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...

System Identification: Theory for the User

From the Back Cover

The field's leading text, now completely updated. 

Modeling dynamical systems ― theory, methodology, and applications. 

Lennart Ljung's System Identification: Theory...

What Are Dynamic Models? Chapter 1 from Dynamic Models in Biology

Throughout this book we use a wide-ranging set of case studies to illustrate different aspects of models and modeling. In this introductory chapter we describe and give examples of different...

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...

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...

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...

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...

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.

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...

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...

Reinforcement Learning: An Introduction

From the book introduction:

The idea that we learn by interacting with our environment is probably the first to occur to us when we think about the nature of learning. When an infant plays...

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...

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...

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...

Averaging Methods in Nonlinear Dynamical Systems

Perturbation theory and in particular normal form theory has shown strong growth during the last decades. So it is not surprising that the authors have presented an extensive revision of the...

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

Feedback Systems: An Introduction for Scientists and Engineers

This is the wiki for the text Feedback Systems (second edition) by Karl J. Åström and Richard M. Murray. On this resource you will find the complete text of the book as well as additional...

MATLAB scripts for "Nonlinear System Identification | System Identification,...

This Github repo contains the data files and MATLAB scripts that were used in "Nonlinear System Identification | System Identification, Part 3".

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

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

Nonlinear Oscillations, Dynamical Systems, and Bifurcations of Vector Fields...

From the reviews: "This book is concerned with the application of methods from dynamical systems and bifurcation theories to the study of nonlinear oscillations. Chapter 1 provides a review...

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...