Vector Derivatives (the Equation of Coriolis) and the Angular Velocity Vecto...

In this video we develop the Equation of Coriolis which describes how a vector in a rotating reference frame changes from the perspective of an observer in a non-rotating reference frame. We...

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Lecture 29: State space representation

This video explains how a system can be modelled in state space form. Also shown is how to obtain transfer function from State space form See More

Time 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). ...

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Cascade Control

When and how to use cascade

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Cascade Control Intro

How can we improve the disturbance rejection of our controllers using additional, relevant measurements? Tune in to find out!

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Lecture 19: Lead and PD compensator Design using Root Locus

This video discusses how a Proportional Derivative [PD] controller and a Lead compensator can be designed using Root Locus See More

Laplace domain – tutorial 6: Transfer function & system properties

In this video, we learn about transfer function and system properties. The following materials are covered:1) what is a transfer function?2) relation between...

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Peter 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...

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Understanding PID Control, Part 3: Expanding Beyond a Simple Derivative

This video describes how to make an ideal PID controller more robust when controlling real systems that don’t behave like ideal linear models. Noise is generated by sensors and is present in...

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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.

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Lecture 14: Routh Hurwitz Criterion

Special cases in Routh Hurwitz criterion i.e (1) a row with only first entry being zero and (2) A row with all entries zero are considered. The video of a pr... See More

Stanford CS234: Reinforcement Learning | Winter 2019 | Lecture 16 - Monte Ca...

Professor Emma Brunskill
Assistant Professor, Computer Science
Stanford AI for Human Impact Lab
Stanford Artificial Intelligence Lab
Statistical Machine Learning Group

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Peter 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...

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RL Course by David Silver - Lecture 4: Model-Free Prediction

An introduction to Monte-Carlo Learning and Temporal Difference Learning

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Peter Ponders PID - Root Locus Is Useless

Root Locus is almost worthless. Knowing where the poles are as only 1 gain is changed is not very useful since one only has a limited choices on response. ... See More

Robotic Car, Closed Loop Control Example

I demonstrate the value of closed loop control in an uncertain environment using my Zumo Robot car. If you're interested in building one yourself and trying this out I think I've given you...

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The Taylor Series

In this video we discuss the Taylor Series (and the closely related Maclaurin Series). These are two specific types of Power Series that allow you to approx...

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Singular Value Decomposition (SVD): Dominant Correlations

This lectures discusses how the SVD captures dominant correlations in a matrix of data.

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TikZ source Code: Feedforward passivity index

TikZ source Code: Feedforward passivity index

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Understanding Sensor Fusion and Tracking, Part 1: What Is Sensor Fusion?

This video provides an overview of what sensor fusion is and how it helps in the design of autonomous systems. It also covers a few scenarios that illustrate the various ways that sensor...

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Data-Driven Control: Eigensystem Realization Algorithm

In this lecture, we introduce the eigensystem realization algorithm (ERA), which is a purely data-driven algorithm to obtain balanced input—output models from impulse response data. ERA was...

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SVD: Image Compression [Python]

This video describes how to use the singular value decomposition (SVD) for image compression in Python.

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TikZ source Code: Mobile Robot Slip

TikZ source Code: Mobile Robot Slip

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Sliding Mode Control Design for Mass-Spring-Damper System

This MATLAB/Simulink example describes the fundamentals of sliding mode control (SMC) and uses SMC to control a mass-spring-damper system.

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Linear Regression 1 [Python]

This video describes how the singular value decomposition (SVD) can be used for linear regression in Python (part 1).

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