A New Approach to Linear Filtering and Prediction Problems

A transcription of R.E. Kalman's seminal paper. Transcribed by John Lukesh, 20 January 2002

The classical filtering and prediction problem is re-examined using the Bode- Shannon...

DC Motor Speed: System Modeling

This examples walks through modeling a simple DC motor in MATLAB.

TinyEKF: Lightweight C/C++ Extended Kalman Filter with Python for prototypin...

TinyEKF is a simple C/C++ implementation of the Extended Kalman Filter that is general enough to use on different projects. In order to make it practical for running on Arduino, STM32, and...

MATLAB Example: Online Recursive Least Squares Estimation

This example shows how to implement an online recursive least squares estimator. You estimate a nonlinear model of an internal combustion engine and use recursive least squares to detect...

A Tutorial on PES Pareto Methods for Analysis of Noise Propagation in Feedba...

This paper represents a tutorial on the so called PES Pareto methodology of analyzing the sources of noise in a feedback loop. Originally conceived for analyzing noise contributors in...

Guaranteed Margins for LQR Regulators

John Doyle's famous paper! He presents a counterexample that shows that are no guaranteed margins for LQG systems. 

MPCTools: Nonlinear Model Predictive Control Tools for CasADi (Python Interf...

This Python package is a collection of model predictive control tools that build on CasADi by providing a simpler interface. Along with the python package, there are a bunch of example files...

MATLAB Function: ztrans

ztrans(f) finds the Z-Transform of f. By default, the independent variable is n and the transformation variable is z. If f does not contain n, ztrans uses symvar. 

Algorithms for Automated Driving

Each chapter of this (mini-)book guides you in programming one important software component for automated driving. Currently, this book contains two chapters: Lane Detection, and Control...

MATLAB Example: Fault Detection Using an Extended Kalman Filter

This example shows how to use an extended Kalman filter for fault detection. The example uses an extended Kalman filter for online estimation of the friction of a simple DC motor...

Perspectives on Control-Relevant Identification Through the Use of Interacti...

This paper presents a control-relevant identification methodology through an intuitive interactive tool called "Interactive Tool for Control Relevant Identification (ITCRI)". ITCRI...

Model Reference Adaptive Control of Aircraft Undergoing Wing Rock

This example shows how to control roll and roll rate of a delta wing aircraft undergoing wing rock. For this example, the system model is unknown. Therefore, you use model reference adaptive...

Model predictive control python toolbox

do-mpc is a comprehensive open-source toolbox for robust model predictive control (MPC) and moving horizon estimation (MHE). do-mpc enables the efficient formulation and solution of control...

Manuscript about ITISE: an Interactive Software Tool for System Identificati...

The paper describes the conceptual basis, main features and functionality of an interactive software tool developed in support of system identification education and discovery.

This...

MATLAB Scripts for video "Linear System Identification | System Identificati...

This Github repo contains the data files and MATLAB scripts that were used in the MATLAB Tech Talk video "Linear System Identification | System Identification, Part 2" 

The Demod Squad: A Tutorial on the Utility and Methodologies for Using Modul...

This paper is a brief tutorial on methods for using modulated signals in feedback loops, and especially of the different methods and trade offs used for demodulating those signals to get...

Python Control Systems Library

The python-control package is a set of python classes and functions that implement common operations for the analysis and design of feedback control systems. The initial goal is to implement...

Benchmarking tools for a priori identifiability analysis

Recent review and benchmark of software tools that can be used for assess the structural identifiability of dynamical systems

Control Design Onramp with Simulink

Learn the basics of feedback control design in Simulink®. Adjust the gains of a PID controller to change the dynamics of a physical system and get the closed-loop system behavior that you...

Two Tank System: C MEX-File Modeling of Time-Continuous SISO System

This MATLAB example shows how to perform IDNLGREY modeling based on C MEX model files. It uses a simple system where nonlinear state space modeling really pays off.

Experimental evaluation of feedforward tuning rules

This paper presents a practical comparison for some of the most relevant tuning rules for feedforward compensators that have been published in the recent years. The work is focused on the...

Fast chirp FMCW Radar in automotive applications

FMCW (frequency-modulated continuous wave radar) modulations have been popularly implemented in the automotive radar applications. This document demonstrates system requirement for a new...

Jupyter Notebook: Code used to generate vibrational control of inverted pend...

Jupyter Notebook: Code used to generate vibrational control of inverted pendulum figures

Data based modeling of nonlinear dynamic systems using System Identification...

Using an engine throttle valve modeling example, this demo shares some perspectives on creation of nonlinear models of dynamic systems from the measurements of its input and outputs. It...

Feedforward tuning rules for measurable disturbances with PID control: a tut...

Feedforward control can be considered as the most well-known control approach to deal with measurable disturbances. It started to be used almost 100 years ago, and since then it is being...