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Generalized predictive control for multirate systems.

机译:多速率系统的广义预测控制。

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摘要

Model predictive control (MPC) is a paradigm that emerged in the late 1970's, and has developed considerably over the last two decades. The two versions which appear to have had the most acceptability are one derived by Clarke et al. [24] and is called GPC for generalized predictive control, and secondly that derived by Cutler and Ramaker [30] called DMC for dynamic matrix control.; Multirate systems are common in industry, especially in chemical process control. The synthesis and analysis of GPC for single-rate systems has drawn considerable attention since the 1980's. On the other hand multirate GPC, practically useful as it may be, has not received much attention. Most of the research in the multirate control area deals with the time-varying nature of multirate systems ([54, 99]) and hence makes the design and analysis more complex. The use of the lifting technique as introduced by Kranc [50] allows one to convert multirate systems into single-rate and linear time-invariant (LTI) equivalent systems. However, its use also presents a challenge in the synthesis problem: the lifted controllers should satisfy certain causality constraint. The main purposes of this thesis are: (1) To develop GPC controllers for multirate systems, taking into account the causality design condition. (2) To develop a sampled-data GPC scheme for multirate systems so that the continuous-time closed-loop performance is optimized, and the inter-sample behavior is improved. (3) To perform robust stability analysis of a general class of multirate MPC controllers in the presence of model-plant mismatch (MPM). Note that GPC belongs to the MPC class of controllers which are all model based algorithms.; The thesis focuses on the synthesis and analysis of GPC for multirate systems, as well as the more general and special case of multirate systems such as non-uniformly sampled systems and fast-control, slow-sampling, dual-rate systems. In addition to these, related topics such as the multirate digital redesign problem and the continuous time delay estimation problem are also investigated in this study.
机译:模型预测控制(MPC)是在1970年代末期出现的一种范例,并且在过去的二十年中得到了很大的发展。似乎具有最高可接受性的两个版本是Clarke等人得出的。 [24]被称为广义预测控制的GPC,其次由Cutler和Ramaker [30]推导的DPC被称为动态矩阵控制。多速率系统在工业中很常见,尤其是在化学过程控制中。自1980年代以来,用于单速率系统的GPC的合成和分析引起了相当大的关注。另一方面,实际上可能有用的多速率GPC并没有引起太多关注。多速率控制领域中的大多数研究都涉及多速率系统的时变性质([54,99]),因此使设计和分析更加复杂。由Kranc [50]引入的提升技术的使用允许将多速率系统转换为单速率和线性时不变(LTI)等效系统。但是,它的使用也对综合问题提出了挑战:提升的控制器应满足某些因果关系约束。本文的主要目的是:(1)考虑因果关系设计条件,为多速率系统开发GPC控制器。 (2)开发用于多速率系统的采样数据GPC方案,以优化连续时间闭环性能,并改善采样间行为。 (3)在存在模型工厂不匹配(MPM)的情况下对通用类别的多速率MPC控制器执行鲁棒的稳定性分析。注意,GPC属于控制器的MPC类,它们都是基于模型的算法。本文主要针对多速率系统的GPC进行综合和分析,以及多速率系统的更一般和特殊情况,例如非均匀采样系统和快速控制,慢采样,双速率系统。除此之外,本研究还研究了相关主题,例如多速率数字重新设计问题和连续时延估计问题。

著录项

  • 作者

    Sheng, Jie.;

  • 作者单位

    University of Alberta (Canada).;

  • 授予单位 University of Alberta (Canada).;
  • 学科 Engineering Chemical.
  • 学位 Ph.D.
  • 年度 2002
  • 页码 122 p.
  • 总页数 122
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类 化工过程(物理过程及物理化学过程);
  • 关键词

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