首页 | 本学科首页   官方微博 | 高级检索  
文章检索
  按 检索   检索词:      
出版年份:   被引次数:   他引次数: 提示:输入*表示无穷大
  收费全文   3篇
  完全免费   2篇
  自动化技术   5篇
  2019年   1篇
  2015年   1篇
  2011年   1篇
  2009年   1篇
  2005年   1篇
排序方式: 共有5条查询结果,搜索用时 62 毫秒
1
1.
This paper presents a new result in the analysis and implementation of path constraints in optimal control problems (OCPs). The scheme uses the well-known concept of discretizing path constraints on a finite number of points, yielding a set of interior-time point constraints replacing the original path constraints. The approach replaces the original OCP by a sequence of OCPs which is shown to converge in a finite number of steps to the solution of the original path constrained problem with -accuracy. Numerical results, verifying the theoretical analysis, are presented. The method is shown to be effective and promising for future applications, particularly in control vector parameterization implementations.  相似文献
2.
An optimal control problem can be formulated through a set of differential equations describing the trajectory of the control variables that minimize the cost functional (related to both state and control variables). Direct solution methods for optimal control problems treat them from the perspective of global optimization: i.e. perform a global search for the control function that optimizes the required objective. In this article we use a recently developed ecologically inspired optimization technique called Invasive Weed Optimization (IWO) for solving such optimal control problems. Usually the direct solution method operates on discrete n-dimensional vectors and not on continuous functions. Consequently it can become computationally expensive for large values of n. Thus, a parameterization technique is required to represent the control functions using a small number of real-valued parameters. Typically, direct methods based on evolutionary computing techniques parameterize control functions with a piecewise constant approximation. This has obvious limitations both for accuracy in representing arbitrary functions, and for optimization efficiency. In this paper a new parameterization is introduced using Bézier curves, which can accurately represent continuous control functions with only a few parameters. It is combined with IWO into a new evolutionary direct method for optimal control. The effectiveness of the new method is demonstrated by solving a wide variety of optimal control problems.  相似文献
3.
针对控制向量参数化方法敏感度方程求解耗时长、时间节点数难确定等问题,提出一种改进的控制向量参数化方法.首先利用分段常数对系统敏感度方程进行近似处理,有效地得到了敏感度方程的近似解析解,避免了对高维敏感度方程数值积分的计算负担;然后根据目标函数关于控制参数的敏感度来选择需要细化的控制参数,得到满足优化精度要求的最优时间节点数.针对非线性CSTR 的仿真研究验证了所提出算法的可行性和有效性.  相似文献
4.
控制向量参数化(Control vector parameterization, CVP) 方法是目前求解流程工业中最优操作问题的主流数值方法,然而,该方法的主要缺点之一是 计算效率较低,这是因为在求解生成的非线性规划(Nonlinear programming, NLP) 问题时,需要随着控制参数的调整,反复不断地求解相关的微分方程组,这也是CVP 方法中最耗时的部分.为了提高CVP 方法的计算效率,本文提出一种新颖的快速近似方法,能够有效减少微分方程组、函数值以及 梯度的计算量.最后,两个经典的最优控制问题上的测试结果及与国外成熟的最优控制 软件的比较研究表明:本文提出的快速近似CVP 方法在精度和效率上兼有良好的表现.  相似文献
5.
为了实现起重机集装箱摆动最优控制,提出一种基于控制向量参数化(CVP)方法的最优控制问题快速求解算法.首先,建立了以摆动能量最小为目标的集装箱装卸最优控制数学模型.其次,采用光滑化惩罚函数路径约束处理方法降低了模型求解难度.进一步,针对控制向量参数化方法微分方程组求解耗时长难题,结合网格划分提出改进四阶Runge--Kutta方法的快速CVP算法加快了最优控制问题求解速度.仿真测试针对不同位置的集装箱装卸任务进行.数值测试结果显示,相较于其他变步长求解方法,改进方法在得到相近求解精度解的同时,求解耗时明显减少,表明本文方法在集装箱装卸最优控制方面的应用价值.  相似文献
1
设为首页 | 免责声明 | 关于勤云 | 加入收藏

Copyright©北京勤云科技发展有限公司  京ICP备09084417号