
Introduction to Noise Filtering
Introduction to filtering - moving average, first-order, anti-aliasing, set point softening
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 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 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 MoreKalman 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 MoreKalman Filter Simulink 2022A example
This model is intended to help illustrate how a Kalman filter can estimate the state of a system. The "real system" is a nonlinear model of the Temperature Control Lab by Prof. John...
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 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 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 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 MoreMIMO Radar: TI Application Report
MIMO radar is a key technology in improving the angle resolution (spatial resolution) of mmwave-radars. This article introduces the basic principles of the MIMO-radar and the different...
See MoreVirtual Labs for control education
This resource provides different links to virtual and remote labs that can be used for control education. Virtual and remote labs are very powerful tools for learning and teaching, that...
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 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 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 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 MoreMATLAB Command: goodnessOfFit
Goodness of fit between test and reference data for analysis and validation of identified models
See MoreOutput Characterization to Linearize a Loop - Control valve application
This application paper explains how a control valve created nonlinearity in a loop and how output characterization solved the problem
See MoreAdaptive Control (Part II) —Modeling the X-15’s Adaptive Flight Control Syst...
This blog post shows how to build from scratch a Simulink model of the famous MH-96, the X-15's Adaptive Flight Control System
See MoreMATLAB Documentation page: nlarx command
This is the Mathworks documentation page for the nlarx MATLAB command.
See MoreUnderstanding Valve Flow Characteristics
The response of flow rate through a control valve depends on the friction losses in the piping in which it is installed as well as the controller signal. The installed characteristic (a...
See MoreRatio Control and Scaled Signal Calculations
When and how to use Ratio Control and use Scaled Signals
See MoreControl Loop Foundation Batch and Continuous Processes - Interactive Source ...
Control Loop Foundation contains workshops that allow the reader to get hands on experience through this web interface. Once a lab is selected, then you may access workshop directions and...
See MoreUse First-Principles Modeling to Get FOPDT Coefficient Values
Conventionally, we obtain model coefficient values by open-loop step-testing of the process; but this creates undesirable process upsets, and only reveals the local process behavior. This...
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