西安石油大学电子工程学院：《自动控制理论 Modern Control System》精品课程教学资源（英文文献资料）Feedback Control

01 Prevention on frequently cases seen in colleges 01: Theft cases 02：Telecom Fraud 03：Fighting and brawling 04：Fire Control and Safety 02 Legal Information 01：Drug control 02：Residence registration 04：Road traffic safety 03：Religion 03 Ways to request help from police 01：Dial 110 02：Come to the police station

《控制理论》课程教学资源（参考书籍）定量过程控制理论 Quantitative Process Control Theory_Chapter 09 Complex Control Strategies

1 8.1 Controller Parameterization for General Plants 2 8.2 H∞ PID Controllers for Unstable Plants 3 8.3 H2 PID Controllers for Unstable Plants 4 8.4 Performance Limitation and Robustness 5 8.5 Maclaurin PID Controllers for Unstable Plants 6 8.6 PID Design for the Best Achievable Performance 7 8.6 All Stabilizing PID Controllers for Unstable Plants

1 7.1 The Feature of Integrating Systems 2 7.2 H∞ PID Controllers for Integrating Plants 3 7.3 H2 PID Controllers for Integrating Plants 4 7.4 Controller Design for General Integrating Plants 5 7.5 Maclaurin PID Controllers for Integrating Plants 6 7.6 Best Achievable Performance of a PID Controllers

1 6.1 The Quasi-H∞ Smith Predictor 2 6.2 The H2 Optimal Controller and the Smith Predictor 3 6.3 Equivalents of the Optimal Controller 4 6.4 The PID Controller and High-Order Controllers 5 6.5 Choice of Weighting Functions 6 6.6 Simplified Tuning for Quantitative Robustness

1 5.1 H2 PID Controllers for the First-Order Plant 2 5.2 Quantitative Tuning of H2 PID Controllers 3 5.3 H2 PID Controllers for the Second-Order Plant 4 5.4 Control of Inverse Response Processes 5 5.5 PID Controllers Based on the Maclaurin Series Expansion 6 5.6 PID Controllers with the Best Achievable Performance 7 5.7 Choice of the Filter

1 3.1 Norms and System Gains 2 3.2 Internal Stability and Performance 3 3.3 Controller Parameterization 4 3.4 Robust Stability and Robust Performance 5 3.5 Robustness of Systems with Time Delays

针对自动化高速公路（Automated highway system，AHS）车队稳定性问题，发展了一种多目标自适应巡航控制算法，根据李雅普诺夫（Lyapunov）稳定性理论对该问题进行了量化分析，并给出了同质与异质车队稳定性的设计要求，基于模型预测控制（Model predictive control，MPC）理论，综合协调驾驶员期望响应、跟驰安全性、车队稳定性、车队整体品质等控制目标，采用加权二次型性能泛函以及线性矩阵不等式约束的形式，将协同式多目标自适应巡航（Adaptive cruise control, ACC）设计问题最终转化成带约束的在线凸二次规划问题。仿真结果表明，相比单车ACC而言，协同ACC的约束空间更为严苛，车队互联系统稳定性易受车间时距、车队规模、多目标权重、瞬态工况、车辆异质性等因素的影响，建议在跟驰安全性、车队稳定性良好的前提下寻求一定的驾乘舒适性与燃油经济性，以确保车队整体品质

针对自动化高速公路（Automated highway system，AHS）车队稳定性问题，发展了一种多目标自适应巡航控制算法，根据李雅普诺夫（Lyapunov）稳定性理论对该问题进行了量化分析，并给出了同质与异质车队稳定性的设计要求，基于模型预测控制（Model predictive control，MPC）理论，综合协调驾驶员期望响应、跟驰安全性、车队稳定性、车队整体品质等控制目标， 采用加权二次型性能泛函以及线性矩阵不等式约束的形式，将协同式多目标自适应巡航（Adaptive cruise control, ACC）设计问题最终转化成带约束的在线凸二次规划问题