Asymptotically Stable Multiple Input-Multiple Output Direct Model Reference Adaptive Controllers for Processes Not Necessarily Satisfying a Positive Real Constraint

针对不一定满足正实数约束过程的渐近稳定多输入多输出直接模型参考自适应控制器

• 批准号: 9111565
• 负责人: Howard Kaufman
• 金额: $ 4.7万
• 依托单位: Rensselaer Polytechnic Institute
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 1991
• 资助国家: 美国
• 起止时间: 1991-09-01 至 1993-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=9111565&HistoricalAwards=false
• 关键词: Asymptotically; Stable; Multiple; Input; Output

A modification is proposed that should, for a very large class of processes, guarantee asymptotic output model following for a very easily implementable direct adaptive control algorithm that can be applied to multiple input multiple output systems. This algorithm in order to satisfy a positive real constraint, has had to incorporate supplementary feedforward dynamics, thus resulting in stability but not perfect asymptotic tracking. The new modification by incorporating part of the feedforward dynamics into the model is such that perfect tracking of the augmented plant and model outputs implies perfect tracking of the original outputs. The proposed research involves the stability proof of the new modified algorithm, a study of procedures for designing robust feedforward dynamics, and an experimental validation study.

提出了一种修改，对于一个非常大的 一类过程，保证渐近输出模型 下面是一个非常容易实现的直接 自适应控制算法，可应用于 多输入多输出系统 该算法 为了满足正的真实的约束， 结合了补充前馈动态，因此 导致稳定性但不是完美的渐近跟踪。 新的修改，包括部分的 前馈动态模型是这样的， 对增强的对象和模型的完美跟踪 输出意味着对原始输出的完美跟踪。 拟议的研究涉及的稳定性证明 新的修改算法，一个研究程序， 设计鲁棒的前馈动态，以及 实验验证研究