
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...
See MoreTinyEKF: 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...
See MoreAdvances in Feedforward Control for Measurable Disturbances (slides)
These slides present several contributions to improve the feedforward control approaches when inversion problem arise: the ideal compensator may not be realizable due to negative delay...
See MoreMPCTools: 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...
See MoreA 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...
See MoreMATLAB 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.
See MoreModel 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...
See MorePerspectives 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...
See MoreManuscript 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...
See MoreGuaranteed Margins for LQR Regulators
John Doyle's famous paper! He presents a counterexample that shows that are no guaranteed margins for LQG systems.
See MoreThe 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...
See MoreBenchmarking 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
See MoreTwo 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.
See MoreControl 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...
See MoreIntroduction to Radar Systems: Target Radar Cross Section
This course is presented by Robert M. O'Donnell, a former researcher at MIT Lincoln Laboratory, and is designed to instill a basic working knowledge of radar systems.
The set of 10 lectures...
See MoreKalman 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...
See MoreExperimental 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...
See MoreData 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...
See MoreVibrational 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...
See MoreRadar Systems Engineering Lecture 4: The Radar Equation
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...
See MoreFeedforward 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...
See MoreMATLAB 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".
See MoreMultifunction 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...
See MoreJupyter Notebook: Code used to generate vibrational control of inverted pend...
Jupyter Notebook: Code used to generate vibrational control of inverted pendulum figures
See MoreAveraging and Vibrational Control of Mechanical Systems
Abstract. This paper investigates averaging theory and oscillatory control for a large class of mechanical systems. A link between averaging and controllability theory is presented by...
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