Title :
A novel method for PID tuning using a modified biogeography-based optimization algorithm
Author :
Sayed, M.M. ; Saad, M.S. ; Emara, H.M. ; Abou El-Zahab, E.E.
Author_Institution :
Dept. of Electr. Power & Machines, Cairo Univ., Cairo, Egypt
Abstract :
Proportional integral derivative (PID) controller tuning is an area of interest for researchers. This paper presents a novel method for PID controller tuning using a modified biogeography-based optimization(MBBO) algorithm. Biogeography-based optimization (BBO) is a novel evolutionary algorithm that is based on the mathematical models of biogeography. Biogeography is the study of the geographical distribution of biological organisms. In the BBO model, problem solutions are represented as islands, and the sharing of features between solutions is represented as immigration and emigration between the islands. In this paper, a modified version of the BBO is proposed to improve its convergence. The MBBO algorithm is compared with the BBO using benchmarks functions. The proposed algorithm is applied to the problem of PID controller tuning and is compared with conventional biogeography-based optimization (BBO), and Particle swarm optimization (PSO).
Keywords :
biocontrol; control system synthesis; evolutionary computation; optimisation; three-term control; PID controller tuning; biological organisms geographical distribution; evolutionary algorithm; modified biogeography-based optimization algorithm; particle swarm optimization; proportional integral derivative controller tuning; Benchmark testing; Biogeography; Cost function; Evolutionary computation; Mathematical model; Tuning; Biogeography-Based Optimizationand PID controller; Process Control; evolutionary algorithm (EA);
Conference_Titel :
Control and Decision Conference (CCDC), 2012 24th Chinese
Conference_Location :
Taiyuan
Print_ISBN :
978-1-4577-2073-4
DOI :
10.1109/CCDC.2012.6244262