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data-driven-robust-tracking-control-of-underactuated-mechanical-systems-using-identified-flat-output icon data-driven-robust-tracking-control-of-underactuated-mechanical-systems-using-identified-flat-output

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 …

datampc_parking icon datampc_parking

arXiv 2011.00413: (MATLAB Simulation) Collision Avoidance in Tightly-Constrained Environments without Coordination: a Hierarchical Control Approach.

dcm-imu icon dcm-imu

The DCM-IMU algorithm is designed for fusing low-cost triaxial MEMS gyroscope and accelerometer measurements. An extended Kalman filter is used to estimate attitude in direction cosine matrix (DCM) formation and gyroscope biases online. A variable measurement covariance method is implemented for acceleration measurements to ensure robustness against temporarily non-gravitational accelerations which usually induce errors to attitude estimate in ordinary IMU-algorithms. The code and data will be added after related scientific work is published and open source publication is approved.

dcsimsep icon dcsimsep

A DC load flow simulator of cascading (separation) in power systems

dct-tracking icon dct-tracking

Matlab code for the paper "Incremental learning of 3D-DCT compact representations for robust visual tracking. X. Li, A. Dick, C. Shen, A. van den Hengel, H. Wang. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2013."

ddea icon ddea

Dynamic Decomposition based Evolutionary Algorithm

ddea-se icon ddea-se

Offline data-driven evolutionary optimization using selective surrogate ensembles

ddsip icon ddsip

Dual Decomposition in Stochastic Integer Programming

deep-sensor icon deep-sensor

A deep learning framework for fault diagnositcs with PyTorch

deepmodel icon deepmodel

Code repository for Model-based Deep Hand Pose Estimation

deeprvea icon deeprvea

Creation of Deep Neural Network models based on data using RVEA

delta-mock icon delta-mock

Delta-MOCK algorithm for Evolutionary Multiobjective Clustering

dem_drone_in_wind icon dem_drone_in_wind

The Matlab code and the data-files for the paper: "Free Energy Principle for State and Input Estimation of a Quadcopter Flying in Wind"

demandresponsebookchapter4 icon demandresponsebookchapter4

This Repository contains the matlab codes to generate the figures in Chapter 4 of the book "Demand Response in Smart Grids".

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