Robust Model Reference Adaptive Controller Design

鲁棒模型参考自适应控制器设计

• 批准号: 9413123
• 负责人: Howard Kaufman
• 金额: $ 11.84万
• 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: 1994
• 资助国家: 美国
• 起止时间: 1994-09-15 至 1996-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=9413123&HistoricalAwards=false
• 关键词: Robust; Model; Reference; Adaptive; Controller

9413123 Kaufman Various direct model reference adaptive control (MRAC) procedures developed by the proposed investigator is especially attractive because they do not require full state feedback or adaptive observers. Other important properties of this class of algorithms include (1) their applicability to non-minimum phase systems, (2) the order of the plant may be much larger than the order of the reference model, and (3) this approach considers plants with multiple inputs and outputs. However, it is important to note that in order to guarantee asymptotic model following or even boundedness, it is sufficient to demonstrate the satisfaction of a positive real type constraint. Although various augmentation schemes have been developed to alleviate this constraint, it is not straightforward to design the needed (usually feedforward compensation to satisfy the positive real condition over the desired (or a maximal) range of parameter variations. Thus, it is proposed to consider recent robust compensation techniques that appear relevant to the design of such compensation. These include a robust feedforward compensator developed for single input-single output adaptive systems which will be extended to multiple input-multiple output systems and the Kharitonvoc polynomial analysis, which will be considered for use in single input-single output systems. The resulting augmentation procedures from this proposed effort in conjunction with the MRAC algorithms should result in easily implementable procedures for designing and synthesizing very robust direct adaptive controllers that are applicable to many systems with significant uncertainty. ***

小行星9413123考夫曼 各种直接模型参考自适应控制（MRAC）的程序开发的建议调查特别有吸引力，因为他们不需要完全的状态反馈或自适应观测器。 这类算法的其他重要特性包括：（1）它们对非最小相位系统的适用性，（2）设备的阶数可能比参考模型的阶数大得多，以及（3）这种方法考虑具有多个输入和输出的设备。 然而，重要的是要注意，为了保证渐近模型跟随性或甚至有界性，证明满足正真实的类型约束就足够了。 尽管已经开发了各种增强方案来减轻这种约束，但是设计所需的（通常是前馈补偿）以在期望的（或最大的）参数变化范围内满足正的真实的条件并不简单。 因此，建议考虑最近出现的强大的补偿技术，这种补偿的设计相关。 这些措施包括一个强大的前馈补偿器开发的单输入单输出自适应系统，将扩展到多输入多输出系统和Kharitonstrike多项式分析，这将被认为是用于单输入单输出系统。 由此产生的增强程序，从这个建议的努力结合MRAC算法应导致易于实现的程序设计和合成非常强大的直接自适应控制器，适用于许多系统具有显着的不确定性。 ***