New opposition cuttlefish optimizer based two-step approach for optimal design of fractional order proportional integral derivative controller for time delay systems

摘要

In this article, an optimal design of the fractional order proportional integral derivative (FOPID) controller for time delay system is proposed. The proposed optimal design is the combined performance of both the cuttlefish optimizer (CFO) and Opposition-based learning (OBL) scheme called CFOBL scheme. The proposed CFOBL uses the concept of opposition based population initialization and opposition based position updating to improve its searching behavior, computational speed and convergence profile in the basic CFO. In FOPID controller, apart from the three tuning parameters (G(P), G(I), and G(D)) there are two additional tuning parameters that are lambda and mu. Here, CFOBL is used to tune the three controller parameters and also to find the optimal values of lambda and mu. The uniqueness of the proposed technique is to reduce the FOPID controller's fault in the higher order time delay scheme by the aid of the controller's increase limits. The objective of the proposed technique is chosen by considering the set point parameters and the accomplished parameters from the time delay system. The proposed technique is used to avoid high-order delays and reliability constraints such as small overruns, time resolution and fixed condition defects. This technique is performed on the MATLAB/Simulink platform and the results are compared with different existing techniques such as Ziegler-Nichols (ZN) tuning method, curve fitting (CF) technique, Wang technique, and regression technique.