Linear Matrix Inequalities in System and Control Theory
E451068
"Linear Matrix Inequalities in System and Control Theory" is a foundational monograph that systematically develops the theory and applications of linear matrix inequalities for analysis and design in modern control engineering.
All labels observed (1)
| Label | Occurrences |
|---|---|
| Linear Matrix Inequalities in System and Control Theory canonical | 1 |
How this entity was disambiguated
This entity first appeared as the object of triple T4539861 — resolving that mention is where its identity was fixed. The disambiguator weighed these candidate entities and picked the highlighted one (or “None”, minting a new entity). This is how homonymy is resolved: the same surface form can point to different entities.
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Linear Matrix Inequalities in System and Control Theory Context triple: [Stephen P. Boyd, notableWork, Linear Matrix Inequalities in System and Control Theory]
-
A.
Lectures in Feedback Design for Multivariable Systems
Lectures in Feedback Design for Multivariable Systems is a technical book by control theorist Alberto Isidori that presents systematic methods for designing feedback controllers for complex multivariable dynamical systems.
-
B.
Nonlinear Control Systems
Nonlinear Control Systems is a foundational textbook by Alberto Isidori that systematically develops the theory and design methods for controlling nonlinear dynamical systems.
-
C.
Lyapunov stability theory
Lyapunov stability theory is a fundamental framework in dynamical systems and control theory that uses energy-like functions to assess the stability of equilibrium points without explicitly solving differential equations.
-
D.
Kailath factorization in linear systems
Kailath factorization in linear systems is a matrix factorization technique used in control and signal processing to efficiently analyze and solve linear dynamical systems.
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E.
Introduction to Stochastic Control Theory
Introduction to Stochastic Control Theory is a foundational textbook that systematically develops the theory and methods for controlling dynamical systems under uncertainty using probabilistic and stochastic-process tools.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Linear Matrix Inequalities in System and Control Theory Target entity description: "Linear Matrix Inequalities in System and Control Theory" is a foundational monograph that systematically develops the theory and applications of linear matrix inequalities for analysis and design in modern control engineering.
-
A.
Lectures in Feedback Design for Multivariable Systems
Lectures in Feedback Design for Multivariable Systems is a technical book by control theorist Alberto Isidori that presents systematic methods for designing feedback controllers for complex multivariable dynamical systems.
-
B.
Nonlinear Control Systems
Nonlinear Control Systems is a foundational textbook by Alberto Isidori that systematically develops the theory and design methods for controlling nonlinear dynamical systems.
-
C.
Lyapunov stability theory
Lyapunov stability theory is a fundamental framework in dynamical systems and control theory that uses energy-like functions to assess the stability of equilibrium points without explicitly solving differential equations.
-
D.
Kailath factorization in linear systems
Kailath factorization in linear systems is a matrix factorization technique used in control and signal processing to efficiently analyze and solve linear dynamical systems.
-
E.
Introduction to Stochastic Control Theory
Introduction to Stochastic Control Theory is a foundational textbook that systematically develops the theory and methods for controlling dynamical systems under uncertainty using probabilistic and stochastic-process tools.
- F. None of above. chosen
Statements (46)
| Predicate | Object |
|---|---|
| instanceOf |
book
ⓘ
scientific monograph ⓘ |
| approach | convex optimization-based control design ⓘ |
| audience |
graduate students in control engineering
ⓘ
practicing control engineers ⓘ researchers in systems and control ⓘ |
| author |
Eric Feron
ⓘ
Laurent El Ghaoui ⓘ Stephen Boyd ⓘ
linked to:
Stephen P. Boyd
Venkataramanan Balakrishnan ⓘ |
| classification | SIAM Studies in Applied Mathematics ⓘ |
| contains |
applications to linear systems
ⓘ
applications to robust and uncertain systems ⓘ numerical aspects of solving LMIs ⓘ theoretical foundations of LMIs ⓘ |
| contribution |
systematic development of LMI theory for control
ⓘ
translation of control specifications into LMIs ⓘ unified framework for many classical control problems ⓘ |
| field |
control theory
ⓘ
convex optimization ⓘ linear matrix inequalities ⓘ systems theory ⓘ |
| focus | analysis and design of control systems using LMIs ⓘ |
| influencedField |
convex methods in signal processing
ⓘ
modern robust control design ⓘ optimization-based control ⓘ |
| language | English ⓘ |
| publicationYear | 1994 ⓘ |
| publisher |
SIAM
ⓘ
Society for Industrial and Applied Mathematics ⓘ
linked to:
SIAM
|
| status | foundational reference in LMI-based control ⓘ |
| topic |
H-infinity control
ⓘ
Lyapunov stability ⓘ controller synthesis ⓘ convex optimization methods in control ⓘ dissipativity ⓘ linear matrix inequalities ⓘ model predictive control foundations ⓘ observer design ⓘ robust control ⓘ semidefinite programming in control ⓘ state-space methods ⓘ |
| usedFor |
formulating control problems as semidefinite programs
ⓘ
performance optimization of control systems ⓘ stability analysis via LMIs ⓘ synthesis of state-feedback and output-feedback controllers ⓘ |
How these facts were elicited
The pipeline generated the facts above by prompting gpt-5.1 with this entity's name + description and the instruction below.
Instruction
You are a knowledge base construction expert. Given a subject entity and a description of it, return factual statements that you know for the subject as a JSON list of dictionaries(triples), where keys must be "subject", "predicate" and "object". The number of facts may be very high, between 25 to 50 or more, for very popular subjects. For less popular subjects, the number of facts can be very low, like 5 or 10. # Requirements - If you don't know the subject at all, return an empty list. - If the subject is not a named entity, return an empty list. - Include at least one triple where predicate is "instanceOf". - Do not get too wordy. - Separate several objects into multiple triples with one object.
Input
Subject: Linear Matrix Inequalities in System and Control Theory Description of subject: "Linear Matrix Inequalities in System and Control Theory" is a foundational monograph that systematically develops the theory and applications of linear matrix inequalities for analysis and design in modern control engineering.
Referenced by (1)
Full triples — surface form annotated when it differs from this entity's canonical label.