Optimization of Fuzzy PID Controller's Parameters

Kudinov, Y.I.; Колесников, В. А.; Olaverri-Monreal, Cristina; Пащенко, А.Ф.; Papic, L.

doi:10.1016/j.procs.2017.01.086

Cited by 44 publications

(21 citation statements)

References 2 publications

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“…Posteriormente, para probar todo el modelo de la planta y del control, utiliza Matlab/Simulink y las librerías de lógica difusa, llevando la información recolectada a un arduino quien es realimentado con las señales del encoder y del control de velocidad de los motores. Finalmente, (Parikh 2018 [42]. Debido a esto, (Kudinov 2017) [42] propone un método simple de controladores, particularmente el PID difuso, con el uso de Matlab, adicionándoles ciertas disposiciones del método de linealización difusa, dividiendo a su vez este procedimiento en tres pasos: Identificación del controlador difuso, estimación de los coeficientes del controlador difuso y finalmente, construcción de un sistema de control digital.…”

Section: Figuraunclassified

Vehículos de guiado autónomo (AGV) en aplicaciones industriales: una revisión

Moreno

Ceballos

2019

Rev. politec.

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Se presenta una revisión del estado del arte de vehículos de guiado autónomo (AGV por sus siglas en inglés: Automated Guided Vehicle) para el transporte de objetos y materia prima en aplicaciones industriales. La revisión de literatura hace énfasis en varios aspectos como la identificación del lugar, aplicación en diferentes entornos, control del vehículo y descripción de los sistemas de software usados para la programación de los robots móviles, de acuerdo a los requisitos o necesidades a resolver. Adicionalmente, se hace un análisis, con base a las referencias citadas, del aporte que hace este tipo de tecnologías no solo a la industria, sino también a otros tipos de modelo de negocio, como lo son el área de la salud, los sistemas de transporte urbano, entre otros.

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Section: Figuraunclassified

Vehículos de guiado autónomo (AGV) en aplicaciones industriales: una revisión

Moreno

Ceballos

2019

Rev. politec.

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“…The control parameters are tuned to achieve stable closed-loop response of the system and reach desired positions within a certain time. Several approaches have been proposed to optimize the PID controller parameters, such as Zeigler-Nichols, a classical method to tune PID control parameters [5], fuzzy logic controller [6,7] and evolutionary algorithms such as genetic algorithm (GA) [8], and swarm optimization algorithms such as ant colony algorithm (ACO) [9], particle swarm optimization (PSO) [10] and artificial bee colony (ABC) algorithm [11].…”

Section: Introductionmentioning

confidence: 99%

Optimized Proportional-Integral-Derivative Controller for Upper Limb Rehabilitation Robot

et al. 2019

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This paper proposes a nature inspired, meta-heuristic optimization technique to tune a proportional-integral-derivative (PID) controller for a robotic arm exoskeleton RAX-1. The RAX-1 is a two-degrees-of-freedom (2-DOFs) upper limb rehabilitation robotic system comprising two joints to facilitate shoulder joint movements. The conventional tuning of PID controllers using Ziegler-Nichols produces large overshoots which is not desirable for rehabilitation applications. To address this issue, nature inspired algorithms have recently been proposed to improve the performance of PID controllers. In this study, a 2-DOF PID control system is optimized offline using particle swarm optimization (PSO) and artificial bee colony (ABC). To validate the effectiveness of the proposed ABC-PID method, several simulations were carried out comparing the ABC-PID controller with the PSO-PID and a classical PID controller tuned using the Zeigler-Nichols method. Various investigations, such as determining system performance with respect to maximum overshoot, rise and settling time and using maximum sensitivity function under disturbance, were carried out. The results of the investigations show that the ABC-PID is more robust and outperforms other tuning techniques, and demonstrate the effective response of the proposed technique for a robotic manipulator. Furthermore, the ABC-PID controller is implemented on the hardware setup of RAX-1 and the response during exercise showed minute overshoot with lower rise and settling times compared to PSO and Zeigler-Nichols-based controllers.

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“…The usage of fuzzy logic associated with CPID controller in [11] with an optimized controller's parameters. In [12], the FPID controller was employed for dual axis turntable servo system. Improved FPID controller is design using predictive functional control structure [13].…”

Section: Introductionmentioning

confidence: 99%

Performance enhancement of split-phase induction motor by using fuzzy-based PID controller

Abdelwanis

El‐Sehiemy

2019

Journal of Electrical Engineering

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This paper presents control and analysis of a split-phase induction motor (SPIM) to drive a centrifugal pumping system. An optimized proportional- integral and derivative (PID) controller, that is capable with a vector closed-loop split-phase induction motor control, is presented and its simulation results are discussed. The fine-tuning procedure is employed for fuzzy PID (FPID) controller parameters in order to sustain the motor speed at the predefined reference values. To assess the performance of the competitive controllers, conventional PID (CPID) and FPID, four operational indices for are suggested for measure the capability of the two controllers. These indices involve individual steady state error (ISSE) for each operating period, total steady state error (TSSE) for overall loading cycle, Individual oscillation index (IOI) and Total oscillation index (TOI), in order to measure the capability of the FPID compared with CPID. The performance of the SPIM accomplished with these performance indices is checked and tested on high and low speed levels. Pulse width modulation (PWM) based simulation studies were employed for SPIM using MATLAB/SIMULINK software. The results show that the overall performance of the SPIM operated with vector control that is tuned by FPID is enhanced compared with CPID.

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Optimization of Fuzzy PID Controller's Parameters

Cited by 44 publications

References 2 publications

Vehículos de guiado autónomo (AGV) en aplicaciones industriales: una revisión

Vehículos de guiado autónomo (AGV) en aplicaciones industriales: una revisión

Optimized Proportional-Integral-Derivative Controller for Upper Limb Rehabilitation Robot

Performance enhancement of split-phase induction motor by using fuzzy-based PID controller

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