论文标题
增强DIDO最佳控制工具箱的功能
Enhancements to the DIDO Optimal Control Toolbox
论文作者
论文摘要
在2020年，DIDO $^©$转20岁！该软件包于2001年出现在基本的，用户友好的MATLAB $^\ CIRCLEDR $ TEAKING-TOOL，以说明Pontryagin原理的各种细微差别，但在NASA宣布使用DIDO执行全球最佳操作后，NASA在2007年迅速上升。从那时起，该工具箱已在其航空根部远远超出其航空航天根的应用中生长：从解决量子控制中的问题到在设计高性能汽车中的快速，非线性灵敏度分析中。最近，它已被用来解决连续的旅行销售人员问题。在过去的二十年中，迪多的算法从简单地使用通用非线性编程求解器发展到快速光谱哈密顿编程技术的多方面参与。本文描述了对定义其数学和算法的内部增强功能的描述。包括机器人技术中的一个挑战示例问题，以展示最新版本的DIDO如何能够逃脱``本地最小值''的陷阱，从而吸引了许多其他轨迹优化方法。
In 2020, DIDO$^©$ turned 20! The software package emerged in 2001 as a basic, user-friendly MATLAB$^\circledR$ teaching-tool to illustrate the various nuances of Pontryagin's Principle but quickly rose to prominence in 2007 after NASA announced it had executed a globally optimal maneuver using DIDO. Since then, the toolbox has grown in applications well beyond its aerospace roots: from solving problems in quantum control to ushering rapid, nonlinear sensitivity-analysis in designing high-performance automobiles. Most recently, it has been used to solve continuous-time traveling-salesman problems. Over the last two decades, DIDO's algorithms have evolved from their simple use of generic nonlinear programming solvers to a multifaceted engagement of fast spectral Hamiltonian programming techniques. A description of the internal enhancements to DIDO that define its mathematics and algorithms are described in this paper. A challenge example problem from robotics is included to showcase how the latest version of DIDO is capable of escaping the trappings of a ``local minimum'' that ensnare many other trajectory optimization methods.
