
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 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 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 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 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 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 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 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 MoreFast 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...
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 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 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 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 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 MoreDealing with Non-Stationarity in Multi-Agent Deep Reinforcement Learning
From the abstract
Recent developments in deep reinforcement learning are concerned with creating decision-making agents which can perform well in various complex domains. A particular...
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 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 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...
See MoreMulti-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...
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 MoreMATLAB 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...
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 MorePython 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...
See MoreMATLAB 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"
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