Robust Control Design with MATLAB® helps the student to learn how to use well-developed advanced robust control design methods in practical cases. To this end, several realistic control design examples from teaching-laboratory experiments, such as a two-wheeled, self-balancing robot, to complex systems like a flexible-link manipulator are given detailed presentation. All of these exercises are conducted using MATLAB® Robust Control Toolbox 3, Control System Toolbox and Simulink®.
2021-11-04 22:16:36 6.18MB Robust MATLAB
1
使用美团的Robust框架进行热更新,
2021-11-04 15:01:25 14.8MB 安卓 Robust 热更新
1
鲁棒抠图的一个小程序,由Jue Wang等人基于OpenCV开发。
2021-11-01 15:20:07 20.5MB mattin
1
cvpr2014 论文saliency optimization from robust background detection的代码
2021-10-29 18:12:33 363KB saliency detection
1
鲁棒控制工具箱提供了一系列的函数和工具以支持带有不确定元素的多输入多输出控制系统的设计。在该工具箱的帮助下,你可以建立带有不确定参数和动态特性的LTI模型,也可以分析MIMO系统的稳定性裕度和最坏情况下的性能。 该工具箱提供了一系列的控制器分析和综合函数,能够分析最坏情况下的性能及确定最坏情况下的参数值。利用模型降阶函数能够对复杂模型进行简化。同时提供了先进的鲁棒控制方法,如H2、H∞、LMI、μ分析等。
2021-10-28 01:33:47 364KB matlab 鲁棒控制
1
鲁棒控制
2021-10-27 22:48:38 1.82MB robust control
1
Robust Place Recognition using an Imaging Lidar.pdf
2021-10-25 10:47:31 3.63MB
1
matlab代码粒子群算法鲁棒粒子群优化RPSO 这是国防科学技术大学数学与系统科学系的博士生罗强写的一种用于RPSO的简单Matlab算法。 它对任何学术用户都是免费的,但是请注意,不能保证没有错误。 热烈欢迎对这种算法的理论或应用进行任何讨论。 如果您使用此代码,请引用以下文章: 罗强东怡鲁棒粒子群优化的共同发展框架。 应用数学与计算,2008,199(2):611-622。 如何使用? 核心算法在PSOed200.m中编码,从而最大程度地减少了给定的目标函数。 在此程序中已开发了四个算法(SPSO,LPSO,FPSP,RPSO),可以通过指定不同的AlgPara来调用。 myFun.m中已实现了许多目标功能。 如果要在程序中包含自己的目标函数,请简单地尝试将函数的代码添加到myFun.m中,作为“开关”的另一个“例”。 主要算法在runPSO.m中,其中显示了如何调用PSOed200的函数。 只需使用不同的参数调用PSOed200.m。 对应的电子邮件:
2021-10-16 21:38:51 38KB 系统开源
1
written by Aharon Ben-Tal Laurent El Ghaoui Arkadi Nemirovski Copyright © 2009 by Princeton University Press PART I. ROBUST LINEAR OPTIMIZATION 1 Chapter 1. Uncertain Linear Optimization Problems and their Robust Counterparts 3 1.1 Data Uncertainty in Linear Optimization 3 1.2 Uncertain Linear Problems and their Robust Counterparts 7 1.3 Tractability of Robust Counterparts 16 1.4 Non-Affine Perturbations 23 1.5 Exercises 25 1.6 Notes and Remarks 25 Chapter 2. Robust Counterpart Approximations of Scalar Chance Constraints 27 2.1 How to Specify an Uncertainty Set 27 2.2 Chance Constraints and their Safe Tractable Approximations 28 2.3 Safe Tractable Approximations of Scalar Chance Constraints: Basic Examples 31 2.4 Extensions 44 2.5 Exercises 60 2.6 Notes and Remarks 64 Chapter 3. Globalized Robust Counterparts of Uncertain LO Problems 67 3.1 Globalized Robust Counterpart — Motivation and Definition 67 3.2 Computational Tractability of GRC 69 3.3 Example: Synthesis of Antenna Arrays 70 3.4 Exercises 79 3.5 Notes and Remarks 79 Chapter 4. More on Safe Tractable Approximations of Scalar Chance Constraints 81 4.1 Robust Counterpart Representation of a Safe Convex Approximation to a Scalar Chance Constraint 81 4.2 Bernstein Approximation of a Chance Constraint 83 4.3 From Bernstein Approximation to Conditional Value at Risk and Back 90 4.4 Majorization 105 4.5 Beyond the Case of Independent Linear Perturbations 109 4.6 Exercises 136 4.7 Notes and Remarks 145 PART II. ROBUST CONIC OPTIMIZATION 147 Chapter 5. Uncertain Conic Optimization: The Concepts 149 5.1 Uncertain Conic Optimization: Preliminaries 149 5.2 Robust Counterpart of Uncertain Conic Problem: Tractability 151 5.3 Safe Tractable Approximations of RCs of Uncertain Conic Inequalities 153 5.4 Exercises 156 5.5 Notes and Remarks 157 Chapter 6. Uncertain Conic Quadratic Problems with Tractable RCs 159 6.1 A Generic Solvable Case: Scenario Uncertainty 159 6.2 Solvable Case I: Simple Interval Uncertainty 160 6.3 Solv
2021-10-15 11:35:36 10.76MB Robust Optimization SOCP LP
1
RobustVerilog Parser 1.2,RobustVerilog Parser 1.2,
2021-10-15 10:30:00 2.93MB RobustVerilog robust verilog
1