Speed control of DC motor using conventional and adaptive PID controllers

Abstract

<p>Proportional Integral Derivative (PID) controllers are <a href="http://www.thesaurus.com/browse/extensively">extensively</a> used in practical industries to control the speed of DC Motors. The single weakness of PID controllers is their sensitivity to variation in parameters and operating conditions; thus, tuning the controller gains to adapt with these variations presents a practical challenge. In this paper, an adaptive mechanism that utilizes a Recursive Least Square (RLS) algorithm, with rate limiters, is implemented to perform an online self-adjusting of each of the PID gains in order to achieve Adaptive PID (APID) controller that will accommodate to system variations. MATLAB/ Simulink software is used to implement and simulate APID control of a Chopper-Fed DC motor. A conventional PID control system is also designed and simulated to obtain results that can be used to judge the performance of the APID controller. Results proved that the APID controller forced the motor speed to track the reference input with <a href="http://www.thesaurus.com/browse/insignificant">insignificant</a> tracking error, and also managed to attain the motor speed at its desired value, regardless of the load changes inflected on the motor. This enhances both transient and steady-state speed responses.</p>

Liquid slosh control by implementing model-free PID controller with derivative filter based on PSO

“…… . 5 ( ) < 5 ( * ) 6 ( ) < 6 ( * ) * , ℎ (19) Then, the updated velocity for the particle is obtained by (20)…”

“…One of the model-free controller is Proportional-integral-derivative (PID) controller. PID is well known with its reliability and robustness and it has been widely used on the numbers of applications such as in [19][20][21]. Despite PID controller is able to solve those system control problems, the tuning of PID parameters is very tedious task.…”

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“…The goal is to have a short response time, a zero overshoot and a steady state error close to zero. In this end, a multiple objective function that should be used depends mainly on the ITAE and the IAE [37].…”

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“…An error is recognized when there is a difference between these two values. The error translated through a proportional-integral-derivative (PID) controlling algorithm to decide the required acceleration or damping that important for spinning speed integrity [17][18][19]. The feedback control circuit alongside the USB communication is designed and simulated using the Proteus simulation system (Design Suite by Labcenter Electronic "version 8.5").…”