evaluate the required natural frequencies, a finite element analysis (FEA) is utilized. A modified genetic algorithm (MGA) with two new operators (health and simulator operators) is presented to accurately detect the locations and extent of the eventual damage. An efficient correlation-based index (ECBI) as the objective function for the optimization algorithm is also introduced. The numerical results of two benchmark examples considering the measurement noise demonstrate the computational advantages of the proposed method to precisely determine the sites and the extent of multiple structural damage.     

Mode decomposition for a synchronous state and its applications

Synchronization of coupled dynamical systems including periodic and chaotic systems is investigated both anlaytically and numerically. A novel method, mode decomposition, of treating the stability of a synchronous state is proposed based on the Floquet theory. A rigorous criterion is then derived, which can be applied to arbitrary coupled systems. Two typical numerical examples: coupled Van der Pol systems (corresponding to the case of coupled periodic oscillators) and coupled Lorenz systems (corresponding to the case of chaotic systems) are used to demonstrate the theoretical analysis.     

Counteracting the dynamical degradation of digital chaos via hybrid control

Chaotic systems would degrade owing to finite computing precisions, and such degradation often seriously affects the performance of digital chaos-based applications. In this paper, a chaotification method is proposed to solve the dynamical degradation of digital chaotic systems based on a hybrid structure, where a continuous chaotic system is applied to control the digital chaotic system, and a unidirectional coupling controller that combines a linear external state control with a modular function is designed. Moreover, we proof rigorously that a class of digital chaotic systems can be driven to be chaotic in the sense that the system is sensitive to initial conditions. Different from the existing remedies, this method can recover the dynamical properties of system, and even make some properties better than those of the original chaotic system. Thus, this new approach can be applied to the fields of chaotic cryptography and secure communication.