
A New Approach to Linear Filtering and Prediction Problems
A transcription of R.E. Kalman's seminal paper. Transcribed by John Lukesh, 20 January 2002
The classical filtering and prediction problem is re-examined using the Bode- Shannon...
See MoreSystem Identification: Theory for the User
From the Back Cover
The field's leading text, now completely updated.
Modeling dynamical systems ― theory, methodology, and applications.
Lennart Ljung's System Identification: Theory...
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 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 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 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 MoreA Tutorial on PES Pareto Methods for Analysis of Noise Propagation in Feedba...
This paper represents a tutorial on the so called PES Pareto methodology of analyzing the sources of noise in a feedback loop. Originally conceived for analyzing noise contributors in...
See MoreRADAR Engineering
Radar technology is used widely today. The principles involved are very fundamental and every engineering student studies them at least once. This playlist covers Radar Engineering for an EE...
See MorePerspectives on Control-Relevant Identification Through the Use of Interacti...
This paper presents a control-relevant identification methodology through an intuitive interactive tool called "Interactive Tool for Control Relevant Identification (ITCRI)". ITCRI...
See MoreManuscript about ITISE: an Interactive Software Tool for System Identificati...
The paper describes the conceptual basis, main features and functionality of an interactive software tool developed in support of system identification education and discovery.
This...
See MoreGuaranteed Margins for LQR Regulators
John Doyle's famous paper! He presents a counterexample that shows that are no guaranteed margins for LQG systems.
See MoreLearning From Data
This is an introductory course in machine learning (ML) that covers the basic theory, algorithms, and applications. ML is a key technology in Big Data, and in many financial, medical...
See MoreSystems modeling and representations (French)
Complete course on systems modeling. Includes examples, MATLAB code, and quizzes.
See MoreMath Background for Machine Learning from Carnegie Melon University
This course provides a place for students to practice the necessary mathematical background for further study in machine learning — particularly for taking 10-601 and 10-701. Topics covered...
See MoreExperimental evaluation of feedforward tuning rules
This paper presents a practical comparison for some of the most relevant tuning rules for feedforward compensators that have been published in the recent years. The work is focused on the...
See MoreReinforcement Learning: An Introduction
From the book introduction:
The idea that we learn by interacting with our environment is probably the first to occur to us when we think about the nature of learning. When an infant plays...
See MoreReinforcement Learning with MATLAB.
This repository contains series of modules to get started with Reinforcement Learning with MATLAB.
It is divided into 4 stages.
In Stage 1, we start with learning RL concepts by manually...
See MoreYann LeCun’s Deep Learning Course at CDS
This course concerns the latest techniques in deep learning and representation learning, focusing on supervised and unsupervised deep learning, embedding methods, metric learning...
See MoreInteractive Course for Control Theory
Control Theory is a topic that finds a widespread application throughout engineering and natural sciences. It is very common in electrical, mechanical and process engineering. Especially...
See MoreVibrational control of nonlinear systems: Vibrational controllability and tr...
In the first part of this work, the criteria for the existence of stabilizing parametric oscillations have been derived. In the present paper, the problem of choosing the stabilizing...
See MoreFeedforward 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...
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 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 MoreModelling, dynamics and control
How do we model the world around us and use this to understand its behaviour? How does behaviour depend upon the engineering choices we make and therefore how do we undertake design to...
See MoreAveraging and Vibrational Control of Mechanical Systems
Abstract. This paper investigates averaging theory and oscillatory control for a large class of mechanical systems. A link between averaging and controllability theory is presented by...
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