Zeroero1

Zeroero1's Stars

• ElhoumYassine/SMC-FDO

  Position control of a pendulum using sliding mode controller with finite time disturbance observer

  1

• attaoveisi/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.

  Language:MATLAB5416

• attaoveisi/Disturbance_observer

  In this note, disturbance rejection control (DRC) based on unknown input observation (UIO), and disturbance-observer based control (DOBC) methods are revisited for a class of MIMO systems with mismatch disturbance conditions. In both of these methods, the estimated disturbance is considered to be in the feedback channel. The disturbance term could represent either unknown mismatched signals penetrating the states, or unknown dynamics not captured in the modeling process, or physical parameter variations not accounted for in the mathematical model of the plant. Unlike the high-gain approaches and variable structure methods, a systematic synthesis of the state/disturbance observer-based controller is carried out. For this purpose, first, using a series of singular value decompositions, the linearized plant is transformed into disturbance-free and disturbance-dependent subsystems. Then, functional state reconstruction based on generalized detectability concept is proposed for the disturbance-free part. Then, a DRC based on quadratic stability theorem is employed to guarantee the performance of the closed-loop system. An important contribution offered in this article is the independence of the estimated disturbance from the control input which seem to be missing in the literature for disturbance decoupling problems. In the second method, DOBC is reconsidered with the aim of achieving a high level of robustness against modeling uncertainties and matched/mismatched disturbances, while at the same time retaining performance. Accordingly, unlike the first method, DRC, full information state observation is developed independent of the disturbance estimation. An advantage of such a combination is that disturbance estimation does not involve output derivatives. Finally, the case of systems with matched disturbances is presented as a corollary of the main results.

  Language:MATLAB256

• avionicscode/Robust-Attitude-Controller-for-UAV-Using-Dynamic-Inversion-and-Extended-State-Observer-controller

  A robust feedback linearization controller is presented for attitude control of an unmanned aerial vehicle (UAV). The objective of this controller is to make the roll angle, pitch angle, and yaw angle track the given trajectories(commands) respectively. This design is developed using dynamic inversion and extended state observer (ESO). Firstly, dynamic inversion is used to linearize and decouple UAV attitude system into three single-input-single-output (SISO) systems, then three proportional-derivative (PD) controllers are designed for these linearized systems. Extended state observers are used to estimate and compensate unmodeled dynamics and extent disturbances. Simulation results show that the proposed controller is effective and robust.

  Language:MATLAB6016

• cdbharath/super-twisting-SMC-quad

  Super Twisting Sliding Mode control for Quadrotor Fault Tolerance

  Language:MATLAB293

• ArduPilot/ardupilot

  ArduPlane, ArduCopter, ArduRover, ArduSub source

  Language:C++10.9k17.4k

• zengwangfa/Underwater-Vehicle

  ROV/AUV航行器控制中心 水下机器人（STM32 & Raspberry Pi）

  Language:C12543

• dorecasan/dual_arm_robot_rbf_terminal_smc

  Language:MATLAB51

• ponba-panda/6DOF-UUV

  NonLinear Controller Development based on the model ROV SF 32K

  Language:MATLAB3

• Ibrahim17Kose/uuv-pid-controller-design

  MATLAB/Simulink scripts and ROS/Gazebo packages for BlueROV2 Heavy manufactured by Blue Robotics

  Language:MATLAB3

• enricoande/Kaxan

  Files for trajectory control of the Kaxan ROV.

  Language:Matlab142

• nwilliterate/adaptive-fuzzy-sliding-mode-control

  adaptive fuzzy sliding mode control for robot manipulator

  Language:MATLAB667

• Fantasty9413/SMC-for-motor

  created a smc(sliding mode control) controller for a motor (for smc learning)

  Language:MATLAB6214

• Abner-fu/SMC

  滑模控制相关论文及仿真复现

  Language:MATLAB15

• JOU-UIP/A-recurrent-neural-network-based-fuzzy-sliding-mode-control-for-4-DOF-ROV-movements

  code

  Language:MATLAB111

• sathvikdivi/Thesis-AUV-Dynamics-and-Control

  Matlab codes for dynamics and control of underwater vehicle energy harvester

  Language:Matlab206

• VarunPwr/SMC-and-Fuzzy-logic-controller-for-AUV

  The repository has a matlab implementation of SMC based controller on an AUV.

  Language:Matlab194

• Badi96/Lagrangian-Neural-Networks-for-AUVs

  Using Lagrangian Neural Networks for system identification of a 6 Degree of Freedom Autonomous Underwater Vehicle (AUV)

  2

• iman-sharifi-ghb/Quadcopter-Trajectory-Tracking-using-Adaptive-Nonlinear-Algorithms

  PID, LQR, Feedback Linearization, Backstepping, Sliding Mode, and Model Reference Adaptive Control for 6-DoF Robot Control

  Language:MATLAB606

• Open-UAV/openuav-turbovnc

  Simulation environment for UAVs, ROVs and AUVs using Gazebo physics and Unity3D rendering.

  Language:QML4114

• MaciPaci/Simulation-of-Underactuated-AUV-Control-Algorithms

  MatLAB and Simulink simulation of different analytical methods of trajectory tracking and path following algorithms for Underactuated Autonomous Vehicles.

  Language:MATLAB706

• rock-control/control-orogen-auv_control

  Component-based structure for 6DOF AUV control

  Language:C++128

• chuanstudyup/AUV-Path-Following-Simulation

  A 3D path following simulation for autonomous underwater vehicle on Matlab/Simulink

  Language:MATLAB968

• adityaravichander/auv_lbf

  Lyapunov based controller design for trajectory tracking of an under-actuated autonomous underwater vehicle(AUV)

  Language:MATLAB397

• mathworks-robotics/modeling-and-simulation-of-an-AUV-in-Simulink

  This repository contains a variety of demonstration example models associated with the Design, Modeling and Simulation of Autonomous Underwater Vehicles webinar and video series.

  Language:MATLAB6831

• bareboat-necessities/wave_height_from_IMU

  Calculate sea wave height from IMU

  Language:Python51

• wartek69/SeaConditionMonitor

  A rpi based sea (wave) monitoring tool

  Language:Python3

• wattnotions/OpenWave

  Open Source Ocean Wave Sensor

  Language:MATLAB84