FOPID controller optimization based on SIWPSO-RBFNN algorithm for fractional-order time delay systems

Perng, Jau-Woei; Chen, Guan-Yan; Hsu, Ya-Wen

doi:10.1007/s00500-016-2050-0

Cited by 14 publications

(6 citation statements)

References 26 publications

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“…The enhancement of the method is observed. Jau-Woei Perng et al, [27] demonstrates the recognition of optimal controller gain for the Fractional Order Proportional Integral Derivative (FOPID) controller based on the Stochastic Inertia Weight Particle Swarm Optimization (SIWPSO) algorithm andRadial Basis Function Neural Network (RBFNN) techniques. The 3D stability regions such as , and factor space are given in the grsaphic representation.…”

Section: Related Workmentioning

confidence: 99%

Flower Pollination Optimization Based PID Controller Tuning Scheme With Robust Stabilization of Gain Scheduled CSTR

Sudha

Subbulekshmi

2020

1790-5044

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In the area of chemical and control engineering, Continuous Stirred Tank Reactor (CSTR) has been deliberated as a most important topic in temperature process control and it is a extremely nonlinear process, which displays stability only in definite regions and unsteadiness in other regions. In this CSTR, Proportional Integral Derivative (PID) controller has been used to minimize the Integral SquareError (ISE) by adjustment of control parameters like k_p,k_i and k_d.But, this conventional controller has high computational complexity, so to reduce this, the optimization based tool has been designed for PID and it was conceptually simple.Earlier, the Genetic Algorithm (GA) optimization has been focused, but it was not guarantee for good fitness and global optimal solution. So to overcome this, here, Flower Pollination based Global Optimization Algorithm (FPGOA) with Gain scheduling based PID controller is proposed for CSTR. When a plant is exposing to big changes in its operational state, the Gain scheduling has been used. The FPGOA is used for tuning the parameters of PID controller for each region to reduce the ISE. The fuzzy gain scheduler has been combined with multiple local linear PID controllers to check the stability of loop for entire regions with various levels of temperatures. This scheduling is an exceptional form of fuzzy control, which customs linguistic rules and fuzzy perceptive to establish the controller factor transition strategy for the dynamic plant dependent on high changes in its operational state to improve the optimization. MATLAB results demonstrate that the feasibility of using the proposed PID controller compared than existing controller, and it shows the FPGOA attained better results, due to the effectual fitness and global optimal solution for the dynamical nonlinear control of CSTR. The response curves of these systems has been generated and compared with existing schemes.

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Section: Related Workmentioning

confidence: 99%

Flower Pollination Optimization Based PID Controller Tuning Scheme With Robust Stabilization of Gain Scheduled CSTR

Sudha

Subbulekshmi

2020

1790-5044

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“…Palanki et al [5] developed software module to run a simulation via the internet. The software module is developed in MATLAB and simulates a regulation problem in a continuous stirred tank reactor (CSTR) in which a series reaction is occurring.…”

Section: K J åStröm Et Al [3]mentioning

confidence: 99%

“…A key element of this combination is the integration of the control system into the structure [4]. The process control system is the entity that is charged with the responsibility for monitoring outputs, making decisions about how best to manipulate inputs so as to obtain desired output behavior, and effectively implement such decisions on the process [5]. The process has a property called self-regulation.…”

Section: Introductionmentioning

confidence: 99%

Comparative Analysis of Pso-Pid and Hu-Pid

Thakur¹,

Batish²

2017

IJERA

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PID control is an important ingredient of a distributed control system. The controllers are also embedded in many special purpose control systems. PID control is often combined with logic, sequential functions, selectors, and simple function blocks to build the complicated automation systems used for energy production, transportation, and manufacturing. Many sophisticated control strategies, such as model predictive control, are also organized hierarchically. PID control is used at the lowest level; the multivariable controller gives the set points to the controllers at the lower level. The PID controller can thus be said to be the "bread and butter" of power system engineering. It is an important component in every control engineer"s tool box. PID controllers have survived many changes in technology, from mechanics and pneumatics to microprocessors via electronic tubes, transistors, integrated circuits. The microprocessor has had a dramatic influence on the PID controller

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“…In industrial utilizations PID controller is mostly applied. In the PID controller parameters including integral gain, proportional gain, and derivative gain, could develop the performance of system [9]. A closed-loop system has lot of examples, like direction control, level control, temperature control, robot mechanism control and so on [10].…”

Section: Introductionmentioning

confidence: 99%

An Effective Technique for Tuning the Time Delay System with PID Controller-Ant Lion Optimizer Algorithm with ANN Technique

George

Ganesan

2020

IJEAT

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Nowadays, the PID controller is very common controller as well as very important controller in industrial utilizations. In the paper, proposed an ALO algorithm and ANN controller is utilized to enhance PID controller performance and control the tuning of TDS. TDS stands for Time delay system. ALO stands for Ant lion optimizer and ANN stands for Artificial neural network. In terms of parameters controlling, the time delay system is controlled and for different delay events low overshoot and fast time settling is reached. The novelty of the presented method is enhancing the PID controller performance by optimizing the PID gain parameters and controlling the highorder TDS. The performance of time delay system can be enhanced through decreasing error, tracking, time delay & error, rapid and exactly for their corresponding reference values. For parameter controlling of time delay system along optimal values, can be significantly enhanced the performance. To analyze the characteristics of the presented method, the various time delay systems are analyzed. The input and gain parameters were utilized to evaluate the objective function from tuning system. Based on proposed method, the optimal result is achieved and evaluated the increae time, settling time, overshoot as well as steady state error in TDS. The suggested controller is executed in MATLAB/Simulink work site and the presented technique performance examined through performance indexes and time domain specifications are evaluated using presented method compared to previous methods like ABC (Artificial Bee colony) algorithm, GSA (Gravitational Search Algorithm) ,FA (Firefly Algorithm).

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FOPID controller optimization based on SIWPSO-RBFNN algorithm for fractional-order time delay systems

Cited by 14 publications

References 26 publications

Flower Pollination Optimization Based PID Controller Tuning Scheme With Robust Stabilization of Gain Scheduled CSTR

Flower Pollination Optimization Based PID Controller Tuning Scheme With Robust Stabilization of Gain Scheduled CSTR

Comparative Analysis of Pso-Pid and Hu-Pid

An Effective Technique for Tuning the Time Delay System with PID Controller-Ant Lion Optimizer Algorithm with ANN Technique

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