Lecture

State-Space Representation: Basics & Transformations

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In course

ME-326: Control systems and discrete-time control

Ce cours inclut la modélisation et l'analyse de systèmes dynamiques, l'introduction des principes de base et l'analyse de systèmes en rétroaction, la synthèse de régulateurs dans le domain fréquentiel et dans l'espace d'état, et la commande de systèmes dis ...

Description

This lecture introduces the state-space representation of systems, focusing on the basics of state variables and their importance in system analysis. The instructor covers methods for transforming a system from transfer function to state-space representation, showcasing different forms such as modal, controllable canonical, and observable canonical representations. The lecture also delves into similar transformations, highlighting the concept of multiple representations for a system and the role of non-singular transformations in generating new state-space models. The importance of controllability and observability in system analysis is briefly mentioned, setting the stage for further exploration in the next lecture.

Instructors (2)

Christophe Salzmann

Expertise Real-time Internet ServicesReal-time controlQuality of Service and Bandwidth adaptationLabVIEW Education PhD | Remote experimentation, Network 2005 – 2005 EPFL Directed by Denis Gillet MS. Degree | Computer Science 1999 – 1999 University of Florida Directed by Prof. H. Latchman Teaching & PhD Past EPFL PhD Students as codirector Damien Perritaz, Evgeny Bogdanov, Wissam Halimi Courses Control systems + TP ME

Alireza Karimi

Alireza Karimi received his B. Sc. and M. Sc. degrees in Electrical Engineering in 1987 and 1990, respectively, from Amir Kabir University (Tehran Polytechnic). Then he received his DEA and Ph. D. degrees both on Automatic Control from Institut National Polytechnique de Grenoble (INPG) in 1994 and 1997, respectively. He was Assistant Professor at Electrical Engineering Department of Sharif University of Technology in Teheran from 1998 to 2000. Then he joined Automatic Laboratory of Swiss Federal Institute of Technology at Lausanne, Switzerland. He is currently Professor of Automatic Control and the head of "Data-Driven Modelling and Control" group. His research interests include data-driven controller tuning and robust control with application to mechatronic systems and electrical grids.

Official source

Ontological neighbourhood

Information engineering

Control theory and engineering: Control theory

Related concepts (32)

State-space representation

In control engineering, model based fault detection and system identification a state-space representation is a mathematical model of a physical system specified as a set of input, output and variables related by first-order (not involving second derivatives) differential equations or difference equations. Such variables, called state variables, evolve over time in a way that depends on the values they have at any given instant and on the externally imposed values of input variables.

Control system

A control system manages, commands, directs, or regulates the behavior of other devices or systems using control loops. It can range from a single home heating controller using a thermostat controlling a domestic boiler to large industrial control systems which are used for controlling processes or machines. The control systems are designed via control engineering process. For continuously modulated control, a feedback controller is used to automatically control a process or operation.

Control engineering

Control engineering or control systems engineering is an engineering discipline that deals with control systems, applying control theory to design equipment and systems with desired behaviors in control environments. The discipline of controls overlaps and is usually taught along with electrical engineering and mechanical engineering at many institutions around the world. The practice uses sensors and detectors to measure the output performance of the process being controlled; these measurements are used to provide corrective feedback helping to achieve the desired performance.

Controllability

Controllability is an important property of a control system and plays a crucial role in many control problems, such as stabilization of unstable systems by feedback, or optimal control. Controllability and observability are dual aspects of the same problem. Roughly, the concept of controllability denotes the ability to move a system around in its entire configuration space using only certain admissible manipulations. The exact definition varies slightly within the framework or the type of models applied.

Industrial control system

An industrial control system (ICS) is an electronic control system and associated instrumentation used for industrial process control. Control systems can range in size from a few modular panel-mounted controllers to large interconnected and interactive distributed control systems (DCSs) with many thousands of field connections. Control systems receive data from remote sensors measuring process variables (PVs), compare the collected data with desired setpoints (SPs), and derive command functions that are used to control a process through the final control elements (FCEs), such as control valves.

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