Adaptive Fuzzy PI Controller Research Articles

Improved Sensorless Control of Doubly Fed Induction Motor Drive Based on Full Order Extended Kalman Filter Observer

The paper deals with a Doubly Fed Induction Motor (DFIM) supplied by two PWM voltages inverters. The aims of this paper are sensorless adaptive Fuzzy-PI speed control decoupled by a vector control applied to a Doubly Fed Induction Motor using full order Extended Kalman Filter. The application of the adaptive Fuzzy-PI controller for speed control brings a very interesting solution to the problems of robustness and dynamics. In order to reduce the number of sensors used, and thus the cost of installation, Extended Kalman Filter Observer is used to estimate the rotor speed, rotor fluxes and stator currents, this observer is a unique observer which offers best possible filtering of the noise in measurement and of the system if the noise covariances are known. Simulation results of the proposed scheme show good performances.

Control Strategy of Intergrated Photovoltaic-UPQC System for DC-Bus Voltage Stability and Voltage Sags Compensation

Power quality problem, because of its various forms and occurrence frequency, has become one of the most critical challenges confronted by a power system. Meanwhile, the development of renewable energy has led to more demands for an integrated system that combines both merits of sustainable energy generation and power quality improvement. In this context, this paper discusses an integrated photovoltaic-unified power quality conditioner (PV-UPQC) and its control strategy. The system is composed of a series compensator, shunt compensator, dc-bus, and photovoltaic array, which conducts an integration of photovoltaic generation and power quality mitigation. The fuzzy adaptive PI controller and the improved Maximum Power Point Tracking (MPPT) technique are proposed to enhance the stability of dc-bus voltage, which is aimed at the power balance and steady operation of the whole system. Additionally, the coordinate control strategy is studied in order to ensure the normal operation and compensation performance of the system under severe voltage sag condition. In comparison to the existing PV-UPQC system, the proposed control method could improve the performance of dc-bus stability and the compensation ability. The dynamic behavior of the integrated system were verified by simulation in MATLAB and PLECS. Selected results are reported to show that the dc-bus voltage was stable and increased under severe situations, which validates the effectiveness of the proposed integrated PV-UPQC system and its control strategy.

Design of Adaptive Fuzzy PI Controller for Electric Vehicle with BLDC Drives

Electric vehicles in concern with its innumerable advantages, replaces the internal combustion engine vehicles (ICEV). The efficiency and performance of the Electric Vehicle (EV) depends mainly on the electric motor and its control technique. The Brushless DC (BLDC) Motor is used as the electric motor in the EV as it has high efficiency and high starting torque. The sensorless direct torque control technique is used to enhance the performance of the EV. The Adaptive Fuzzy PI (AFPI) Controller is the proposed controller in the EV. The comparison of reference torque and actual torque produce the error. It is applied to the AFPI controller which produces an output of reference torque. The EV with stationary reference frame theory of direct torque control with AFPI controller is simulated using MATLAB/SIMULINK.

Research and Application of Low Voltage Ride through (LVRT) and the Power Grid Adaptability Testing Device for Frequency Converter

In order to study the response characteristics of converters applied in the field of renewable power integration and motor speed regulation when grid fault appears, the traditional LVRT schemes and effects of converters are analyzed, and the integrated design of AC and DC sources scheme based on power electronics technology is proposed.The three-phase four-wire topology AC and DC sources and adaptive fuzzy PI control algorithm is adopted to realize the real-time adjustment of the DC output voltage and dynamic control of the three-phase or single-phase AC output voltage. Meanwhile, the dynamic control includes the drop amplitude, the drop time, the frequency, and the Harmonic. The 40KW LVRT and grid adaptability testing device for converter is developed. The laboratory test proved that the dynamic response time of the device is less than 5ms, the harmonic content of the AC output voltage is less than 1%, and the protection mechanism is complete and reliable. The upper computer sets parameters offline or online, tests circularly and operates conveniently.

Research and Application of Low Voltage Ride Through Testing Device for Low Voltage Frequency Converter in Thermal Power Plant

In order to improve the Low Voltage Ride through (LVRT) level of the low voltage auxiliary frequency converter in the thermal power plant and effectively solve problems including the inaccurate drop time of voltage drop device, which is controlled by the switching structure of the traditional multi-winding transformer, excessive magnetizing inrush current occurs during the closing process, and the 30KW testing device for LVRT of the frequency converter in the thermal power plant is developed. It is designed with a three-phase four-wire back-to-back power electronic topology, together with adaptive fuzzy PI control algorithm. They can precisely set the voltage drop amplitude and time, ensuring automatic periodic cycle test controlled by upper computer. A LVRT field experiment has been carried out on low-voltage auxiliary frequency converter both before and after the transformation in a thermal power plant in Jiangxi Province. It proves that the dynamic response time of the power electronic voltage drop device is less than 5ms, the harmonic content in the converter voltage output is less than 0.5%. Additionally, the device boasts convenient operation and well-developed protection mechanism.

Frequency regulation strategy for private EVs participating in integrated power system of REs considering adaptive Markov transition probability

The active power imbalance caused by renewable energies (REs) and loads is usually viewed as a main reason for the grid frequency variation. Private electric vehicles (EVs) participating in integrated power system frequency regulation of REs has great realistic significance, the bidirectional wireless power transfer system for EVs is analyzed in this paper, a fuzzy adaptive PI controller is proposed to achieve the charge and discharge control of EVs at any power value. Then a Markov model with adaptive Markov transition probability is developed to analyze the stochastic distribution of EVs. Considering the basic travel demands of the owners and the EV battery state of charge (SOC), a new advanced frequency regulation strategy is further proposed, and the regulation ability of EVs is quantitatively described. Finally, the effectiveness of the proposed frequency regulation strategy is verified by simulation results.

Research on the control system of APF for micro grid

The power supply of micro grid is less stable than of conventional grid, and the harmonic pollution is more severe, aiming at this situation, in order to increase dynamic response performance, and the steady-state compensation accuracy of an active power filter (APF), a new design scheme of APF applied to AC micro grid is proposed. In this scheme, ip −iq algorithm is used to detect the harmonics, and the hysteresis control method is applied to control the compensation current, and the fuzzy adaptive PI controller is applied to maintain the DC-side voltage. An test platform using FPGA EP3C55F484C8N as the controller is established. The effectiveness and correctness of the proposed control method are verified in the simulation and experiment.

Analysis and Suppression for Frequency Oscillation in a Wind-Diesel System

In a wind-diesel system with weak network architecture, many techniques are utilized to enhance its stability. However, the frequency oscillation between the grid-side converter and the diesel generator may be caused by their interactions, and there are only a few studies considering this issue, which is a major challenge for the stability. To tackle this challenge, the cause of frequency oscillation is studied, and an adaptive fuzzy PI controller based on the variable universe is proposed to suppress oscillation in this paper. The control parameter of the wind turbine generator (WTG) converter's dc-link voltage loop and wind speed has an important influence on the oscillation. Our main idea is to suppress frequency oscillation by the optimizing control parameter. In order to analyze the interaction between WTG and diesel generator, we develop the small-signal models of the wind-diesel generator. Subsequently, the adaptive fuzzy PI controller based on the variable universe is proposed in the dc-link voltage loop to optimize control parameter instead of gain-scheduled PI controller, and its key feature is the innovative use of an extension factor with d-axis current in the output universe. The function of the extension factor is to adapt WTG to different wind speeds. The experimental results demonstrate that the proposed controller can significantly suppress frequency oscillation. The oscillation amplitude of isolated grid frequency is also significantly reduced by up to 0.175 Hz.

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.

Grid interconnection of renewable energy sources using multifunctional grid-interactive converters: A fuzzy logic based approach

This paper proposes a multi-objective control strategy using adaptive fuzzy PI (AFPI) controller for grid-interactive converter (GIC). The proposed controller utilizes the robust and adaptive nature of fuzzy logic control (FLC) and simple structure of PI controller to effectively improve the dynamic performance of the GIC during uncertainties. In the proposed method, the gains of the PI controller are dynamically adjusted by the fuzzy logic based supervisory control system according to the system operating conditions. Hence, it provides fast dynamic response with reduced overshoot and settling time during disturbances. In addition, the proposed Takagi–Sugeno (TS) fuzzy model is computationally more effective when compared to mamdani type fuzzy models. In the proposed multi-objective control scheme, the GIC is utilized to provide various ancillary services in addition to its primary function of injecting active power to the grid. Computer simulation shows that the dynamic performance of the proposed controller is robust than the conventional PI controller during disturbances. Additionally, the results are compared with the existing literature to validate the performance of the proposed controller.

MPPT control of wind turbines by direct adaptive fuzzy-PI controller and using ANN-PSO wind speed estimator

This paper proposes a maximum power point tracking (MPPT) technique based on the tip speed ratio control for small scale wind turbines (WTs). In this paper, artificial neural network based particle swarm optimization has been trained offline to learn the characteristic of the turbine power as a function of wind and machine speeds. Afterwards, it has been realized online to estimate the varying wind speed. It is essential to design a controller that can track the maximum peak of energy regardless of wind speed changes. Therefore, this work provides a novel robust direct adaptive fuzzy–Proportional-Integral (PI) controller during the MPPT process through tuning duty cycle of the boost converter for permanent magnet synchronous generator driven by a WT. The proposed method has successfully decreased the ripples of coefficient of power (Cp) which is the index of MPPT mode, under variations of the wind speed in comparison with conventional controller. Finally, a systematic analysis is presented which is in good agreement with simulation results, confirming the effectiveness of the proposed strategy.

Artificial Intelligence Based First Order Adaptive Sliding Mode Controller for Position Control of a DC Motor Actuator

This paper presents an Artificial Intelligence (AI) based approach uniquely applied to Permanent Magnet DC motor actuator for position control. The AI method employed in this work is Fuzzy logic. A first order lag Sliding mode controller is tuned and combined with an Adaptive Fuzzy- PI controller architecture which operates in parallel. The controller architecture proposed in this study is aimed at improving the disturbance rejection capability, steady state as well as transient performance of the conventional Adaptive Fuzzy-PI controller and sliding mode controller. Hence, the robust control law of the proposed controller (SM+FZ-PI) consists of a discontinuous Sliding mode output added to a continuous Adaptive Fuzzy-PI controller output. The sliding mode controller switches on only when disturbance in the system is detected. The performance of the proposed controller architecture has been compared with a conventional PID and Adaptive Fuzzy-PI controllers for performance evaluation with respect to several operating conditions such as load torque disturbance injection, noise injection in feedback loop, motor non-linearity exhibited by parameters variation, and a step change in reference input demand. The proposed controller (SM+FZ-PI), had the best disturbance rejection and steady state error elimination.

Adaptive fuzzy PI controller with shifted control singletons

It is well known the fact that the design of a fuzzy control system is based on the human expert experience and control engineer knowledge regarding the controlled plant behavior. As a direct consequence, a fuzzy control system can be considered as belonging to the class of intelligent expert systems. The tuning procedure of a fuzzy controller represents a quite difficult and meticulous task, being based on prior data regarding good knowledge of the controlled plant. The complexity of the tuning procedure increases with the number of the fuzzy linguistic variables and, consequently, of the fuzzy inference rules and thus, the tuning process becomes more difficult. The paper presents a new design strategy for such expert fuzzy system, which improves their performance without increasing the number of fuzzy linguistic variables. The novelty consists in extending the classic structure of the fuzzy inference core with an intelligent module, which tunes one of the control singletons, providing a significant simplification of the design and implementation procedure. The proposed strategy implements a logical, not physical, supplementation of the linguistic terms associated to the controller output. Therefore, a fuzzy rules set with a reduced number of linguistic terms is used to implement the expert control system. This logical supplementation is based on an intelligent algorithm which performs a shifting of only one of the control singletons (the singleton associated to the SMALL_ linguistic variable), its value becoming variable, a fact that allows an accurate control and a better performance for the expert control system. The logic of this intelligent algorithm is to initially provide a high controller output, followed by a slowdown of the control signal near to the operating set point. The main advantage of the proposed expert control strategy is its simplicity: a reduced number of linguistic terms, combined with an intelligent tuning of a single parameter, can provide results as accurate as other more complex available solutions involving tuning of several parameters (well described by the technical literature). Also, a simplification of the preliminary off-line tuning procedure is performed by using a reduced set of fuzzy rules. The generality of the proposed expert control strategy allows its use for any other controlled process.

An adaptive fuzzy PI controlled bus quantity enhancer for wave energy systems

This paper introduces an adaptive fuzzy PI controller (AFPIC) for a exible AC transmission system (F ACTS)- based dynamic powerlter (DPF) to be used in wave energy conversion systems. The new F ACTS device stabilizes the DC-common bus voltage, reduces quality of power troubles, and enhances energy utilization by acting as a bus quantity enhancer (BQE). The design and realization of the proposed F ACTS-based DPF and efficient control schemes are fully studied. To validate the efficiency of the proposed BQE F ACTS device, a digital simulation model and a laboratory test system are developed in the MATLAB/Simulink/ Simpower software environment for comparison. Various experimental test models of the proposed BQE system and dynamic error-based controller structures have been utilized to verify the simulation results. It has been shown that the utilization of the proposed AFPIC with the novel BQE device and multivariable error driven control strategy is very effective to eliminate stochastic wave inuences on voltage on the load side and load variations on the source side by decreasing voltage sag and swells. The effectiveness of the BQE is also tested by applying error energy-based performance indices ISE, IAE, and ITAE.

Adaptive Fuzzy-PI control of redundant humanoid arm using full-body balance

This paper presents an adaptive Fuzzy-PI control strategy that incorporates a humanoid's upper body rotational motion when controlling its redundant arm. Essentially, fuzzy logic interconnects two different dimensional information by utilizing a humanoid's angular momentum error at the torso to actively adjust its end-effector's control parameters (PI) at every loop. The results from two different simulations show that the tracking errors of the proposed Fuzzy-PI scheme is relatively smaller than those of the conventional method. These results imply that Fuzzy-PI can partially compensate for errors in one dimension (end-effector) by taking into account the state of another dimension (torso).

DC Side Ripple Voltage Analysis and Fuzzy PI Control Strategy Research for APF

Owing to the problems of DC side capacitor value choice in the application of Active Power Filter (APF), this article presents a technique based on the analysis of the ripple voltage in DC side by graining appropriately the undulation control rate within the range of settings and control DC voltage so that the voltage fluctuation rate can reach minimum value under the condition of specific capacitance which is aimed at getting good compensation effects. In order to achieve the stability of the DC side capacitor voltage control, we introduce a new technique on the DC output voltage deviation square values of adaptive fuzzy PI control. Meanwhile, a Space Vector Pulse Width Modulation (SVPWM) is used to conduct optimization design for the DC side voltage waveform. The simulation results show that using this method reduces the DC voltage ripple and achieves steady DC output voltage.

A new method for detection of fake data and adaptive fuzzy PI control for power system stability

This paper presents a fuzzy PI controller as a power system stabilizer. The fuzzy PI controller has been designed in order to prepare an auxiliary signal for the excitation system of the synchronous generator. The proposed controller utilizes a combination of a fuzzy logic controller (FLC) and a PI controller, which are the most recent researches in the problem at hand. In comparison with the conventional fuzzy controllers, the proposed fuzzy PI controller takes advantage of both FLC and conventional PI controller to overcome all kind of disturbances. The damping of oscillations local modes in a power system will substantially be controlled by employing this controller as a replacement for conventional PSS. Furthermore, the presented paper considers the conventional PSS and compares its performance with respect to three proposed types of fuzzy PI controller. Correspondingly, the effects of the supplementary signals in damping oscillation have been shown. Finally, to scrutinize the effectiveness of the proposed controller in damping oscillations, a three-phase short circuit condition is studied in order to clarify the application of the developed methodology. The achieved outcomes show that the proposed controller for stabilizing power system can provide very good damping characteristic.

Adaptive Fuzzy-PI Control for Active Front Steering System of Armoured Vehicles: Outer Loop Control Design for Firing On The Move System

An armoured vehicle tends to lose its dynamic mobility when firing on the move. This is due to the effect of the firing force that reacts at the centre of the weapon platform, which creates an unwanted yaw moment at the vehicle’s centre of gravity. In order to enhance the mobility performance of the armoured vehicle, a control strategy, i.e. yaw rejection control, is designed and test on an armoured vehicle model. The purpose of the control strategy is to maintain the directional mobility of the armoured vehicle by providing a steering correction angle to the pitman arm steering system. The control strategy proposed in this study consists of two main structures: yaw rate feedback control using a Proportional-Integral-Derivative (PID) controller and Lateral Force Rejection Control (LFRC) using an adaptive Fuzzy-Proportional-Integral (adaptive Fuzzy-PI) controller. The simulation results in terms of yaw and lateral motions were observed, and the proposed control strategy was shown to successfully improve the directional mobility of the armoured vehicle after firing. The benefit of the proposed control strategy with adaptive fuzzy-PI control is evaluated by comparing its performance to fuzzy-PI and proportional-integral (PI) control strategies.

Fuzzy Adaptive PI Controller for DTFC in Electric Vehicle

This paper presents a technique to control the electric vehicle (EV) speed and torque at any curve. Our propulsion model consist of two permanent magnet synchronous (PMSM) motors. The fuzzy adaptive PI controller is used to adjust the different static error constants, as per the speed error. The suggested based on the direct torque fuzzy control (DTFC). A Mamdani type fuzzy direct torque controller is first developed and then rules are modified using stator current membership functions. The computations are ensured by the electronic differential, this driving process permit to steer each driving wheels at any curve separately.Modeling and simulation are carried out using the Matlab/Simulink tool to investigate the performance of the proposed system.

A Servo Control System Based on Fuzzy PI Method for Transverse Flux Machine in Mechanical Press

A control method for servo control system of Assembled Claw Pole Stator Transverse Flux Machine(ACPTFM) by controlling the armature current Root-Mean-Square (RMS) and the angle between armature current and no-load EMF is proposed in this paper. The servo control system of ACPTFM is composed of a series of closed-loop controllers, and the most complexity design of speed controller is described in detail. Fuzzy adaptive PI control method which integrates the advantages of fuzzy control and PI control is adopted to design the speed controller. Experimental results show that it can improve the system dynamic response and steady state accuracy.