
Laplace domain – tutorial 5: Inverse Laplace transform
In this video, we cover inverse Laplace transform which enables us to travel back from Laplace to the time domain. We will learn how to use simple tricks alo...
See MorePeter Ponders PID. Second Order Plus Dead Time , SOPDT, Temperature Control,...
In this video I derive the equations for the controller gains and a low pass filter for a SOPDT system with a very long dead time To make the simulation mo...
See MoreFrequency domain – tutorial 3: filtering (periodic signals)
In this video, we learn about filtering which enables us to manipulate the frequency content of a signal. A common filtering application is to preserve desi...
See MorePeter Ponders PID - Tank Level Control
Cartesian, Polar, Cylindrical, and Spherical Coordinates
In this video we discuss Cartesian, Polar, Cylindrical, and Spherical coordinates as well as develop forward and reverse transformations to go from one coord...
See MoreTime domain - tutorial 6: elementary signals
In this video, we cover two elementary signals, unit step and unit impulse, which will be extensively used in this course. The following materials are covere...
See MorePeter Ponders PID - Why PID with 2nd Derivative Gain?
If you have ever tuned a hydraulic system and wondered why PID control didn't work better than PI control the answer is here. Since the 1980s people have kn...
See MoreFourier Series: Part 2
This video will show how to approximate a function with a Fourier series, which is an infinite sum of sines and cosines. We will discuss how these sines and cosines form a basis for the...
See MoreRouth-Hurwitz Criterion, Special Cases
This video presents two special cases that you can encounter when filling out the Routh Array. The first case is when there is a zero in a row with at least one non-zero element following...
See MoreUnderstanding and Sketching the Root Locus
In this video we discuss how to sketch the root locus for a system by developing a series of 5 core rules augmented by 5 supplemental rules (for a total of 1...
See MoreStanford CS234: Reinforcement Learning | Winter 2019 | Lecture 11 - Fast Rei...
Professor Emma Brunskill
Assistant Professor, Computer Science
Stanford AI for Human Impact Lab
Stanford Artificial Intelligence Lab
Statistical Machine Learning Group
What Is a Control System and Why Should I Care? (Part 2)
This talk gives a glimpse of some of the methods and math that allow us to understand feedback systems. Continuing on from Part 1, it gives a description of how we use scientific principles...
See MoreLecture 4: Electromechanical system Transfer functions and Analogous circuit...
Simulating the Lorenz System in Matlab
This video shows how simple it is to simulate dynamical systems, such as the Lorenz system, in Matlab, using ode45.
See MoreSVD and Optimal Truncation
This video describes how to truncate the singular value decomposition (SVD) for matrix approximation.
See MoreFuzzy Inference System Walkthrough | Fuzzy Logic Part 2
This video walks step-by-step through a fuzzy inference system. Learn about concepts like membership function shapes, fuzzy operators, multiple-input inference systems, and rule firing...
See MoreControl System with MATLAB - Block Diagram Reduction
The Frobenius Norm for Matrices
This video describes the Frobenius norm for matrices as related to the singular value decomposition (SVD).
See MoreStability of Closed Loop Control Systems
This video explains why we need design tools like the Routh-Hurwitz Criterion, Bode Plots, Nyquist Plots, and Root Locus. This is an introduction into the difficulties of determining the...
See MoreDesigning a Lag Compensator with Root Locus
This video walks through a phase lag compensator example using the Root Locus method.
See MoreControl Systems Lectures - Time and Frequency Domain
This lecture introduces the time and frequency domains. A very quick description of the Laplace Transform is given which will be the base of many of classical control lectures in the future...
See MoreRouth Stability Criterion Intro and Example
I introduce and walk through an example problem of how we can use the Routh Stability Criterion to rigorously determine the necessary and sufficient conditio...
See MoreReachability and Controllability with Cayley-Hamilton [Control Bootcamp]
Here we use the Cayley-Hamilton Theorem to show that the full state space is reachable if and only if the system is controllable.
See MoreIMC Design of an Unstable Process Example
In this video, I cover how we can use IMC method to rigorously design a controller for an inherently unstable process (has a positive pole).
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...
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