粘弹性运动带动力响应分析

基于Kelvin粘弹性材料本构模型及带运动方程,建立了运动带非线性动力学分析模型.基于该模型和Lie群分析方法推导了匀速运动及简谐运动带线性问题的解析解;基于该非线性模型的数值仿真讨论了运动带材料参数、带稳态运动速度、扰动速度对系统动态响应的影响.结果表明:1)当带匀速运动时,无论系统是线性还是非线性,运动带横向振动"频率"都随着带运动稳态速度增加而减小.2)随着材料粘性增加,系统耗散能力逐渐增强,动态响应逐渐减小.3)当带运动速度简谐波动时,系统动态响应随扰动速度增大而增大.扰动频率对带横向振动影响较大.     

一类非线性随机种群系统最优生育率控制

研究了一类非线性随机种群系统动力学模型的最优生育率控制问题.在加入外部随机因素扰动下,系统模型将会更具有实际意义.针对随机种群系统生育率控制问题,应用It?o公式,相应的伴随方程和变分不等式等经典理论,获得了随机种群系统最优生育率控制所满足的必要条件及其最优性组(由积分-偏微分方程和变分不等式组成).文中得到的结论是确定性种群系统的扩展,对随机控制理论具有现实的应用价值.     

基于自抗扰控制的直升机航向控制方法

针对直升机航向动力学包含输入非线性、时变参数和主-尾旋翼之间的强耦合的特性,传统的控制方法很难实现良好的性能.提出了一种自抗扰控制器的设计方法,并设计了扩张状态观测器,对参数不确定性和外部干扰进行估计,并实时补偿.与常规控制相比,在保证闭环稳定性的同时,能够应对模型参数的不确定性以及扰动,能够进一步使跟踪误差满足期望精度.并针对实际模型直升机实验平台航向动力学模型,在参数不确定性和主旋翼有扰动情况下,仿真结果验证了该方法的有效性.     

基于鲁棒最优控制的在线机器学习方法

基于再生核Hilbert空间(reproducing kernel Hilbert space,RKHS)的统计学习模型被广泛应用于函数逼近、图像处理、模式识别和回归分析等领域,并且也在非线性随机动力学系统的辨识问题中有着很好的表现.本文提出一个基于鲁棒最优控制的RKHS模型学习方法,来实现对非线性随机动力学系统的高效在线建模.利用本文得到的关于再生核空间的一些理论结果,本文将随机动力学系统的在线学习问题转化为一组具有有界随机扰动的离散时变线性系统的输出反馈镇定问题,并利用模型预测控制技术来设计相应的控制算法和学习算法.与现有的RKHS模型学习方法相比,在不引入任何数据窗口原理、剪枝技术、学习步长的调整机制以及对噪声统计性质的假设的情形下,新方法可以在保证模型参数快速且鲁棒收敛的同时,实现对动力学系统的自适应高精度建模.此外,本文首次从最优控制的视角出发,研究动力学系统的在线核学习问题.在本文提出的研究框架下,现有各种控制技术可以被利用起来开发新的鲁棒学习方法,这也为核学习理论的研究和算法的开发提供一些新的思路.本文亦给出了数值算例和对比结果,用来说明新方法的有效性.     

基于随机Hamilton实现的车摆系统干扰抑制控制

研究车摆系统在外部随机激励以及不确定扰动同时作用下的干扰抑制控制问题.首先给出了系统的随机不确定非线性动态模型,并通过反馈控制完成了系统的Hamilton实现,分析了系统的耗散性能.然后基于系统的耗散实现设计了干扰抑制控制器,该控制器设计能够充分利用系统的能量产生、耗散和转换特性.仿真结果验证了文章方法的有效性.     

无晨昏电场下带电粒子在中性片磁场中运动的周期轨

为了描述无晨昏电场情况下带电粒子在中性片磁场非小扰动区中运动的动力学特征,建立了一个非线性的动力学系统.运用Mawhin重合度理论探讨了一类非线性问题的周期解,然后将其应用于无晨昏电场情况下带电粒子在远磁尾中性片磁场非小扰动区中运动的动力学模型的周期解问题的研究,得出了带电粒子在初始位置逐渐远离中性片运动过程中存在周期轨的结果.在此基础上,还可以进一步探讨该模型同宿轨等其它动力学行为的存在性问题.     

旋转输液管动力稳定性理论分析北大核心CSCD

基于Lagrange原理和假设模态法建立了旋转输液管的动力学模型.通过降阶升维的方法求解系统的特征值问题,并分析了旋转输液管自由振动特性.得到了不同端部集中质量和转速下,系统特征值随流速升高的演变轨迹.揭示了临界流速随系统参数的变化规律.研究发现,内部流体的流动对旋转输液管动力学特性存在显著影响.在某些参数组合下,系统低阶模态能够形成不同形式的内共振关系.预示了旋转输液管模型蕴含丰富的动力学现象.     

基于Leslie-Gower捕食-被食模型的渔业收获问题

考虑了基于Leslie-Gower模型的生物经济学捕获问题,通过对税收政策的控制影响渔业生态系统,研究了系统的动力学行为,并通过Pontryagins最大值原理考虑了最优的税收政策,最后给出了系统仿真.     

基于扩张状态观测器的轮式移动机器人抗饱和自适应滑模轨迹跟踪控制

针对带有输入饱和约束的轮式移动机器人鲁棒轨迹跟踪问题,文章提出一种抗饱和自适应滑模控制方法.考虑到系统参数摄动和外部扰动等不确定因素对系统控制性能的影响,首先设计非线性扩张状态观测器来估计系统不确定因素,并基于估计值设计抗饱和自适应滑模控制器,消除系统的参数摄动、外部扰动和输入饱和约束对系统控制性能的影响.仿真对比结果验证了文章所提控制方法的优越性和有效性.     

基于等价输入扰动的空间桁架振动控制的研究(英文)

基于等价输入扰动(EID)的方法,通过对抑制外界未知扰动(匹配的或者非匹配的),实现了对空间桁架的振动控制.首先利用有限元分析(FEA),计算空间桁架的质量矩阵,阻尼矩阵,刚度矩阵及输入矩阵,进而建立空间桁架的模型.为了便于分析和设计,利用模态降阶的方法对模型进行降阶处理.在降阶的模型的基础上,设计等价输入扰动观测器观测外部未知扰动.基于观测的结果,进一步地设计了空间桁架的振动控制方法.最后给出数值仿真,以证实所提方法的有效性.     

Avoiding extremes using partial control

Dynamical systems can be prone to severe fluctuations due to the presence of chaotic dynamics. This paper explains for a toy chaotic economic model how such a system can be regulated by the application of relatively weak control to keep the system confined to a bounded region of the phase space, even in the presence of strong external disturbances. Since the control here is weaker than the disturbance, the system cannot be controlled to a particular trajectory, but under certain circumstances it can be partially controlled to avoid extreme values. Partial control depends on the existence of a certain set called a ‘safe sets’. We describe the safe set and how it varies with parameters, sometimes continuously and sometimes discontinuously.     

状态和控制均含时滞的受外界扰动的线性系统的最优控制

主要研究一类受外界持续扰动且状态和控制含不同时滞的线性系统的最优控制,首先通过变量代换,将系统化为控制不含时滞的滞后型微分系统.接着使用最优控制的极大值原理的必要条件,得到含超前和滞后项的两点边值问题.为了得到最优控制律的解析解,引进一个灵敏参数ε,得到两点边值问题序列,通过迭代法,得到最优控制律的解析解.并对外界扰动状态构造降维观测器,来实现最优控制律的物理可实现性.最后实例验证了上述方法的有效性.     

Robust intelligent sliding model control using recurrent cerebellar model articulation controller for uncertain nonlinear chaotic systems

In this paper, a robust intelligent sliding model control (RISMC) scheme using an adaptive recurrent cerebellar model articulation controller (RCMAC) is developed for a class of uncertain nonlinear chaotic systems. This RISMC system offers a design approach to drive the state trajectory to track a desired trajectory, and it is comprised of an adaptive RCMAC and a robust controller. The adaptive RCMAC is used to mimic an ideal sliding mode control (SMC) due to unknown system dynamics, and a robust controller is designed to recover the residual approximation error for guaranteeing the stable characteristic. Moreover, the Taylor linearization technique is employed to derive the linearized model of the RCMAC. The all adaptation laws of the RISMC system are derived based on the Lyapunov stability analysis and projection algorithm, so that the stability of the system can be guaranteed. Finally, the proposed RISMC system is applied to control a Van der Pol oscillator, a Genesio chaotic system and a Chua’s chaotic circuit. The effectiveness of the proposed control scheme is verified by some simulation results with unknown system dynamics and existence of external disturbance. In addition, the advantages of the proposed RISMC are indicated in comparison with a SMC system.     

Proportional economic growth under conditions of limited natural resources

The paper is devoted to economic growth models in which the dynamics of production factors satisfy proportionality conditions. One of the main production factors in the problem of optimizing the productivity of natural resources is the current level of resource consumption, which is characterized by a sharp increase in the prices of resources compared with the price of capital. Investments in production factors play the role of control parameters in the model and are used to maintain proportional economic development. To solve the problem, we propose a two-level optimization structure. At the lower level, proportions are adapted to the changing economic environment according to the optimization mechanism of the production level under fixed cost constraints. At the upper level, the problem of optimal control of investments for an aggregate economic growth model is solved by means of the Pontryagin maximum principle. The application of optimal proportional constructions leads to a system of nonlinear differential equations, whose steady states can be considered as equilibrium states of the economy. We prove that the steady state is not stable, and the system tends to collapse (the production level declines to zero) if the initial point does not coincide with the steady state. We study qualitative properties of the trajectories generated by the proportional development dynamics and indicate the regions of production growth and decay. The parameters of the model are identified by econometric methods on the basis of China’s economic data.     

Bernoulli substitution in the Ramsey model: Optimal trajectories under control constraints

We consider a neoclassical (economic) growth model. A nonlinear Ramsey equation, modeling capital dynamics, in the case of Cobb-Douglas production function is reduced to the linear differential equation via a Bernoulli substitution. This considerably facilitates the search for a solution to the optimal growth problem with logarithmic preferences. The study deals with solving the corresponding infinite horizon optimal control problem. We consider a vector field of the Hamiltonian system in the Pontryagin maximum principle, taking into account control constraints. We prove the existence of two alternative steady states, depending on the constraints. A proposed algorithm for constructing growth trajectories combines methods of open-loop control and closed-loop regulatory control. For some levels of constraints and initial conditions, a closed-form solution is obtained. We also demonstrate the impact of technological change on the economic equilibrium dynamics. Results are supported by computer calculations.     

On exact solutions to the Kolmogorov–Feller equation

The integrodifferential Kolmogorov–Feller equation describing the stochastic dynamics of a system subjected to a regular “force” and a random external disturbance in the form of short pulses with random “amplitudes” and occurrence times is considered. The equation is written in differential form. A method for finding the regular force from a given stationary probability distribution is described. The method is illustrated by examples.     

Towards a second cybernetics model for cognitive systems

We introduce an adaptive system for dynamics recognition. Thereby, an externally presented dynamics (stimulus) is mapped onto a mirror dynamics which is capable to simulate (simulus). A sudden change of the external dynamics leads to an surprisingly quick re-adaptation of the simulus, even if the presented dynamics is chaotic. The system consists of an internal pool of dynamical modules. The modules are forced to the latter dynamics in the sense of Pyragas' control mechanism by the stimulus. The control term, i.e. the strength of forcing, is used as a measure for which modules fit best to the external dynamics. In a sense, this defines a “dynamics-gradient” within the pool. The mirror dynamics now can be constructed by a linear combination of the best fitting modules with weights given by the control term amplitudes. If one adds the so-constructed mirror dynamics to the pool, one has a representation of the corresponding external dynamics within the pool. Later if the same external dynamics is presented again an even quicker adaptation is possible since a well-fitting module is already present. In order not to blow up the dimensionality of the pool, one can eliminate modules that have not been used for a long time. In principle, the modules can undergo an internal control. In addition, one principally can introduce evolution within the pool. Therefore, the system is able to show what sometimes is called a “second cybernetics”, i.e. a hyper-dynamics of the dynamics modules.     

On automorphisms of a distance-regular graph with intersection array {204, 175, 48, 1; 1, 12, 175, 204}

The research is focused on the question of proportional development in economic growth modeling. A multilevel dynamic optimization model is developed for the construction of balanced proportions for production factors and investments in a situation of changing prices. At the first level, models with production functions of different types are examined within the classical static optimization approach. It is shown that all these models possess the property of proportionality: in the solution of product maximization and cost minimization problems, production factor levels are directly proportional to each other with coefficients of proportionality depending on prices and elasticities of production functions. At the second level, proportional solutions of the first level are transferred to an economic growth model to solve the problem of dynamic optimization for the investments in production factors. Due to proportionality conditions and the homogeneity condition of degree 1 for the macroeconomic production functions, the original nonlinear dynamics is converted to a linear system of differential equations that describe the dynamics of production factors. In the conversion, all peculiarities of the nonlinear model are hidden in a time-dependent scale factor (total factor productivity) of the linear model, which is determined by proportions between prices and elasticities of the production functions. For a control problem with linear dynamics, analytic formulas are obtained for optimal development trajectories within the Pontryagin maximum principle for statements with finite and infinite horizons. It is shown that solutions of these two problems differ crucially from each other: in finite horizon problems the optimal investment strategy inevitably has the zero regime at the final stage, whereas the infinite horizon problem always has a strictly positive solution. A remarkable result of the proposed model consists in constructive analytical solutions for optimal investments in production factors, which depend on the price dynamics and other economic parameters such as elasticities of production functions, total factor productivity, and depreciation factors. This feature serves as a background for the productive fusion of optimization models for investments in production factors in the framework of a multilevel structure and provides a solid basis for constructing optimal trajectories of economic development.     

Modelling and passive control of flexible guiding hoisting system with time-varying length

ABSTRACT

A coupled dynamic modelling of the flexible guiding hoisting system is established, which includes the transverse-longitudinal-coupled vibration and the rotational vibration. Substituting vibrational energy of the system into Hamilton principle and applying the dynamic constraint, a distributed parameter mathematical model of the multi-rope system is derived. It is governed by coupled partial differential equations and ordinary differential equations (PDEs-ODEs), where the dynamic constraint in the form of an unknown moving force is the only connection between the hoisting conveyance and the guiding ropes. Based on Galerkin method, the dynamic response of the system is validated by numerical calculation and ADAMS simulation. Besides, an absorber with artificial intelligence optimization is proposed to reduce system vibration. The simulation result has demonstrated that a hoisting conveyance resonance can be observed when the external disturbance frequency is close to the system natural frequencies. Moreover, a vibration absorber can effectively diminish the resonant peaks of the first three orders of the guiding rope.     

Optimal Dynamics of Innovation in Models of Economic Growth

A nonlinear model of economic growth which involves production, technology stock, and their rates as the main variables is considered. Two trends (growth and decline) in the interaction between the production and R&D investment are examined in the balanced dynamics. The optimal control problem of R&D investment is studied for the balanced dynamics and the utility function with the discounted consumption. The Pontryagin optimality principle is applied for designing the optimal nonlinear dynamics. An existence and uniqueness result is proved for an equilibrium of the saddle type and the convergence property of the optimal trajectories is shown. Quasioptimal feedbacks of the rational type for balancing the dynamical system are proposed. The growth properties of the production rate, R&D, and technology intensities are examined on the generated trajectories.