Controllability and observability of polynomial dynamical systems

1981 ◽  
Vol 5 (5) ◽  
pp. 543-552 ◽  
Author(s):  
John Baillieul
Keyword(s):  
Dynamical Systems ◽  
Polynomial Dynamical Systems ◽  
Controllability And Observability

On the Nonlinear Observability of Polynomial Dynamical Systems

2021 ◽  
Vol 1 (1) ◽  
pp. 88-94
Author(s):  
Daniel Gerbet ◽  
Klaus Röbenack
Keyword(s):  
Dynamical Systems ◽  
Nonlinear Systems ◽  
State Space ◽  
Polynomial Dynamical Systems ◽  
Higher Dimensional ◽  
Dimensional State Space ◽  
System Properties ◽  
Controllability And Observability ◽  
Important System ◽  
Nonlinear Observability

Controllability and observability are important system properties in control theory. These properties cannot be easily checked for general nonlinear systems. This paper addresses the local and global observability as well as the decomposition with respect to observability of polynomial dynamical systems embedded in a higher-dimensional state-space. These criteria are applied on some example system.

scholarly journals Network-based Observability and Controllability Analysis of Dynamical Systems: the NOCAD toolbox

F1000Research ◽  
2019 ◽  
Vol 8 ◽  
pp. 646
Author(s):  
Dániel Leitold ◽  
Ágnes Vathy-Fogarassy ◽  
János Abonyi
Keyword(s):  
Neural Network ◽  
Caenorhabditis Elegans ◽  
Dynamical Systems ◽  
Network Science ◽  
Sensor Placement ◽  
Life Sciences ◽  
The Neural Network ◽  
Structural Controllability ◽  
Controllability And Observability

The network science-based determination of driver nodes and sensor placement has become increasingly popular in the field of dynamical systems over the last decade. In this paper, the applicability of the methodology in the field of life sciences is introduced through the analysis of the neural network of Caenorhabditis elegans. Simultaneously, an Octave and MATLAB-compatible NOCAD toolbox is proposed that provides a set of methods to automatically generate the relevant structural controllability and observability associated measures for linear or linearised systems and compare the different sensor placement methods.

scholarly journals SPECIAL CURVES AND POSTCRITICALLY FINITE POLYNOMIALS

2013 ◽  
Vol 1 ◽  
Author(s):  
MATTHEW BAKER ◽  
LAURA DE MARCO
Keyword(s):  
Fixed Point ◽  
Dynamical Systems ◽  
Moduli Space ◽  
Dense Subset ◽  
Rational Curves ◽  
Rational Maps ◽  
Complex Polynomial ◽  
Polynomial Dynamical Systems ◽  
Postcritically Finite ◽  
Cubic Polynomials

AbstractWe study the postcritically finite maps within the moduli space of complex polynomial dynamical systems. We characterize rational curves in the moduli space containing an infinite number of postcritically finite maps, in terms of critical orbit relations, in two settings: (1) rational curves that are polynomially parameterized; and (2) cubic polynomials defined by a given fixed point multiplier. We offer a conjecture on the general form of algebraic subvarieties in the moduli space of rational maps on ${ \mathbb{P} }^{1} $ containing a Zariski-dense subset of postcritically finite maps.

scholarly journals Analyzing control properties of multi-agent linear systems

2020 ◽  
pp. 81-85
Author(s):  
M. Isabel Garcıa-Planas
Keyword(s):  
Dynamical Systems ◽  
Linear Time ◽  
Communication Channels ◽  
Power Grids ◽  
Multi Agent Systems ◽  
Agent Systems ◽  
Linear Time Invariant ◽  
Multi Agent ◽  
Controllability And Observability ◽  
Time Invariant

The networked multi-agent systems that they are interconnected via communication channels have great applicability in multiple areas, such as power grids, bioinformatics, sensor networks, vehicles, robotics and neuroscience, for example. Consequently, they have been widely studied by scientists in different fields in particular in the field of control theory. Recently an interest has grown to analyze the control properties as consensus controllability and observability of multi-agent dynamical systems motivated by the fact that the architecture of communication network in engineering multi-agent systems is usually adjustable. In this paper, we analyze how to improve the control properties in the case of multiagent linear time-invariant dynamical systems.

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