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Function-Approximation-and-Adaptive-PID-Gain-Tuning-using-Neural-Networks-and-Reinforcement-Learning
System Identification and Self-Tuning PID Control using NN6-Dof-Robot-Trajectory-Tracking-using-Adaptive-Nonlinear-Algorithms
PID, LQR, Feedback Linearization, Backstepping, Sliding Mode, and Model Reference Adaptive Control for 6-DoF Robot ControlTrajectory-Tracking-of-8DOF-Robot-via-Fuzzy-Sliding-Mode-Control-with-Fuzzy-Identification
Tiltrotor Control and System Identification using Fuzzy C-Means Clustering.Self-Tuning-PID-Control-using-Reinforcement-Learning-Based-Neural-Network
Novel adaptive tuning of the PID gains using an Actor-Critic-based Neural Network for Attitude Control of a 6-Dof, 4-motor RobotPID-Tuning-using-Genetic-and-Particle-Swarm-Optimization
Offline Tuning PID gains in a given system using Heuristic Methods, including Genetic Algorithm andParticle Swarm OptimizationVideo-Synopsis-Summarization-Car-Detection-Tracking
Detection, Counting, Tracking, and Summarization of the Vehicles using Computer Vision algorithms in a video camera recorded on a highway.6DoF-Robot-PID-Control-in-V-REP
Control Quadcopter using PID Controller in Vrep CoppeliaSim Software with PythonInverted-Pendulum-Control-using-state-feedback-Controller-and-observer
Camera-Operations-Homography-and-Fundamental-Matrix-Using-SIFT-KNN-RANSAC-Algorithms
SIFT, SURF, and ORB detector to extract the keypoints like corners. Fundumental Matrix and Homographical Transformation for Panorama Images.Inductive-Logic-Programming-ILP-using-Prolog-Programming-Aleph-Metagol-in-Maze
Extract Symbolic Rules using Background Knowledge and Environement Setting to find the State Transition rules in the Maze gridworld.Histogram-Oriented-Gradients-HOG-Supported-Vector-Machine-SVM-Face-Detection
Extract features from the Stanford Dataset using Histogram of Oriented Gradients (HOG) and use Supported Vector Machine (SVM) to map the features to the assigned labels. Next, use Non-Maximum Suppression and Heatmap method to find the best bounding box on the face.Simulation-of-3DOF-Manipulator-on-6DoF-Cube-body-using-Newtonian-Lagrangian-and-Quaternions-Methods
Double-Inverted-Pendulums-Control-Using-State-Feedback
Modeling-Simulation-Design-and-Fabrication-of-2-wheel-mobile-balanced-robot-2WMBR
Modeling a Mobile Robot using Advanced Dynamics Methods, Design & Simulation using Matlab and SolidWorks, Control using PID Controller, and Implemetation using Arduino UNO, Kalman Filter, and DC Motors..Retrospective-Cost-Adaptive-Controller-using-Recursive-Least-Square
CNN-Street-View-House-Number-Detection-SVHN
We use Convelutional Neural Networks (CNN), as a Deep Learning paradigm, to detect the house numbers using the MNIST dataset.Symbolic-Reinforcement-Learning-Prolog-Programming
Safe Q-Learning via a Symbolic Logical Programming (Prolog) paradigm in Maze Gridworld.Awesome-Fuzzy-Systems
Lets practice some fuzzy examples according to Wong's Book, including Gradient Descend Algorithm, Recursive Least Square, ...Love Open Source and this site? Check out how you can help us