Self-tuning Fuzzy PI 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.

Study on improved Ip-iq APF control algorithm and its application in micro grid

In order to enhance the tracking velocity and accuracy of harmonic detection by ip-iq algorithm, a novel ip-iq control algorithm based on the Instantaneous reactive power theory is presented, the improved algorithm adds the lead correction link to adjust the zero point of the detection system, the Fuzzy Self-Tuning Adaptive PI control is introduced to dynamically adjust the DC-link Voltage, which meets the requirement of the harmonic compensation of the micro grid. Simulation and experimental results verify the proposed method is feasible and effective in micro grid.

Application of a self-tuning fuzzy PI–PD controller in an active anti-roll bar system for a passenger car

A fuzzy proportional-integral-derivative (PID) controller has not been widely investigated for active anti-roll bar (AARB) application due to its unspecific mathematical analysis and the derivative kick problem. This paper briefly explains how the derivative kick problem arises due to the nature of the PID controller as well as the conventional fuzzy PID controller in association with an AARB. There are two types of controllers proposed in this paper: self-tuning fuzzy proportional-integral–proportional-derivative (STF PI–PD) and PI–PD-type fuzzy controller. Literature reveals that the PI–PD configuration can avoid the derivative kick, unlike the standard PID configuration used in fuzzy PID controllers. STF PI–PD is a new controller proposed and presented in this paper, while the PI–PD-type fuzzy controller was developed by other researchers for robotics and automation applications. Some modifications were made on these controllers in order to make them work with an AARB system. The performances of these controllers were evaluated through a series of handling tests using a full car model simulated in MATLAB Simulink. The simulation results were compared with the performance of a passive anti-roll bar and the conventional fuzzy PID controller in order to show improvements and practicality of the proposed controllers. Roll angle signal was used as input for all the controllers. It is found that the STF PI–PD controller is able to suppress the derivative kick problem but could not reduce the roll motion as much as the conventional fuzzy PID would. However, the PI–PD-type fuzzy controller outperforms the rest by improving ride and handling of a simulated passenger car significantly.

A Variable Universe Self-Tuning Fuzzy-PI Speed Controller for Induction Motor with DTC-SVM

In the paper, To control the speed of induction motor drive with DTC-SVM, A variable universe self-tuning fuzzy-PI(VUFPI) controller was designed based on the concept of variable universe to generate the torque reference value, Two inputs of the fuzzy controller are speed error and error change rate, the output of the fuzzy controller are adjustment parameters (,) of PI controller parameters (Kp, Ki), the input and output variable universe of fuzzy controller were regulated by scale factor which is calculated according to error grade, The simulation results show that the proposed method has fast response speed and lower torque ripple.

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.

Fuzzy Self-Tuning PI Control for the Upper Limb Rehabilitation Robot

It is well known that the robot powered by pneumatic muscle actuator (PMA) which with highly nonlinear, time lag and time-varying characteristics is not easy to control. In this paper, we presented a hybrid fuzzy and PI controller for the upper-limb rehabilitation robot which was designed and built in our lab to assist patients post-stroke in the rehabilitation. The experimental results showed that controller can improve dynamic and static performance of the device, then it can control robot effectively to aid patients carrying on the systematized recovery training.

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.

Experimental Study of Fuzzy PI Controller of HEV DC/DC Converter

This paper aims to improve the control performance of series HEV, and mainly conducts the study of the basic components of the control systems bidirectional DC/DC converter and motor drive circuit--the buck chopper and boost chopper. Also, this paper constructs a hardware platform and designs the fuzzy self-tuning PI controller. Through the comparative experiments of PI control and fuzzy PI control, it has been verified that the fuzzy PI controller has better control effect.

Design of Fuzzy Self-Tunning Controller for Permanent Magnet Synchronous Motor

Permanent magnet synchronous motors(PMSM) as a representative of high efficiency motor was being used widely in the area of medium and small-sized power, high-accuracy,high reliability and wide-scope speed governing servo system.Otherwise,because traditional PI controller can not satisfy the high-performance of PMSM servo system,Fuzzy self-tuning PI(Fuzzy-PI) control method was used in this system, and proportion and integral parameter of PI controller is optimized by fuzzy logic.By simulation experiment, it was proved that Fuzzy-PI method had more steady and less q-axis current pulse to PI control in the transition procedure of PMSM governing.

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

Design of BLDCM Fuzzy Control System for Electric Vehicle Based on DSP

In this paper, the design of BLDCM fuzzy control system for electric vehicle which bases on TMS320F2812 Digital Signal Processor (DSP) is given. The design methods of hardware and software of the control system are described in details. Using of brushless DC motor current and speed double closed loop control, meanwhile, the fuzzy self-tuning PI algorithm is applied in the control system, and achieve the intelligent control of brushless DC motor control system. In this paper, the PWM control of the overlapping commutation method to suppress torque ripple. Experimental results show that this system has such characteristics as sound controlling effects, obvious restrain of torque pulsation and reliable operation.

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

AC Motor Speed Control Double Close Loop Cascade Fuzzy PI Controller Design

Cascade Speed Regulation System has the nonlinear characteristics and whose structure parameters are variable easily. Fuzzy control theory which based on conventional Cascade Speed Regulation System is introduced into such system. An asynchronous motor model is built, and a fuzzy parameter self-tuning controller is designed in this paper, the controller is simulated in Matlab, The simulation result shows the difference between the conventional PI controller and the fuzzy parameter self-tuning PI controller. From these simulation results, all performance indexes of the fuzzy PI controller with parameters self-tuning are vastly superior to those of the conventional PI controller.

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.