
Feedforward Control
When a Ratio Control strategy takes action too soon, use Feedforward to temper the dynamics. When a disturbance can be measured, but would not be a ratio of the control output use...
See MoreLearning Dynamic Systems & Control Engineering with a Video Game
Engineering Students at Northern Illinois University are learning one of their core subjects, Dynamic Systems & Control, with the aid of a video game.
See MoreRatio Control and Scaled Signal Calculations
When and how to use Ratio Control and use Scaled Signals
See MoreTwo Tank System: C MEX-File Modeling of Time-Continuous SISO System
This MATLAB example shows how to perform IDNLGREY modeling based on C MEX model files. It uses a simple system where nonlinear state space modeling really pays off.
See MoreMultifunction Phased Array Radar (MPAR) for Aircraft and Weather Surveillanc...
MIT Lincoln Laboratory and M/A-COM are jointly conducting a technology demonstration of affordable Multifunction Phased Array Radar (MPAR) technology for Next Generation air traffic control...
See MoreMin IAE Tuning
Procedure and Commentary on tuning for minimum Integral of the Absolute Error
See MoreAdaptive 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
See MoreWhy the Riccati Equation Is important for LQR Control
This Tech Talk looks at an optimal controller called linear quadratic regulator, or LQR, and shows why the Riccati equation plays such an important role in solving it efficiently. The talk...
See MoreMATLAB Command: resid
This MATLAB command is part of the system identification toolbox and provides a way to compute and test residuals.
See MoreMATLAB Example: Train Multiple Agents for Area Coverage
This example demonstrates a multi-agent collaborative-competitive task in which you train three proximal policy optimization (PPO) agents to explore all areas within a grid-world environment...
See MoreSystem Identification: Full-State Models with Control
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...
See MoreInteractive Tool for Loop Shaping understanding based on PID control
Loop shaping is a design method where it is attempted to choose a controller such that the loop transfer function obtains the desired shape. In this module the loop transfer function is...
See MoreUnderstanding Valve Flow Characteristics
The response of flow rate through a control valve depends on the friction losses in the piping in which it is installed as well as the controller signal. The installed characteristic (a...
See MoreDecoding a Laplace Representation of a Controller
A how to relate the Laplace notation to the PID controller variation and features
See MoreFirst Order Plus Dead Time Tuning App for PI Controllers
The FOPTD_PI Tool is a Matlab-Interactive tuning tool of PI controllers for First Order PlusTime Delay processes. It can be used to teach basic control concepts based on a set of PI tuning...
See MoreMATLAB scripts for "Nonlinear System Identification | System Identification,...
This Github repo contains the data files and MATLAB scripts that were used in "Nonlinear System Identification | System Identification, Part 3".
See MoreAutomotive 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...
See MoreAveraging Methods in Nonlinear Dynamical Systems
Perturbation theory and in particular normal form theory has shown strong growth during the last decades. So it is not surprising that the authors have presented an extensive revision of the...
See MoreLinear Regression 2 [Python]
This video describes how the singular value decomposition (SVD) can be used for linear regression in Python (part 2).
See MoreStanford CS234: Reinforcement Learning | Winter 2019 | Lecture 1 - Introduct...
Professor Emma Brunskill
Assistant Professor, Computer Science
Stanford AI for Human Impact Lab
Stanford Artificial Intelligence Lab
Statistical Machine Learning Group
RL Course by David Silver - Lecture 7: Policy Gradient Methods
Looks at different policy gradients, including Finite Difference, Monte-Carlo and Actor Critic.
See MoreIIR Filters - Theory and Implementation (STM32)
Tutorial on IIR (Infinite Impulse Response) digital filters, including digital filtering overview, IIR filter theory, FIR vs IIR, Z-transform design/analysis, design using analogue...
See MoreData-Driven Control: BPOD and Output Projection
In this lecture, we introduce the output projection for balancing proper orthogonal decomposition (BPOD), to reduce the number of adjoint simulations required when the number of measurements...
See MoreA Nonlinear, 6 DOF Dynamic Model of an Aircraft: the Research Civil Aircraft...
In this video we develop a dynamic model of an aircraft by describing forces and moments generated by aerodynamic, propulsion, and gravity that act on the aircraft. This video outlines the...
See MoreGimbal Lock in reference to the Apollo missions
A gimbal is a pivoted support that permits rotation of an object about an axis. For this reason, a set of three axes gimbals are used in spacecrafts to help with orientation attitude control...
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