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Everything about State-space representation
Mathematical model of a system in control engineering
In control engineering and system identification, a state-space representation is a mathematical model of a physical system that uses state variables to track how inputs shape system behavior over time through first-order differential equations or difference equations. These state variables change based on their current values and inputs, while outputs depend on the states and sometimes the inputs too. The state space is a geometric space where the axes are these state variables, and the system’s state is represented by a state vector. Wikipedia →
🧭 Start here: a 6-step reading path
- Read the overview: State-space representationA 5-minute orientation
- Skim a recent paper: Scaling Representation Learning From Ubiquitous ECG With State-Space ModelsInfluential work since 2022
- Pick up a classic book: Hanʼguk hyŏndaesaThe most-reprinted book on the subject
- Read the landmark paper: Relation between atomic coherent-state representation, state multipoles, and generalized phase-space distributionsCited 270 times
- Go sideways: Realization (systems)A closely related topic
- Go sideways: ControllabilityA closely related topic
📖 Definitions
No dictionary entry for this exact phrase.
🗂️ The subject at a glance
🏆 Landmark papers (most cited)
Relation between atomic coherent-state representation, state multipoles, and generalized phase-space distributions
State-space representation for fractional order controllers
State-space representation of unsteady airfoil behavior
State-space representation of the unsteady aerodynamics of flapping flight
Audio Mamba: Bidirectional State Space Model for Audio Representation Learning
A state space representation of the chain ladder linear model
A quantum state vector phase space representation
State Space Representation of the Nonself-Adjoint Acoustic Duct System
🆕 Influential since 2022
Scaling Representation Learning From Ubiquitous ECG With State-Space Models
Performance analysis of real-time precise point positioning with GPS and BDS state space representation
MambaGait: Gait recognition approach combining explicit representation and implicit state space model
State Space Representation of Jiles–Atherton Hysteresis Model and Application for Closed-Loop Control
Multi-scale representation for image deraining with state space model
📚 Books worth reading
Hanʼguk hyŏndaesaAnmin Chŏngchʻaek Pʻorŏm (2005) · 2005
Ranked by number of editions on Open Library, a rough measure of how lasting a book is.
🔗 Related topics
- Realization (systems) In systems theory, a realization of a state space model is an implementation of a given input-output behavior. That is, given an input-output relationship…
- Controllability Controllability is an important property of a control system and plays a crucial role in many regulation problems, such as the stabilization of unstable…
- State variable A state variable is one of the set of mathematical variables that are used to describe the "state" of a system, e.g. of a dynamical system or a thermodynamical…
- Transfer function In engineering, a transfer function (also known as system function or network function) of a system, sub-system, or component is a mathematical function…
- Ackermann's formula In control theory, Ackermann's formula provides a method for designing controllers to achieve desired system behavior by directly calculating the feedback…
- Distributed parameter system In control theory, a distributed-parameter system (as opposed to a lumped-parameter system) is a system whose state space is infinite-dimensional. Such…
- Observability Observability is a measure of how well internal states of a system can be inferred from knowledge of its external outputs. In control theory, the observability…
- Stochastic control Stochastic control or stochastic optimal control is a sub field of control theory that deals with the existence of uncertainty either in observations or…