《控制系統(tǒng)理論及應用進展(英文版)》匯集了眾多長期積極致力于控制系統(tǒng)理論及應用研究的學者的論文。這些學者絕大部分都來自于同一所母!獡碛形迨贻x煌歷史的中國科學技術大學!犊刂葡到y(tǒng)理論及應用進展(英文版)》的結集出版也是為了慶祝2008年中國科學技術大學五十周年華誕。《控制系統(tǒng)理論及應用進展(英文版)》共分十五章,涵蓋了控制系統(tǒng)理論及其應用的許多方面。書中控制系統(tǒng)理論的具體內容有:自適應控制、分岔控制、數(shù)字控制、容錯控制、H-infinity控制、學習控制、神經(jīng)和模糊控制、非線性控制、優(yōu)化、參數(shù)估計、預測控制、魯棒控制、隨機控制、系統(tǒng)辨識和變結構控制;控制應用的內容:包括飛行器飛行控制、建筑物震動控制、微機控制系統(tǒng)、醫(yī)療機器人、投資組合管理、機器人編隊控制和智能結構。
《控制系統(tǒng)理論及應用進展(英文版)》的各個章節(jié)技術性強,內容豐富,可作為工程、應用數(shù)學和相關學科本科生、研究生以及相關科技工作者學習和研究控制系統(tǒng)理論及應用的參考書。
Preface to the USTC Alumnis Series
Preface Gang Tao, Jing Sun
Chapter 1
A Sensitivity-Based View to the Stochastic Learning and Optimization
Xi-Ren Cao, Fang Cao
Chapter 2
Brief Review of Research on Robust Pole Clustering and Robust Structural Control
Sheng-Guo Wang
Chapter 3
Two Challenging Problems in Control Theory
Minyue Fu
Chapter 4
Developments in Receding Horizon Optimization-Based Controls:
Towards Real-time Implementation for Nonlinear Systems with
Fast Dynamics
Jing Sun, Reza Ghaemi, Ilya Kolmanovsky
Chapter 5
Multivariable Model Reference Adaptive Control
Gang Tao
Chapter 6
On Computer-Controlled Variable Structure Control Systems
Bin Wang, Xinghuo Yu, Xiangjun Li, Changhong Wang
Chapter 7
Multi-Robot Formation Control Based on Feedback from Onboard Sensors
Tore Gustavi, Maja Karasalo, Xiaoming Hu
Chapter 8
Semiactive Control Strategies for Vibration Reduction in Smart Structures
Ningsu Luo
Chapter 9
Identification and Control of Nonlinear Dynamic Systems via a Constrained Input-Output Neurofuzzy Network
Marcos Gonzgez-Olvera, Yu Tang
Chapter 10
Decomposition-Based Robot Control
Guangjun Liu
Chapter 11
From Adaptive Observers to Decoupled State and Parameter Estimations
Qinghua Zhang
Chapter 12
Reduced-Order Controllers for the H∞ Control Problem with Unstable Invariant Zeros or Infinite Zeros
Xin Xin
Chapter 13
Recent Advances in Bifurcation Control
Hua O. Wang
Chapter 14
Intelligent Medical Robot Application —— Tele-Neurosurgical Robot Case Study
Weimin Shen, Jason Gu, Yanjun Shen
Chapter 15
Applications of Stochastic Control Theory in Portfolio Management
Tao Pang