
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 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 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 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 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 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 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 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 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 MoreDealing 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...
See MoreFeedback Systems: An Introduction for Scientists and Engineers
This is the wiki for the text Feedback Systems (second edition) by Karl J. Åström and Richard M. Murray. On this resource you will find the complete text of the book as well as additional...
See MoreProcess Dynamics and Control Course
This course focuses on a complete start to finish process of physics-based modeling, data driven methods, and controller design. Although some knowledge of computer programming is required...
See MoreFull Stack Deep Learning
There are many great courses to learn how to train deep neural networks. However, training the model is just one part of shipping a deep learning project. This course teaches full-stack...
See MoreFast chirp FMCW Radar in automotive applications
FMCW (frequency-modulated continuous wave radar) modulations have been popularly implemented in the automotive radar applications. This document demonstrates system requirement for a new...
See MoreNonlinear Oscillations, Dynamical Systems, and Bifurcations of Vector Fields...
From the reviews: "This book is concerned with the application of methods from dynamical systems and bifurcation theories to the study of nonlinear oscillations. Chapter 1 provides a review...
See MoreMulti-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...
See MoreModel Identification and Adaptive Control - From Windsurfing to Telecommunic...
This book is based on a workshop entitled: "Model Identification and Adaptive Control: From Windsurfing to Telecommunications" held in Sydney, Australia, on December 16, 2000. The workshop...
See MoreThe Demod Squad: A Tutorial on the Utility and Methodologies for Using Modul...
This paper is a brief tutorial on methods for using modulated signals in feedback loops, and especially of the different methods and trade offs used for demodulating those signals to get...
See MoreNo! Not Laplace Transforms
In my 13-year industrial career, I never used Laplace transforms. However, transfer functions and block diagram notation are efficient methods to describe dynamic behaviors, and are often...
See MoreBenchmarking tools for a priori identifiability analysis
Recent review and benchmark of software tools that can be used for assess the structural identifiability of dynamical systems
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