非线性随机动力学与控制的哈密顿理论框架

 近几年来，笔者提出与发展了随机激励的耗散的哈密顿系统理 论，包括精确平稳解、等效非线性系统法、拟哈密顿系统随机平均法、 拟哈密顿系统的随机稳定性与随机分岔、首次穿越损坏分析方法及非 线性随机最优控制策略，从而构成了一个非线性随机动力学与控制的 哈密顿理论框架.本文简要介绍这一理论框架.     

随机最优控制方法识别动力学系统局部非线性

利用随机动态规划方法可以得到线性二次型高斯问题的最优控制解．基于这一结果与系统辨识问题最优控制解的概念,将动力学系统中局部非线性结构参数的辨识问题转化为求解对应线性系统的最优控制问题,利用线性系统随机最优控制的理论与方法,结合FSM（ForceStateMapping）方法,提出了识别动力学系统中局部非线性回复力类型及结构参数的新方法．所研究系统由大的线性子结构与一个或多个非线性子结构组成,其中线性结构的模型参数已知,待辨识量为局部非线性结构参数．     

非线性轨迹优化问题的保辛自适应求解方法

非线性轨迹优化问题一般是一个非线性最优控制问题。将非线性系统的最优控制问题导入到哈密顿体系的辛几何空间当中,基于对偶变量变分原理提出了求解非线性最优控制问题的一种保辛自适应方法。以时间区段两端协态作为独立变量,在时间区段内采用拉格朗日插值近似状态和协态变量,并利用对偶变量变分原理将非线性最优控制问题转化为非线性方程组的求解,保持了哈密顿系统的辛几何结构。并进一步,提出了基于多层次迭代的自适应算法,提高了非线性最优控制问题的求解效率。数值实验验证了该算法在求解非线性轨迹优化问题中的有效性。     

随机激励的耗散的Hamilton系统理论的研究进展

近几年中,利用Ｈａｍｉｌｔｏｎ系统的可积性与共振性概念及Ｐｏｉｓｓｏｎ括号性质等,提出了高斯白噪声激励下多自由度非线性随机系统的精确平稳解的泛函构造与求解方法,并在此基础上提出了等效非线性系统法,提出了拟Ｈａｍｉｌｔｏｎ系统的随机平均法,并在该法基础上研究了拟Ｈａｍｉｌｔｏｎ系统随机稳定性、随机分岔、可靠性及最优非线性随机控制,从而基本上形成了一个非线性随机动力学与控制的Ｈａｍｉｌｔｏｎ理论框架．本文简要介绍了这方面的进展．     

拟不可积Hamilton系统响应的随机最优控制

提出了一种基于拟不可积Hamilton系统随机平均法和随机动态规划原理的控制策略,它可以对受高斯白噪声激励的拟不可积Hamilton系统进行非线性随机最优控制,以使系统的响应最小化,利用拟不可积Hamilton系统随机平均法可以将受控的拟不可积Hamilton系统降维成一维的It随机微分方程,利用随机动态规划原理可以为系统响应最小化问题建立动态规划方程,在控制力为有界的条件下,从动态规划方程中可以确定出最优控制规律,受控系统的响应是通过求解与It6随机微分方程相联系的FPK方程得到的,用一个例子阐述了这一随机最优控制策略的实施过程。     

IUTAM非线性随机动力学讨论会简介

国际理论与应用力学联合会非线性随机动力学讨论会(IUTAM Symposium On Nonlinear Stochastic Dynamics)于2002年8月26－30日在美国Urbana—ChamPaign依利诺斯大学的Robert Allerton公园与会议中心召开．主办单位是依利诺斯大学航空航天工程系．依利诺斯大学N．Sri Na—machchivaya教授与佛罗里达大西洋大学Y．K．Lin院士任共同主席．与会代表79人．参加会议的国家有：美国、德国、加拿大、英国、法国、中国、俄罗斯、意大利、挪威、捷克、南非、斯洛伐尼亚．美国代表占绝大多数，代表较多的国家还有德国与加拿大．44位学者做了大会邀请报告．11位年轻学者作了墙报交流．会议还组织了一次关于随机动态系统将来发展的晚间讨论会．作者作为中国唯一代表出席了会议，做了题为“最优控制的拟部分可积哈密顿系统的李亚普诺夫指数与稳定性”的大会邀请报告，受到代表们的好评．     

拟哈密顿系统的随机稳定性

迄今，有关随机稳定性的具体研究成果在多限于单自由度或二维线性随机系统。本文简要介绍近来我们在多自由度拟哈密顿系统（在弱随机激励与小耗散力作用下的哈密顿系统）的随机性上取得的一些新成果。     

多自由度非线性随机系统的响应与稳定性

响应与稳定性分析一直是随机动力学研究的热点, 发展预测随机响应及判定系统响应性态的方法具有重要的科学意义与广阔的应用前景. 本文综述了有关多自由度非线性随机系统的响应与稳定性的研究. 首先简介用于随机系统响应预测的Fokker-Planck-Kolmogorov方程法、随机平均法、等效线性化法、等效非线性系统法和Monte Carlo模拟法, 评述其优缺点, 进而讨论了多自由度非线性随机系统响应的精确平稳解、近似瞬态解的研究现状. 然后介绍了随机系统稳定性分析的两类方法, 即Lyapunov函数法及Lyapunov指数法,并综述了多自由度非线性随机系统稳定性分析的研究现状. 最后给出几点发展建议.     

非保守非线性刚-弹-液-控耦合分析动力学及其应用研究

非保守非线性刚-弹-液-控耦合分析动力学是与航天动力学和多体动力学相关的重要研究课题之一, 研究这一理论和应用课题具有重要理论意义和实际应用价值. 本研究建立了非保守非线性两类变量的刚-弹-液-控耦合分析动力学的Hamilton型拟变分原理, 并以该Hamilton型拟变分原理的泛函为依据, 分析了刚-弹-液-控耦合中的刚-弹耦合、刚-液耦合与弹-液耦合、控-刚耦合的特点. 借助于Lagrange-Hamilton体系, 从Hamilton型拟变分原理出发推导出非保守非线性刚-弹-液-控耦合系统的Lagrange方程, 并应用该Lagrange方程推导出系统的控制方程. 进一步以该控制方程为依据, 分析了刚-弹-液-控耦合中的刚-弹耦合、刚-液耦合与弹-液耦合、控-刚耦合的机理. 从两个方面概要地研究了非保守非线性刚-弹-液-控耦合系统的Lagrange方程的应用: 一方面, 应用该Lagrange方程建立了相应的有限元计算模型, 分析了这类计算模型的优越性; 另一方面, 应用系统的控制方程对实际问题进行解析的分析讨论, 说明了应用解析的分析讨论来研究问题与应用数值的、定量的分析方法来研究问题的互补特性. 最后, 讨论了几个相关的问题.      

载流圆板在磁场中的随机稳定性分析

本文根据大挠度板壳力学基础理论和电磁弹性力学理论,建立了载流圆板的非线性磁弹性随机振动力学模型,采用伽辽金变分法将其变换成非线性常微分动力学方程．通过拟不可积哈密顿系统的平均理论将该方程等价为一个一维伊藤随机微分方程．通过计算该方程的最大Lyapunov 指数判断该系统的局部随机稳定性,并进一步采用基于随机扩散过程的奇异边界理论判断该系统的全局稳定性．最后通过讨论该系统的稳态概率密度函数图的形状变化讨论了该动力系统的随机Hopf分岔的变化规律,并采用数值模拟对理论分析进行了验证．     

An Optimal Nonlinear Feedback Control Strategy for Randomly Excited Structural Systems

A strategy for optimal nonlinear feedback control of randomlyexcited structural systems is proposed based on the stochastic averagingmethod for quasi-Hamiltonian systems and the stochastic dynamicprogramming principle. A randomly excited structural system isformulated as a quasi-Hamiltonian system and the control forces aredivided into conservative and dissipative parts. The conservative partsare designed to change the integrability and resonance of the associatedHamiltonian system and the energy distribution among the controlledsystem. After the conservative parts are determined, the system responseis reduced to a controlled diffusion process by using the stochasticaveraging method. The dissipative parts of control forces are thenobtained from solving the stochastic dynamic programming equation. Boththe responses of uncontrolled and controlled structural systems can bepredicted analytically. Numerical results for a controlled andstochastically excited Duffing oscillator and a two-degree-of-freedomsystem with linear springs and linear and nonlinear dampings, show thatthe proposed control strategy is very effective and efficient.     

A minimax optimal control strategy for partially observable uncertain quasi-Hamiltonian systems

A stochastic minimax optimal control strategy for partially observable uncertain quasi-Hamiltonian systems is proposed. First, the stochastic optimal control problem of a partially observable nonlinear uncertain quasi-Hamiltonian system is converted into that of a completely observable linear uncertain system based on a theorem due to Charalambous and Elliot. Then, the converted stochastic optimal control problem is solved by a minimax optimal control strategy based on stochastic averaging method and stochastic differential game. The worst-case disturbances and the optimal controls are obtained by solving a Hamilton-Jacobi-Isaacs (HJI) equation. As an example, the stochastic minimax optimal control of a partially observable Duffing–van der Pol oscillator with uncertain disturbances is worked out in detail to illustrate the procedure and effectiveness of the proposed control strategy.     

A NEW STOCHASTIC OPTIMAL CONTROL STRATEGY FOR HYSTERETIC MR DAMPERS

I. INTRODUCTION Magneto-rheological (MR) ?uid as a smart material possesses fairly good essential characteristics suchas reversible change between liquid and semi-solid in milliseconds with a controllable yield strengthwhen exposed to a magnetic ?eld. A…     

Optimal Bounded Control for Minimizing the Response of Quasi Non-Integrable Hamiltonian Systems

A strategy for designing optimal bounded control to minimize theresponse of quasi non-integrable Hamiltonian systems is proposed basedon the stochastic averaging method for quasi non-integrable Hamiltoniansystems and the stochastic dynamical programming principle. Theequations of motion of a controlled quasi non-integrable Hamiltoniansystem are first reduced to an one-dimensional averaged Itô stochasticdifferential equation for the Hamiltonian by using the stochasticaveraging method for quasi non-integrable Hamiltonian systems. Then, thedynamical programming equation for the control problem of minimizing theresponse of the averaged system is formulated based on the dynamicalprogramming principle. The optimal control law is derived from thedynamical programming equation and control constraints without solvingthe equation. The response of optimally controlled systems is predictedthrough solving the Fokker–Planck–Kolmogrov (FPK) equation associatedwith completely averaged Itô equation. Finally, two examples are workedout in detail to illustrate the application and effectiveness of theproposed control strategy.     

Stochastic minimax semi-active control for MDOF nonlinear uncertain systems under combined harmonic and wide-band noise excitations using MR dampers

A stochastic minimax semi-active control strategy for multi-degrees-of-freedom (MDOF) strongly nonlinear systems under combined harmonic and wide-band noise excitations is proposed. First, a stochastic averaging procedure is introduced for controlled uncertain strongly nonlinear systems using generalized harmonic functions and the control forces produced by Magneto-rheological (MR) dampers are split into the passive part and the active part. Then, a worst-case optimal control strategy is derived by solving a stochastic differential game problem. The worst-case disturbances and the optimal semi-active controls are obtained by solving the Hamilton–Jacobi–Isaacs (HJI) equations with the constraints of disturbance bounds and MR damper dynamics. Finally, the responses of optimally controlled MDOF nonlinear systems are predicted by solving the Fokker–Planck–Kolmogorov (FPK) equation associated with the fully averaged Itô equations. Two examples are worked out in detail to illustrate the proposed control strategy. The effectiveness of the proposed control strategy is verified by using the results from Monte Carlo simulation.     

Optimal Bounded Control of First-Passage Failure of Quasi-Integrable Hamiltonian Systems with Wide-Band Random Excitation

The optimal bounded control of quasi-integrable Hamiltonian systems with wide-band random excitation for minimizing their first-passage failure is investigated. First, a stochastic averaging method for multi-degrees-of-freedom (MDOF) strongly nonlinear quasi-integrable Hamiltonian systems with wide-band stationary random excitations using generalized harmonic functions is proposed. Then, the dynamical programming equations and their associated boundary and final time conditions for the control problems of maximizinig reliability and maximizing mean first-passage time are formulated based on the averaged Itô equations by applying the dynamical programming principle. The optimal control law is derived from the dynamical programming equations and control constraints. The relationship between the dynamical programming equations and the backward Kolmogorov equation for the conditional reliability function and the Pontryagin equation for the conditional mean first-passage time of optimally controlled system is discussed. Finally, the conditional reliability function, the conditional probability density and mean of first-passage time of an optimally controlled system are obtained by solving the backward Kolmogorov equation and Pontryagin equation. The application of the proposed procedure and effectiveness of control strategy are illustrated with an example.     

STOCHASTIC OPTIMAL CONTROL FOR THE RESPONSE OF QUASI NON-INTEGRABLE HAMILTONIAN SYSTEMS~

A strategy is proposed based on the stochastic averaging method for quasi nonintegrable Hamiltonian systems and the stochastic dynamical programming principle. The proposed strategy can be used to design nonlinear stochastic optimal control to minimize the response of quasi non-integrable Hamiltonian systems subject to Gaussian white noise excitation. By using the stochastic averaging method for quasi non-integrable Hamiltonian systems the equations of motion of a controlled quasi non-integrable Hamiltonian system is reduced to a one-dimensional averaged Ito stochastic differential equation. By using the stochastic dynamical programming principle the dynamical programming equation for minimizing the response of the system is formulated.The optimal control law is derived from the dynamical programming equation and the bounded control constraints. The response of optimally controlled systems is predicted through solving the FPK equation associated with It5 stochastic differential equation. An example is worked out in detail to illustrate the application of the control strategy proposed.     

STOCHASTIC OPTIMAL CONTROL OF STRONGLY NONLINEAR SYSTEMS UNDER WIDE-BAND RANDOM EXCITATION WITH ACTUATOR SATURATION

A bounded optimal control strategy for strongly non-linear systems under non-white wide-band random excitation with actuator saturation is proposed. First, the stochastic averaging method is introduced for controlled strongly non-linear systems under wide-band random excitation using generalized harmonic functions. Then, the dynamical programming equation for the saturated control problem is formulated from the partially averaged Itō equation based on the dynamical programming principle. The optimal control consisting of the unbounded optimal control and the bounded bang-bang control is determined by solving the dynamical programming equation. Finally, the response of the optimally controlled system is predicted by solving the reduced Fokker-Planck-Kolmogorov （FPK） equation associated with the completed averaged Itō equation. An example is given to illustrate the proposed control strategy. Numerical results show that the proposed control strategy has high control effectiveness and efficiency and the chattering is reduced significantly comparing with the bang-bang control strategy.