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...

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...

Linear Algebra Review

This short course is a quick review of linear algebra, intended for students who have already taken a previous course in linear algebra or have some experience with vectors and matrices. The...

Interactive Tool for PID understanding

The module PID Basics is designed to explore the properties of a simple feedback loop by showing the time and frequency responses of a closed-loop system and demonstrating how these...

Kalman Filter Design

This example shows how to perform Kalman filtering. Both a steady state filter and a time varying filter are designed and simulated.

ITCLI: An Interactive Tool for Closed-Loop Identification

The Interactive Tool for Closed-Loop Identification (ITCLI) is an interactive software tool for understanding SISO closed-loop identification using prediction-error techniques. The tool...

Advances in feedforward control for measurable disturbances

The efficient compensation of load disturbances is one of the most important tasks in any control system. Most industrial processes are affected by disturbances and only feedback is commonly...

Z-Transform - Practical Applications

Covering practical applications of the Z-transform used in digital signal processing, for example, stability analysis and frequency response of discrete-time systems. Theory, C code, and...

Introducing Feedback Control to Middle and High School STEM Students, Part 2...

This paper was presented at the 2019 IFAC Advances on Control Education Conference (IFAC-ACE), Philadelphia, PA, USA, July 7-9, 2019, and is in the conference proceedings. This paper aims at...

Introduction to Noise Filtering

Introduction to filtering - moving average, first-order, anti-aliasing, set point softening

Kalman Filter Virtual Lab

The Kalman Filter virtual laboratory contains interactive exercises that let you study linear and extended Kalman filter design for state estimation of a simple pendulum system. The virtual...

Introducing Feedback Control to Middle and High School STEM Students, Part 1...

This paper was presented at the 2019 IFAC Advances on Control Education Conference (IFAC-ACE), Philadelphia, PA, USA, July 7-9, 2019, and is in the conference proceedings. This paper aims at...

Discrete Fourier Transform

The discrete Fourier transform, or DFT, is the primary tool of digital signal processing. The foundation of the product is the fast Fourier transform (FFT), a method for computing the DFT...

Simulating Test Signals for a Radar Receiver

This example shows how to simulate received signal of a monostatic pulse radar to estimate the target range. A monostatic radar has the transmitter collocated with the receiver. The...

Kalman Filter Simulink 2022A example

This model is intended to help illustrate how a Kalman filter can estimate the state of a system. The "real system" is a nonlinear model of the Temperature Control Lab by Prof. John...

TCLab PID Control

Implement a PID controller on the Temperature Control Lab hardware to drive the temperature from room temperature to 60 degrees C. This resource lets you attempt the design yourself first...

Advances in feedforward control for measurable disturbances (in Spanish)

The efficient compensation of load disturbances is one of the most important tasks in any control system. Most industrial processes are affected by disturbances and only feedback is commonly...

Koopman Spectral Analysis (Control)

In this video, we explore extensions of Koopman theory for control systems. Much of the excitement and promise of Koopman operator theory is centered around the ability to represent...

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...

Radar Systems Engineering MATLAB Documentation and Examples

The functions in this section give you the MATLAB tools needed to evaluate the performance of a radar system. You can use the radar equation to evaluate the radar received signal-to-noise...

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...

Virtual Labs for control education

This resource provides different links to virtual and remote labs that can be used for control education. Virtual and remote labs are very powerful tools for learning and teaching, that...

Data-Driven Dynamical Systems Overview

This video provides a high-level overview of this new series on data-driven dynamical systems. In particular, we explore the various challenges in modern dynamical systems, along with...

Various games for learning Controller Design

Since 2005, we are using educational games in the course „Einführung in die Regelungstechnik“ (Introduction to automatic control). 

The project started with the game spaceballRT, which uses...

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...