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...

Kalman 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...

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...

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...

Kalman Filter Simulink 2022A example

This model is intended to help illustrate how a Kalman filter can estimate the state of a system. The "real system" is a nonlinear model of the Temperature Control Lab by Prof. John...

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...

Guaranteed Margins for LQR Regulators

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

Virtual Labs for control education

This resource provides different links to virtual and remote labs that can be used for control education. Virtual and remote labs are very powerful tools for learning and teaching, that...

Virtual Lab for a Two-tanks system

This is a virtual lab for a two-tank system that can be used for modelling and control learing/teaching purposes. Open-loop tests and closed-loop simulatons based on PI control or PI plus...

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...

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...

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

Control Loop Foundation Batch and Continuous Processes - Interactive Source ...

Control Loop Foundation contains workshops that allow the reader to get hands on experience through this web interface. Once a lab is selected, then you may access workshop directions and...

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...

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...

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...

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...

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...

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...

Smart Projectile State Estimation Using Evidence Theory

This journal article provides a very good practical understanding of Dempster-Shafer theory using sensor fusion and state estimation as the backdrop.

Virtual Laboratory for Vibrations and Control Theory

This virtual lab developed in Matlab Simscape provides an innovative tool for learning and teaching fundamentals of mechanical vibrations including mass-spring-damper systems. 

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...