PID-Controller Tuning Optimization with Genetic Algorithms in Servo Systems

Jaen-Cuéllar, Arturo Yosimar; Romero-Troncoso, René de Jesús; Morales-Velazquez, Luis; Osornio-Ríos, Roque Alfredo

doi:10.5772/56697

Cited by 96 publications

(55 citation statements)

References 37 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…At present, a number of studies have been carried out on the use of intelligent technologies in power supply systems [1][2][3][4][5][6][7][8][9], and in particular, for solving the problems of controllers parameterization [10][11][12], as well as on developing controllers working on the basis of artificial intelligence technologies [13][14][15][16]. A control system that adjusts AER and ARRS tuning and built on the basis of an adaptive neuro-fuzzy inference system is proposed in this work to improve the stability and reliable integration of the DG plants in EPS.…”

Section: Introductionmentioning

confidence: 99%

Neuro Fuzzy Control system for Distributed Generation Plants

Bulatov¹,

Kryukov²

2018

Proceedings of the VTH International Workshop "Critical Infrastructures: Contingency Management, Intelligent, Agent-Based, Clou

View full text Add to dashboard Cite

The transition of electric power industry to a new technological platform based on the concept of smart power grids with an active-and-adaptive network will allow to increase the efficiency of control, durability and reliability of power supply systems. The idea of applying the intelligent algorithms to control power grids becomes more pressing in case of wide using the distributed generation plants (DGP) and other grid active elements that allow to control power grid operation modes. The article describes the DGP consisting of synchronous generators that operate in various modes and often with poor power supply quality. To provide the parallel operation stability of synchronous turbo/ hydro generators of DGP, automatic excitation regulator (AER) and automatic regulator of rotor speed (ARRS) are used. Due to low inertia constant of distributed generation unit rotors, the problem of matched tuning of AER and ARRS becomes more topical. To increase stability and reliable integration of DGP in power grids, a control system built on a neurofuzzy match system is proposed. The system corrects AER/ ARRS settings. In this case, the following smart technologies were used: genetic algorithm to search optimal settings of AER and ARRS; a neuro-fuzzy network to identify an operation mode of a DGP and power grid; fuzzy interference to correct settings of AER/ ARRS in various modes of DGP operation. Based on modelling done in MATLAB system the efficiency of using the proposed neuro-fuzzy match system to identify DGP operation modes and to adaptively control matched tuning of AER and ARRS of synchronous generators is shown. If using the intellectual control system, one can decrease transition process time, generator voltage / frequency overcontrol, as well as provide reliability and durability of a power system in various operation modes of a DGP and power grids.

show abstract

Section: Introductionmentioning

confidence: 99%

Neuro Fuzzy Control system for Distributed Generation Plants

Bulatov¹,

Kryukov²

2018

Proceedings of the VTH International Workshop "Critical Infrastructures: Contingency Management, Intelligent, Agent-Based, Clou

View full text Add to dashboard Cite

show abstract

“…In particular, as the damping ratios usually have a very small value, the accurate estimation of the damping ratio is a complicated issue [32]. In the literature, many problems that involve the search and selection of the best-suited parameters for specific models have been solved by means of optimization algorithms, where genetic algorithms (GA) have demonstrated to be an efficient tool for solving these problems [33].…”

Section: Introductionmentioning

confidence: 99%

A Two-Step Strategy for System Identification of Civil Structures for Structural Health Monitoring Using Wavelet Transform and Genetic Algorithms

et al. 2017

View full text Add to dashboard Cite

Nowadays, the accurate identification of natural frequencies and damping ratios play an important role in smart civil engineering, since they can be used for seismic design, vibration control, and condition assessment, among others. To achieve it in practical way, it is required to instrument the structure and apply techniques which are able to deal with noise-corrupted and non-linear signals, as they are common features in real-life civil structures. In this article, a two-step strategy is proposed for performing accurate modal parameters identification in an automated manner. In the first step, it is obtained and decomposed the measured signals using the natural excitation technique and the synchrosqueezed wavelet transform, respectively. Then, the second step estimates the modal parameters by solving an optimization problem employing a genetic algorithm-based approach, where the micropopulation concept is used to improve the speed convergence as well as the accuracy of the estimated values. The accuracy and effectiveness of the proposal are tested using both the simulated response of a benchmark structure and the measurements of a real eight-story building. The obtained results show that the proposed strategy can estimate the modal parameters accurately, indicating than the proposal can be considered as an alternative to perform the abovementioned task.

show abstract

“…Singh and Sharma have proposed a fractional order PID controller with a PSO approach, providing better servo and regulatory response [24]. The combined PID control tuning by coupling the gain-phase margin method with genetic algorithm has been applied for position control in a servo system [25]. A virtual feedback control has been implemented to control the state variables using extended Kalman filter (EKF) in the feedback path using particle swarm optimization technique for CSTR process [7].…”

Section: Introductionmentioning

confidence: 99%

Genetic Algorithm Based PID Controller Tuning Approach for Continuous Stirred Tank Reactor

Jayachitra¹,

Vinodha

2014

Advances in Artificial Intelligence

139

View full text Add to dashboard Cite

Genetic algorithm (GA) based PID (proportional integral derivative) controller has been proposed for tuning optimized PID parameters in a continuous stirred tank reactor (CSTR) process using a weighted combination of objective functions, namely, integral square error (ISE), integral absolute error (IAE), and integrated time absolute error (ITAE). Optimization of PID controller parameters is the key goal in chemical and biochemical industries. PID controllers have narrowed down the operating range of processes with dynamic nonlinearity. In our proposed work, globally optimized PID parameters tend to operate the CSTR process in its entire operating range to overcome the limitations of the linear PID controller. The simulation study reveals that the GA based PID controller tuned with fixed PID parameters provides satisfactory performance in terms of set point tracking and disturbance rejection.

show abstract

PID-Controller Tuning Optimization with Genetic Algorithms in Servo Systems

Cited by 96 publications

References 37 publications

Neuro Fuzzy Control system for Distributed Generation Plants

Neuro Fuzzy Control system for Distributed Generation Plants

A Two-Step Strategy for System Identification of Civil Structures for Structural Health Monitoring Using Wavelet Transform and Genetic Algorithms

Genetic Algorithm Based PID Controller Tuning Approach for Continuous Stirred Tank Reactor

Contact Info

Product

Resources

About