Adaptive Critics for Nonlinear Continuous-Time Systems

非线性连续时间系统的自适应批评

• 批准号: 0501451
• 负责人: Frank Lewis
• 金额: $ 23.99万
• 依托单位: University of Texas at Arlington
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2005
• 资助国家: 美国
• 起止时间: 2005-07-15 至 2009-06-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0501451&HistoricalAwards=false
• 关键词: Adaptive; Critics; Nonlinear; Continuous; Time

Intellectual Merit: The PI proposes to work on continuous-time versions of Adaptive Dynamic Programming (ADP), an emerging novel class of designs which offers hope of brain-like capabilities in the (approximately) optimal management of large complex systems subject to random disturbance, nonlinearity and a need for foresight. He will work on stability proofs, convergence analysis and new designs, together. Specific research goals involve neural network ADP for output feedback and nonlinear filtering, neurocontrol with entropy and nonstandard value functionals, model-based continuous time ADP and small-time-step approximate tuning for model-free continuous time ADP.Neural networks provide a way to approximate unknown nonlinear functions, needed as part of general ADP, with greater accuracy than traditional approximators for a limited number of parameters.Broader Impacts: The PI plans to write a textbook on ADP in engineering, which is needed very greatly at the present time. The related books currently available are either collections of papers less accessible to the average student (such as the Handbook of Learning and Approximate Dynamic Programming, IEEE Press, 2004) or textbooks which focus on methods of reinforcement learning developed for psychology or artificial intelligence, which do not scale well to large engineering tasks. The PI will also insert the new designs/algorithms into the practical applications worked on at the Automation and Robotics Research Institute (ARRI), into undergraduate courses, and into his program for high school students in Hands-On Design and Learning for Intelligent Control Systems.

知识分子的优点：PI提议为自适应动态编程（ADP）的连续时间版本进行工作，这是一种新兴的新颖的设计类型，可在大型复杂系统（大约）最佳管理中具有脑状功能的希望，受到随机干扰的随机干扰，非线性和对远见的需求。他将共同研究稳定性证明，融合分析和新设计。特定的研究目标涉及用于输出反馈和非线性过滤的神经网络ADP，具有熵和非标准价值功能的神经控制，基于模型的连续时间ADP和小时短的近似调谐，用于无模型连续时间ADP。作为一般ADP的一部分所需的近似未知的非线性功能，比传统近似器具有更高的准确性。当前可用的相关书籍是普通学生无法访问的论文（例如学习和近似动态编程手册，IEEE Press，2004年），或者教科书着眼于为心理学或人工智能开发的加强学习方法，这是这些方法，这是这些方法，这些方法是为了心理学或人工智能的。不能很好地扩展到大型工程任务。 PI还将将新的设计/算法插入在自动化和机器人研究所（ARRI）的实际应用中，将本科课程插入，并将其用于智能控制系统的动手设计和学习的高中生的课程。