When stabilization and optimization meet: a codesign approach

当稳定和优化相遇时：协同设计方法

• 批准号: DP210102600
• 负责人: Prof Dragan Nesic
• 金额: $ 34.69万
• 依托单位: The University of Melbourne
• 依托单位国家: 澳大利亚
• 项目类别: Discovery Projects
• 财政年份: 2021
• 资助国家: 澳大利亚
• 起止时间: 2021-03-09 至 2024-03-08
• 项目状态: 已结题
• 来源: https://dataportal.arc.gov.au/RGS/Web/Grants/DP210102600
• 关键词: When; stabilization; optimization; meet; codesign

The next generation of engineered systems need to perform complex tasks with precision, and be robust, resilient and adaptive to their environment enabled by the confluence of control, optimization, learning and computation Understanding the interplay between robust stability and optimization is key to this endeavor. Many techniques, such as model predictive control and reinforcement learning, rely on an intricate interplay between an optimization-based control algorithm and an optimization routine used to calculate the control law. This project aims to develop a general design framework for stability, suboptimality and robustness of such algorithms, that can be used in range of novel applications, such as driverless cars and drones.

下一代工程系统需要精确地执行复杂的任务，并通过控制，优化，学习和计算理解强大的稳定性和优化之间的相互作用的相互作用是对这项工作的关键的关键。许多技术，例如模型预测控制和增强学习，都依赖于基于优化的控制算法和用于计算控制法的优化程序之间的复杂相互作用。该项目旨在为这种算法的稳定性，次优和鲁棒性开发一个通用设计框架，该算法可用于多种新型应用程序，例如无人驾驶汽车和无人机。