Development of a tool for tuning in matlab PID controllers, using genetic algorithms based on optimization techniques multiobjective
Vol. 1 No. 1 (2014), Las TIC aplicadas a la industria
Vol. 1 No. 1 (2014)

Development of a tool for tuning in matlab PID controllers, using genetic algorithms based on optimization techniques multiobjective

Las TIC aplicadas a la industria
https://doi.org/10.23850/23899573.86
Brayan René Acevedo Jaimes
Juan Camilo Fonseca Galindo
July Andrea Gómez Camperos
PDF (Español (España))

Keywords

Genetic Algorithms
Multiobjective Optimization
PID
MatLab
Controller Tuning Algoritmos genéticos
Optimización multiobjetivo
Controlador PID
Matlab
Sintonización

How to Cite

Acevedo Jaimes, B. R., Fonseca Galindo, J. C., & Gómez Camperos, J. A. (2014). Development of a tool for tuning in matlab PID controllers, using genetic algorithms based on optimization techniques multiobjective. Revista Sennova: Revista Del Sistema De Ciencia, Tecnología E Innovación, 1(1), 80–103. https://doi.org/10.23850/23899573.86
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Abstract

This document shows the versatility and efficiency by the development of a tool in Matlab for tuning proportional, integral and derivative controller (PID) using genetic algorithms (GA), based techniques for multiobjective optimization (MOP) based on Pareto fronts, calculating optimally constant proportional gain, integral gain and derivative gain (KP, KI, KD) for error minimization, mitigation of the maximum overshoot and settling time reduction in a given plant. Performance that is implementing genetic algorithms provide solutions to multiple targets in PID controllers, the tuning of existing PID controllers Sisotool Matlab compares different control systems closed loop formed by a transfer function is simulated, the controller and feedback loop.

In these systems the behavior that drivers have to pass on a stair at the entrance to the ground is analyzed. With the realization of this tool is to optimize the shape of tuning PID controllers currently in use, today there is no tool to help structurally the tuning process without using a complex programming level and extensive knowledge in control, the use and integration of a number of techniques that allow a more versatile and efficient tool, usable in the task of tuning PID controllers which can simulate and calibrate by methods of evolutionary computational intelligence without have profound knowledge of programming.

https://doi.org/10.23850/23899573.86
PDF (Español (España))

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