
The Kalman Filter
This article introduces the Kalman filter at a high level and tries to provide some insight into how the filter is able to estimate state by combining measurements and models.
This is an...
See MoreHow a Kalman Filter Works in Pictures
This article builds up some intuition about the Kalman filter using pictures before diving into the mathematics. A beginner will come away with an understanding of what the Kalman filter is...
See MoreAn Introduction to the Kalman Filter
The purpose of this paper is to provide a practical introduction to the discrete Kalman filter. This introduction includes a description and some discussion of the basic discrete Kalman...
See MoreRadar Tutorial (English)
This page provides a detailed overview of radar principles and technologies, including mathematical, physical and technical explanations. “Radartutorial” explains the fundamentals of radar...
See MoreDiscrete Fourier Transform
The discrete Fourier transform, or DFT, is the primary tool of digital signal processing. The foundation of the product is the fast Fourier transform (FFT), a method for computing the DFT...
See MoreIntroducing Feedback Control to Middle and High School STEM Students, Part 1...
This paper was presented at the 2019 IFAC Advances on Control Education Conference (IFAC-ACE), Philadelphia, PA, USA, July 7-9, 2019, and is in the conference proceedings. This paper aims at...
See MoreWhat's a Control System and Why Should I Care? A whirlwind tour through the ...
This paper aims to provide some introduction, a cheat sheet, and some context for college level STEM students about to take that first controls class. In some cases, it provides context...
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 MoreSystem Identification Overview
System identification is a methodology for building mathematical models of dynamic systems using measurements of the input and output signals of the system. This overview from Mathworks...
See MoreKalman Filter Design
This example shows how to perform Kalman filtering. Both a steady state filter and a time varying filter are designed and simulated.
See MoreIntroduction: PID Controller Design
In this tutorial we will introduce a simple, yet versatile, feedback compensator structure: the Proportional-Integral-Derivative (PID) controller. The PID controller is widely employed...
See MoreIntroducing Feedback Control to Middle and High School STEM Students, Part 2...
This paper was presented at the 2019 IFAC Advances on Control Education Conference (IFAC-ACE), Philadelphia, PA, USA, July 7-9, 2019, and is in the conference proceedings. This paper aims at...
See MoreIntroduction to Noise Filtering
Introduction to filtering - moving average, first-order, anti-aliasing, set point softening
See MoreMATLAB Example: Solve Constrained Nonlinear Optimization, Problem-Based
This example shows how to find the minimum of a nonlinear objective function with a nonlinear constraint by using the problem-based approach.
See More3-DOF Orientation Tracking with IMUs
This document is not meant to be a comprehensive review of orientation tracking for virtual reality applications but rather an intuitive introduction to inertial measurement units (IMUs) and...
See MoreHow Kalman Filters Work, Part 1
This article looks at four popular estimation filter architectures: particle filter, sigma point filter, extended Kalman filter, and the Kalman filter. It discusses how all four of these...
See MoreNonlinear Model Identification
Mathwork overview page describing nonlinear model identification. Use nonlinear model identification when a linear model does not completely capture your system dynamics. You can identify...
See MoreTCLab PID Control
Implement a PID controller on the Temperature Control Lab hardware to drive the temperature from room temperature to 60 degrees C. This resource lets you attempt the design yourself first...
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 MoreAlgorithms to Antenna: Increasing Angular Resolution Using MIMO Radar
Articles in Microwaves & RF that talks about how forming virtual arrays with multiple-input, multiple-output waveforms makes it possible to generate more focused beam patterns.
See MoreMATLAB Example: Train MBPO Agent to Balance Cart-Pole System
This example shows how to train a model-based policy optimization (MBPO) agent to balance a cart-pole system modeled in MATLAB. For more information on MBPO agents, see Model-Based Policy...
See MoreUsing Simscape™ to Model a Quanser QUBE-Servo 2 with Friction
Modelling a DC servomotor is one of the common examples used in control system textbooks and courses. Given that so many systems use DC motors, e.g. robot manipulator arms, it’s an important...
See MoreIncreasing Angular Resolution with Virtual Arrays
This MATLAB example introduces how forming a virtual array in MIMO radars can help increase angular resolution. It shows how to simulate a coherent MIMO radar signal processing chain using...
See MoreHow Simulations Work
This article sets out the critical aspects of building good simulations — that is, simulations that are accurate, easy to develop and analyze, and fast. The first sections deal with how a...
See MoreRadar Systems Engineering MATLAB Documentation and Examples
The functions in this section give you the MATLAB tools needed to evaluate the performance of a radar system. You can use the radar equation to evaluate the radar received signal-to-noise...
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