Real Time Steam Temperature Regulation using Self-Tuning Fuzzy PID Controller on Hydrodiffusion Essential Oil Extraction System

Yusoff, Zakiah Mohd; Muhammad, Zuraida; Hezri, Mohd; Rahiman, Fazalul; Taib, Mohd Nasir

doi:10.21307/ijssis-2017-626

Cited by 4 publications

(6 citation statements)

References 38 publications

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“…It can be seen that the PSO algorith m by using the concave function decreasing inertia weight has been accelerated, the inert ia weight is reduced fast in the init ial stage of the algorith m, and the convergence speed of the algorith m is accelerated, the optimization accuracy is the highest. The PSO algorith m is used for PID parameter tuning, according to the PSO algorithm tuning principle and the different ways of implementation, the tuning methods can be divided into off-line PSO-PID and on-line PSO-PID [13][14][15][16][17][18]. Figure 4 is the PSO-PID control system structure diagram.…”

Section: Fig2 Optimization Comparison Between Ga and Psomentioning

confidence: 99%

Research on SVG DC-Side Voltage Control Based-on PSO Algorithm

Xiao¹

2016

IJITCS

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The operation flow of particle swarm optimization (PSO) is presented, at the same time the PSO algorithm and GA algorith m are used to find the optimal value of the standard function, simu lation results show that the PSO algorith m has better global search performance and faster search efficiency. The inertia weight decreasing strategy of PSO algorith m is studied, the simulation results show that the concave function decreasing strategy can accelerate the convergence rate of the algorithm. The stability control of the DC-side voltage is very important for the static var generator (SVG) co mpensation, but the disadvantages of the traditional PI control are fixed parameters and poor adaptability of dynamic response, PSO algorith m is introduced to the optimizat ion of PI parameters, so online PSO-PI control and off-line PSO-PI control are obtained, the SVG voltage loop transfer function is used as the controlled object. The simulat ion results show that the PSO-PI control can satisfy the time varying system of the controlled object with strong adaptability.

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Section: Fig2 Optimization Comparison Between Ga and Psomentioning

confidence: 99%

Research on SVG DC-Side Voltage Control Based-on PSO Algorithm

Xiao¹

2016

IJITCS

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“…The good controller is defined as a controller that could minimize the error between desired target and output in the steady-state manner [17]. The standard performance indexes used in the system's step response are percentage overshoot, rise time, settling time and accumulated error [3][4][5][6][7][18][19]. The percentage overshoot is the percentage of the maximum excess value versus the final value.…”

Section: Introductionmentioning

confidence: 99%

“…The rise time is the time for 1291 the step response to reach from 0 to its final value. The accumulated error is the summation of the absolute error of the step response at the sampling instants [19]. The settling time is the time taken to attain the nearly constant value of set point [19][20][21].…”

Section: Introductionmentioning

confidence: 99%

“…The accumulated error is the summation of the absolute error of the step response at the sampling instants [19]. The settling time is the time taken to attain the nearly constant value of set point [19][20][21]. This performance index was applied to many applications and it is desirable to optimize a number of different system performances to meet some requirements such as smaller overshoot, minimizing the settling time of the output, fast rise time, smaller steady-state error and the smaller load effect [19].…”

Section: Introductionmentioning

confidence: 99%

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Real time robustness test evaluation performance for intelligent fuzzy controller in extraction process

Yusoff

Ashar

Muhammad

et al. 2019

IJEECS

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This paper presents the real time robustness test using intelligent fuzzy based controller in extraction process of essential oil is discussed in this study. Previous finding shows that the quality of the essential oil is affected by the steam temperature that acts as the control variable in this study. The robustness test is applied to the system during running process to show the system is robust to any operation conditions t make sure the controller is able to give a smooth control output response. The dynamic performance of the system are represented by applying standard performance criteria such as rise time Tr, settling time Ts, overshoot <em>%OS</em>, root mean square error (RMSE) and time on recovering load disturbance. Generally, the objectives in designing the controllers have been achieved because all intelligent fuzzy based controllers capable to regulate the desired set point by acting on the change in the output compared with the set point.

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“…Numerous research works and books have been reported in this framework [2], [3], [4]. Recently, several emerging controller's design of industrial processes have been developed [5], [6], [7] and a large volume of published studies describing the implementation of PID controllers such as in water level regulation [8], temperature regulation [9], impressed current cathodic protection (ICCP) system [10], and conveyor belt system [11]. The PID controller tuning approaches are mainly used to ensure the stability of the closed-loop systems and meet objectives such as set-point changes, disturbance rejection, robustness against plant modelling uncertainty, noise attenuation ...…”

Section: Introductionmentioning

confidence: 99%