WKBJ近似保辛吗?

WKBJ短波近似是最常用的有效求解方法之一。保守体系的微分方程可用Hamilton体系的方法描述,其特点是保辛。保辛给出保守体系结构最重要的特性。但WKBJ短波近似却未曾考虑保辛的问题。本文给出验证近似解保辛的条件,并指出WKBJ近似难于保辛。然后给出正则变换的摄动保辛方法。数值例题展示了提出的保辛算法的有效性。     

基于混合优化的运载器大气层内闭环制导方法

针对运载器大气层内最优闭环制导问题,研究了一种将求解最优控制问题的间接法与直接法相结合求解最优上升轨迹的轨迹在线规划与闭环制导方法。该方法采用高斯伪谱法求解基于间接法推导的最优上升轨迹两点边值问题,能以较少的离散节点获得较高的求解精度,并具有较高的求解效率。为了进一步保证制导的实时性与飞行安全要求,提出了轨迹在线规划与闭环制导策略。最优上升轨迹求解结果表明,在同等的求解精度条件下,混合优化算法的离散节点个数仅为间接法的25%~40%,计算效率提高了50倍左右。建立导航模型进行闭环制导蒙特卡洛打靶仿真,制导算法满足实时性与过程约束要求,关机点高度、速度、弹道倾角及轨道倾角的最大偏差分别为-8.93 m、-3.35 m/s、0.015°、0.0018°,算法具有较高的制导精度。     

哈密顿系统正则变换在时变最优控制中的应用

利用哈密顿系统正则变换和生成函数理论求解线性时变最优控制问题,构造了新的最优控制律形式并提出了控制增益计算的保结构算法. 利用生成函数求解最优控制导出的哈密顿系统两端边值问题,并构造线性时变系统的最优控制律,由第2类生成函数所构造的最优控制律避免了末端时刻出现无穷大反馈增益. 控制系统设计中需求解生成函数满足的时变矩阵微分方程组. 根据生成函数与哈密顿系统状态转移矩阵之间的关系,从正则变换的辛矩阵描述出发,导出了求解这组微分方程组的保结构递推算法.为了保持递推计算中的辛矩阵结构,哈密顿系统状态转移矩阵的计算中利用了Magnus级数.      

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。     

非线性方程的保辛近似算法

保守体系的微分方程可用Hamilton体系的方法描述,其特点是保辛。两个辛矩阵之和不能保辛,两个辛矩阵的乘积仍是辛矩阵。最常用的小参数摄动法用的是加法,因此对辛矩阵不能保辛。从保辛的角度,要用正则变换。本文针对非线性微分方程,运用自变量坐标变换,对原系统进行变换。由此推导出变换后系统的变分原理。引入Hamilton对偶变量,通过数学变换,得到变系数非线性方程。针对该方程,本文提出了保辛摄动算法。通过数值算例,对不同步长下,保辛摄动法、多尺度摄动法、龙格库塔法和精确解的结果做了比较。数值例题表明,对于非线性方程,本文提出的保辛摄动算法有良好的精度。在步长增大的情况下,保辛摄动保持了良好的稳定性。     

短波近似的保辛算法

WKBJ短波近似是最常用的有效求解方法之一。保守体系的微分方程可用Hamilton体系的方法描述,其特点是保辛。保辛给出保守体系结构最重要的特性。但WKBJ短波近似却未曾考虑保辛的问题。WKBJ近似可用自变量坐标变换,然后再给出其保辛摄动。数值例题展示了本文变换保辛算法的有效性。     

多体系统轨迹跟踪的瞬时最优控制保辛方法

随着近年来机器人在各行业领域的广泛应用,对机器人的动力学与控制性能不断提出新的要求,特别是对设计越来越复杂、操作越来越灵巧的智能机器人,要求其能够对目标轨迹实现高精度跟踪以满足实际工作需求. 因此,针对机器人多体系统对目标轨迹跟踪的任务需求,基于微分代数方程提出瞬时最优控制保辛方法. 首先,采用多体动力学绝对坐标建模方法建立机器人系统的普适动力学方程,即微分代数方程;然后,采用保辛方法将连续时间域内的微分代数方程进行离散化,进而得到以当前位置、速度和拉式乘子为未知量的非线性代数方程组;其次,通过引入对目标轨迹跟踪以及对控制加权的瞬时最优性能指标,根据瞬时最优控制理论获得当前最优控制输入;最后,通过离散时间步的更新完成对目标轨迹的跟踪任务. 为了验证本文方法的有效性,以双摆轨迹跟踪控制为例进行了数值仿真,结果表明:针对机器人轨迹跟踪任务所提出的瞬时最优控制保辛方法能够实现对目标轨迹的高精度跟踪,且瞬时最优控制由受控微分代数方程推导获得,更具一般性,能够适应其他复杂多体系统的轨迹跟踪控制问题.      

HYBRID OPTIMIZATION STRATEGY FOR MOTION PLANNING OF SPACE ROBOT SYSTEM WITH PRISMATIC JOINT

研究了自由漂浮带滑移铰空间机器人非完整运动规划的最优控制问题,提出一种由高斯伪谱法求解可行解与直接打靶法求解最优解相结合的混合优化策略.首先,根据多体系统动力学理论建立空间机器人的动力学模型,给定系统的初始和目标位形,将空间机器人运动规划问题描述成博尔察（Bolza）型最优控制问题;然后,利用高斯伪谱法将最优控制问题离散为非线性规划问题,求解在较少勒让德-高斯（Legendre-Gauss,LG）点时状态变量和控制变量对应的可行解;最后,在LG点处离散控制变量,作为直接打靶法的初值,利用序列二次规划算法求解空间机器人系统的优化运动轨迹和最优控制输入.通过数值仿真,系统优化运动轨迹光滑平稳,最优控制输入也能很好地满足各种约束条件,仿真结果验证了该混合优化策略的鲁棒性和有效性.     

带滑移铰空间机器人运动规划的混合优化策略

研究了自由漂浮带滑移铰空间机器人非完整运动规划的最优控制问题,提出一种由高斯伪谱法求解可行解与直接打靶法求解最优解相结合的混合优化策略.首先,根据多体系统动力学理论建立空间机器人的动力学模型,给定系统的初始和目标位形,将空间机器人运动规划问题描述成博尔察(Bolza)型最优控制问题;然后,利用高斯伪谱法将最优控制问题离散为非线性规划问题,求解在较少勒让德-高斯(Legendre--Gauss,LG)点时状态变量和控制变量对应的可行解;最后,在LG点处离散控制变量,作为直接打靶法的初值,利用序列二次规划算法求解空间机器人系统的优化运动轨迹和最优控制输入.通过数值仿真,系统优化运动轨迹光滑平稳,最优控制输入也能很好地满足各种约束条件,仿真结果验证了该混合优化策略的鲁棒性和有效性.     

一维离散结构能带结构与表面态的辛分析方法

本文基于辛几何方法推导了一维离散周期结构、半无穷周期结构和含杂质半无穷周期结构的本征方程,力求建立一个完整的辛分析体系。通过辛分析,将一维离散半无限周期结构转化到一个元胞上求解,大大简化了计算量。对于含杂质半无穷周期结构,结合辛分析和W-W算法,给出求解含杂质半无穷周期结构本征值问题的精确、稳定和高效算法。数值算例说明了本文算法的有效性。     

Observer design and output feedback stabilization for nonlinear multivariable systems with diffusion PDE-governed sensor dynamics

This paper addresses the problems of observer design and output feedback stabilization for a class of nonlinear multivariable systems, where the nonlinear system dynamics are described by ordinary differential equations (ODEs), and the sensor dynamics are governed by diffusion partial differential equations (PDEs). Based on the Luenberger observer theory, a Luenberger-type PDE-ODE cascaded observer is derived to estimate the state variables of the system. Then, an observer-based output feedback stabilizing controller is developed. The exponential stability of both the observer error system and closed-loop control system is proven via the Lyapunov direct method. Finally, numerical examples are provided to illustrate the effectiveness of the proposed design methods.     

基于对偶变量变分原理的完整约束系统保辛算法

基于对偶变量变分原理,选择积分区间两端位移为独立变量,构造了求解完整约束哈密顿动力系统的高阶保辛算法。首先,利用拉格朗日多项式对作用量中的位移、动量及拉格朗日乘子进行近似;然后,对作用量中不包含约束的积分项采用Gauss积分近似,对作用量中包含约束的积分项采用Lobatto积分近似,从而得到近似作用量;最后,在此近似作用量的基础上,利用对偶变量变分原理,将求解完整约束哈密顿动力系统问题转化为一组非线性方程组的求解。算法具有保辛性和高阶收敛性,能够在位移的插值点处高精度地满足完整约束。算法的收敛阶数及数值性质通过数值算例验证。     

Globally convergent homotopy algorithms for nonlinear systems of equations

Probability-one homotopy methods are a class of algorithms for solving nonlinear systems of equations that are accurate, robust, and converge from an arbitrary starting point almost surely. These new globally convergent homotopy techniques have been successfully applied to solve Brouwer fixed point problems, polynomial systems of equations, constrained and unconstrained optimization problems, discretizations of nonlinear two-point boundary value problems based on shooting, finite differences, collocation, and finite elements, and finite difference, collocation, and Galerkin approximations to nonlinear partial differential equations. This paper introduces, in a tutorial fashion, the theory of globally convergent homotopy algorithms, deseribes some computer algorithms and mathematical software, and presents several nontrivial engineering applications.This work was supported in part by DOE Grant DE-FG05-88ER25068, NASA Grant NAG-1-1079, and AFOSR Grant 89-0497.     

Particle swarm optimization-based algorithm of a symplectic method for robotic dynamics and control

Multibody system dynamics provides a strong tool for the estimation of dynamic performances and the optimization of multisystem robot design. It can be described with differential algebraic equations(DAEs). In this paper, a particle swarm optimization(PSO) method is introduced to solve and control a symplectic multibody system for the first time. It is first combined with the symplectic method to solve problems in uncontrolled and controlled robotic arm systems. It is shown that the results conserve the energy and keep the constraints of the chaotic motion, which demonstrates the efficiency, accuracy, and time-saving ability of the method. To make the system move along the pre-planned path, which is a functional extremum problem, a double-PSO-based instantaneous optimal control is introduced. Examples are performed to test the effectiveness of the double-PSO-based instantaneous optimal control. The results show that the method has high accuracy, a fast convergence speed, and a wide range of applications.All the above verify the immense potential applications of the PSO method in multibody system dynamics.     

多体系统Lagrange方程数值算法的研究进展

Lagrange方法是建立多体系统动力学方程的普遍方法之一, 其方程的形式为常微分方程组或微分-代数方程组,数值计算与数 值分析是研究多体系统动力学特性的重要方法。本文简要介绍了多 体系统动 力学方程的第一、二类Lagrange方程和修正的Lagrange方 程的基本形式及这些方程的正则形式,着重介绍了正则方程在数值 计算中的特点,就多体系统Lagrange方程的隐式算法、辛算法和多 体系统动力学特性的数值分析方法(包括数值仿真、 Poincarè映射 和Lyapunov指数的计算方法)的研究现状进行了综述。     

多体系统Lagrange方程数值算法的研究进展

Lagrange方法是建立多体系统动力学方程的普遍方法之一,其方程的形式为常微分方程组或微分 - 代数方程组,数值计算与数值分析是研究多体系统动力学特性的重要方法.本文简要介绍了多体系统动力学方程的第一、二类Lagrange方程和修正的Lagrange方程的基本形式及这些方程的正则形式,着重介绍了正则方程在数值计算中的特点,就多体系统Lagrange方程的隐式算法、辛算法和多体系统动力学特性的数值分析方法(包括数值仿真、Poincar'e映射和Lyapunov指数的计算方法)的研究现状进行了综述.     

Parametric variational solution of linear-quadratic optimal control problems with control inequality constraints

A parametric variational principle and the corresponding numerical algo- rithm are proposed to solve a linear-quadratic （LQ） optimal control problem with control inequality constraints. Based on the parametric variational principle, this control prob- lem is transformed into a set of Hamiltonian canonical equations coupled with the linear complementarity equations, which are solved by a linear complementarity solver in the discrete-time domain. The costate variable information is also evaluated by the proposed method. The parametric variational algorithm proposed in this paper is suitable for both time-invariant and time-varying systems. Two numerical examples are used to test the validity of the proposed method. The proposed algorithm is used to astrodynamics to solve a practical optimal control problem for rendezvousing spacecrafts with a finite low thrust. The numerical simulations show that the parametric variational algorithm is ef- fective for LQ optimal control problems with control inequality constraints.     

Reliability Index and Failure Probability

Abstract

Numerical algorithms for the solution of nonlinear algebraic equation systems are discussed. Special application to the mechanism and multibody system kinematic analysis, as well as to the problems of constraint stabilization during dynamics simulation is regarded. Special attention is paid to the approaches of a separate solution of the differential equations and constraint stabilization. Numerical procedures that are effective additions to the well-known algorithms based on the Newton-Raphson method are presented. The problems of loss of precision and achievement of large unreal increments of the varying parameters are discussed. The traditional Newton-Raphson method is modified by applying a step reduction procedure that is developed numerically for the symbolic form of kinematic and dynamic equations. An optimization method for stabilization of constraints using the mass matrix of dynamic equations is suggested. According to the objective function defined the stabilization procedure provides minimal deviations of the parameters and their velocities with respect to the solution of the differential equations. No generalized coordinate partitioning is required either for solution of the dynamic equations or for stabilization of the constraints. Several examples of kinematic analysis of single and four contour plane mechanisms and constraint stabilization are solved, and the results are compared. The advantages of the algorithms developed are tested with a high-degree of initial deviation from the real solution. It is also shown that the step correction algorithm could provide admissible solution even when, in many cases, the classical approaches are not reliable. An example of the direct and inverse kinematic problem solutions of the four-degrees-of-freedom spatial platform is presented.