Abstract
This paper we present Chemical Reaction Optimization (CRO) algorithm for determining optimal parameters of PI controller. The model of doubly fed induction generator (DFIG) is used as a plant in this paper. Tuning PI controller using traditional method such as Ziegler-Nichols (ZN) method usually produces large overshoot and Integral time absolute error, integral absolute error and integral square error performance indices. Therefore, recently researchers have applied random search approach such as genetic algorithm (GA) and particle swarm optimization (PSO) and Grey Wolf Optimizer (GWO) to find optimal parameters for PI controller. Among modern heuristics algorithm, CRO was introduced in 2010, it combines features of both GA and Simulated Annealing (SA) to find global minimum in search space. CRO has been applied to solve successfully many optimization problems such as: Minimum transportation cost, resource-constrained project scheduling problem, channel assignment problem in wireless mesh networks, standard continuous benchmark functions, and so on. In this paper we present to apply CRO algorithm to search optimal parameters for PI controller. The comparison between tuning PI controller by CRO and traditional Ziegler-Nichols method is presented. The simulation results show the advantages of PI tuning using CRO compared to traditional method in terms of performance index and setting time.
Highlights
Proportional Integral and Derivative (PID) controllers have been used in industrial control applications for a long time
By adding a derivative term in to Proportional Integral (PI) controller improves the stability of control loop
In chemical point of view, the chemical reaction begins with some molecules with large energy react with each other through sequence of elementary reactions [6]. They transform to molecules with minimum energy for existence. This nature is implemented in Chemical Reaction Optimization (CRO) algorithm for solving optimization problems
Summary
Proportional Integral and Derivative (PID) controllers have been used in industrial control applications for a long time. This is due to its simplicity, low cost design and robust performance in a wide range of operating conditions. Random search algorithms are widely choose to solve nonlinear optimization problems. CRO is modern meta-heuristics for optimization problem It simulates the nature of chemical reaction. They transform to molecules with minimum energy for existence This nature is implemented in CRO algorithm for solving optimization problems. We use CRO algorithm to find global optimization for parameters of PI controller and compare result with tradition tuning method ZieglerNichols with respect to integral performance indices
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