Design and Optimization of Fractional Order PIλ Dµ Controller Using Grey Wolf Optimizer for Automatic Voltage Regulator System

Author(s): Santosh Kumar Verma*, Shyam Krishna Nagar.

Journal Name: Recent Advances in Electrical & Electronic Engineering
Formerly Recent Patents on Electrical & Electronic Engineering

Volume 11 , Issue 2 , 2018

Become EABM
Become Reviewer

Graphical Abstract:


Background: This paper presents a novel optimized Fractional-Order Proportional-Integral Derivative (FOPID) controller for controlling the terminal voltage of an automatic voltage regulator system. The parameters of the proposed controller are optimized using a recent meta-heuristic technique known as Grey Wolf Optimizer (GWO).

Methods: A recent meta-heuristic technique known as Grey Wolf Optimizer (GWO) is used for fine tuning of FOPID controller parameters. Initial values of proportional gain (Kp), integral gain (Ki), and derivative gain (Kd) of the controller are tuned using Ziegler-Nichols (ZN) method where values of λ and µ are chosen randomly. A nonlinear fitness function consisting of rise-time, settling-time, maximum-overshoot and Integral of Time Square Error (ITSE) has been chosen as the fitness function for the proposed algorithm to get the optimum solution.

Results: The proposed FOPID controller provides faster response (i.e. minimum rise-time (0.0292 sec.)), minimum settling time (0.1107sec.) and desired frequency domain characteristics (Gain margin=25.2, Phase margin=60.2).

Conclusion: The proposed FOPID controller provide faster and better control action for AVR system. Additionally, it also improves the robustness of the system with respect to model uncertainties. Simulation results are validated with the existing techniques in the literature with the help of figures and also summarised in tables.

Keywords: Automatic voltage regulator, Integer order PID controller, grey wolf optimizer, fractional order control, fractional calculus, PID controller.

Rights & PermissionsPrintExport Cite as

Article Details

Year: 2018
Page: [217 - 226]
Pages: 10
DOI: 10.2174/2352096511666180124150326
Price: $58

Article Metrics

PDF: 16