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...

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. 

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...

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. 

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...

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...

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...

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...

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".

Simulink Onramp

Learn the basics of how to create, edit, and simulate models in Simulink®. Use block diagrams to represent real-world systems and simulate components and algorithms.

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...

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" 

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...

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

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...

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...

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.

Multifunction Phased Array Radar (MPAR) for Aircraft and Weather Surveillanc...

MIT Lincoln Laboratory and M/A-COM are jointly conducting a technology demonstration of affordable Multifunction Phased Array Radar (MPAR) technology for Next Generation air traffic control...

Vibrational control of nonlinear systems: Vibrational controllability and tr...

In the first part of this work, the criteria for the existence of stabilizing parametric oscillations have been derived. In the present paper, the problem of choosing the stabilizing...