Explicit Nonlinear Model Predictive Control

本書以風電機組SCADA(supervisory control and data acquisition, 數據采集與監視控制系統)數據分析與智能建模為主線，分析風電SCADA數據特點，提出風電SCADA數據分析模式，依次介紹預處理方法、參數特徵分析、部件行為特性分析、運行狀態分析和數據智能識別、運行參數智能預測、運行狀態智能診斷等內容。全書共八章，依SCADA數據分析模式展開介紹：第1章介紹風電SCADA數據特點、分析模式、研究現狀與面臨的挑問題，第2章介紹SCADA數據預處理方法，第3～5章以統計法、知識發現為主，第6～8章以智能建模、輔助決策為主，為風電機組設計製造研發、運行維護決策提供理論知識、方法工具和數據支撐。

本書是經典力學領域的經典著作，預備知識要求極低，僅需基礎微積分和本科基礎物理學知識，因此適合本科到研究生入門階段的課程使用，也適合數學、物理和工程專業的學生群體。This is an intuitively motivated presentation ofmany topics in classical mechanics and related areas of control theory and calculus of variations. All topics throughout the book are treated with zero tolerance for unrevealing definitions and for proofs which leave the reader in the dark. Some areas of particular interest are： an extremely short derivation of the ellipticity of planetary orbits; a statement and an explanation of the “tennis racket paradox”; a heuristic explanation (and a rigorous treatment) of the gyroscopic effect; a revealing equivalence between thedynamics of a particle and statics of a spring; a short geometrical explanation of Pontryagin’s Maximum Principle, and more. In the last chapter, aimed at more advanced readers, the Hamiltonian and the momentum are compared to forces in a certain static problem. This gives a palpable physical meaning to some seemingly abstract concepts and theo