@inproceedings{scholars8044,
       publisher = {Institute of Electrical and Electronics Engineers Inc.},
          volume = {2017-D},
            note = {cited By 1; Conference of 3rd IEEE International Symposium in Robotics and Manufacturing Automation, ROMA 2017 ; Conference Date: 19 September 2017 Through 21 September 2017; Conference Code:134001},
         journal = {2017 IEEE 3rd International Symposium in Robotics and Manufacturing Automation, ROMA 2017},
            year = {2017},
             doi = {10.1109/ROMA.2017.8231739},
           title = {Development of a nature inspired algorithm based controller for DC servo motor},
           pages = {1--5},
            isbn = {9781538625392},
             url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85048391327&doi=10.1109\%2fROMA.2017.8231739&partnerID=40&md5=14879c60ae165550063b8d9bb2df9722},
        abstract = {Proportional-Integral-Derivative (PID) controller is incorporated in Direct-Current (DC) servo motor control application due to its efficiency and ease of implementation. Nevertheless, the existing PID tuning methods are time consuming, and yet expertise and experience are required. Therefore, new approaches to tune PID controller is very important with the aim of obtaining better performances. The objective of this research is to investigate nature inspired algorithms used in PID controller tuning optimization. The simulation results show that both meta-heuristic algorithms Simulated Annealing (SA) and Differential Evolution (DE) based PID controller produce better performance compared with Ziegler Nichols (ZN) PID controller. {\^A}{\copyright} 2017 IEEE.},
          author = {Kok, L. Y. and Elamvazuthi, I. and Ramani, K.},
        keywords = {Controllers; Electric control equipment; Electric machine control; Evolutionary algorithms; Heuristic algorithms; Manufacture; Proportional control systems; Robotics; Simulated annealing; Three term control systems; Two term control systems, Differential Evolution; Its efficiencies; Meta heuristic algorithm; Nature inspired algorithms; Pid controller tuning; PID controllers; Proportional integral derivative controllers; Servo motor control, DC motors}
}