刘庆泉, 沈阳理工大学副 授,研究生师。1998年本 毕业于南京理工大学, 后在东北大学分别获得通信与信息系统 业硕 学位 控 理论与控 工程 业博 学位,并在沈阳自动化研究所博 后流动 完成博 后研究工作,获“中国博 后 学基 资助项目”(一等资助)。本 毕业后在沈阳理工大学从 学工作,现为该校装备工程学 信息对抗技术 业 研室 任。 讲课程有:电子对抗技术、 测与识别技术、高频电子线路、信息论、DSP技术与应用等。 要的研究方向为:网络化控 系统、人驾驶飞 器控 系统等。目前已发表SCI/EI检 学术论文60多篇,出版学术 2部。 持 参与多项省部级纵向、横向 研项目。曾获得4项辽 省自然 学学术成果奖。
基于物联网的网络化控 技术 在逐渐形成,并受到关注,网络化控 技术 要应用于大城市交通系统的实时指挥 控 ,航空工业中的飞机 航自动化控 ,石油化工 冶 等连续流程工业的生产控 调整,战术 的数字化 控 ,网络赋能 药控 等。不同于以往的研究成果,《离散系统网络化控 理论:传输速率定理》针对网络通信信 传输速率受限的 况,研究了线性离散系统的网络化控 问题,在多 况下证 了确保系统可镇定的传输速率下界,给出了控 性能与传输速率之间固有的 衡关系,提出了新的量化、编码 控 策略,实现了控 与通信一体化设计。
1 Networked Control Schemes o The Basis of Infor*tio Theory
1.1 Stabiliz*io of Stochastic Linear Systems With D*a-R*e Constraints
1.1.1 Introdu*io
1.1.2 Problem Formul*io
1.1.3 Lower Bound of D*a R*es for Stabiliz*io
1.2 Observer-Based Dynamic Feedback Control Under Communic*io Constraints
1.2.1 Introdu*io
1.2.2 Problem St*ement and Preliminaries
1.2.3 Quantized Feedback Control Under D*a-R*e Limit*io
1.2.4 Numerical Example
1.3 A Quantiz*io and Coding Scheme Under Infor*tion-r*e Limit*io
1.3.1 Introdu*io
1.3.2 Problem Formul*io
1.3.3 Lower Bounds of Infor*tio R*e for Stabiliz*io
1.3.4 Simul*ions
References
2 Quantiz*ion, Coding, and Control Schemes Under D*a R*e Limit*ions
2.1 Quantized St*e Feedback Control Without Disturbances
2.1.1 Introdu*io
2.1.2 Problem Formul*io
2.1.3 The Bit-Alloc*io Algorit*
2.1.4 Numerical Example
2.2 Bit-Alloc*io Schemes for Systems with Disturbances
2.2.1 Introdu*io
2.2.2 Problem Formul*io
2.2.3 Bit-Alloc*io Schemes
2.2.4 Numerical Example
2.3 Dynamic Quantiz*io Schemes for Output Feedback Control
2.3.1 Introdu*io
2.3.2 Problem Formul*io
2.3.3 Output Feedback Control
2.3.4 Numerical Example
2.4 Feedback Control With Measurement Quantiz*io and Control Signal Quantiz*io
2.4.1 Introdu*io
2.4.2 Problem Formul*io
2.4.3 Control Under Communic*io Constraints
2.4.4 Numerical Example
References
3 Robust Control of Parameter Uncertai Systems Under D*a-R*e Constraints
3.1 Quantiz*io and Coding Schemes for Robust Control
3.1.1 Introdu*io
3.1.2 Problem Formul*io
3.1.3 Robust Control Under D*e-R*e Constraints
3.1.4 Numerical Example
3.2 A Time-Varying Recu*ive Alloc*io (TVRA) Algorit* for Robust Control
3.2.1 Introdu*io
3.2.2 Problem Formul*io
3.2.3 Time-Varying Recu*ive Alloc*io (TVRA) Algorit*
3.2.4 Numerical Example
References
4 Stabiliz*io of Linear Time-Invariant Systems Over Packet Dropout Communic*io Channels
4.1 Quantized St*e Feedback Control
4.1.1 Introdu*io
4.1.2 Problem Formul*io
4.1.3 Quantiz*ion, Coding, and Control Schemes
4.1.4 Numerical Example
4.2 Quantized Feedback Control For MIMO Systems
4.2.1 Introdu*io
4.2.2 Problem Formul*io
4.2.3 Quantiz*io and Control Schemes
4.2.4 Numerical Example
References
5 Stabiliz*io of Networked Control Systems with D*a-R*e Limit*ions and Time Delays
5.1 Stabiliz*io of Systems without Disturbances
5.1.1 Introdu*io
5.1.2 Problem Formul*io
5.1.3 Networked Control with Time Delays
5.1.4 Numerical Example
5.2 Stabiliz*io of Systems with Disturbances
5.2.1 Introdu*io
5.2.2 Problem Formul*io
5.2.3 Networked Control Under Communic*io Constraints
5.2.4 Numerical Example
5.3 Networked Control over Noisy Channel with Time Delays 151
5.3.1 Introdu*io 151
5.3.2 Problem Formul*io 152
5.3.3 Networked Control Under Communic*io Constraints 153
5.3.4 Numerical Example 157
5.4 Stabiliz*io of MIMO Control Systems
5.4.1 Introdu*io
5.4.2 Problem Formul*io
5.4.3 Networked Control Under D*a-R*e Limit*ions
5.4.4 Numerical Example
References
6 LQG Control of Linear Systems Under D*a-R*e Constraints
6.1 Quantized St*e Feedback Control
6.1.1 Introdu*io
6.1.2 Problem Formul*io
6.1.3 LQG Control Under D*a-R*e Constraints
6.1.4 Numerical Example
6.2 LQ Control of Networked Control Systems With Limited D*a R*es
6.2.1 Introdu*io
6.2.2 Problem Formul*io
6.2.3 LQ Control Under D*a-R*e Constraints
6.2.4 Numerical Example
6.3 Input and Output Quantized Control of LQG Systems under Infor*tio Limit*io
6.3.1 Introdu*io
6.3.2 Problem Formul*io
6.3.3 LQG Control Under D*e-R*e Constraints
6.3.4 Numerical Example
References