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...

System 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...

What 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...

A 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...

Perspectives 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...

Guaranteed Margins for LQR Regulators

John Doyle's famous paper! He presents a counterexample that shows that are no guaranteed margins for LQG systems. 

Manuscript 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...

Benchmarking 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

Vibrational 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...

Multi-Agent Reinforcement Learning: Independent vs Cooperative Agents

From the Abstract:

Intelligent human agents exist in a cooperative social environment that facilitates learning. They learn not only by trialand -error, but also through cooperation by...

Experimental 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...

Averaging 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...

The 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...

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...

Model 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...

Multifunction 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...

Reinforcement 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...

Fast 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...

Averaging 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...

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...

Nonlinear 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...

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...

Feedback 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...

An efficient orientation filter for inertial and inertial/magnetic sensor ar...

This report presents a novel orientation filter applicable to IMUs consisting of tri-axis gyroscopes and accelerometers, and MARG sensor arrays that also include tri-axis magnetometers. The...

Automatic Updates of Transition Potential Matrices in Dempster-Shafer Networ...

Journal article that develops an evidential reasoning network capable of learning/updating the relationships between Frames of Discernment (the sets over which Dempster-Shafer reasons that...