The MRSim (Multi-Robot Simulator) is an extension of the Autonomous mobile robotics toolbox SIMROBOT (SIMulated ROBOTs) created for MatLab 5 in 2001. MRSim allows the user to simulate the behavior of multiple mobile robots in virtual environments. When compared to its predecessor SIMROBOT, MRSim presents two key contributions: 1) It is fitted to the new MatLab versions - Previously, users were unable to work with SIMROBOT functions since most of them were incompatible with the new MatLab versions. MatLab significantly evolved over the last 10 years, making SIMROBOT obsolete. In this extension, all features of SIMROBOT were updated and improved based on the new MatLab functions; 2)It is also fitted to suit multi-robot applications - although SIMROBOT was endowed with various interesting features for mobile robotics, it presented several limitations for multi-robot applications. Therefore, MRSim was created primarily to allow users to develop multi-robot applications, which would benefit working with some specific requirements such as multi-hop communication. Moreover, most of the functionalities in MRSim have an integrated help (which can be accessed just by typing help function) that allows to easily understand the dynamics of how to create and run simulations. In sum, just like SIMROBOT, each robot in MRSim can be equipped with several virtual sensors and can be driven by its own control algorithm. The toolbox includes two independent applications. The first one is the EDITOR (simedit), which allows the user to create and modify the virtual environment,to edit the control algorithms of robots, to load and save simulation, and others. The second application, SIMULATOR (simview), can be run directly from the EDITOR or separately from MatLab Command Window and serves as a simulation viewer. A MatLab help file is being currently created and will be add in the future.

本书主要论述了移动机器人导航系统和路径跟踪控制算法的设计方法。首先，基于常用的 移动机器人导航系统的原理、所选用的民用单频GPS接收机数据的特点和航迹推算导航系统 数据的特点，提出了三种GPS和航迹推算导航综合导航系统信息融合算法。这些算法利用 GPS与航迹推算导航系统具有互补的特性，在解算负担小的基础上，能够很好地融合民用单频 GPS接收机和航迹推算系统的导航信息，为室外移动机器人提供长期稳定、准确的导航信息。 其次，介绍了移动机器人路径规划应用的蚁群算法。针对传统蚁群算法容易陷入早熟、收敛速 度慢和生成路径转折多等问题，提出了相应的改进措施。改进后的蚁群算法在提高搜索速度的 基础上，扩大了搜索范围，并且能够提供转折较少的路径。最后，基于模型算法控制方法和神经 网络的模型算法控制方法为移动机器人设计了路径跟踪控制算法。

针对水下机器人轨迹跟踪控制的速度跳变问题,提出了一种基于生物启发神经动力学模型的自治水下机器人(AUV)三维轨迹跟踪控制算法。利用生物启发神经动力学模型的平滑、有界输出的特性,构造简单的中间虚拟变量,克服了海流影响下AUV反步轨迹跟踪控制的速度跳变问题,并且控制效果能够达到全局渐近稳定、输出结果连续平滑。利用Lyapunov函数证明了所提方法的稳定性。将该方法对“海筝二号”水下机器人进行三维轨迹跟踪控制的仿真实验,仿真结果表明了所提控制方法的有效性。

使用PX4:registered:自动驾驶仪的UAV工具箱支持包，您可以从MATLAB:registered:和Simulink:registered:访问自动驾驶仪外围设备。 借助EmbeddedCoder:registered:，您还可以自动生成C ++代码并使用PX4工具链来构建和部署专门为Pixhawk:registered:和Pixracer飞行管理单元（FMU）量身定制的算法，同时结合机载传感器数据和其他PX4特定服务。 PX4是Lorenz Meier的商标。

C语言用于dsp运动控制PID算法 改程序经过验证 好用的

PID是一个闭环控制算法。因此要实现PID算法，必须在硬件上具有闭环控制，就是得有反馈。比如控制一个电机的转速，就得有一个测量转速的传感器，并将结果反馈到控制路线上，下面也将以转速控制为例。

经典模糊控制法，详细实用C程序子函数，只需要调用就可以了，用于恒温控制等决对管用。

要想更好的了解TCP端到端拥塞控制机制，首先要学习端到端拥塞控制的4个基本也是最主要的算法:slow_start, congestion avoidance, fast retransmit, fast recovery。

PID控制算法的C语言实现（附代码）经典控制算法PID，通熟易懂，入门必备

本文探讨了液压伺服系统的模糊自整定PID控制方法，同时利用MATLAB软件提供的Simulink和Fuzzy工具箱对液压伺服调节系统的模糊自整定PID控制系统进行仿真，并与常规PID控制进行了比较。