In this study, Artificial Bee Colony (ABC) algorithm is applied to the Automatic Voltage Regulator (AVR) system for obtaining optimal control. The tuning performance of this algorithm and its contribution to the robustness of the control system are also extensively and comparatively investigated. In the performance analysis, Particle Swarm Optimization (PSO) algorithm and Differential Evolution (DE) algorithm are used for the purpose of comparison. These analyses are realized by benefiting from different analysis methods such as transient response analysis, root locus analysis, bode analysis and statistically Receiver Operating Characteristic (ROC) analysis. Afterwards, the robustness analysis is applied to the AVR system, which is tuned by ABC algorithm in order to determine its response to changes in the system parameters. At the end of the study, it is shown that the ABC algorithm is successfully applied to the AVR system for improving the performance of the controller and shows a better tuning capability than the other similar population based optimization algorithms for this control application.

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Comparative performance analysis of artificial bee colony algorithm for automatic voltage regulator (AVR) system

Fractional-order PID (FOPID) controller is a generalization of standard PID controller using fractional calculus. Compared to PID controller, the tuning of FOPID is more complex and remains a challenge problem. This paper focuses on the design of FOPID controller using chaotic ant swarm (CAS) optimization method. The tuning of FOPID controller is formulated as a nonlinear optimization problem, in which the objective function is composed of overshoot, steady-state error, raising time and settling time. CAS algorithm, a newly developed evolutionary algorithm inspired by the chaotic behavior of individual ant and the self-organization of ant swarm, is used as the optimizer to search the best parameters of FOPID controller. The designed CAS-FOPID controller is applied to an automatic regulator voltage (AVR) system. Numerous numerical simulations and comparisons with other FOPID/PID controllers show that the CAS-FOPID controller can not only ensure good control performance with respect to reference input but also improve the system robustness with respect to model uncertainties.

Optimum design of fractional order PIλDµ controller for AVR system using chaotic ant swarm

PID controller for automatic voltage regulator using teaching–learning based optimization technique

Chaotic multi-objective optimization based design of fractional order PIλDμ controller in AVR system

This paper proposes a novel tuning design of proportional integral derivative (PID) controller via an improved kidney-inspired algorithm (IKA) with a new objective function. The main objective of the proposed approach is to optimize the transient response of the AVR system by minimizing the maximum overshoot, settling time, rise time and peak time values of the terminal voltage, and eliminating the steady state error. After obtaining the optimal values of the three gains of the PID controller (KP, KI, and KD) with the proposed approach, the transient response analysis was performed and compared with some of the current heuristic algorithms-based approaches in literature to show the superiority of the optimized PID controller. In order to evaluate the stability of the automatic voltage regulator (AVR) system tuned by IKA method, the pole/zero map analysis and Bode analysis are performed. Finally, the robustness analysis of the proposed approach has been carried out with variations in the parameters of the AVR system. The numerical simulation results demonstrated that the proposed IKA tuned PID controller has better control performances compared to the other existing approaches. The essence of the presented study points out that the proposed approach may successfully be applied for the AVR system.

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Improved Kidney-Inspired Algorithm Approach for Tuning of PID Controller in AVR System

This paper presents a novel design method for determining the optimal PID controller parameters of an automatic voltage regulator (AVR) system using the chaotic ant swarm (CAS) algorithm. In the tuning process of parameters, the CAS algorithm is iterated to give the optimal parameters of the PID controller based on the fitness theory, where the position vector of each ant in the CAS algorithm corresponds to the parameter vector of the PID controller. The proposed CAS-PID controllers can ensure better control system performance with respect to the reference input in comparison with GA-PID controllers. Numerical simulations are provided to verify the effectiveness and feasibility of PID controller based on CAS algorithm.

Yu Guo

Papers

CAS algorithm-based optimum design of PID controller in AVR system