AN APPROACH TO PARAMETER IDENTIFICATION FOR A SINGLE-DEGREE-OF-FREEDOM DYNAMICAL SYSTEM BASED ON SHORT FREE ACCELERATION RESPONSE

An approach to parameter identification for the single-degree-of-freedom (s.d.o.f.) system is presented. It fits into the group of parametric system identification methods that use a structured mathematical model. It uses the free acceleration response of the system in order to estimate the parameters of the equation of motion for the model under consideration. The approach has been numerically tested on Duffing's oscillator with dry friction at different sampling rates of the acceleration time history and at different signal-to-noise ratios (SNR). The experiment has been carried out on an experimental device with the features of Duffing's oscillator. The validity and advantages of the approach are presented. The results show that this approach offers parameter identification with good quality for short time series using only a modest number of data points for a wide range of s.d.o.f. systems.     

Controlling the Chen attractor using linear feedback based on parameter identification

In this paper we investigate the method for controlling the chaotic Chen system with unknown parameters using linear feedback functions based on parameter identification.The observer is applied to the identification of the unknown parameters of Chen system.Then an efficient feedback function is designed for controlling the Chen system.Numerical simulations are provided to show the effectiveness and feasibility of the developed controller.     

利用阵发混沌现象测定未知信号参数

利用Duffing方程对频率的极端敏感性产生阵发混沌现象,研究了一种利用该现象定量检测未知的微弱周期信号的各项参数的新方法,通过理论分析和实例仿真证明了该方法的可行性,并针对仿真结果提出了改进措施,提高了检测精度.     

Observer Based Multi-Level Fault Reconstruction for Interconnected Systems

The problem of local fault (unknown input) reconstruction for interconnected systems is addressed in this paper. This contribution consists of a geometric method which solves the fault reconstruction (FR) problem via observer based and a differential algebraic concept. The fault diagnosis (FD) problem is tackled using the concept of the differential transcendence degree of a differential field extension and the algebraic observability. The goal is to examine whether the fault occurring in the low-level subsystem can be reconstructed correctly by the output at the high-level subsystem under given initial states. By introducing the fault as an additional state of the low subsystem, an observer based approached is proposed to estimate this new state. Particularly, the output of the lower subsystem is assumed unknown, and is considered as auxiliary outputs. Then, the auxiliary outputs are estimated by a sliding mode observer which is generated by using global outputs and inverse techniques. After this, the estimated auxiliary outputs are employed as virtual sensors of the system to generate a reduced-order observer, which is caplable of estimating the fault variable asymptotically. Thus, the purpose of multi-level fault reconstruction is achieved. Numerical simulations on an intensified heat exchanger are presented to illustrate the effectiveness of the proposed approach.     

Parameters identification and synchronization of chaotic systems based upon adaptive control

A novel control method is proposed for a class of chaotic systems dependent linearly on unknown parameters based upon adaptive control. With this method parameters identification and synchronization of chaotic systems can be achieved simultaneously. Simulation results with Lorentz system and Chen's system are presented to show the effectiveness of the approach.     

Efficient model order reduction for dynamic systems with local nonlinearities

In the nonlinear structural analysis, the nonlinear effects are commonly localized and the rest of the structure behaves in a linear manner. Considering this fact, this research work proposes a harmonic balance solution in order to determine the nonlinear response of the structures. The solution is simplified by using an exact dynamic reduction along with the modal expansion technique. This novel approach, which is applicable to both discrete and continuous systems, converts the system equations of motion in each harmonic to a small set of nonlinear algebraic equations. The full set of system equations is reduced to a discrete system with a few generalized degrees of freedom (DOFs) confined to the localized nonlinear regions. The resultant reduced order model is shown to be accurate enough for determining the periodic response. To demonstrate the capability of the proposed method, numerical case studies for continuous and discrete systems, including systems with internal resonance, have been studied and the outcomes are validated with benchmark studies. In addition, the method is applied in the identification process of an experimental test setup with unknown frictional support parameters, and the results are presented and discussed.     

On recovering the parameters and velocity state of the Duffing's oscillator

In this Letter, we propose a simple method to recover the unknown parameters and the velocity state from a known suitable output which is the position of the Duffing mechanical oscillator. We show that the system is constructible. Hence, it allows us to obtain an integral output parametrization of the remaining state. Based on this integral parametrization, we construct an iterative integral equation of the output. This method is numerically feasible and easy to implement by means of integrators, avoiding the necessity to evaluate the derivatives of the output.     

一类时变时滞混沌系统的参数辨识方法

时变的未知时滞参数普遍存在于混沌系统中,它使得混沌系统同步控制变得非常困难. 针对时滞混沌系统中参数时变且未知的问题, 提出了一种新颖的辨识方法. 该方法首先将未知时变参数用分段常数函数来近似, 把求解非线性函数的问题转化为参数向量选择问题, 其中分段常数函数的高度向量成为待求解参数向量; 然后推导了目标函数对分段常数高度向量的梯度信息, 结合序列二次规划法求解得最优分段函数; 随着分段数的增加, 最优分段函数将逼近原非线性时变函数. 数值实例结果验证了该方法的有效性.     

Parametric estimation of the Duffing system by using a modified gradient algorithm

The Letter presents a strategy for recovering the unknown parameters of the Duffing oscillator using a measurable output signal. The suggested approach employs the construction of an integral parametrization of one auxiliary output. It is calculated by measuring the difference between the output and its respective delay output. First we estimate the auxiliary output, followed by the application of a modified gradient algorithm, then we adjust the gains of the proposed linear estimator, until this error converges to zero. The convergence of the proposed scheme is shown using Lyapunov method.     

A new identification control for generalized Julia sets

In this paper, we propose a new method to realize drive-response system synchronization control and parameter identification for a class of generalized Julia sets. By means of this method, the zero asymptotic sliding variables are applied to control the fractal identification. Furthermore, the problems of synchronization control are solved in the case of a drive system with unknown parameters, and the unknown parameters of the drive system can be identified in the asymptotic synchronization process. The results of simulation examples demonstrate the effectiveness of this new method. Particularly, the basic Julia set is also discussed.     

Periodic synchronization of community networks with non-identical nodes uncertain parameters and adaptive coupling strength

In this paper, we propose a novel approach for simultaneously identifying unknown parameters and synchronizing time-delayed complex community networks with nonidentical nodes. Based on the LaSalle＇s invariance principle, a cri- teflon is established by constructing an effective control identification scheme and adjusting automatically the adaptive coupling strength. The proposed control law is applied to a complex community network which is periodically synchro- nized with different chaotic states. Numerical simulations are conducted to demonstrate the feasibility of the proposed method.     

Chen系统的自适应追踪控制

利用非线性单输入控制器实现混沌Chen系统的自适应追踪控制.根据Chen系统的结构特点选取合适的反馈方式，设计单输入自适应控制器，使Chen系统自适应追踪参数未知的Rossler系统的某一变量，并由Lyapunov直接方法证明误差信号渐近稳定于零.数值仿真结果表明该控制方法可行，且可以实现未知参数的辨识.     

ADAPTIVE CONTROL AND IDENTIFICATION OF CHAOTIC SYSTEMS

A novel adaptive control and identification on-line method is proposed for a class of chaotic system with uncertain parameters. We prove that, using the presented method, a controller and identifier is developed which can remove chaos in nonlinear systems and make the system asymptotically stabilizing to an arbitrarily desired smooth orbit. And at the same time, estimates to uncertain parameters converge to their true values. The advantage of our method over the existing result is that the controller and identifier is directly constructed by analytic formula without knowing unknown bounds about uncertain parameters in advance. A computer simulation example is given to validate the proposed approach.     

Using wavelet multi-resolution nature to accelerate the identification of fractional order system

Because of the fractional order derivatives, the identification of the fractional order system(FOS) is more complex than that of an integral order system(IOS). In order to avoid high time consumption in the system identification, the leastsquares method is used to find other parameters by fixing the fractional derivative order. Hereafter, the optimal parameters of a system will be found by varying the derivative order in an interval. In addition, the operational matrix of the fractional order integration combined with the multi-resolution nature of a wavelet is used to accelerate the FOS identification, which is achieved by discarding wavelet coefficients of high-frequency components of input and output signals. In the end, the identifications of some known fractional order systems and an elastic torsion system are used to verify the proposed method.     

Adaptive generalized projective synchronization of two different chaotic systems with unknown parameters

This paper presents a general method of the generalized projective synchronization and the parameter identification between two different chaotic systems with unknown parameters. This approach is based on Lyapunov stability theory, and employs a combination of feedback control and adaptive control. With this method one can achieve the generalized projective synchronization and realize the parameter identifications between almost all chaotic （hyperchaotic） systems with unknown parameters. Numerical simulations results are presented to demonstrate the effectiveness of the method.     

Randomly transitional phenomena in the system governed by Duffing's equation

This paper deals with turbulent or chaotic phenomena which occur in the system governed by Duffing's equation, a special type of two-dimensional periodic system. By using analog and digital computers, experiments are carried out with special reference to the change of attractors and of average power spectra of the random processes under the variation of the system parameters. On the basis of the experimental results, an outline of the random process is made clear. The results obtained in this paper will be applied to various physical problems and will also serve as material for the development of a proper mathematics of this phenomenon.     

Synchronization of Modified Chua＇s Circuit with x｜x｜ Function

This paper considers the chaos synchronization of the modified Chua＇s circuit with x｜x｜ function. We firstly show that a couple of the modified Chua systems with different parameters and initial conditions can be synchronized using active control when the values of parameters both in drive system and response system are known aforehand.Furthermore, based on Lyapunov stability theory we propose an adaptive active control approach to make the states of two identical Chua systems with unknown constant parameters asymptotically synchronized. Moreover the designed controller is independent of those unknown parameters. Numerical simulations are given to validate the proposed synchronization approach.     

Identifying time-dependent damping and stiffness functions by a simple and yet accurate method

The inverse vibration problem is a mathematical process to determine unknown mechanical parameters from measured vibration data. In this study the data of displacement are chosen in order to identify a time-dependent function of damping or stiffness. However, when both functions are to be identified we require both the data of displacement and velocity. This is the first time that a closed-form estimation method for the inverse vibration problems of estimating time-dependent parameters has been constructed. We are able to transform the inverse vibration problem into an identification problem governed by a parabolic-type partial differential equation (PDE). Then, a one-step group-preserving scheme (GPS) for the semi-discretization of PDE is established, which can be used to derive a closed-form solution for estimating parameters. The new Lie-group estimation method has three further advantages: it does not require any prior information on the functional forms of unknown functions; no initial guesses are required; and no iterations are required. Numerical examples were examined to show that the present approach is highly accurate and efficient even for identifying discontinuous and oscillatory parameters. Against the noise is good when only one function is estimated; however, the present approach is slightly weak against the noise when both functions are identified.     

Adaptive synchronization of Rossler and Chen chaotic systems

A novel adaptive synchronization method is proposed for two identical Rossler and Chen systems with uncertain parameters. Based on Lyapunov stability theory, we derive an adaptive controller without the knowledge of the system parameters, which can make the states of two identical Rossler and Chen systems globally asymptotically synchronized. Especially, when some unknown uncertain parameters are positive, we can make the controller more simple and, besides, the controller is independent of those positive uncertain parameters. All results are proved using a well-known Lyapunov stability theorem. Numerical simulations are given to validate the proposed synchronization approach.