Enhanced chaotic spiral dynamic algorithm with application to controller design

Abstract

This paper present an enhanced chaotic spiral dynamic algorithm (ECSDA) for optimization problems and their application in single link flexible manipulator system (SLFMS). The algorithm is developed by integrating logistic chaotic pattern into the original spiral dynamic algorithm (SDA). The artificial bee colony optimization (ABC) searching method is also adopted in ECSDA to increase its capability to find the best possible local optimum solution. This hybrid technique reduces the probability of ECSDA getting trapped at local optimum. ECSDA is used to optimize the PD controller parameters of a single link flexible manipulator system (SLFMS). The results show that the ECSDA outperforms the SDA with improved search capability and escaping local optima and is able to tune the PD controller of SLFMS for the desired output.