A nonlinear programming approach to optimal design centering, tolerancing, and tuning

Liu, P.; Tromp, Herman

doi:10.1109/tcs.1976.1084191

Cited by 89 publications

(26 citation statements)

References 7 publications

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“…The upper bound on large change tolerances of parameters for the third-order sensitivity model of the circuit can be even six times higher than that for the first-order sensitivity model [7]. Consequently, a higher order sensitivity model of the circuit, aided by nonlinear programming techniques, gives precise indications of the nominal values and tolerances of elements [8]. A similar conclusion about higher…”

Section: Introductionmentioning

confidence: 93%

High‐order sensitivity invariants

Izydorczyk

Chojcan

2010

Circuit Theory & Apps

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SUMMARYThe aim of the research reported in this paper is to extend the notion of invariant sensitivity sum, widely known for electrical networks, from first-order sensitivities to high-order sensitivities. The results are high-order invariant sums of sensitivities of the first and the second kind, formulated for nonlinear lumped circuit, which consists of one-port and two-ports only. One-ports are generalized resistances, capacitances, inductances, voltages, and current sources, whereas two-ports are nonlinear generalizations of four types of controlled sources. It is observed that the invariant sums actually found for nonlinear lumped networks are generalizations of sums given earlier by authors for linear lumped networks. The article is illustrated by numerical sensitivity analysis of simple linear and nonlinear circuits.

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Section: Introductionmentioning

confidence: 93%

High‐order sensitivity invariants

Izydorczyk

Chojcan

2010

Circuit Theory & Apps

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“…The extension to the general case is straightforward. Polak and Mayne [7] describe an algorithm for minimization subject to constraints (1) and (2); an improved algorithm is presented in (5). Both of these first order algorithms are easily modified to solve inequalities (1) and (2).…”

Section: Dq Mayne and E Polakmentioning

confidence: 99%

“…(1) The iteration counter is i; j is the number of times that the second order step v(z) has been employed. …”

Section: A Stabilised Conceptual Algorithmmentioning

confidence: 99%

“…M a n y design problems, such as the design of circuits, control systems and structures [1,4,8] can be formulated as determining a parameter vector z E R n which satisfies: is a compact interval of the real line. The constraint ~J(z, a)~< 0 for all c~E m a y represent a constraint on a time response (e.g., on the deflection of a framed structure in response to an earthquake) or on a frequency response of a circuit or a control system; in such applications ~ is a time or a frequency interval.…”

Section: Introductionmentioning

confidence: 99%

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A quadratically convergent algorithm for solving infinite dimensional inequalities

Mayne

Polak

1982

Appl Math Optim

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“…The pre-fabrication tuning is concerned with the designation of some parameters as candidates for tuning, based on manufacturing requirements, and on their strong effect on the response behavior [1][2][3]. In post-fabrication tuning, the objective is twofold:…”

Section: Introductionmentioning

confidence: 99%

A neural-network-based approach for post-fabrication circuit tuning

El-Gamal

Abdel-Malek

Sorour

2004

Neural Comput & Applic

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A hierarchical neural-network-based approach for circuit tuning at the post-fabrication stage is proposed. In this approach, measurements that characterize the behavior of the circuit under test are first selected. The best candidates of circuit parameters for tuning are also determined. A training set comprising the selected circuit measurements is then constructed. These measurements are calculated during simulations in which the circuit parameter values are uniformly distributed in a tolerance region around their nominal values. The training set is fed to a self organizing map neural network to cluster the measurements. The generated clusters are manipulated and classified via a hierarchical circuit tuning procedure. Based on this classification, tuning values for the tuning parameters are calculated. Situations in which the circuit cannot be tuned are also addressed. Experimental results indicate that the developed approach provides a robust and efficient technique for circuit tuning.

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A nonlinear programming approach to optimal design centering, tolerancing, and tuning

Cited by 89 publications

References 7 publications

High‐order sensitivity invariants

High‐order sensitivity invariants

A quadratically convergent algorithm for solving infinite dimensional inequalities

A neural-network-based approach for post-fabrication circuit tuning

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