Predictive Control for Linear and Hybrid Systems (Paperback)
暫譯: 線性與混合系統的預測控制 (平裝本)

Francesco Borrelli, Alberto Bemporad, Manfred Morari

  • 出版商: Cambridge
  • 出版日期: 2017-07-27
  • 售價: $3,180
  • 貴賓價: 9.5$3,021
  • 語言: 英文
  • 頁數: 440
  • 裝訂: Paperback
  • ISBN: 1107652871
  • ISBN-13: 9781107652873
  • 相關分類: Machine Learning
  • 立即出貨 (庫存=1)

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商品描述

Model Predictive Control (MPC), the dominant advanced control approach in industry over the past twenty-five years, is presented comprehensively in this unique book. With a simple, unified approach, and with attention to real-time implementation, it covers predictive control theory including the stability, feasibility, and robustness of MPC controllers. The theory of explicit MPC, where the nonlinear optimal feedback controller can be calculated efficiently, is presented in the context of linear systems with linear constraints, switched linear systems, and, more generally, linear hybrid systems. Drawing upon years of practical experience and using numerous examples and illustrative applications, the authors discuss the techniques required to design predictive control laws, including algorithms for polyhedral manipulations, mathematical and multiparametric programming and how to validate the theoretical properties and to implement predictive control policies. The most important algorithms feature in an accompanying free online MATLAB toolbox, which allows easy access to sample solutions. Predictive Control for Linear and Hybrid Systems is an ideal reference for graduate, postgraduate and advanced control practitioners interested in theory and/or implementation aspects of predictive control.

商品描述(中文翻譯)

模型預測控制(Model Predictive Control, MPC)是過去二十五年來工業界主導的先進控制方法,本書對其進行了全面的介紹。書中採用簡單且統一的方法,並關注實時實施,涵蓋了預測控制理論,包括MPC控制器的穩定性、可行性和魯棒性。明確的MPC理論在具有線性約束的線性系統、切換線性系統以及更一般的線性混合系統的背景下進行了介紹,並且能夠高效計算非線性最優反饋控制器。作者基於多年的實踐經驗,使用大量範例和示範應用,討論了設計預測控制法則所需的技術,包括多面體操作的算法、數學和多參數編程,以及如何驗證理論特性並實施預測控制策略。最重要的算法在隨附的免費在線MATLAB工具箱中提供,方便用戶輕鬆訪問範例解決方案。《線性與混合系統的預測控制》是對研究生、碩士生及對預測控制的理論和/或實施方面感興趣的高級控制實踐者的理想參考書。

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