Annika 's starred repositories
ego_planner_v2
适配XTDrone,完成ego_swarm_v2/ego_planner_v2的移植,并在树林环境中完成测试。
clash-for-linux
clash-for-linux
CurveFittingProgram
Implements the BFS and Hill-climbing algorithms to find the function f(x) using C++ for a given set of data
rpg_trajectory_evaluation
Toolbox for quantitative trajectory evaluation of VO/VIO
csdn_downloader
csdn下载,csdn免积分下载,csdn免会员下载,csdn付费内容下载 免费资源 体验地址:http://servicedev.tpddns.cn:8181/#/login?c=12
FMT-Firmware
Firmament Autopilot Embedded System
fixed_wing_formation_control
Fixed-Wing UAV Formation Controller Design and Implementation
px4_offboard_lowlevel
Low-level control of PX4 Multi-rotor vehicles in Offboard mode
t265_to_mavros
用于T265定点指点的功能包
mzlogin.github.io
Jekyll Themes / GitHub Pages 博客模板 / A template repository for Jekyll based blog
RungeKuttaCpp
A collection of explicit runge-kutta integrators, written in C++
mavsim_public
Repository for the textbook: Small Unmanned Aircraft: Theory and Practice, by Randy Beard and Tim McLain
CERLAB-UAV-Autonomy
[CMU] A Versatile and Modular Framework Designed for Autonomous Unmanned Aerial Vehicles [UAVs] (C++/ROS/PX4)
Missile-Guidance
Simulations of various missile Guidance Laws
SmartRockets
Rocket simulation with genetic algorithm for guidance. C++/SFML
-Aircraft-Pitch-System-Modeling-Analysis-and-Control-Design
An autopilot that controls the pitch of an aircraft.
shenlan_college_control_algorithm
深蓝学院控制规划课程控制部分课后作业代码,包括PID控制器、Stanley控制器、LQR控制器、MPC控制器。
AHU-AI-Repository
安徽大学人工智能学院资源仓库
ros_motion_planning
Motion planning and Navigation of AGV/AMR:ROS planner plugin implementation of A*, JPS, D*, LPA*, D* Lite, Theta*, RRT, RRT*, RRT-Connect, Informed RRT*, ACO, PSO, Voronoi, PID, LQR, MPC, DWA, APF, Pure Pursuit etc.
A-Particle-Swarm-Optimization-with-Adaptive-Learning-Weights-Tuned-by-A-Multiple-Input-Multiple-Outp
Source Code of MFCPSO; A Particle Swarm Optimization with Adaptive Learning Weights Tuned by A Multiple-Input Multiple-Output Fuzzy Logic Controller
Fuzzy_Self_Balancing_Vehicle
Implement Sugeno and Mamdani Fuzzy Rules for Adaptive Controller on a Two-wheeled Self-balancing Robot
AFISMC
a new observer-based adaptive fuzzy integral sliding mode controller (AFISMC) is proposed based on the Lyapunov stability theorem. The plant under study is subjected to a square-integrable disturbance and is assumed to have mismatch uncertainties both in state- and input-matrices. In addition, a norm-bounded time varying term is introduced to address the possible existence of un-modelled/nonlinear dynamics. Based on the classical sliding mode controller (SMC), the equivalent control effort is obtained to satisfy the sufficient requirement of SMC and then the control law is modified to guarantee the reachability of the system trajectory to the sliding manifold. The sliding surface is compensated based on the observed states in the form of linear matrix inequality (LMI). In order to relax the norm-bounded constrains on the control law and solve the chattering problem of SMC, a fuzzy logic (FL) inference mechanism is combined with the controller. An adaptive law is then introduced to tune the parameters of the fuzzy system on-line. Finally, by aiming at evaluating the validity of the controller and the robust performance of the closed-loop system, the proposed regulator is implemented on a real-time mechanical vibrating system.