- author = "Iman Gholaminezhad and Ali Jamali and Hirad Assimi",
- booktitle = "Second RSI/ISM International Conference on Robotics and Mechatronics (ICRoM 2014)",
- title = "Automated synthesis of optimal controller using multi-objective genetic programming for two-mass-spring system",
- year = "2014",
- month = oct,
- pages = "041--046",
- abstract = "There are much research effort in the literature using genetic programming as an efficient tool for design of controllers for industrial systems. In this paper, multi-objective uniform-diversity genetic programming (MUGP) is used for automated synthesis of both structure and parameter tuning of optimal controllers as a many-objective optimisation problem. In the proposed evolutionary design methodology, each candidate controller illustrated by a transfer function, whose optimal structure and parameters, obtained based on performance optimisation of each candidate controller. The performance indices of each controller are treated as separate objective functions, and thus solved using the multi-objective method of this work. A two-mass-spring system is considered to show the efficiency of the proposed method using performance optimisation of open loop and closed loop control system characteristics. The results show that the proposed method is a computationally efficient framework compared to other methods in the literature for automatically designing both structure and parameter tuning of optimal controllers.",
- keywords = "genetic algorithms, genetic programming",
-
DOI = "
doi:10.1109/ICRoM.2014.6990874",
-
notes = "Dept. of Mech. Eng., Univ. of Guilan, Rasht, Iran
Also known as \cite{6990874}",
