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Jingdong book

机器人控制系统的设计与MATLAB仿真（附光盘1张）

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Jingdong book

机器人控制系统的设计与MATLAB仿真（附光盘1张）

Name: 机器人控制系统的设计与MATLAB仿真（附光盘1张）
Brand: Jingdong book
SKU: 3118071721
Price: 51.44 USD
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《机器人控制系统的设计与MATLAB仿真》各部分内容既相互联系又各自独立，读者可根据需要选择学习。《机器人控制系统的设计与MATLAB仿真》适用于从事生产过程自动化、计算机应用、机械电子和电气自动化领域工作的工程技术人员阅读，也可作为大专院校工业自动化、自动控制、机械电子、自动化仪表、计算机应用等专业的教学参考书。

Content Description

本书系统地介绍了机器人控制的几种先进设计方法，是作者多年来从事机器人控制系统教学和科研工作的结晶，同时融入了国内外同行近年来所取得的新成果。

全书以机器人为对象，共分10章，包括先进PID控制、神经网络自适应控制、模糊自适应控制、迭代学习控制、反演控制、滑模控制、自适应鲁棒控制、系统辨识和路径规划。每种方法都给出了算法推导，实例分析和相应的MATLAB仿真设计程序。

本书各部佞内容既相互联系又各自独立，读者可根扭需要选择学习，本书适用于从事生产过程自动化、计算机应用、机械电子和电气自动化领域工作的工程技术人员阅读，也可作为大专院校工业自动化、自动控制、机械电子、自动化仪表、计算机应用等专业的数学参考书。

Author Description

刘金琨，辽宁人，1965年生。分别于1989年7月，1994年3月和1997年3月获东北大学工学学士，工学硕士和工学博士学位。1997年3月至1998年12月浙江大学工业控制技术研究所做博士后研究工作。1999年1月至1999年7月在香港科技大学从事合作研究。1999年11月至今在北京航空航天大学自动化学院从事教学与科研工作，现任教授，主讲《智能控制》、《工业过程控制》和《系统辨识》等课程。研究方向为控制与应用。自从事研究工作以来，主持国家自然基金等科研项目10余项，以第一作者发表学术论文70余篇。曾出版北京市高等教育精品教材《智能控制》，《先进PID控制及其MATLAB仿真》和《滑模变结构控制MATLAB仿真》等著作。

Catalogue

第1章绪论
1.1 机器人控制方法简介
1.1.1 机器人常用的控制方法
1.1.2 不确定机器人系统的控制
1.2 机器人动力学模型及其结构特性
1.3 基于S函数的SIMULINK仿真
1.3.1 S函数简介
1.3.2 S函数使用步骤
1.3.3 S函数的基本功能及重要参数设定
第2章机器人独立PD控制
2.1 机器人独立PD控制
2.1.1 控制律设计
2.1.2 收敛性分析
2.1.3 仿真实例
2.2 基于重力补偿的机器人PD控制
2.2.1 控制律设计
2.2.2 控制律分析
2.3 机器人鲁棒自适应PD控制
2.3.1 问题的提出
2.3.2 机器人动力学模型及其结构特性
2.3.3 控制器的设计
2.3.4 机器人动态方程的线性推导
2.3.5 仿真实例
参考文献
第3章机器人神经网络自适应控制
3.1 定理与引理
3.1.1 全局不变集定理
3.1.2 用Barbalat引理作类Lyapunov分析
3.1.3 一种微分方程不等式的收敛性分析
3.2 RBF网络的逼近
3.2.1 RBF神经网络
3.2.2 网络结构
3.2.3 逼近算法
3.2.4 参数对逼近效果的影响
3.2.5 仿真实例
3.3 基于模型不确定补偿的RBF网络机器人自适应控制
3.3.1 问题的提出
3.3.2 模型不确定部分的RBF网络逼近
3.3.3 控制器的设计
3.3.4 仿真实例
3.4 基于模型分块逼近的机器人RBF网络自适应控制
3.4.1 问题的提出
3.4.2 控制律的设计
3.4.3 稳定性分析
3.4.4 仿真实例
3.5 工作空间中机械手的神经网络自适应控制
3.5.1 工作究竟直角坐标与关节角位置的转换
3.5.2 机械手的神经网络建模
3.5.3 控制器的设计
3.5.4 仿真实例
3.6 基于模型整体逼近的机器人RBF网络自适应控制
3.6.1 问题的提出
3.6.2 基于RBF神经网络逼近的控制器
3.6.3 针对f(x)中各项分别进行神经网络逼近
3.6.4 仿真实例
3.7 基于死区补偿的神经网络自适应鲁棒控制
3.7.1 死区非线性特性
3.7.2 系统描述
3.7.3 GL矩阵和GL乘法算子
3.7.4 RBF神经网络死区补偿器的设计
3.7.5 系统的稳定性分析
3.7.6 仿真实例
3.8 机器人神经网络数字控制
……
第4章机器人模糊自适应控制
第5章机器人迭代学习控制及重复控制
第6章机器人反演控制
第7章机器人滑模控制
第8章机器人自适应鲁棒控制
第9章机器人参数观测、辨识及控制
第10章机器人路径规划

Book Abstract

第1章绪论

1.1 机器人控制方法简介

机器人学科是一门迅速发展的综合性前沿学科，受到工业界和学术界的调试重视。机器人的核心是机器人控制系统，从控制工程的角度来看，机器人是一个非线性和不确定性系统，机器人智能控制是近年来机器人控制领域研究的前沿课题，已取得了相当丰富的成果。

机器人轨迹跟踪控制系统的主要目的是通过给定各关节的驱动力矩，使得机器人的位置、速度等状态变量跟综给定的理想轨迹。

1.1.1 机器人常用的控制方法

常用的机器人控制方法有以下几种。

（1）基于模型的控制方法：与一般的机械系统一样，当机器人的结构及其机械参数确定后，其动态特性将由动力学方程即数学模型来描述。因此，可以采用自动控制理论所提供的设计方法，通过基于数学模型的方法设计机器人控制器。基于被控对象数学模型的控制方法有前馈补偿控制、计算力矩法、最优控制方法、非线性反馈控制方法等。但在实际工程中，由于机器人是一个非线性和不确定性系统，很难得到机器人精确的数学模型，使这些方法难以得到实际应用。

（2）PID控制：机器人控制常采用PD控制和PID控制，其优点是控制律简单，易于实现，无需建模，但这类方法有两个明显的缺点，一是难于保证受控机器人具有良好的动态和静态品质，二是需要较大的控制能量。

（3）自适应控制：自适应控制是根据要求的性能指标

……

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