A Convex Approach Solving Simultaneous Mechanical Structure and Control System Design Problems With Multiple Closed-loop Performance Specifications
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".