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EN
Finding an acceptable compromise between various objectives is a necessity in the design of contemporary microwave components and circuits. A primary reason is that most objectives are at least partially conflicting. For compact microwave structures, the design trade-offs are normally related to the circuit size and its electrical performance. In order to obtain comprehensive information about the best possible trade-offs, multi-objective optimization is necessary that leads to identifying a Pareto set. Here, a framework for fast multi-objective design of compact micro-strip couplers is discussed. We use a sequential domain patching (SDP) algorithm for numerically efficient handling of the structure bandwidth and the footprint area. Low cost of the process is ensured by executing SDP at the low-fidelity model level. Due to its bi-objective implementation, SDP cannot control the power split error of the coupler, the value of which may become unacceptably high along the initial Pareto set. Here, we propose a procedure for correction of the S-parameters’ characteristics of Pareto designs. The method exploits gradients of power split and bandwidth estimated using finite differentiation at the patch centres. The gradient data are used to correct the power split ratio while leaving the operational bandwidth of the structure at hand intact. The correction does not affect the computational cost of the design process because perturbations are pre-generated by SDP. The final Pareto set is obtained upon refining the corrected designs to the high-fidelity EM model level. The proposed technique is demonstrated using two compact microstrip rat-race couplers. Experimental validation is also provided.
EN
This work examines the reduced-cost design optimization of dual- and multi-band antennas. The primary challenge is independent yet simultaneous control of the antenna responses at two or more frequency bands. In order to handle this task, a feature-based optimization approach is adopted where the design objectives are formulated on the basis of the coordinates of so-called characteristic points (or response features) of the antenna response. Due to only slightly nonlinear dependence of the feature points on antenna geometry parameters, optimization can be attained at a low computational cost. Our approach is demonstrated using two antenna structures with the optimum designs obtained in just a few dozen of EM simulations of the respective structure.
EN
Introduction of fly-by-wire and increasing levels of automation significantly improve the safety of civil aircraft, and result in advanced capabilities for detecting, protecting and optimizing A/C guidance and control. However, this higher complexity requires the availability of some key flight parameters to be extended. Hence, the monitoring and consolidation of those signals is a significant issue, usually achieved via many functionally redundant sensors to extend the way those parameters are measured. This solution penalizes the overall system performance in terms of weight, maintenance, and so on. Other alternatives rely on signal processing or model-based techniques that make a global use of all or part of the sensor data available, supplemented by a model-based simulation of the flight mechanics. That processing achieves real-time estimates of the critical parameters and yields dissimilar signals. Filtered and consolidated information is delivered in unfaulty conditions by estimating an extended state vector, including wind components, and can replace failed signals in degraded conditions. Accordingly, this paper describes two model-based approaches allowing the longitudinal flight parameters of a civil A/C to be estimated on-line. Results are displayed to evaluate the performances in different simulated and real flight conditions, including realistic external disturbances and modeling errors.
4
Content available remote New trends in optimization in electromagnetics
EN
This paper reviews recent advances in optimisation of electromagnetic problems. CAD assisted optimal design often necessitates repetitive usage of numerically intensive field computation where cost-effective approaches are required. Modern algorithms increasingly rely on surrogate modelling, kriging-assisted methods, pareto-optimality and design sensitivity.
PL
Nowoczesne metody projektowania oparte na wspomaganiu komputerowym z wykorzystaniem numerycznego oblicznia pól elektromagnetycznych wymagają skutecznych, a przede wszystkim szybkich i efektywnych metod optymalizacyjnych. Ostatnie lata przyniosły eksplozję nowych podejść i algorytmów. Artykuł jest próbą uogólnienia efektów ostatnich badań – w tym również dorobku autora – ze szczególnym uwzględnieniem najnowszych osiągnięć i spodziewanych nowych rozwiązań.
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