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Control Systems in Practice, Part 10: Nichols Chart, Nyquist Plot, and Bode ...
Explore three popular methods to visualize the frequency response of a linear time-invariant (LTI) system: the Nichols chart, the Nyquist plot, and the Bode plot. Learn about each method...
See MoreUnderstanding PID Control, Part 7: Important PID Concepts
Now that you ’ve gotten an overview of PID tuning techniques, this video moves on to discussing two important concepts in PID control: cascaded loops and discrete systems. Both concepts are...
See MoreAn introduction to Beamforming
This video talks about how we actually have more control over the shape of the beam than just adding additional elements, or adjusting the position and orientation of the elements. We can...
See MoreReinforcement Learning for Engineers, Part 4: The Walking Robot Problem
This video shows how to use the reinforcement learning workflow to get a bipedal robot to walk. It also looks at how to modify the default example to make it look more like how one would set...
See MoreUnderstanding 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...
See MoreRadar Tutorial (English)
This page provides a detailed overview of radar principles and technologies, including mathematical, physical and technical explanations. “Radartutorial” explains the fundamentals of radar...
See MoreStanford Engineering Everywhere: CS223A - Introduction to Robotics
The purpose of this course is to introduce you to basics of modeling, design, planning, and control of robot systems. In essence, the material treated in this course is a brief survey of...
See MoreAutonomous Navigation, Part 2: Understanding the Particle Filter
This video presents a high-level understanding of the particle filter and shows how it can be used in Monte Carlo localization to determine the pose of a mobile robot inside a building. We...
See MoreFree Video Course in Radar Systems Engineering
This Free Radar Systems Engineering Course (video, audio and screen captured ppt slides) and separate pdf slides) has been developed as a first course in Radar Systems for first year...
See MoreAn Introduction to the Kalman Filter
The purpose of this paper is to provide a practical introduction to the discrete Kalman filter. This introduction includes a description and some discussion of the basic discrete Kalman...
See MoreControl Systems in Practice, Part 9: The Step Response
This video covers a few interesting things about the step response. We’ll look at what a step response is and some of the ways it can be used to specify design requirements for closed loop...
See MoreKalman Filter Virtual Lab
The Kalman Filter virtual laboratory contains interactive exercises that let you study linear and extended Kalman filter design for state estimation of a simple pendulum system. The virtual...
See MoreITCLI: An Interactive Tool for Closed-Loop Identification
The Interactive Tool for Closed-Loop Identification (ITCLI) is an interactive software tool for understanding SISO closed-loop identification using prediction-error techniques. The tool...
See MoreModeling Physical Systems, An Overview
This video sets the stage for the topics that I want to cover over the next month or two. This is an overview of how you go from a physical system to a linear model where you can design a...
See MoreIntroduction to Noise Filtering
Introduction to filtering - moving average, first-order, anti-aliasing, set point softening
See MoreThe AVA Flight Computer
This video describes the board design, hardware architecture, and software components of the All Vehicle Avionics (AVA) flight computer that was designed by Joe Barnard of BPS Space. This...
See MoreUnderstanding PID Control, Part 6: Manual and Automatic Tuning Methods
The previous video showed three different approaches to developing a mathematical model of your physical system. Now that we have this model, we can use it to tune a PID controller that will...
See MoreLinear Algebra Review
This short course is a quick review of linear algebra, intended for students who have already taken a previous course in linear algebra or have some experience with vectors and matrices. The...
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 MoreZ-Transform - Practical Applications
Covering practical applications of the Z-transform used in digital signal processing, for example, stability analysis and frequency response of discrete-time systems. Theory, C code, and...
See MoreReinforcement Learning for Engineers, Part 3: Policies and Learning Algorith...
This video provides an introduction to the algorithms that reside within the agent. We’ll cover why we use neural networks to represent functions and why you may have to set up two neural...
See MoreAutonomous Navigation, Part 4: Path Planning with A* and RRT
This video explores some of the ways that we can use a map like a binary occupancy grid for motion and path planning. We briefly cover what motion planning means and how we can use a graph...
See MoreWhat Are Dynamic Models? Chapter 1 from Dynamic Models in Biology
Throughout this book we use a wide-ranging set of case studies to illustrate different aspects of models and modeling. In this introductory chapter we describe and give examples of different...
See MoreSystem Identification Methods
System Identification is the process of determining the model or the equations of motion for your system. This is incredibly important because basing a control system design off of a bad...
See MoreUnderstanding Kalman Filters, Part 4: An Optimal State Estimator Algorithm
Discover the set of equations you need to implement a Kalman filter algorithm. You’ll learn how to perform the prediction and update steps of the Kalman filter algorithm, and you’ll see how...
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