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...

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...

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...

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...

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...

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...

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...

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.

Fixed-Point HDL-Optimized Minimum-Variance Distortionless-Response (MVDR) Be...

This example shows how to implement a fixed-point HDL-optimized minimum-variance distortionless-response (MVDR) beamformer in MATLAB.

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...

Algorithms to Antenna: Increasing Angular Resolution Using MIMO Radar

Articles in Microwaves & RF that talks about how forming virtual arrays with multiple-input, multiple-output waveforms makes it possible to generate more focused beam patterns.

The Institute for Systems Theory and Automatic Control MATLAB Apps

The Institute for Systems Theory and Automatic Control offers 5 Matlab Apps on the topics of the Nyquist Criterion, Robustness and Stability, Loopshaping, Controllability and Observability...

Creating Discrete-Time Models

This MATLAB example shows how to create discrete-time linear models using the tf, zpk, ss, and frd commands.

Thoughts on Furthering the Control Education of Practicing Engineers

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 to...

Nonlinear Model Identification

Mathwork overview page describing nonlinear model identification. Use nonlinear model identification when a linear model does not completely capture your system dynamics. You can identify...

Why Choose Model-Based Reinforcement Learning?

What is the difference between model-free and model-based reinforcement learning? Explore the differences and results as the learning models are applied to balancing a cart/pole system as an...

Guaranteed Margins for LQR Regulators

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

MATLAB Function: phased.MVDRBeamformer

The phased.MVDRBeamformer System object™ implements a narrowband minimum-variance distortionless-response (MVDR) beamformer. The MVDR beamformer is also called the Capon beamformer. An MVDR...

Using the Reinforcement Learning Toolbox™ to Balance an Inverted Pendulum

Reinforcement learning (RL) is a subset of Machine Learning that uses dynamic data, not static data like unsupervised learning or supervised learning. Reinforcement learning is used in many...

MIMO Radar: TI Application Report

MIMO radar is a key technology in improving the angle resolution (spatial resolution) of mmwave-radars. This article introduces the basic principles of the MIMO-radar and the different...