liuyuan0123 Goto Github PK
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My journal articles, conference presentations, class projects, and PhD dissertation from my graduate work at the University of Arizona.
Model Predictive Control of Adaptive Cruise Control Vehicles.
Reinforcment Learning - Actor and Critic is used for the control of a 4 reservoirs system
Adaptive MPC
AA277 Formation Control ADMM
Adversarial attacks in consensus-based multi-agent reinforcement learning
A short MATLAB code for Advection Diffusion Reaction PDEs in Time Domain
A project to implement the algorithms from Introduction to Algorithms (Cormen, Leiserson, Rivest, and Stein) in Python, Ruby and other programming languages.
An open autonomous driving platform
Code for implementing and experimenting with cooperative manipulation controllers. Includes a controller based on a novel extended relative Jacobian formulation.
Implementation of Attitude Optimal Backstepping Controller for UAV
Secure Privacy Preserving Average Consensus
A list of awesome Robotics resources
Computing Controlled Invariant Sets in Two Moves
Codes for the paper "Consensus Learning for Cooperative Multi-Agent Reinforcement Learning"
Collision Probability Calculation and Optimal Avoidance Control for Spacecraft.
textbook about control, robotics, system
Multi-robot coordination package based on coordination_oru with ROS support
Stable Gaussian Process based Tracking Control of Euler-Lagrange Systems
A reliable controller is critical for execution of safe and smooth maneuvers of an autonomous vehicle. The controller must be robust to external disturbances, such as road surface, weather, wind conditions, and so on. It also needs to deal with internal variations of vehicle sub-systems, including powertrain inefficiency, measurement errors, time delay, etc. These factors introduce issues in controller performance. In this paper, a feed-forward compensator is designed via a data-driven method to model and optimize the controller’s performance. Principal Component Analysis (PCA) is applied for extracting influential features, after which a Time Delay Neural Network is adopted to predict control errors over a future time horizon. Based on the predicted error, a feedforward compensator is then designed to improve control performance. Simulation results in different scenarios show that, with the help of with the proposed feedforward compensator, the maximum path tracking error and the steering wheel angle oscillation are improved by 44.4% and 26.7%, respectively.
This paper presents a data-driven control design framework to achieve robust tracking control without exploiting mathematical model of nonlinear underactuated mechanical systems (UMS). The method leverages the differential flatness property of linearized systems and online estimation and compensation of disturbances by active disturbance rejection control (ADRC). The differentially flat output is derived directly from measured data with unknown dynamics and parameters of UMS by the flat output identification (FOID) algorithm. A reduced nominal model of UMS is proposed to simplify the process of finding flat output and trajectory planning. Technique of sparse regression is applied to identify the relationships between flat output and system states, which reduces the order of the well-known extended state observer (ESO) and thereby make the ESO more effective for both trajectory planning and tracking in terms …
Implement simu for practce
Code to replicate experiments in paper
基于python的Django框架学生信息管理系统
Model-based design and verification for robotics.
A few simple tutorials for dynamical systems and control. Most require Matlab.
This repository contains the scripts for the Dynamic Trajectory Project
A declarative, efficient, and flexible JavaScript library for building user interfaces.
🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.
TypeScript is a superset of JavaScript that compiles to clean JavaScript output.
An Open Source Machine Learning Framework for Everyone
The Web framework for perfectionists with deadlines.
A PHP framework for web artisans
Bring data to life with SVG, Canvas and HTML. 📊📈🎉
JavaScript (JS) is a lightweight interpreted programming language with first-class functions.
Some thing interesting about web. New door for the world.
A server is a program made to process requests and deliver data to clients.
Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.
Some thing interesting about visualization, use data art
Some thing interesting about game, make everyone happy.
We are working to build community through open source technology. NB: members must have two-factor auth.
Open source projects and samples from Microsoft.
Google ❤️ Open Source for everyone.
Alibaba Open Source for everyone
Data-Driven Documents codes.
China tencent open source team.