Self-tuning Fuzzy PI Controller Research Articles

Design and experimental implementation of DC-DC converter based self-tuning fuzzy PI controller

Bu çalışmada kendinden ayarlı bulanık PI (SFPI) kontrolör tabanlı DA-DA yükselten dönüştürücü topolojisi sunulmuştur. Dönüştürücünün kapalı çevrim transfer fonksiyonu elde edilmiş ve kararlılık analizi için küçük işaret modeli incelenerek tasarımı gerçekleştirilmiştir. Giriş-çıkış ilişkisi kara kutu modelleme ile doğrulanmıştır. Sistemin farklı anahtarlama frekanslarında 20 kHz ile 100 kHz aralığındaki davranışları incelenmiştir. Sistemin dinamik tepkisini test etmek için geleneksel PI kontrolör uygulanmış ve sistemde giriş gerilimi ve yük değişimleri gibi durumlarda gerilim regülasyonunun yetersiz olduğu gözlenmiştir. Bu nedenle dönüştürücünün çıkış gerilim regülasyonunu iyileştirmek için SFPI kontrolör önerilmiştir. Önerilen SFPI ile PI kontrolörler yükselme zamanı, yerleşme zamanı ve aşma gibi performans kriterleri ile karşılaştırılmıştır. Analiz sonuçlarına göre önerilen kontrolör ve sönümleme devrelerinin tasarlanması ile güç dönüşümündeki kayıpların azaltılarak sistem veriminin iyileştirildiği gözlenmiştir. Prototipi gerçekleştirilen dönüştürücünün nominal gerilimi 48 V, gücü 100 W olup sistemin genel verimi %92,9 olarak bulunmuştur. Sistemin analiz ve benzetim sonuçları deneysel sonuçlarla doğrulanmıştır.

Self-tuning Fuzzy-PI controller for load frequency control analysis with the integration of wind energy

ABSTRACT Optimal novel Self-tuning Fuzzy-PI (STFPI) controller has been introduced to analyze the LFC (Load Frequency Control) in a multi-unit unified system. The finest constraints of this suggested STFPI controller are found using quasi-opposition-based Jaya (QOB Jaya) algorithm. The investigation is performed over a two area multi-generation unified system. The examined model considers both renewable-type (wind) and conventional-type (thermal, diesel, & hydro) generating sources. The efficacy of the proposed controller is confirmed by (i) varying the size of loading, (ii) changing the constraints of designed system, and (iii) injecting arbitrary loading into the power system. It has been derived that the value of the objective function (Integral Time Absolute Error) with QOB Jaya tuned STFPI controller is improved by 95.44%, 85.17%, and 50% as compared to PSO-tuned PID Controller, QOB Jaya-tuned FPI Controller, and Jaya-tuned STFPI Controller, respectively. The supremacy of the projected controller is proved by doing comparisons among the responses of fuzzy-PI controller and a pre-published outcome such as PSO (particle swarm optimization) tuned PID (proportional-integral-derivative) controller.

Steam temperature control of essential oil extraction system using Fuzzy-Fopi controller

This research proposed a closed-loop temperature control using a self-tuning fuzzy fractional-order PI (FOPI) controller to overcome the problem. The controller will regulate the steam temperature at a desired level to protect the oil from excessive heat. Self capability of fuzzy rules was found to facilitate the tuning using only information about output error and rate of output error. The proposed controller was found to be more in terms of energy consumption and produce better response compared to self-tuning fuzzy PI. Essential oil quality assessment was also performed for citronella oil samples that were extracted at 85ºC and 100ºC (uncontrolled). Significant improvement had been observed in the sample extracted at 85ºC based on physical and chemical evaluations using refractive index measurement and GC-MS analysis.Keywords: fuzzy control; fractional-order PID; essential oil extraction; hydro-steam distillation.

Photovoltaic Grid-Connected Micro-Inverter Based on Self-Tuning Fuzzy-PI Controller

This paper introduces a kind of grid-connected micro-inverter system. Photovoltaic micro-inverter system is a highly nonlinear and time-varying system. Compared to traditional linear control strategy, Fuzzy Controller has better robustness and stability in the changing or non-linear application. Matlab simulation model for current tracking PV Grid-connected Micro-inverter was completed based on the Fuzzy self-tuning PI controller and the control strategy was tested on the micro-inverter prototype. The resu1ts show that this control strategy can effectively reduce the tracking error of the net current, and improve the system’s dynamic response.

Research on PMSM Fuzzy PI Control System

In this paper, a fuzzy PI control method is proposed in order to overcoming shortcomings of traditional PI regulator control permanent magnet synchronous motor, in this paper. This method combined traditional PI control with fuzzy control is enable to achieve self-tuning fuzzy parameters PI control and take into account sensitivity, and robustness of the system. A double-loop (current loop and velocity loop) fuzzy control system is designed by this method. Modular design of the fuzzy PI controller based on FPGA chip is realized and simulation and experimental is done. The experimental results show that this system has advantages of fast response characteristic, good stability and high precision adjustment.

A Comparative Study of Control Methods for Induction Motor and High Performance Z-source Inverter

Design studies of the most suitable controller for the speed of induction motor (SIM) and peak DC-link voltage (PDV) of high performance z-source inverter (HP-ZSI) greatly affects performance of hybrid electric vehicles. This paper is to give comprehensive analyses comparison and evaluations of the different control techniques as PI controller, self-tuning fuzzy PI controller (SFP) and genetic algorithms optimal tuning gains of the PI controller for controlling the SIM based on criteria of the integral of the absolute value of speed error. With control PDV, this paper also presents comparisons of the different techniques as PI controller, fuzzy logic controller, SFP based on observation of its response and total harmonic distortion of current. All methods are applied to the closed loop of the SIM which relies on direct torque control combined with modified space vector modulation and closed loop of PDV in HP-ZSI. These methods are verified by Matlab software. DOI: http://dx.doi.org/10.11591/telkomnika.v11i6.2445 Full Text: PDF

Self-Tuning Fuzzy PI-Type Controller in Z-Source Inverter for Hybrid Electric Vehicles

This paper presents new algorithms to control speed induction motor (SIM) and the peak dc-link voltage (PDV) across the inverter bridge in z-source inverters (ZSI) by applying self-tuning fuzzy PI controller (SFP) with robust structure and non-linear characteristic. In particular, this so-called SFP based control algorithm (SFPA) is applied to a closed loop speed control system of induction motor, which relies on direct torque control scheme combined with modified space vector modulation (DTCMSVM) control strategy with so many exceptional features (e.g. fast torque response, low steady state torque ripple, and high accurate). Additionally, SFPA is used to control SIM and PDV are more adaptive to the sudden change of parameters such as load torque, stator resistance and dc input voltage (DIV), respectively. The transient response of SIM and PDV are thus improved with less over shoot, short rise time, small steady-state error and fast settling time, with low disturbance for output voltage stabilization in the inverter bridge. As a result, we achieve higher accuracy and robustness of SIM control system. Our new SFPA is verified in both simulation and experimental implementation using MATLAB and dSPACE DS1103, respectively. DOI: http://dx.doi.org/10.11591/ijpeds.v2i4.571

A Unique Novel Approach for Design and Analysis of A Robust Decentralized Self-Tuning Fuzzy PI Controller for a Multi Input Multi Output Process

Problem statement: In the real world most of the controlled processes in industries are Multi-Input Multi-Output (MIMO) in nature.They have more than a single controlled variable that should be manipulated in order to achieve the desired control performance. Approach: Control of non linear Multi Input Multi Output processes, it is a difficult task because of the non stationary behaviour, substantial coupling of multiple variables and severe disturbances. Self tuning fuzzy control is a technique applied to control a MIMO process when the plant parameters are subjected to perturbations and when the dynamics of the systems are too complex for a mathematical model to describe. In this study, a decentralized self tuning fuzzy PI controller is designed for a Multi Input Multi Output Process. Results: The performances of the proposed STFPIC for the MIMO process are compared with fuzzy PI controller under both normal and under -10% deviation in time constant in terms of the performance measure Integral Time Absolute Error (ITAE). Conclusion: The proposed STFPIC for the MIMO process shows remarkably improved performance than FPIC.

Rule Extraction through Self-Organizing Map for a Self-Tuning Fuzzy Logic Controller

Complex, imprecise, ill-defined and uncertain systems can be identified by fuzzy modeling. The identification of such a linguistic model consists of two parts; structure identification and parameter estimation. In this paper, we proposed Self-Organizing Map (SOM) clustering technique for structure identification. Initial parameters of the input-output membership functions (MFs) will be estimated from the clustering results. In the process of proto-type generation, the gradient descent method is used to refine and tune the parameters effectively. The proposed scheme has been successfully tested to identify the rules required to realize the gain factor of self-tuning fuzzy PI controller, which is highly non-linear in nature. Here, the system identification method is integrated with rule extraction method in such a way that it can pick up required rules from any processes. Finally, examples of various systems are given to illustrate the effectiveness of the proposed approach.

A robust self-tuning fuzzy PI scheme for DTC induction motor drive

In this paper, application of self-tuning fuzzy PI scheme (STPIFLC) for Direct Torque Controlled Induction Motor (DTC IM) drive is proposed. In the proposed approach, the output scaling factor (SF) is adjusted online by fuzzy rules according to the current trend of the controlled process. The rule base for tuning the output SF is defined on error (e) and change of error (?e) of the controlled variable using triangular equally overlapped membership functions (MFs). The performance of the proposed self-tuning fuzzy PI controller is compared with the corresponding fuzzy logic controller and PI controller. The performance index based on speed error is assigned to provide a numerical comparison among different controllers. Simulation results show that the proposed STPIFLC for DTC IM drive gives remarkably improved performance and high robustness compared with those obtained by the application of a conventional controller (PI).

Reduced rule base self-tuning fuzzy PI controller for TCSC

In this paper, a reduced rule base self-tuning fuzzy PI controller (STFPIC) for thyristor controlled series capacitor (TCSC) is proposed. Essentially, a STFPIC consists of two fuzzy logic controllers (FLC). In this work, for each FLC, 49 rules have been used and as a result, the overall complexity of the STFPIC increases substantially. To reduce this complexity, application of singular value decomposition (SVD) based rule reduction technique is also proposed in this paper. By applying this methodology, the number of rules in each FLC has been reduced from 49 to 9. Therefore, the proposed rule base reduction technique reduces the total number of rules in the STFPIC by almost 80% (from 49 × 2 = 98 to 9 × 2 = 18), thereby reducing the complexity of the STFPIC significantly. The feasibility of the proposed algorithm has been tested on 2-area 4-machine power system and 10-machine 39-bus system through detailed digital simulation using MATLAB/SIMULINK.

A self-tuning fuzzy PI controller for TCSC to improve power system stability

In this paper, a self-tuning fuzzy PI controller (STFPIC) is proposed for thyristor-controlled series capacitor (TCSC) to improve power system dynamic performance. In a STFPIC controller, the output-scaling factor is adjusted on-line by an updating factor ( α). The value of α is determined from a fuzzy rule-base defined on error ( e) and change of error (Δ e) of the controlled variable. The proposed self-tuning controller is designed using a very simple control rule-base and the most natural and unbiased membership functions (MFs) (symmetric triangles with equal base and 50% overlap with neighboring MFs). The comparative performances of the proposed STFPIC and the standard fuzzy PI controller (FPIC) have been investigated on two multi-machine power systems (namely, 4 machine, 2 area system and 10 machine 39 bus system) through detailed non-linear simulation studies using MATLAB/SIMULINK. From the simulation studies it has been found out that for damping oscillations, the performance of the proposed STFPIC is better than that obtained by the standard FPIC. Moreover, the proposed STFPIC as well as the FPIC have been found to be quite effective in damping oscillations over a wide range of operating conditions and are quite effective in enhancing the power carrying capability of the power system significantly.

A self-tuning fuzzy PI controller

A robust self-tuning PI-type fuzzy logic controller (FLC) is presented. Depending on the process trend, the output scaling factor (SF) of the controller is modified on-line by an updating factor ( α). The value of α is determined from a rule-base defined on error ( e) and change of error ( Δe) of the controlled variable. The proposed self-tuning controller is designed using a very simple control rule-base and the most natural and unbiased membership functions (MFs) (symmetric triangles with equal base and 50% overlap with neighboring MFs). The proposed scheme is tested for a wide variety of processes including a marginally stable system with different values of dead time. Performance comparison between the conventional PI-type and proposed self-tuning FLCs is made in terms of several performance criteria such as peak overshoot, settling time, rise time, integral absolute error and integral-of-time-multiplied absolute error, in addition to the responses due to step input and load disturbance. Results for various processes show that the proposed FLC outperforms its conventional counterpart in each case.