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...

Free Video Course in Radar Systems Engineering

This Free Radar Systems Engineering Course (video, audio and screen captured ppt slides) and separate pdf slides) has been developed as a first course in Radar Systems for first year...

Stanford Engineering Everywhere: CS223A - Introduction to Robotics

The purpose of this course is to introduce you to basics of modeling, design, planning, and control of robot systems. In essence, the material treated in this course is a brief survey of...

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...

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...

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...

Learning From Data

This is an introductory course in machine learning (ML) that covers the basic theory, algorithms, and applications. ML is a key technology in Big Data, and in many financial, medical...

Systems modeling and representations (French)

Complete course on systems modeling. Includes examples, MATLAB code, and quizzes.

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: 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. 

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...

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...

RADAR Engineering

Radar technology is used widely today. The principles involved are very fundamental and every engineering student studies them at least once. This playlist covers Radar Engineering for an EE...

Modelling, dynamics and control

How do we model the world around us and use this to understand its behaviour? How does behaviour depend upon the engineering choices we make and therefore how do we undertake design to...

Process Dynamics and Control Course

This course focuses on a complete start to finish process of physics-based modeling, data driven methods, and controller design. Although some knowledge of computer programming is required...

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...

MATLAB toolbox for control 101 course

Community toolbox project led by Anthony Rossiter and sponsored by MathWorks. The project incorporates input from various international collaborators. The aim is to make the developed...

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...

Multi-agent reinforcement learning: An overview

From the abstract:

Multi-agent systems can be used to address problems in a variety of do- mains, including robotics, distributed control, telecommunications, and economics. The complexity...

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.

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...

Kalman and Bayesian Filters in Python

Introductory text for Kalman and Bayesian filters. All code is written in Python, and the book itself is written using Juptyer Notebook so that you can run and modify the code in your...

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...

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...

No! Not Laplace Transforms

In my 13-year industrial career, I never used Laplace transforms.  However, transfer functions and block diagram notation are efficient methods to describe dynamic behaviors, and are often...