Simulation Study of Flow Control Based On PID ANFIS Controller for Non-Linear Process Plants

Solatian, Payam; Abbasi, Seyed Hamidreza; Shabaninia, Faridoon

doi:10.5923/j.ajis.20120205.04

Cited by 10 publications

(4 citation statements)

References 10 publications

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“…ADAM-4000 family is an intelligent interface for environmental sensors that allows interfacing sensors to PC through RS-485 and RS-232 communication protocol [20]. The required algorithms have been implemented in the Simulink environment and PI controllers have been used to control the power converters [21]- [22]. SEPIC converter allows setting the working point of the PV module (Fig.…”

Section: The Hardware Platformmentioning

confidence: 99%

A tool for performance evaluation of MPPT algorithms for photovoltaic systems

et al. 2018

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The use of photovoltaic (PV) systems as electrical power generator is increasing rapidly and this growth is expected to be continuous. As well known in PV systems the tracking of the maximum power point (MPP) is fundamental. For this reason, many testing systems and maximum power point tracking (MPPT) algorithms have been developed. Testing systems are used for the development as well as for assessing the quality of PV products. The typical problem related to the evaluation of PV system performances and MPPT algorithm comparison is the guarantee of the repeatability of the testing conditions (e.g. temperature and radiation). In this paper, a testing system for PV applications has been developed and characterized. Flexibility, ease of use, low cost, capability to evaluate the characteristic curves of more than one PV panel simultaneously (same environmental conditions), the capability of algorithms simulation, and capability of tracking MPP on the base of different MPPT algorithms are some of the main characteristics. Experimental tests have been carried out to show the capability of the developed architecture. Different MPPT algorithms have been compared in the same environmental conditions both in the steady and dynamic state.

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Section: The Hardware Platformmentioning

confidence: 99%

A tool for performance evaluation of MPPT algorithms for photovoltaic systems

et al. 2018

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“…PWM output signal then controls the power converter through a gate driver circuit. A Proportional Integral (PI) control strategy has been used as a controller in this paper [25] [26]. PV module temperature and solar irradiation have been measured via PT100 temperature sensor and a Pyranometer, respectively.…”

Section: The Testing Systemmentioning

confidence: 99%

Performance comparison of a two PV module experimental setup using a modified MPPT algorithm under real outdoor conditions

Soulatiantork

2018

Solar Energy

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The importance of Photovoltaic (PV) systems as a sustainable energy resource is widely recognized. The real maximum power point (MPP) is the most crucial parameter that must be considered to assure that maximum power is harvested from the PV module at all operating points. To this end, several PV testing systems and MPP tracker algorithms have been developed to find the real MPP. Issues related to the comparison of maximum power point tracking (MPPT) algorithms, evaluation, and comparison of PV testing system performances are the repeatability and reproducibility of testing conditions such as solar irradiation and PV module temperature. In this work, a flexible, low-cost testing system for PV applications is presented, and two identical PV modules have been compared at the same environmental conditions. A model-based (MB) MPPT algorithm, previously developed by the authors of this study, has been used. The MB algorithm has been evaluated and its efficiency is reported as 99.65%. The experimental test has been carried out and the performance of the developed architecture is validated, and two PV modules have been compared in real-time. It has been shown that the generated energy percentage difference between two identical PV modules is 0.6%. It is also worth mentioning that the proposed testing system is capable of hosting, evaluating and comparing four different MPPT algorithms, four PV modules and a combination of them.

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“…Using the PID input, output data sets and ANFIS can be trained in which the membership functions are tuned either through back propagation or hybrid method for PID based ANFIS [16]. FIS structure basically consists of a knowledge base -rule base and a database and reasoning mechanism -a decision making unit, fuzzification inference and defuzzification inference which derives the output depending on the input.…”

Section: Adaptive Neuro Fuzzy Inference Systemmentioning

confidence: 99%

“…A decentralized neuro-fuzzy controller [13] has been created in order to improve the ride comfort and to increase the stability of semi-active HC suspension system. In this paper the PID based ANFIS controller approach [16] is used to provide the travelling comfort for the HC suspension system when subjected to a sudden shock. This paper is organized in the following manner.…”

Section: Introductionmentioning

confidence: 99%

Enhancement of travelling comfort using PID based adaptive neuro fuzzy inference system for half car model

Kalaivani

Lakshmi²,

Sneha

2013

IET Chennai Fourth International Conference on Sustainable Energy and Intelligent Systems (SEISCON 2013)

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In this paper, pioneering Adaptive Neuro Fuzzy Inference System (ANFIS) which is trained with well known traditional Proportional, Integral and Derivative (PID) controller data for Half Car (HC) model is proposed to improve the travelling comfort. The travelling performance is generally assessed at the design stage in automobile industries by simulating the vehicle response to various road excitations. In this work, the disturbance from the road is assumed to be a jerk which represents a sudden shock. Initially a PID controller is designed and tuned to give better response. Secondly the PID tuning parameters are optimized using popular stochastic global optimization technique -Genetic Algorithm (GA) by considering the body acceleration as the Performance Index (PI). At last, an ANFIS which inherits the features of Neural Network (NN) and Fuzzy Logic (FL) is used for control purpose. The modelling of system and simulation with and without controllers are carried out in MATLAB/ Simulink environment. A comparison is made among the responses obtained and it shows that, the system with PID based ANFIS gives significant reduction of the Sprung mass Displacement (SD) and thus improves the travelling comfort.

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Simulation Study of Flow Control Based On PID ANFIS Controller for Non-Linear Process Plants

Cited by 10 publications

References 10 publications

A tool for performance evaluation of MPPT algorithms for photovoltaic systems

A tool for performance evaluation of MPPT algorithms for photovoltaic systems

Performance comparison of a two PV module experimental setup using a modified MPPT algorithm under real outdoor conditions

Enhancement of travelling comfort using PID based adaptive neuro fuzzy inference system for half car model

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