On decision-making strategies for improved-reliability size reduction of microwave passives: Intermittent correction of equality constraints and adaptive handling of inequality constraints

Kozieł, Sławomir; Pietrenko‐Dabrowska, Anna; Mahrokh, Marzieh

doi:10.1016/j.knosys.2022.109745

Cited by 8 publications

(8 citation statements)

References 71 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Figure 15. Recently, a strategy for improved handling of equality constraints was proposed in [45], which is briefly outlined and illustrated in this section. (a) inequality constraint: the designs produced from the current design x (i) may be located in either feasible or infeasible region, (b) equality constraint: essentially all designs produced from x (i) are infeasible due to feasible region being a thin set.…”

Section: Equality Constraint Control Through Optimization-based Corre...mentioning

confidence: 99%

“…According to [45], the inequality constraints are handled by means of the adaptive scheme (e.g., [42]), whereas the equality constraints are corrected after each iteration of the optimization process. The correction process has been explained in Figure 16.…”

Section: Correction Proceduresmentioning

confidence: 99%

“…The overall optimization procedure is embedded in the standard trust-region gradientbased framework with numerical derivatives [54]. For more details, see [45].…”

Section: Correction Proceduresmentioning

confidence: 99%

“…An alternative methodology has been developed as well, based on a separate treatment of equality and inequality constraints [45]. The specific geometry of the feasible regions corresponding to equality constraints (i.e., being thin sets in a set-theory sense) calls for a special treatment to control the design quality in a satisfactory manner.…”

Section: Introductionmentioning

confidence: 99%

“…The specific geometry of the feasible regions corresponding to equality constraints (i.e., being thin sets in a set-theory sense) calls for a special treatment to control the design quality in a satisfactory manner. Consequently, in the technique of [45], the equality constraints are treated using a correction-based scheme launched before each iteration of the core algorithm, whereas the inequality constraints are dealt with implicitly using the previously mentioned penalty function approach.…”

Section: Introductionmentioning

confidence: 99%

See 4 more Smart Citations

Optimization-Based High-Frequency Circuit Miniaturization through Implicit and Explicit Constraint Handling: Recent Advances

Pietrenko‐Dabrowska

Koziel²,

Mahrokh³

2022

Energies

Self Cite

View full text Add to dashboard Cite

Miniaturization trends in high-frequency electronics have led to accommodation challenges in the integration of the corresponding components. Size reduction thereof has become a practical necessity. At the same time, the increasing performance demands imposed on electronic systems remain in conflict with component miniaturization. On the practical side, the challenges related to handling design constraints are aggravated by the high cost of system evaluation, normally requiring full-wave electromagnetic (EM) analysis. Some of these issues can be alleviated by implicit constraint handling using the penalty function approach. Yet, its performance depends on the arrangement of the penalty factors, necessitating a costly trial-and-error procedure to identify their optimum setup. A workaround is offered by the recently proposed algorithms with automatic adaptation of the penalty factors using different adjustment schemes. However, these intricate strategies require a continuous problem-dependent adaptation of the penalty function throughout the entire optimization process. Alternative methodologies have been proposed by taking an explicit approach to handle the inequality constraints, along with correction-based control over equality conditions, the combination of which proves to be demonstrably competitive for some miniaturization tasks. Nevertheless, optimization-based miniaturization, whether using implicit or explicit constraint handling, remains a computationally expensive task. A reliable way of reducing the aforementioned costs is the incorporation of multi-resolution EM fidelity models into the miniaturization procedure. Therein, the principal operation is based on the simultaneous monitoring of factors such as quality of the constraint satisfaction, as well as algorithm convergence status. This paper provides an overview of the abovementioned size-reduction algorithms, in which theoretical considerations are illustrated using a number of antenna and microwave circuit case studies.

show abstract

Section: Equality Constraint Control Through Optimization-based Corre...mentioning

confidence: 99%

Section: Correction Proceduresmentioning

confidence: 99%

“…The overall optimization procedure is embedded in the standard trust-region gradientbased framework with numerical derivatives [54]. For more details, see [45].…”

Section: Correction Proceduresmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Optimization-Based High-Frequency Circuit Miniaturization through Implicit and Explicit Constraint Handling: Recent Advances

Pietrenko‐Dabrowska

Koziel²,

Mahrokh³

2022

Energies

Self Cite

View full text Add to dashboard Cite

show abstract

Globalized simulation-driven miniaturization of microwave circuits by means of dimensionality-reduced constrained surrogates

Kozieł

Pietrenko‐Dabrowska

Mahrokh

2022

Sci Rep

Self Cite

View full text Add to dashboard Cite

Small size has become a crucial prerequisite in the design of modern microwave components. Miniaturized devices are essential for a number of application areas, including wireless communications, 5G/6G technology, wearable devices, or the internet of things. Notwithstanding, size reduction generally degrades the electrical performance of microwave systems. Therefore, trade-off solutions have to be sought that represent acceptable compromises between the ability to meet the design targets and physical compactness. From an optimization perspective, this poses a constrained task, which is computationally expensive because a reliable evaluation of microwave components has to rely on full-wave electromagnetic analysis. Furthermore, due to its constrained nature, size reduction is a multimodal problem, i.e., the results are highly dependent on the initial design. Thus, utilization of global search algorithms is advisable in principle, yet, often undoable in practice because of the associated computational expenses, especially when using nature-inspired procedures. This paper introduces a novel technique for globalized miniaturization of microwave components. Our technique starts by identifying the feasible region boundary, and by constructing a dimensionality-reduced surrogate model therein. Global optimization of the metamodel is followed by EM-driven local tuning. Application of the domain-confined surrogate ensures low cost of the entire procedure, further reduced by the incorporation of variable-fidelity EM simulations. Our framework is validated using two microstrip couplers, and compared to nature-inspired optimization, as well as gradient-based size reduction. The results indicate superior miniaturization rates and low running cost, which make the presented algorithm a potential candidate for efficient simulation-based design of compact structures.

show abstract

Computationally-efficient statistical design and yield optimization of resonator-based notch filters using feature-based surrogates

Koziel,

Haq

2023

Sci Rep

Self Cite

View full text Add to dashboard Cite

Modern microwave devices are designed to fulfill stringent requirements pertaining to electrical performance, which requires, among others, a meticulous tuning of their geometry parameters. When moving up in frequency, physical dimensions of passive microwave circuits become smaller, making the system performance increasingly susceptible to manufacturing tolerances. In particular, inherent inaccuracy of fabrication processes affect the fundamental operating parameters, such as center frequency or bandwidth, which is especially troublesome for narrow-band structures, including notch filters. The ability to quantify the effects of tolerances, and—even more—to account for these in the design process, are instrumental in making the designs more reliable, and to increase the likelihood that adequate operation is ensured despite manufacturing errors. This paper proposes a simple yet computationally efficient and reliable procedure for statistical analysis and yield optimization of resonator-based notch filters. Our methodology involves feature-based surrogate models that can be established using a handful of training data points, and employed for rapid evaluation of the circuit fabrication yield. Furthermore, a yield optimization procedure is developed, which iteratively sets up a sequence of feature-based models, constructed within local domains relocated along the optimization path, and uses them as predictors to find a robust (maximum yield) design at a low computational cost. The presented approach has been demonstrated using two complementary split ring resonator (CSRR)-based notch filters. The cost of statistical design is about a hundred of EM simulations of the respective filter, with yield evaluation reliability corroborated through EM-based Monte Carlo analysis.

show abstract

On decision-making strategies for improved-reliability size reduction of microwave passives: Intermittent correction of equality constraints and adaptive handling of inequality constraints

Cited by 8 publications

References 71 publications

Optimization-Based High-Frequency Circuit Miniaturization through Implicit and Explicit Constraint Handling: Recent Advances

Optimization-Based High-Frequency Circuit Miniaturization through Implicit and Explicit Constraint Handling: Recent Advances

Globalized simulation-driven miniaturization of microwave circuits by means of dimensionality-reduced constrained surrogates

Computationally-efficient statistical design and yield optimization of resonator-based notch filters using feature-based surrogates

Contact Info

Product

Resources

About