Optimal Tuning of Robust Controller Based on Artificial Bee Colony Algorithm

2012 ◽  
Vol 562-564 ◽  
pp. 1668-1672 ◽  
Author(s):  
Kun Xu ◽  
Ming Yan Jiang
Keyword(s):  
Pid Controller ◽  
Artificial Bee Colony Algorithm ◽  
Artificial Bee Colony ◽  
Proportional Integral Derivative ◽  
Robust Controller ◽  
Optimal Tuning ◽  
Bee Colony ◽  
Constraint Factors ◽  
Controller Performance ◽  
Swarm Intelligence Algorithm

Artificial bee colony algorithm (ABCA) is a novel swarm intelligence algorithm for global optimization. An efficient method based on ABCA is proposed for optimal tuning of robust proportional-integral-derivative (PID) controller in this paper. A multi-objective optimization is applied to balance several constraint factors of controller. Performance of robust PID controller is evaluated by a three-order and time-delay transfer function with 40%, 50% and 60% uncertainty, respectively. Simulation result clearly demonstrates that the designed controller can obtain an optimal tuning and endure parameter fluctuation. From comparisons of robust PID controller in different uncertainties, a conclusion can be obtained that performance of robust PID controller will be worse as the uncertainty increases, even obtain a divergent solution when the uncertainty is more than 60%.

Research on Swarm Intelligence Algorithm with an Artificial Bee Colony Algorithm for Lot Streaming Problem in Job Shop

2014 ◽  
Vol 951 ◽  
pp. 239-244 ◽  
Author(s):  
Xiao Qiang Xu ◽  
De Ming Lei
Keyword(s):  
Swarm Intelligence ◽  
Artificial Bee Colony Algorithm ◽  
Artificial Bee Colony ◽  
Job Shop ◽  
Lot Streaming ◽  
Lot Scheduling ◽  
Bee Colony ◽  
Intelligence Algorithm ◽  
Second Period ◽  
Swarm Intelligence Algorithm

The lot streaming (LS) problem in job shop with equal-size sub-lots and intermittent idling is considered. An effective swarm intelligence algorithm with an artificial bee colony (ABC) algorithm is proposed for the minimization of total penalties of tardiness and earliness. In the first period of ABC, the employed bee phase and the onlooker bee phase are both for lot/sub-lot scheduling. In the second period, the LS conditions are determined in the employed bee phase and the lot/sub-lot is scheduled in the onlooker phase. The worst solution of the swarm is replaced with the elite one every few cycles. Computational results show the promising advantage of ABC.

scholarly journals Optimal PID controller design using artificial bee colony algorithm for robot arm

2021 ◽  
Vol 21 (1) ◽  
pp. 84
Author(s):  
Ghassan A. Sultan ◽  
Muhammed K. Jarjes
Keyword(s):  
Pid Controller ◽  
Artificial Bee Colony Algorithm ◽  
Artificial Bee Colony ◽  
Controller Design ◽  
Dynamic Performance ◽  
Control Process ◽  
Robot Arm ◽  
Bee Colony ◽  
Pid Controller Design ◽  
Best Parameter

<p class="Default"><span>Proportional integral derivation (PID) controller is used in this paper for optimal design, and tuning by zeigler and nichol (ZN) with artificial bee colony algorithm. The best parameter were found using these algorithms for best performance of a robot arm. The advantage of using ABC were highlighted. The controller using the new algorithm was tested for valid control process. Different colony size has been performed for tuning process, settling time, from time domain performance, rise time, overshot, and steady state error with ABC tuning give better dynamic performance than controller using the (ZN).</span></p>

scholarly journals Active vibration control of a horizontal flexible plate structure using intelligent proportional–integral–derivative controller tuned by fuzzy logic and artificial bee colony algorithm

2019 ◽  
Vol 39 (4) ◽  
pp. 1159-1171 ◽  
Author(s):  
M Sukri Hadi ◽  
Intan Z Mat Darus ◽  
M Osman Tokhi ◽  
Mohd Fairus Jamid
Keyword(s):  
Vibration Control ◽  
Artificial Bee Colony Algorithm ◽  
Artificial Bee Colony ◽  
Active Vibration Control ◽  
Flexible Plate ◽  
Proportional Integral Derivative ◽  
Proportional Integral Derivative Controller ◽  
Proportional Integral ◽  
Bee Colony ◽  
Active Vibration

This paper presents the development of an intelligent controller for vibration suppression of a horizontal flexible plate structure using hybrid Fuzzy–proportional–integral–derivative controller tuned by Ziegler–Nichols tuning rules and intelligent proportional–integral–derivative controller tuned by artificial bee colony algorithm. Active vibration control technique was implemented during the development of the controllers. The vibration data obtained through experimental rig was used to model the system using system identification technique based on auto-regressive with exogenous input model. Next, the developed model was used in the development of an active vibration control for vibration suppression of the horizontal flexible plate system using proportional–integral–derivative controller. Two types of controllers were proposed in this paper which are the hybrid Fuzzy–proportional–integral–derivative controller and intelligent proportional–integral–derivative controller tuned by artificial bee colony algorithm. The performances of the developed controllers were assessed and validated. Proportional–integral–derivative–artificial bee colony controller achieved the highest attenuation for first mode of vibration with 47.54 dB attenuation as compared to Fuzzy–proportional–integral–derivative controller with 32.04 dB attenuation. The experimental work was then conducted for the best controller to confirm the result achieved in the simulation work.

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