
Dynamic Modeling in Process Control
I'll show you how we can build the dynamic models necessary to derive process transfer functions as an introduction to process control.
See MoreData-Driven Control: Eigensystem Realization Algorithm Procedure
In this lecture, we describe the eigensystem realization algorithm (ERA) in detail, including step-by-step algorithmic instructions.
See MorePID Control - A brief introduction
In this video, I introduce the topic of PID control. This is a short introduction design to prepare you for the next few lectures where I will go through several examples of PID control....
See MoreStanford CS234: Reinforcement Learning | Winter 2019 | Lecture 3 - Model-Fr...
Professor Emma Brunskill
Assistant Professor, Computer Science
Stanford AI for Human Impact Lab
Stanford Artificial Intelligence Lab
Statistical Machine Learning Group
Equations of Motion for a Planar Vehicle
In this video we outline equations of motion for a simple planar vehicle. This model is suitable for vehicles such as boats or hovercraft that that are rest...
See MorePeter Ponders PID-Fuzzy Logic vs PID
There are many academic and engineering papers showing how good fuzzy logic control is relative to PID control. Every FL vs PID paper I have seen compares...
See MoreRL Course by David Silver - Lecture 4: Model-Free Prediction
An introduction to Monte-Carlo Learning and Temporal Difference Learning
See MoreUsing a Homogeneous Transformation Matrix to Combine Rotation and Translatio...
In this video we discuss how to properly deal with coordinate frames that are both rotated and translated from one another. We develop a homogeneous transfo...
See MorePeter Ponders PID - T0P1 Part 4, Misc Topics
This video covers another way to compute symbolic gains, the difference between having the P gain act on the error or just the feedback, extending bandwidt...
See MoreComputing the DFT Matrix
This video discusses how to compute the Discrete Fourier Transform (DFT) matrix in Matlab and Python. In practice, the DFT should usually be computed using the fast Fourier transform (FFT)...
See MoreRouth-Hurwitz Criterion, Beyond Stability
This video explains of few uses of the Routh-Hurwitz Criterion that go beyond simply determining how many poles exist in the right half plane. I cover how to determine gain margin and how...
See MoreThe Routh-Hurwitz Stability Criterion
In this video we explore the Routh Hurwitz Stability Criterion and investigate how it can be applied to control systems engineering. The Routh Hurwitz Stabi...
See MoreIdentifying Dominant Balance Physics from Data - Jared Callaham
This video illustrates a new algorithm to identify local dominant physical balance relations from multiscale spatiotemporal data.
See MoreRelationship Between Poles and Performance of a Dynamic System
In this video we establish the relationship between pole locations and associated performance of a dynamic system. This relationship is useful to translate ...
See MoreLinear Systems of Equations
This video describes linear systems of equations and when they have solutions.
See MoreLaplace domain – tutorial 2: Region of Convergence (ROC)
In this video, we learn five golden rules on how to quickly find the Region of Convergence (ROC) of Laplace transform. Learn Signal Processing 101 in 31 lect...
See MoreTime domain - tutorial 11: system properties from impulse response
In this video, we learn how to find system properties from the impulse response. Specifically, memoryless, causal, stable and invertible systems will be ful...
See MorePID Control with Posicast, 9 - (In English)
This is part III of PID control with Posicast
See MoreControl Systems Lectures - LTI Systems
This lecture describes what it means when we say a system is linear and time invariant. I also try to give an example as to why these systems are so important when designing control systems...
See MoreManipulating Aerodynamic Coefficients
In this video we discuss some potential problems you may encounter when attempting to perform operations with dimensionless aerodynamic coefficients such as CL and CD.
See MoreTime domain - tutorial 2: signal representation
In this video, we review how to represent information as a signal. The information can be anything such as voice (1D) or an image (2D) or even a video (3D). ...
See MoreTuning a Fuzzy Logic Controller with Data | Fuzzy Logic, Part 4
This video covers the basics of data-driven approaches to tuning fuzzy inference systems. See what it means to find an optimal solution, which fuzzy inference parameters are being tuned...
See MoreInternal Model Control Example Problem
I walk through how to design a feedback controller based on a given process transfer function, using Internal Model Control.
See MoreBode Plots by Hand: Real Poles or Zeros
This is a continuation of the Control Systems Lectures. This video describes the benefit of being able to approximate a Bode plot by hand and explains what a Bode plot looks like for a...
See MoreDirect Synthesis Method Numerator Dynamics Problem
I walk through how to design a PID feedback controller when given a second order process with numerator dynamics, using the Direct Synthesis Method.
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