Adaptive Fuzzy PI Research Articles

Morphing Omni-directional Panel Mechanism: A novel active roof design for improving the performance of the wind delivery system

The INVELOX is a wind delivery system which captures the wind from every directions and then funnels the flow to the ground-level generator. In this paper, a novel roof mechanism has been introduced to improve the performance of the wind delivery system. The proposed mechanism, called Morphing Omni-directional Panel Mechanism (MOPM), is a flexible roof designed for INVELOX system to improve the system efficiency by increasing the amount of captured air while reducing the wind escaping, concurrently. Leveraging the flexible structure, the MOPM roof enables the wind delivery system to operate over a wider range of wind speeds (1–55 m/s). On the other hand, a combination of an adaptive fuzzy system and PI anti-windup controller has been designed for the MOPM. Using the proposed control system, the roof can properly orient to the desired direction. The performance of the control system has been validated using the experimental and simulated analysis. The CFD simulations along with the experimental analysis have been done to evaluate the performance of the proposed roof design. The results show that the MOPM ameliorates the flow speed at the Venturi section by at least 6% when the outside wind speed is low. Unlike the INVELOX, MOPM can accelerate the flow speed at the Venturi section to the optimum speed (25 m/s) when the outside wind speed is around 10 m/s. The MOPM is capable of maintaining the flow speed in the Venturi section at 25 m/s in high outside wind speeds up to 55 m/s.

Hybrid Adaptive Control for PEMFC Gas Pressure

This paper addresses the issues of nonlinearity and coupling between anode pressure and cathode pressure in proton exchange membrane fuel cell (PEMFC) gas supply systems. A fuzzy adaptive PI decoupling control strategy with an improved advanced genetic algorithm (AGA) is proposed. This AGA s utilized to optimize the PI parameters offline, and the fuzzy adaptive algorithm s used to adjust the PI parameters dynamically online to achieve the approximate decoupling control of the PEMFC gas supply system. According to the proposed dynamic model, the PEMFC gas supply system with the fuzzy–AGA–PI decoupling control method was simulated for comparison. The simulation results demonstrate that the proposed control system can reduce the pressure difference more efficiently with the classical control method under different load changes.

Combined Error Adaptive Fuzzy–PI for Reducing DC Voltage Ripple in ThreePhase SPWM Boost Rectifier Under Unbalanced DGs System

Combined Error Adaptive Fuzzy–PI for Reducing DC Voltage Ripple in ThreePhase SPWM Boost Rectifier Under Unbalanced DGs System

The black-start capability improvement of VSC-based HVDC transmission system using fuzzy-adaptive PI controller

ABSTRACT The High Voltage DC Transmission (HVDC) transmission system commissioned in 1954 was planned for meeting the objectives like economy, faster recovery rate, frequency conversion, bulk power transmission, rapid controllability from sending and receiving end and so on. These objectives are difficult to achieve easily with the HVAC system. Among these, quicker reccovery rate, which is also called black start capability during fault and maintenance, is considered in this paper. This is achieved effectively when real power is controlled from sending end, while the dc link voltage is controlled at the other end. For this, better control schemes from both sending and receiving end, fast acting phase locked loop (PLL) and faster and intelligent adaptable controllers play a vital role. Hence, new PLL, fuzzy-adaptive PI with faster and effective control schemes are proposed to improve the black start rate of HVDC links. The performance of the proposed system is verified with traditional PI with conventional technique and with fuzzy-adaptive PI controller. The results are verified using MATLAB/SIMULINK software.

Design of Fuzzy Adaptive Pi Controller for Inherently Unstable System

Desired performance of any process depends on the control action taken by the controller. Choice of control structure and the design approach is mainly concerned with a priori knowledge of the process dynamics governed by any system, its limitations to achieve desire response and calculation of system state at different instant of time. Many practitioners and researchers in the field of control agree that controller design can be quite laborious in cases where the plant is unstable. The controller synthesis becomes a challenge for such systems because there are certain design and performance limitations that narrow the range of feasible solutions. These constraints reflect imperfect controller design which may work satisfactorily in one situation and may fail completely in other. Adaptive control where the controller parameters adjust them self as per the system requirements, is a candidate solution for such problem. This paper mainly focuses on design of model reference adaptive control based PI (Proportional-Integral) controller for unstable system. Adaptation mechanism is developed by fuzzy logic which makes the controller more versatile and reduces the design requirements. Results are compared with the conventional controller tuned with Ziegler-Nichols method. Detailed simulation Study and experimental validation shows the effectiveness of proposed Fuzzy Adaptive PI controller to control the unstable system for obtaining the desired performance out of it.

Improvement of adaptive fuzzy control to adjust speed for a doubly fed induction motor drive (DFIM)

This paper presents the doubly fed induction motor (DFIM) speed control using adaptive fuzzy logic PI (AFLPI) controller to give better dynamic performances. Before the advent of modern technology, integral proportional based current controller is usually used due to its simplicity. But, the performance of closed-loop control is largely influenced by this type of speed and torque controllers used, as long as the PI controllers suffer from tuning problem. To overcome the problem, a new technique AFLPI based speed controller for direct field oriented control fed DFIM to get fast speed response and to minimize the torque ripple. The application of this type of control is very satisfactory to replace the conventional PI controller and, even the fuzzy logic PI (FLPI) controller. The performance of the field oriented controlled DFIM drive has simulated at different operating conditions using the AFLPI controller and the obtained results are compared with FLPI controller and conventional PI controller. Accordingly, an improvement in dynamic and robustness is clearly appears in AFLPI controller simulation results compared to the others aforementioned controllers. Simulation Results are presented for the three techniques using Matlab/Simulink to prove the dynamic performances and robustness.

Integrated Avoid Collision Control of Autonomous Vehicle Based on Trajectory Re-Planning and V2V Information Interaction.

An integrated longitudinal-lateral control method is proposed for autonomous vehicle trajectory tracking and dynamic collision avoidance. A method of obstacle trajectory prediction is proposed, in which the trajectory of the obstacle is predicted and the dynamic solution of the reference trajectory is realized. Aiming at the lane changing scene of autonomous vehicles driving in the same direction and adjacent lanes, a trajectory re-planning motion controller with the penalty function is designed. The reference trajectory parameterized output of local reprogramming is realized by using the method of curve fitting. In the framework of integrated control, Fuzzy adaptive (proportional-integral) PI controller is proposed for longitudinal velocity tracking. The selection and control of controller and velocity are realized by logical threshold method; A model predictive control (MPC) with vehicle-to-vehicle (V2V) information interaction modular and the driver characteristics is proposed for direction control. According to the control target, the objective function and constraints of the controller are designed. The proposed method’s performance in different scenarios is verified by simulation. The results show that the autonomous vehicles can avoid collision and have good stability.

Adaptive and Fuzzy PI Controllers Design for Frequency Regulation of Isolated Microgrid Integrated With Electric Vehicles

The number of electric vehicles and renewable energy resources integrated into the power system is increasing day by day. The objective behind the development of electric vehicles and renewable energy sources is to build a sustainable and green power system. The renewables either don't possess system inertia or have less system inertia, therefore, they don't effectively respond to the load variations. The battery storage system of electric vehicles is used as the first line of defense to counter the effect of load/frequency variations and make the system stable. As active power is inversely proportional to the system frequency, for this purpose electric vehicles are included in the microgrid environment. In this paper, an isolated microgrid having a reheat turbine system, wind turbine system, photovoltaic system, and electric vehicles is studied. The output of the renewables is not controlled to utilize its maximum output power. Therefore, adaptive droop control and fuzzy PI control mechanisms are implemented to cater to the frequency variations of the isolated microgrid; the former regulates the power of electric vehicles while maintaining the energy needs of each EV and the later controls the output power of reheat turbine system according to the frequency variation. Furthermore, the genetic algorithm optimization toolbox is utilized to optimize the parameters of the adaptive and fuzzy PI controllers. The proposed model is developed in MATLAB/Simulink which shows that these control techniques effectively sustained the system frequency of isolated microgrid in the desired limits.

A Novel Double Closed-loop Control Method for Single-phase PWM Rectifier

Abstract The research object is the single-phase PWM rectifier in this paper. The goal of DC voltage dynamic response speed improvement and unit power factor realization is the rectifier oriented. Based on current inner loop DQ decoupling control and voltage outer loop adaptive fuzzy PI control, a double closed-loop control method for single-phase PWM rectifier is proposed. Firstly, based on the second-order generalized integrator algorithm, the DQ current decoupling control mathematical model is established by analyzing the rectifier decoupling control. Secondly, fuzzy PI control algorithm is designed for voltage outer loop control. Finally, simulation verification is carried out. Simulation results prove that the proposed control strategy has good dynamic performance.

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.

Robust maneuvering of autonomous underwater vehicle: an adaptive fuzzy PI sliding mode control

The control issues in nonlinear trajectory tracking of an autonomous underwater vehicle (AUV) are a challenging task due to the complex oceanic environment, highly nonlinear coupled dynamics, imprecise hydrodynamic coefficients and unpredictable external disturbances such as ocean waves, current fluctuations and tides. This paper addresses an adaptive fuzzy PI sliding mode control (AFPISMC) for trajectory tracking control of AUV to achieve high precise maneuvering in undersea environment. An AFPISMC is basically comprised of an equivalent control based on approximately known inverse dynamic model output and continuous adaptive PI term is designed to eliminate chattering effect. Furthermore, it does not require a priori knowledge of upper bounds on uncertainties in the dynamic parameters of an AUV. In this approach, decoupled single input fuzzy PI control strategy is employed along with a reduced rule base and self-tuning control law is derived to modify hitting gain in order to enhance tracking response. The overall control scheme guarantees the global asymptotic stability based on Lyapunov theory. Finally, the effectiveness and robustness of the proposed approach are demonstrated through simulation and comparison studies.