非线性复系统X^m-BX-C=0的Hermite正定解

非线性矩阵方程在控制理论、动态规划、梯形网络和随机过滤等领域有广泛应用.在一定条件下讨论了m次非对称复系统X^m-BX-C=0(m≥2)的Hermite正定解问题.给出了该系统存在正定解的充要条件,并利用系数矩阵的极大极小特征值所构成代数方程的根以及Brouwer不动点定理,获得了其正定解的存在区间.为迭代求出该系统的正定解,给出了与原方程同解且具对称结构的非线性系统.然后针对系数矩阵B分别为正定、负定、不定3种情况构造出相应的迭代格式,并根据相关代数方程的特征性质,分别证明了所建立的3种迭代格式的收敛性.与此同时根据每种迭代的特点,给出了迭代初始矩阵的选取方法.运用一个5次复系统的数值算例,检验了所给方法的有效性及可行性.

Super-harmonic resonance of gear transmission system under stick-slip vibration in high-speed train

This work deals with super-harmonic responses and the stabilities of a gear transmission system of a high-speed train under the stick-slip oscillation of the wheel-set.The dynamic model of the system is developed with consideration on the factors including the time-varying system stiffness,the transmission error,the tooth backlash and the self-excited excitation of the wheel-set.The frequency-response equation of the system at super-harmonic resonance is obtained by the multiple scales method,and the stabilities of the system are analyzed using the perturbation theory.Complex nonlinear behaviors of the system including multi-valued solutions,jump phenomenon,hardening stiffness are found.The effects of the equivalent damping and the loads of the system under the stick-slip oscillation are analyzed.It shows that the change of the load can obviously influence the resonance frequency of the system and have little effect on the steady-state response amplitude of the system.The damping of the system has a negative effect,opposite to the load.The synthetic damping of the system composed of meshing damping and equivalent damping may be less than zero when the wheel-set has a large slippage,and the system loses its stability owing to the Hopf bifurcation.Analytical results are validated by numerical simulations.

Modeling and Control of Nonlinear Discrete-time Systems Based on Compound Neural Networks

An adaptive inverse controller for nonliear discrete-time system is proposed in this paper. A compound neural network is constructed to identify the nonlinear system, which includes a linear part to approximate the nonlinear system and a recurrent neural network to minimize the difference between the linear model and the real nonlinear system. Because the current control input is not included in the input vector of recurrent neural network (RNN), the inverse control law can be calculated directly. This scheme can be used in real-time nonlinear single-input single-output (SISO) and multi-input multi-output (MIMO) system control with less computation work. Simulation studies have shown that this scheme is simple and affects good control accuracy and robustness.

Multimodel Approach for Intelligent Control and Applications

The use of the multimodel approach in the modelling, analysis and control of non-linear complex and/or ill-defined systems was advocated by many researchers. This approach supposes the definition of a set of local models valid in a given region or domain. Different strategies exist in the literature and are generally based on a partitioning of the non-linear system’s full range of operation into multiple smaller operating regimes each of which is associated with a locally valid model or controller. However, most of these strategies, which suppose the determination of these local models as well as their validity domain, remain arbitrary and are generally fixed thanks to a certain a priori knowledge of the system whatever its order. Recently, we have proposed a new approach to derive a multimodel basis which allows us to limit the number of models in the basis to almost four models. Meanwhile, the transition problem between the different models, which may use either a simple commutation or a fusion technique, remains still arise. In this plenary talk, a fuzzy fusion technique is presented and has the following main advantages: （1） use of a fuzzy partitioning in order to determine the validity of each model which enhances the robustness of the solution; 2 introduction, besides the four extreme models, of another model, called average model, determined as an average of the boundary models.

Response of harmonically and stochastically excited strongly nonlinear oscillators with delayed feedback bang-bang control

We studied the response of harmonically and stochastically excited strongly nonlinear oscillators with delayed feedback bang-bang control using the stochastic averaging method. First, the time-delayed feedback bang-bang control force is expressed approximately in terms of the system state variables without time delay. Then the averaged It6 stochastic differential equations for the system are derived using the stochastic averaging method. Finally, the response of the system is obtained by solving the Fokker-Plank-Kolmogorov （FPK） equation associated with the averaged lt6 equations. A Duffing oscillator with time-delayed feedback bang-bang control under combined harmonic and white noise excitations is taken as an example to illus- trate the proposed method. The analytical results are confirmed by digital simulation. We found that the time delay in feedback bang-bang control will deteriorate the control effectiveness and cause bifurcation of stochastic jump of Duffing oscillator.

A Survey of Repetitive Control for Nonlinear Systems

In aerospace engineering and industry, control tasks are often of a periodic nature,while repetitive control is especially suitable for tracking and rejection of periodic exogenous signals.Because of limited research effort on nonlinear systems, we give a survey of repetitive control for nonlinear systems in this paper.First,a brief introduction of repetitive control is presented.Then,after giving a brief overview of repetitive control for linear systems,this paper summarizes design methods and existing problems of repetitive control for nonlinear systems in detail.Lastly,relationships between repetitive control and other control schemes are analyzed to recognize repetitive control from different aspects more insightfully.

OVERVIEW OF COMPLEX SYSTEMS IN SPORT

The complex systems approach offers an opportunity to replace the extant pre-dominant mechanistic view on sport-related phenomena.The emphasis on the environment-system relationship,the applications of complexity principles,and the use of nonlinear dynamics mathematical tools propose a deep change in sport science.Coordination dynamics,ecological dynamics,and network approaches have been successfully applied to the study of different sport-related behaviors,from movement patterns that emerge at different scales constrained by specific sport contexts to game dynamics.Sport benefit from the use of such approaches in the understanding of technical,tactical,or physical conditioning aspects which change their meaning and dilute their frontiers.The creation of new learning and training strategies for teams and individual athletes is a main practical consequence.Some challenges for the future are investigating the influence of key control parameters in the nonlinear behavior of athlete-environment systems and the possible relatedness of the dynamics and constraints acting at different spatio-temporal scales in team sports.Modelling sport-related phenomena can make useful contributions to a better understanding of complex systems and vice-versa.

A CASE OF REFERENCE ON COMPLEXITY

The author argues that the population system of human societies, the highest form of lives on the planet, may serve as standard paradigm for study of complex systems. it turned out to be a well investigable, nonlinearly controllable dynamic system, where census plays pivotal role. The theory has led China to succeed in checking the upsurge of population growth of 1970-80s and remains reliable basis for family-planning policy-making in all countries world-wide. It suggests that statistics could be a powerful tool in studying holistic properties of complex systems.

Taming complexity in nonlinear dynamical systems by recycled signal

In this paper, the impacts of the recycled signal on the dynamic complexity have been studied theoretically and numerically xn a prototypical nonlinear dynamical system. The Melnikov theory is employed to determine the critical boundary, and the sta- tistical complexity measure （SCM） is defined and calculated to quantify the dynamic complexity. It has been found that one can switch the dynamics from the periodic motion to a chaotic one or suppress the chaotic behavior to a periodic one, merely via adjusting the time delay or the amplitude of the recycled signal, therefore, providing a candidate to tame the dynamic com- plexity in nonlinear dynamical systems.

ON COMPLEX DYNAMIC CONTROL SYSTEMS

This paper presents some recent works on the control of dynamic systems,which have certain complex properties caused by singularity of the nonlinear structures,structure^varyings, or evolution process etc. First, we consider the structure singularity of nonlinear control systems. It was revealed that the focus of researches on nonlinear control theory is shifting from regular systems to singular systems. The singularity of nonlinear systems causes certain complexity. Secondly, the switched systems are considered. For such systems the complexity is caused by the structure varying. We show that the switched systems have significant characteristics of complex systems. Finally, we investigate the evolution systems. The evolution structure makes complexity, and itself is a proper model for complex systems.