
Introduction 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 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 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 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 MoreOnline Tuning using Simulink’s Closed-Loop PID Autotuner Block
Learn how to conduct an online tuning of a PI-speed controller using the MATLAB/Simulink Closed-Loop PID Autotuner Block. Tuned controller is validated on a Quanser QLabs Virtual QUBE-Servo...
See MoreFOPDT Models from Skyline Inputs
The classic textbook method to generate FOPDT models is the reaction curve technique, a pre-computer era technique: Start from a steady state, make a step and hold in the controller output...
See MoreFeedforward Control
When a Ratio Control strategy takes action too soon, use Feedforward to temper the dynamics. When a disturbance can be measured, but would not be a ratio of the control output use...
See MoreMATLAB Documentation page: idLinear mapping object
This is the Mathworks documentation page for the idLinear mapping object.
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 MoreDSP Related
Website with a lot of good content for any DSP scientists, researchers, and developers.
See MoreProcess Control is Inventory Control
You change the inventory of heat to change temperature. You change the inventory of material to change level. Understanding how the inventory relates to the controlled variable is...
See MoreFeedforward Control
When and how to use Feedforward Control
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...
See MoreGain 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...
See MoreMin IAE Tuning
Procedure and Commentary on tuning for minimum Integral of the Absolute Error
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 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...
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