CAREER: Theory and Application of Hybrid Estimation

混合估计作为一种强有力的鲁棒自适应方法，近年来在解决许多结构和/或参数不确定性问题方面取得了巨大的成功，从故障检测和隔离到目标跟踪和识别，从生物医学信号处理到复杂系统分解。 目前存在的瓶颈问题与混合估计是，现有的技术是没有足够的成本效益的大多数现实世界的混合估计问题，其中涉及一个大的模式集。 混合估计的进一步发展的最严重的障碍是与现有的技术局限于一个固定的结构的事实。 换句话说，现有的混合估计具有固定结构固有的基本限制，因为它不能有效地处理涉及不仅仅是几个模式的问题，不幸的是，大多数现实问题都是这种情况。 这种限制源于现有技术的基本假设，即系统模式在任何时候都可以由一个小的和固定的一组模型，可以事先确定的准确表示。 因此，现有的固定结构的混合估计已经到达这样一个阶段，即在其固定结构内不再能够期望有很大的改进。 然而，现有的研究工作几乎完全局限于这个固定的结构。 在这个建议中，提出了混合估计技术的理论和应用的调查。 本文提出的理论研究包括发展几种有前途的和互补的变结构算法，这些算法具有很高的成本效益，不复杂和通用性，足以适用于大多数混合估计问题，并朝着发展一个统一的混合估计理论做了一些工作。可以基于测量序列使模型集合而不是模型本身自适应，测量序列携带关于当前有效的系统模式的有价值的信息。 这是一个很有前途的新方向，大大改善了现有的技术，这是由PI最近发起的。 它的巨大潜力已被证明由PI，这是不复杂的，普遍适用的，并显着更具成本效益比国家的最先进的固定结构的混合估计这样的算法的最近发展。 本项目的研究成果将对估计、决策和辨识的理论和应用研究及其应用领域产生重大影响。 在短期内，它将大大推进国家的最先进的混合估计技术，并在长期内，它将提供洞察力和推力，在随机系统理论，随机信号处理和统计推断的未来调查。教育和人力资源开发是拟议的职业发展计划的组成部分。 该计划的主要教育目标是培养学生发展科学探究和技术发现和发明的能力、知识和技能，从而为他们从事工程职业做好准备。 这是通过以下方式实现的：1）在PI的创新和密切指导下，为学生提供参与高级研究项目的机会; 2）开发新的研究生和本科生课程，以更好地教育和培训学生; 3）通过编写教科书来传播拟议研究的结果，以接触更多的学生。

9734285LiHybrid estimation, as powerful robust adaptive approach, has found great success recently in solving many problems compounded with structural and/or parametric uncertainty, ranging from fault detection and isolation to target tracking and recognition, and from biomedical signal processing to complex system decomposition. The bottle-neck problem currently exists with hybrid estimation is that existing techniques are not cost-effective enough for most real-world hybrid estimation problems, which involve a large set of modes. The most serious barrier for the further development of hybrid estimation is associated with the fact that existing techniques are confined to a fixed structure. In other words, existing hybrid estimation has a fundamental limitation, inherent to the fixed structure, in that it cannot handle effectively problems involving more than just a few modes, which is, unfortunately, the case for most real-world problems. This limitation stems from the fundamental assumption of the existing techniques that the system mode at any time can be represented accurately by one of a small and fixed set of models that can be determined a priori. As a result, existing hybrid estimation with a fixed structure has arrived at such a stage that great improvement can no longer be expected within its fixed structure. Nevertheless, existing research effort is confined almost entirely to this fixed structure. In this proposal, an investigation of the theory and application of hybrid estimation techniques is proposed. The theoretical research proposed includes the development of several promising and complementary variable structure algorithms that are highly cost-effective, uncomplicated and general enough to be applicable to most hybrid estimation problems, and some work toward the development of a unified theory of hybrid estimation.The technical approach that will be undertaken for the proposed research is to use variable structure in hybrid estimation: The set of models, rather than the models themselves, may be made adaptive based on measurement sequences, which carries valuable information about the system mode currently in effect. This is a promising new direction for improving significantly on the existing techniques, which was initiated by the PI recently. Its great potential has been demonstrated by the recent development of such an algorithm by the PI that is uncomplicated, generally applicable, and significantly more cost-effective than the state-of-the-art fixed structure hybrid estimators. This project is expected to have a significant impact on the theoretical and applied research in estimation, decision and identification, and their application areas. In the short term it will advance significantly the state-of-the-art hybrid estimation techniques, and in the long term, it will provide insight and thrust to future investigation in stochastic systems theory, random signal processing and statistical inference.Education and human resource development are integrated components of the proposed career development plan. The primary education objective of this plan is to train students to develop ability, knowledge, and skills for scientific inquiry and technological discovery and invention, hence preparing them well for their pursuit of an engineering career. This is achieved by the following: 1) Provide students opportunities to participate in advnced research projects under innovative and close guidance of the PI; 2) Develop new graduate and undergraduate courses for better educating and training students; 3) Disseminate results from the proposed reseach by textbook writing to reach out to more students.***