MétaCan
Menu
Back to cohort
Record W2062606777 · doi:10.1115/1.1876493

A Convex Approach Solving Simultaneous Mechanical Structure and Control System Design Problems With Multiple Closed-loop Performance Specifications

2004· article· en· W2062606777 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJournal of Dynamic Systems Measurement and Control · 2004
Typearticle
Languageen
FieldDecision Sciences
TopicProbabilistic and Robust Engineering Design
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsConvex optimizationController (irrigation)Control theory (sociology)Set (abstract data type)Loop (graph theory)Convex combinationMatrix (chemical analysis)Mathematical optimizationComputer scienceRegular polygonMathematicsControl (management)

Abstract

fetched live from OpenAlex

Abstract In this paper, a new integrated design method, referred to as the extended multiple simultaneous specification (EMSS) method, is proposed to solve simultaneous mechanical structure and control system design problems in which a set of n multiple closed-loop performance specifications must be simultaneously satisfied. To utilize this approach, all closed-loop performance specifications considered must have the property that they are convex with respect to the closed-loop system transfer matrix. With the proposed approach, a simply implemented two-stage design approach is used to determine a set of open-loop mechanical system design parameters and a closed-loop controller which simultaneously satisfies a set of n closed-loop performance specifications. In the first stage, for each closed-loop performance specification, one “sample system,” i.e., the closed-loop system with one set of mechanical design parameters with a closed-loop controller chosen from the set of all linear controllers, is determined by trial and error, such that the specification is satisfied. In the second stage, the transfer matrix of the final system, which satisfies all n performance specifications, is determined through the convex combination of the transfer matrices of n sample systems. A linear programming problem is solved to give the combination vector for this convex combination. With the closed-loop transfer matrix given, the mechanical design parameters, the closed-loop controller structure and its gains, are solved algebraically. In this paper, we establish conditions for the existence of a solution to this integrated design problem as well as prove that the EMSS approach retains the stability properties of the sample systems. Experimental results of the EMSS method, carried out on a linear positioning system are given, verifying the effectiveness of the proposed method. We note that the proposed EMSS method works well when the number of design parameters to be determined is small. Further, the proposed EMSS method also has some utility as a controller design method, to determine a closed-loop controller that satisfies a set of n multiple closed-loop performance specifications, given a fixed mechanical system structure.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.005
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.943
Threshold uncertainty score0.754

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.056
GPT teacher head0.227
Teacher spread0.171 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it