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Active Filters01:25

Active Filters

924
Active filters are electronic circuits that use operational amplifiers (op-amps), resistors, and capacitors to filter out unwanted frequency components from a signal. A first-order low-pass active filter is designed to pass signals with a frequency lower than a certain cutoff frequency and attenuate frequencies higher than that cutoff frequency. The transfer function for a first-order low-pass active filter is:
924
Linear Approximation in Frequency Domain01:26

Linear Approximation in Frequency Domain

131
Linear systems are characterized by two main properties: superposition and homogeneity. Superposition allows the response to multiple inputs to be the sum of the responses to each individual input. Homogeneity ensures that scaling an input by a scalar results in the response being scaled by the same scalar.
In contrast, nonlinear systems do not inherently possess these properties. However, for small deviations around an operating point, a nonlinear system can often be approximated as linear....
131
Aliasing01:18

Aliasing

224
Accurate signal sampling and reconstruction are crucial in various signal-processing applications. A time-domain signal's spectrum can be revealed using its Fourier transform. When this signal is sampled at a specific frequency, it results in multiple scaled replicas of the original spectrum in the frequency domain. The spacing of these replicas is determined by the sampling frequency.
If the sampling frequency is below the Nyquist rate, these replicas overlap, preventing the original...
224
Passive Filters01:27

Passive Filters

606
Passive filters are utilized to shape the frequency spectrum of signals across a diverse array of applications. These filters, using only passive elements like resistors (R), inductors (L), and capacitors (C), are capable of selectively allowing or blocking certain frequency ranges without the need for external power sources.
Low-Pass Filters
Low-pass filters are designed to transmit signals with frequencies lower than the cutoff frequency, ωc, and attenuate those above it. The cutoff...
606
Reconstruction of Signal using Interpolation01:10

Reconstruction of Signal using Interpolation

335
Signal processing techniques are essential for accurately converting continuous signals to digital formats and vice versa. When a continuous signal is sampled with a period T, the resulting sampled signal exhibits replicas of the original spectrum in the frequency domain, spaced at intervals equal to the sampling frequency. To handle this sampled signal, a zero-order hold method can be applied, which creates a piecewise constant signal by retaining each sample's value until the next...
335
Phase-lead and Phase-lag Controllers01:22

Phase-lead and Phase-lag Controllers

224
Understanding the working function of different types of controllers can be illustrated with practical analogies, such as adjusting a stereo's volume equalizer. Cranking up the bass involves a phase-lead controller, which functions as a high-pass filter, while increasing the treble uses a phase-lag controller, which acts as a low-pass filter. PD controllers, similar to high-pass filters, enhance the system's response to high-frequency components. PI controllers, akin to low-pass...
224

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Design and Characterization Methodology for Efficient Wide Range Tunable MEMS Filters
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Filtrado adaptativo basado en lógica difusa para la alineación de transferencia

Zhaohui Gao1, Jiahui Yang2, Chengfan Gu3

  • 1School of Electronic Engineering, Xi'an Shiyou University, Xi'an 710065, China.

Sensors (Basel, Switzerland)
|August 28, 2025
PubMed
Resumen
Este resumen es generado por máquina.

Este estudio introduce un filtro adaptativo de lógica difusa para mejorar la precisión de la alineación de la transferencia del sistema de navegación por inercia (SINS). El nuevo método mejora la estimación del estado de SINS mediante la gestión efectiva de los errores del modelo del sistema, logrando una precisión superior al 18%.

Palabras clave:
Filtración robusta y adaptativaTeoría de la lógica difusaNavegación inercial con correa hacia abajoAlineación de transferencia

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Área de la Ciencia:

  • Sistemas de navegación
  • Teoría de control
  • Procesamiento de señales

Sus antecedentes:

  • Los sistemas de navegación inercial Strapdown (SINS) requieren una alineación de transferencia precisa para los vehículos tácticos en el aire.
  • Los errores del modelo del sistema en los filtros de Kalman degradan la precisión de la estimación del estado SINS.

Objetivo del estudio:

  • Desarrollar un método de filtrado adaptativo basado en la lógica difusa para la alineación de la transferencia SINS.
  • Para mitigar el impacto de los errores del modelo del sistema en la estimación del estado del SINS.

Principales métodos:

  • Diseñó un enfoque de filtrado adaptativo basado en lógica difusa para la alineación de transferencia de SINS.
  • Modelos de estado y error de medición integrados con residuos en el marco de filtro de Kalman.
  • Utilizó reglas difusas para estimar la medición del sistema y predijo covariancias de estado minimizando los residuos.

Principales resultados:

  • El método propuesto trata eficazmente los errores del modelo del sistema en la alineación de transferencia SINS.
  • Alcanzó al menos un 18,83% de precisión en comparación con los métodos de referencia.
  • Las simulaciones y los experimentos validaron el rendimiento del método.

Conclusiones:

  • El filtro adaptativo de lógica difusa mejora significativamente la precisión de alineación de la transferencia SINS.
  • Este enfoque ofrece una solución robusta para la navegación de vehículos tácticos en el aire.
  • El método demuestra un rendimiento superior en la gestión de las incertidumbres del modelo.