Pradeep Kumar Mohanty

Design and performance analysis of PID controller for an automatic voltage regulator system using simplified particle swarm optimization

Abstract This paper presents the design and performance analysis of Proportional Integral Derivate (PID) controller for an Automatic Voltage Regulator (AVR) system using recently proposed simplified Particle Swarm Optimization (PSO) also called Many Optimizing Liaisons (MOL) algorithm. MOL simplifies the original PSO by randomly choosing the particle to update, instead of iterating over the entire swarm thus eliminating the particles best known position and making it easier to tune the behavioral parameters. The design problem of the proposed PID controller is formulated as an optimization problem and MOL algorithm is employed to search for the optimal controller parameters. For the performance analysis, different analysis methods such as transient response analysis, root locus analysis and bode analysis are performed. The superiority of the proposed approach is shown by comparing the results with some recently published modern heuristic optimization algorithms such as Artificial Bee Colony (ABC) algorithm, Particle Swarm Optimization (PSO) algorithm and Differential Evolution (DE) algorithm. Further, robustness analysis of the AVR system tuned by MOL algorithm is performed by varying the time constants of amplifier, exciter, generator and sensor in the range of −50% to +50% in steps of 25%. The analysis results reveal that the proposed MOL based PID controller for the AVR system performs better than the other similar recently reported population based optimization algorithms.

Teaching-learning based optimization algorithm based fuzzy-PID controller for automatic generation control of multi-area power system

Fuzzy-PID controller is proposed for AGC of multi-area power system.TLBO algorithm is applied to optimize the parameters of fuzzy-PID controller.The superiority of proposed approach over LCOA, GA, PS and SA based PID controller is shown.Robustness analysis is performed under wide changes in system parameters and disturbance. This paper deals with the design of a novel fuzzy proportional-integral-derivative (PID) controller for automatic generation control (AGC) of a two unequal area interconnected thermal system. For the first time teaching-learning based optimization (TLBO) algorithm is applied in this area to obtain the parameters of the proposed fuzzy-PID controller. The design problem is formulated as an optimization problem and TLBO is employed to optimize the parameters of the fuzzy-PID controller. The superiority of proposed approach is demonstrated by comparing the results with some of the recently published approaches such as Lozi map based chaotic optimization algorithm (LCOA), genetic algorithm (GA), pattern search (PS) and simulated algorithm (SA) based PID controller for the same system under study employing the same objective function. It is observed that TLBO optimized fuzzy-PID controller gives better dynamic performance in terms of settling time, overshoot and undershoot in frequency and tie-line power deviation as compared to LCOA, GA, PS and SA based PID controllers. Further, robustness of the system is studied by varying all the system parameters from -50% to +50% in step of 25%. Analysis also reveals that TLBO optimized fuzzy-PID controller gains are quite robust and need not be reset for wide variation in system parameters.

Tuning and Assessment of Proportional–Integral–Derivative Controller for an Automatic Voltage Regulator System Employing Local Unimodal Sampling Algorithm

Abstract—This article presents an approach for obtaining proportional–integral–derivative controller parameters for an automatic voltage regulator system based on a local unimodal sampling optimization algorithm. A conventional integral time of squared error objective function and modified objective functions in terms of integral time of absolute error, integral of absolute error, integral of squared error, peak overshoot, and settling time with appropriate weighting factors are employed to tune the controller parameters. Different objective functions are employed to obtain optimized proportional–integral–derivative controller gains. Superiority of proposed technique over some recently published modern heuristic optimization techniques, such as artificial bee colony algorithm, particle swarm optimization algorithm, and differential evolution algorithm, for the same automatic voltage regulator system is demonstrated. Simulation results reveal that the proposed proportional–integral–derivative controlled automatic voltage regulator system tuned by the local unimodal sampling algorithm with modified objective function exhibits better performance in terms of settling time, peak overshoot, and stability. The robustness of the system tuned by the proposed algorithm is also studied satisfactorily by varying the time constants of the automatic voltage regulator system in the range of –50% to +50% in steps of 25%.

Robust analysis and design of PID controlled AVR system using Pattern Search algorithm

This paper has been presented in keeping the view of optimal design of a Proportional-Integral-Derivative (PID) controller based on Pattern Search (PS) Optimization algorithm. In order to determine the optimum parameters of the PID controller for an automatic voltage regulator (AVR) system in a 3-ph generator this meta-heuristic algorithm is used. In this paper, the objective function is expressed as a function of Integral Time Absolute Error (ITAE), damping ratio, settling time, peak time and the peak value of the amplitude of the wave. The proposed method is found to be better than Artificial Bee Colony (ABC) algorithm with objective function as Integral Time Square Error (ITSE). It has been observed that different parameters of the AVR system such as settling time, peak time, rise time, oscillations and overshoot improve drastically. The AVR systems results were analyzed by different methods like of transient analysis, root locus analysis and bode analysis. Moreover, the results obtained by the simulation derive that the AVR tuned by Pattern Search algorithm are highly better and robust.

Design and comparative performance analysis of PID controlled automatic voltage regulator tuned by many optimizing liaisons

This paper deals with the design of Proportional, Integral, and Derivative (PID) controller to an Automatic Voltage Regulator (AVR) tuned by recently developed Simplified Particle Swarm Optimization algorithm so called, Many Optimizing Liaisons (MOL) algorithm. MOL simplifies the original PSO by randomly choosing the particle to update, instead of iterating over the entire swarm thus eliminating the particles best known position and making it easier to tune the behavioural parameters. The proposed method is compared with the earlier used PSO algorithm. For performance studies; Transient response analysis, Bode plot analysis and Root locus analysis are explained in details. The robustness analysis is done by varying the time constants of amplifier, exciter, generator & sensor in the range of -50% to + 50% with a step size of 25% respectively. The results of these analyses using the MOL algorithm are found to be better with respect to the analysis of the PID controller using PSO algorithm.

Automatic voltage regulator using TLBO algorithm optimized PID controller

This paper deals with design and analysis of AVR using proportional-integral-derivative (PID) controller optimized by Teaching Learning Based Optimization (TLBO) algorithm The optimum gain of the controller for the proposed model is obtained with objective function as Integral Time Absolute Error (ITAE). The performance of the system is found to be better in every aspect in terms of the settling point, rise point & peak overshoot. By changing the different components of AVR (sensor, generator, exciter & amplifier) by ±50 % robustness analysis is performed.

Optimal Load Frequency Control of an Unified Power System with SMES and TCPS

TCPS (Thyristor-controlled phase shifter) and SMES (Super Conducting Magnetic Storage) are implemented in this research work to regulate the frequency of an interlocked two area power system. Two distinct PD + PID double-loop controller is recommended in each area for frequency regulation in the scrutinized system. The optimum controller gains are obtained using firefly algorithm considering ISE (Integral Square Error) as objective function. The system responses of this suggested model is examined by introducing a rapid load variation of 0.1 pu in area 1. The supremacy of the recommended PD + PID controller is established over PID controller considering several time response indices like peak overshoots, settling time and minimum undershoots. The toughness of the proposed system is also verified by amplifying the loading of the system.

SOS Algorithm Tuned PID/FuzzyPID Controller for Load Frequency Control with SMES

The article presents a newly advanced, novel and proficient symbiotic organism search optimization technique to resolve the stability problem of a power system. A two area reheat based thermal system is considered with the SOS tuned proportional-integral-derivative controller along with fuzzy-PID (FPID) controller separately. The supremacy of this designed power system is verified by introducing a disturbance on load of 0.15 p.u. in one control zone. The validation of the implemented SOS technique is analyzed by doing a comparison with the dynamic responses of the FPID controller over a two area reheat based thermal power system. Finally, a profound verification is achieved to analyze the robustness and non-linearity of the modeled controller by subjecting a 5% of generation rate constraints (GRCs) to the designed system with the existance of superconducting magnetic energy storage.

Design and Implementation of Whale Optimization Algorithm Based PIDF Controller for AGC Problem in Unified System

Design aspect of controller mechanism to regulate the load frequency in an interconnected generating system is usually regarded as an optimization issue with various constraints. As per the need of the designer, the controller must be designed to fulfill the desired requirements to yield a suitable solutions. This paper presents whale optimization algorithm (WOA) based conventional proportional integral derivative type controller where a filter is employed in the derivative part of the controller for a two area combined thermal power system. The derivative filter is included here to reduce the unwanted signal in the input side of the controller. In the optimization process time based error function is taken as fitness function (ITAE) for designing controller parameters. The performance ability of the controller is modeled with MATLAB Simulink package. The efficiency and dominace of recommended WOA tuned PIDF controller is compared with Jaya based PIDF controller using time domain simulations which validates the effectiveness of WOA based proposed controller employed in the aforesaid dual area combined power system.

Performance evaluation of DEPSO algorithm on automatic voltage regulator using conventional PID & Fuzzy-PID controller

This paper describes about the design and scrutiny of AVR using three different controllers namely Fuzzy-PID, PID-N & PID. The proposed system is optimized using novel DEPSO algorithm tuned by aforementioned three controllers. Objective function for the AVR system is taken as Integral Time Absolute Error (ITAE). The dynamic response of the system is obtained. Finally it is being observed that FPID proves better in terms of peak overshoot & settling time than the other two. The robustness analysis is by varying time constants by ± 50 %.