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PI Controller: Design01:24

PI Controller: Design

1.3K
Proportional Integral (PI) controllers are a fundamental component in modern control systems, widely used to enhance performance and mitigate steady-state errors. They are particularly effective in applications such as automatic brightness adjustment on smartphones, where they excel at mitigating steady-state errors for step-function inputs. Unlike PD controllers, which require time-varying errors to function optimally, PI controllers leverage their integral component to address residual...
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PD Controller: Design01:26

PD Controller: Design

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In automotive engineering, car suspension systems often employ Proportional Derivative (PD) controllers to enhance performance. PD controllers are utilized to adjust the damping force in response to road conditions. A controller, acting as an amplifier with a constant gain, demonstrates proportional control, with output directly mirroring input.
Designing a continuous-data controller requires selecting and linking components like adders and integrators, which are fundamental in Proportional,...
679
Time and frequency -Domain Interpretation of PI Control01:27

Time and frequency -Domain Interpretation of PI Control

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Proportional-Integral (PI) controllers are essential in many control systems to improve stability and performance. They are commonly used in everyday devices like thermostats to enhance system damping and reduce steady-state error. When the zero in the controller's transfer function is optimally placed, the system benefits significantly in terms of stability and accuracy.
Acting as a low-pass filter, the PI controller slows the system's response and extends settling times. This requires...
444
Controller Configurations01:22

Controller Configurations

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Controller configurations are crucial in a car's cruise control system because they manage speed over time to maintain a consistent pace regardless of road conditions, thereby meeting design goals. In traditional control systems, fixed-configuration design involves predetermined controller placement. System performance modifications are known as compensation.
Control-system compensation involves various configurations, most commonly series or cascade compensation, in which the controller...
399
PID Controller01:19

PID Controller

777
Proportional-Integral-Derivative (PID) controllers are widely used in various control systems to enhance stability and performance. In a thermostat, it adjusts heating or cooling based on the temperature difference between the actual and desired levels. They are often used in automotive speed systems, effectively managing sudden speed changes while maintaining a constant speed under varying conditions. On the other hand, PI controllers, commonly employed in voltage regulation, enhance stability...
777
One-Degree-of-Freedom System01:24

One-Degree-of-Freedom System

873
In mechanical engineering, one-degree-of-freedom systems form the basis of a wide range of electrical and mechanical components. Using these models, engineers can predict the behavior of various parts in a larger system, which gives them insight into how different forces interact with each other.
A one-degree-of-freedom system is defined by an independent variable that determines its state and behavior. One example of a one-degree-of-freedom system is a simple harmonic oscillator, such as a...
873

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Video Experimental Relacionado

Updated: Feb 20, 2026

The Modular Design and Production of an Intelligent Robot Based on a Closed-Loop Control Strategy
11:53

The Modular Design and Production of an Intelligent Robot Based on a Closed-Loop Control Strategy

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Controlador fraccional inteligente adaptativo para el seguimiento de trayectorias de robots móviles

Mohammad A Jaradat1, Khaled S Hatamleh2, Mohammad Hayajneh3

  • 1Mechanical Engineering Department, American University of Sharjah, Sharjah, United Arab Emirates; Mechanical Engineering Department, Jordan University of Science & Technology, Irbid, 22110, Jordan.

ISA transactions
|February 18, 2026
PubMed
Resumen

Un controlador fraccional inteligente adaptativo de orden fraccionario de retroalimentación de estado completo (FOFSC) mejora el seguimiento de trayectorias de robots móviles de transmisión diferencial. Este enfoque novedoso optimiza las ganancias de control para un mejor rendimiento en sistemas de entrega autónomos.

Palabras clave:
Robot de transmisión diferencialControlador de orden fraccionarioControlador de orden enteroControlador fraccional inteligente adaptativoOptimización de lobos grisesSeguimiento de trayectorias

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Área de la Ciencia:

  • Robótica y Sistemas de Control
  • Inteligencia Artificial
  • Mecatrónica

Sus antecedentes:

  • Los robots móviles autónomos con ruedas son cruciales para tareas como los sistemas de entrega.
  • El control preciso del seguimiento de trayectorias es un desafío clave para estos robots.
  • El control de orden fraccionario ofrece ventajas sobre el control de orden entero debido a la memoria y la no localidad.

Objetivo del estudio:

  • Proponer un controlador fraccional inteligente adaptativo de orden fraccionario de retroalimentación de estado completo (FOFSC) para mejorar el seguimiento de trayectorias de robots de transmisión diferencial (DDR).
  • Comparar el rendimiento del FOFSC propuesto con un controlador de orden entero de retroalimentación de estado completo (IOFSC).
  • Evaluar enfoques de optimización adaptativos y no adaptativos utilizando la optimización de lobos grises (GWO).

Principales métodos:

  • Desarrollo de un FOFSC que utiliza la optimización de lobos grises (GWO) para la sintonización de ganancias.
  • Implementación de estrategias de optimización adaptativas (actualizaciones de ganancias en línea) y no adaptativas (sintonización de ganancias fuera de línea).
  • Análisis comparativo frente a un IOFSC utilizando simulaciones y validación experimental en una plataforma de robot QBot 2e.

Principales resultados:

  • El FOFSC inteligente adaptativo demostró un rendimiento superior de seguimiento de trayectorias en comparación con el IOFSC.
  • Las mejoras clave en el rendimiento incluyen una velocidad de convergencia más rápida y errores de seguimiento minimizados.
  • El FOFSC adaptativo manejó eficazmente las perturbaciones y se adaptó a los cambios de trayectoria sin reajustes.

Conclusiones:

  • El FOFSC inteligente adaptativo propuesto mejora significativamente el seguimiento de trayectorias para robots de transmisión diferencial.
  • El control de orden fraccionario, particularmente en una configuración adaptativa, ofrece una solución robusta para sistemas autónomos.
  • El algoritmo GWO optimiza eficazmente los parámetros del controlador para mejorar la navegación robótica.