
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.
See MoreIntroduction to Noise Filtering
Introduction to filtering - moving average, first-order, anti-aliasing, set point softening
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 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 MoreImproving the Beginner's PID - Introduction
In conjunction with the release of the new Arduino PID Library Brett has released this series of posts that explain his PID code. He start's with what he call's “The Beginner’s PID.” He...
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 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 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 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 MorePost-Pandemic: A Hybrid Lab Experience
This article discusses the importance of a hybrid laboratory model, blending physical hardware with digital twins. Example using the Quanser Interactive Lab (QLabs) platform is given.
See MoreMin IAE Tuning
Procedure and Commentary on tuning for minimum Integral of the Absolute Error
See MoreTuning 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...
See MoreDecoding a Laplace Representation of a Controller
A how to relate the Laplace notation to the PID controller variation and features
See MoreRatio Control and Scaled Signal Calculations
When and how to use Ratio Control and use Scaled Signals
See MorePID 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...
See MoreIntegral Wind-Up and Solution
What is integral wind-up and how velocity mode solves it.
See MoreMATLAB Command: goodnessOfFit
Goodness of fit between test and reference data for analysis and validation of identified models
See MoreCohen-Coon Tuning
A procedure and commentary on this tuning approach that includes deadtime.
See MoreOverride and Reset Feedback
Override controllers are for safety or switching to auxiliary variables. The non-selected controller needs to prevent becoming wound up.
See MoreMATLAB function: phased.LCMVBeamformer
The phased.LCMVBeamformer object implements a narrowband linear-constraint minimum-variance (LCMV) beamformer for a sensor array. The LCMV beamformer belongs to the family of constrained...
See MoreControl Valve Problems
Control valve problems can severely affect control loop performance and, unless eliminated, they can make controller tuning a challenging (sometimes impossible) task. Some problems are quite...
See MoreCascade Control
When and how to use Cascade Control
See MoreNonlinear Control Output Signal Characterization
If the process gain makes large changes over the operating range, then tuning PID (or other linear) controllers is difficult. If tuned for one region, the controller is undesirably sluggish...
See MoreBumpless Transfer and Tuning
Switching from MAN to AUTO mode or LOCAL to CASCADE or changing the controller integral time should not cause a change in the controller output, a bump. But a primitive coding of the PID...
See MoreIntroduction to the A* Algorithm
An interactive visual explanation of the A* algorithm using motivating examples from computer games.
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