
Kalman Filter Virtual Lab
The Kalman Filter virtual laboratory contains interactive exercises that let you study linear and extended Kalman filter design for state estimation of a simple pendulum system. The virtual...
See MoreInteractive Tool for PID understanding
The module PID Basics is designed to explore the properties of a simple feedback loop by showing the time and frequency responses of a closed-loop system and demonstrating how these...
See MoreIntroduction to Noise Filtering
Introduction to filtering - moving average, first-order, anti-aliasing, set point softening
See MoreITCLI: An Interactive Tool for Closed-Loop Identification
The Interactive Tool for Closed-Loop Identification (ITCLI) is an interactive software tool for understanding SISO closed-loop identification using prediction-error techniques. The tool...
See MoreZ-Transform - Practical Applications
Covering practical applications of the Z-transform used in digital signal processing, for example, stability analysis and frequency response of discrete-time systems. Theory, C code, and...
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 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 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 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 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 MoreRoad Sign Detection using Transfer Learning on RetinaNet
This blog outlines a number of open-source resources for transfer learning that are worthy of exploring, ands show the result of using transfer learning on RetinaNet to develop a road sign...
See MoreSimulating Test Signals for a Radar Receiver
This example shows how to simulate received signal of a monostatic pulse radar to estimate the target range. A monostatic radar has the transmitter collocated with the receiver. The...
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 MoreFixed-Point HDL-Optimized Minimum-Variance Distortionless-Response (MVDR) Be...
This example shows how to implement a fixed-point HDL-optimized minimum-variance distortionless-response (MVDR) beamformer in MATLAB.
See MoreUsing the Reinforcement Learning Toolbox™ to Balance an Inverted Pendulum
Reinforcement learning (RL) is a subset of Machine Learning that uses dynamic data, not static data like unsupervised learning or supervised learning. Reinforcement learning is used in many...
See MoreTwitter Thread: Vibrational control of mechanical systems
This Twitter thread by @ahmedallibhoy walks through an explanation of controlling an inverted pendulum with an open-loop vibrational controller.
See MoreAlgorithms for Automated Driving
Each chapter of this (mini-)book guides you in programming one important software component for automated driving. Currently, this book contains two chapters: Lane Detection, and Control...
See MoreMATLAB Example: Fault Detection Using an Extended Kalman Filter
This example shows how to use an extended Kalman filter for fault detection. The example uses an extended Kalman filter for online estimation of the friction of a simple DC motor...
See MoreThoughts on Furthering the Control Education of Practicing Engineers
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 to...
See MoreMATLAB Function: phased.MVDRBeamformer
The phased.MVDRBeamformer System object™ implements a narrowband minimum-variance distortionless-response (MVDR) beamformer. The MVDR beamformer is also called the Capon beamformer. An MVDR...
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 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 MoreMatlab Radar Designer App
The Radar Designer app is an interactive tool that assists engineers and system analysts with high-level design and assessment of radar systems at the early stage of radar development. Using...
See MoreConventional and Adaptive Beamformers
This example illustrates how to apply digital beamforming to a narrowband signal received by an antenna array. Three beamforming algorithms are illustrated: the phase shift beamformer...
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.
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