Application of Genetic Programming for Fine Tuning PID Controller Parameters Designed Through Ziegler-Nichols Technique

Almeida, Gustavo Maia de; Silva, Valceres Vieira Rocha e; Nepomuceno, Erivelton G.; Yokoyama, Ryuichi

doi:10.1007/11539902_37

Cited by 13 publications

(9 citation statements)

References 6 publications

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“…We then establish reasonable boundaries for each parameter so as to prevent unreasonable parameters. This is similar to the approach carried out in [17].…”

Section: Planned Implementation On the Uavmentioning

confidence: 63%

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A novel bacterial foraging algorithm for automated tuning of PID controllers of UAVs

Oyekan

2010

The 2010 IEEE International Conference on Information and Automation

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Up to now, PID controllers have been widely deployed in Unmanned Aerial Vehicles (UAVs) and other automatical control systems, and have the benefit of simple tuning performed by trial and error. Their applications avoid some complicated modeling efforts however tuning these controllers do need experienced operators and may sometimes be time consuming. This paper presents a novel approach that could be used for the automatic tuning of a PID controller for a UAV. This approach relies on the bacteria foraging technique to guide the search for the optimal parameters of a PID controller in the parameters search space. Experimental results show that the proposed approach is able to improve the parameters chosen by the classical Ziegler Nicholas method.

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“…We then establish reasonable boundaries for each parameter so as to prevent unreasonable parameters. This is similar to the approach carried out in [17].…”

Section: Planned Implementation On the Uavmentioning

confidence: 63%

“…Where I ZN is the integral parameter value chosen by the Ziegler Nicholas approach of tuning as in [17]. The variable randAngle is a uniformly distributed random number generator producing numbers between 0 and 360.…”

Section: B Modifications To the Berg And Brown Modelmentioning

confidence: 99%

A novel bacterial foraging algorithm for automated tuning of PID controllers of UAVs

Oyekan

2010

The 2010 IEEE International Conference on Information and Automation

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show abstract

“…Figure 4 represent a block diagram of the feedback control system based on genetic PID controller. The controller parameters are tuned by genetic algorithms starting from initial population (Almeida et al, 2005), which is generated randomly and now it is important to calculate the fitness of each chromosome in the population (save best fit individual from the initial population). This is achieved by setting these values to the PID controller, to test the system output response by using unit step input signal as shown in Fig.…”

Section: Genetic Controller Algorithmmentioning

confidence: 99%

“…Genetic algorithms (GAs) are one of the efficient tools that are employed in solving optimization problems (Rothlauf, 2006). Because of the simplicity and robustness, PID controllers are frequently the used controllers in industries (Almeida et al, 2005). Parameters adjustment of PID controllers is an old challenge in the field of control system design.…”

Section: Introductionmentioning

confidence: 99%

“…Some of methods have been proposed to select the PID coefficients, but they are not completely systematic methods and result in a poorly tuned controller that needs some trail and error. So far, finding new methods to automatically select PID parameters was interest of researches (Ho, 2003), (Almeida et al, 2005), (Nasri et al, 2007), and (Mansour, 2011). However in this chapter, the selection of optimal PID controller coefficients are introduced and applied based on genetic algorithms technique.…”

Section: Introductionmentioning

confidence: 99%

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