Feedforward tuning rules for measurable disturbances with PID control: a tut...

Feedforward control can be considered as the most well-known control approach to deal with measurable disturbances. It started to be used almost 100 years ago, and since then it is being...

What are Polynomial Models?

This Mathworks page provides an overview of polynomial models. 

A Tutorial on PES Pareto Methods for Analysis of Noise Propagation in Feedba...

This is the recorded talk of the paper by the same title.

Understanding P, I, and D

Understanding what the proportional, integral, and derivative terms do within the PID controller is essential to choose appropriate action, trouble shoot controllers, chose appropriate...

System Identification: Regression Models

This lecture provides an overview of modern data-driven regression methods for linear and nonlinear system identification, based on the dynamic mode decomposition (DMD), Koopman theory, and...

Android and iPhone E-Learning App for Nyquist Stability Criterion

In our Nyquist App, you can analyze the stability of the closed loop by using the Nyquist stability criterion. With the Nyquist stability criterion, you can determine the stability of the...

Wind Tunnel Testing: Introduction and Data Acquisition

This is the first of our 3 part series on wind tunnel testing. In this video, we introduce the concept of wind tunnel testing as well as discuss the process for acquiring aerodynamic data in...

Automotive Radar MATLAB Documentation and Examples

MATLAB documentation and examples for probabilistic and physics-based radar sensor models, simulation of MIMO antennas, waveforms, I/Q radar signals, micro-Doppler signatures, detections...

Dealing with Non-Stationarity in Multi-Agent Deep Reinforcement Learning

From the abstract

Recent developments in deep reinforcement learning are concerned with creating decision-making agents which can perform well in various complex domains. A particular...

The Linear Quadratic Regulator (LQR)

Lecture notes for ECE717 on LQR control by Laurent Lessard. There is a section that shows how the Algebraic Riccati Equation is part of the LQR solution by "completing the square".

Adaptive Control (Part II) —Modeling the X-15’s Adaptive Flight Control Syst...

This blog post shows how to build from scratch a Simulink model of the famous MH-96, the X-15's Adaptive Flight Control System

What are Nonlinear ARX Models?

This Mathworks page provides an overview of Nonlinear ARX Models.Nonlinear ARX models extend the linear ARX models to the nonlinear case. The structure of these models enables you to model...

Advanced process control (APC): Theory & Applications in SAGD

This webinar is presented by Thiago Avila and covers what APC is, why we do it, examples of APC in the SAGD industry, what optimization opportunities are available, and where this technology...

Wind Tunnel Data Analysis and Testing Considerations

This is the last video in our 3 part series on wind tunnel testing. In this video, we discuss what typical plots of wind tunnel data might look like and how to extract relevant information...

Multi-agent reinforcement learning: An overview

From the abstract:

Multi-agent systems can be used to address problems in a variety of do- mains, including robotics, distributed control, telecommunications, and economics. The complexity...

Adaptive Control (Part I) — Hypersonics and the MIT Rule

This blog post introduces the algorithm that ruled the adaptive flight control system of the first manned hypersonic aircraft, the North American X-15.

Smart Projectile State Estimation Using Evidence Theory

This journal article provides a very good practical understanding of Dempster-Shafer theory using sensor fusion and state estimation as the backdrop.

The Navigation Equations: Computing Position North, East, and Down

In this video we show how to compute the inertial velocity of a rigid body in the vehicle-carried North, East, Down (NED) frame. This is achieved by rotating the velocity expressed in the...

Data-Driven Control: Change of Variables in Control Systems (Correction)

This video corrects a typo in the previous lecture.

Koopman Spectral Analysis (Multiscale systems)

In this video, we discuss recent applications of data-driven Koopman theory to multi-scale systems.

Stanford CS234: Reinforcement Learning | Winter 2019 | Lecture 10 - Policy G...

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

Manipulating 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.

Data-Driven Control: Observer Kalman Filter Identification

In this lecture, we introduce the observer Kalman filter identification (OKID) algorithm. OKID takes natural input--output data from a system and estimates the impulse response, for later...

Randomized SVD: Power Iterations and Oversampling

This video discusses the randomized SVD and how to make it more accurate with power iterations (multiple passes through the data matrix) and oversampling.

RL Course by David Silver - Lecture 1: Introduction to Reinforcement Learnin...

Introduces reinforcment learning (RL), an overview of agents and some classic RL problems.