Kalman Filter Design

This example shows how to perform Kalman filtering. Both a steady state filter and a time varying filter are designed and simulated.

Introducing 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...

Discrete 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...

Introducing 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...

Introduction to Noise Filtering

Introduction to filtering - moving average, first-order, anti-aliasing, set point softening

Perspectives 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...

Using 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...

A 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...

MATLAB 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...

Manuscript 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...

Road 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...

Algorithms 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.

Using 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...

MIMO 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...

Nonlinear 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...

TCLab 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...

Guaranteed Margins for LQR Regulators

John Doyle's famous paper! He presents a counterexample that shows that are no guaranteed margins for LQG systems. 

Thoughts 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...

Tuning PID Controllers

Tuning controllers is the procedure for choosing the coefficient values for the P, I and D modes.  It must be simple to execute, fast, and non-disruptive to the operating process.  Heuristic...

Decoding a Laplace Representation of a Controller

A how to relate the Laplace notation to the PID controller variation and features

Cascade Control

When and how to use Cascade Control

Multi-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...

MATLAB Command: goodnessOfFit

Goodness of fit between test and reference data for analysis and validation of identified models

PID Controller Variations

It is important to understand the variations on the PID algorithm when tuning and when choosing a version that is consistent within your use context.  Unfortunately, there are many names for...

Gain Scheduling (Pre-programmed Controller Parameter Adjustment)

Process gain and time-constants change with operating flow rate, tank levels, temperatures, etc.  This often requires re-tuning of the controller coefficient values.  However, once done...