PI Controller In Terms Research Articles

An Optimal Fuzzy Logic Sliding Mode Voltage Regulation DC-grid System for Hybrid Electric Ships with FC-Battery Energy Storage System

This work proposes a fuzzy logic sliding mode control based on MOPSO optimization to increase voltage stability, particularly during load variations, while also combining FC-battery storage systems. The controller makes advantage of the converters' existing capabilities to reduce voltage fluctuations and improve system efficiency in a number of ship operating modes, including transient loads, without the need for additional equipment like as DC choppers or passive/active filters. By minimising voltage variation under load fluctuations and other influencing variables, the MOPSO develops control orders to manage load distribution among the FC and DG battery storage systems. The suggested control approach is compared to traditional sliding mode and PI controllers in terms of performance. According to the findings, the novel approach can improve battery power smoothing, steady state voltage management, and stable and speedy control performance.

Robust hybrid nonlinear control approach for stability enhancement of a constant power load DC-DC boost converter

This paper presents a robust hybrid super-twisting reaching law-based sliding mode controller in conjunction with a complementing recursive backstepping controller for DC-DC boost converters with constant power loads (CPLs). The key control goal is to keep the DC-bus voltage steady and constant while continuously powering the CPL. The nonlinear dynamical model of the DC-DC boost converter is translated into Brunovsky’s canonical forms, utilizing the precise feedback linearization technique to attain this control goal. It is worth mentioning that the dynamical model has been modified with bounded external uncertainties to demonstrate the restraint performance for huge loads and input voltage variations. The proposed hybrid controller is then constructed using this model. Furthermore, to ensure the large signal stability of the whole system under the designed control law, the Lyapunov stability theory is used. Numerical simulation analysis are carried out in MATLAB/Simulink to validate the performance of the designed robust controller for a DC–DC boost converter feeding a CPL when the operating point change. The results show that the designed controller outperforms both existing nonlinear controllers and a traditional PI controller in terms of ensuring the system’s stability and fast response in a variety of operating modes. Finally, in order to confirm the theoretical design and simulation results of the designed robust hybrid controller, experimental results are also provided in this paper.

Optimization of Fractional Order PI Controller by PSO Algorithm Applied to a Grid-Connected Photovoltaic System

With the increasing integration of renewable energies into power grids, their control and power quality are becoming the main focus of many research efforts. In a grid-connected photovoltaic system, the control strategy is necessary to efficiently use the solar energy as well as to ensure high power quality. This paper presents a study on the robustness of a Fractional Order PI controller based on the Particle Swarm Optimization algorithm (PSO-FOPI) in a grid-connected PV system. The controller used was integrated into the inverter to apply voltage-oriented control (VOC). Fractional order controllers have an additional degree of freedom, so that a wider range of parameters is available to provide better control. Parameter optimization of the FOPI and classical PI controllers are performed using the PSO algorithm. The performance of the FOPI controller is compared with that of the classical PI controller. A complete study of the behavior of the grid connected PV system is tested using MATLAB/Simulink. The simulation results show the performance and efficiency of the PSO-FOPI controller compared to the classical PI controller in terms of rapidity, stability and precision, as well as the THD reduction of the current injected to the grid for any variation of solar irradiance.

Design PI Controller for Tank Level in Industrial Process

In today’s chemical, refinery, and petrochemical sectors, separation tanks are one of the most significant separating processes. One or more separation tanks must operate consistently and reliably for multiple facilities’ safe and efficient operation. Therefore, in this paper, a PI controller unit has been designed to improve the performance of the tank level controller of the industrial process in Basrah Refinery Station. The overall system mathematical model has been derived and simulated by MATLAB to evaluate the performance. Further, to improve the performance of the tank level controller, optimal PI parameters should be calculated, which Closed-Loop PID Autotuner has been used for this task. Several experiments have been conducted to evaluate the performance of the proposed system. The results indicated that the PI controller based on the Autotuner Method is superior to the conventional PI controller in terms of ease to implement and configuration also less time to get optimal PI gains.

Dynamic simulator and model predictive control of a milk pasteurizer

In this study, the design, optimization and dynamic modelling of a milk pasteurization unit have been developed, using the pseudo-component approach for describing milk properties. The fluid has been regarded as a mixture of five major categories, namely water, fats, proteins, carbohydrates, and minerals. Exploiting the optimal pasteurizer configuration, selected based on the total annualized cost, a dynamic model of the process has been also derived. The simulation of the system is then used as a virtual plant to develop a nonlinear model predictive control (NMPC) designed for rejecting the more important disturbances that can enter the system. The predicted trajectories have been calculated with a simplified version of the dynamic model, obtained by neglecting parameters temperature dependence. The NMPC performance has been compared with a PI controller in terms of set-point tracking and disturbance rejection. Similar results have been obtained when using the different control algorithms for the output responses, but the NMPC showed better behaviour of the manipulated variables.

Mixed-integer Modelling and Optimization of a Heat Source and a Storage System

Thermal energy storages introduce flexibility into heating systems with numerous advantages on system performance, and operational and maintenance costs. One of the most prominent advantages is the ability to use heat sources at the operating points with higher efficiency To use the full potential of a thermal energy storage, an adequate control technique is required to control the heat sources connected to it. This paper models a heating system containing a heat source and a thermal energy storage and uses this model for optimal scheduling of the heat source. The optimal schedule is obtained through application of model predictive control which takes into account the efficiency of the heat source. A PI controller is also designed by following practical optima to serve as a baseline for comparison with the MPC-based scheduler. The obtained results show that the optimal scheduler is advantageous compared to the PI controller in terms of both energy efficiency and satisfying the posed constraints.

Fast‐converging robust PR‐P controller designed by using symmetrical pole placement method for current control of interleaved buck converter‐based PV emulator

AbstractIn this study, the interleaved buck converter‐based photovoltaic (PV) emulator current control is presented. A proportional‐resonant‐proportional (PR‐P) controller is designed to resolve the drawbacks of conventional PI controllers in terms of phase management, which means balancing currents evenly between active phases to avoid thermally stressing and provide optimal ripple cancelation in the presence of parameter uncertainties. The resonant path of the controller (PR) with a constant proportional unity gain is designed considering the changing dynamics of a notch filter by pole placement method (adding mutually complementary poles to the notch transfer function) at PWM switching frequency. The proportional gain path (P) of the controller is used to determine the compatibility of the controller with parameter uncertainty of the phases and designed by utilizing loop‐shaping method. The proposed controller shows superior performance in terms of 10 times faster‐converging transient response, zero steady‐state error with significant reduction in current ripple. Equal load sharing that constitutes the primary concern in multiphase converters is achieved with the proposed controller. Implementing of robust control theory involving comprehensive time and frequency domain analysis reveals 13% improvement in the robust stability margin and 12‐degree bigger phase toleration with the PR‐P controller. In addition to these, the proposed unconventional design process of the controller reduces the computational complexity and provides cost‐effectiveness and simple implementation. Moreover, implementing of auxiliary resistor‐capacitor (RC) circuits parallel with the inductors to sense the current in each phase removes the need for current measurement sensors that contribute to overall cost of the system.

Discrete‐time integral terminal sliding mode based maximum power point controller for the PMSG‐based wind energy system

This study proposes a discrete-time integral terminal sliding mode controller (DITSMC) integrated with a sensorless maximum power point tracking (MPPT) method for a permanent magnet synchronous generator (PMSG)-based wind energy conversion system (WECS). The effects of the parameters of the proposed DITSMC on the convergence-time and the error-bound are investigated by the simulation studies. The dynamic performance of the DITSMC has been evaluated experimentally on a test bench for step-type wind changes. The optimum coefficient between the output voltage of the generator and the extracted power from the WECS is determined only for a wind speed by offline studies. Then, the MPPT can be provided using this coefficient for all wind speeds in the operating range of the WECS without any mechanical sensor. Additionally, the experimental studies show that DITSMC has better performance than the PI controller in terms of the settling time and thus the efficiency of the WECS.

Linear Active Disturbances Rejection Control (LADRC) Applied for Wind Turbine DFIG Based Operating in Primary Frequency Control for a Micro-Grid

The objective of this paper is to simulate the vector control of a double-fed induction generator (DFIG) when it operating in system frequency control for the micro-grid structure. The control is provided by the linear active disturbances rejection control (LADRC) controller wish has several benefits over to the conventional PI controller such as the estimation and compensation in real time of the internal and external disturbances wish can be summarized in the parameters uncertainties. To ensure the performances and achieve the advantages of the LADRC controller in case of primary frequency control, the results are compared with the conventional PI by a simulation in MATLAB/Simulink. The results obtained have shown that the LADRC controller is much more efficient compared to a conventional PI controller in terms of control, finally with the advantage of rejecting internal and external disturbances with simple scheme of control, the primary frequency control can be better applied with this type of controller with a good dynamic frequency support and a reduction of the frequency variations.

Comparative Analysis on Speed Control of a Three Phase Induction Motor Drive Using Proportional Integral Differential and Scalar Closed Loop Fuzzy Logic Approach

The principles of controlling an AC driven three phase induction motor employing constant volts/hertz (v/f) control method and the space vector pulse width modulation (SVPWM) technique are reviewed. The induction motor is one of the most common electrical motors in usage, owing to its unique characteristics. Its further application strength requires a robust, problem handling, fast and intelligent speed control system. As a result of this, developing an intelligent knowledge based fuzzy logic controller (FLC) became eminent, and on this basis, this paper is presented. By varying the motor speed with input reference speed, an error signal and a feedback loop is generated. The FLC then operates on the principles of mapping with corrective measure of an error signal generated and it is regulated by sets of programmable IF-THEN rules integrating the Mamdani fuzzy inference approach. The rules projected and formed are used to overcome drawbacks such as complexities and insensitivities to changes in model parameters associated to conventional controllers. The application of the constant v/f method was used to maintain constant voltage to frequency ratio, therefore, creating a constant magnetic field and a maximum torque throughout the operating range. This in turn generates a voltage and an angle command for the actualization of the SVPWM technique. This entire set up was repeated but now with a classical control method like the proportional integral differential (PID) controller. With a simulation time of 2s, results showed that with FLC, a better speed response can be achieved from a 5Hp 350V 50Hz AC motor attaining steady-state at 0.21s at no-load conditions. Simulation results showed a superior dynamic scheme of the FLC over the PI controller in terms of sensitivity to changes in model parameters. With a load torque of 10Nm applied at 1s, the FLC achieved stability at 1.2s still maintaining a constant speed of 157rads/s.

An Efficient Nonlinear Backstepping Controller Approach of a Wind Energy Conversion System Based on a DFIG

In this paper, we present an efficient and adaptive nonlinear control model for wind energy conversion system based on a doubly-fed induction generator (DFIG). The aim of this work is to develop a model which combines the vector control and the nonlinear Backstepping approach to control the currents rotor and the mechanical speed of the DFIG to extract the maximum of the power generated. The performance of the system is tested and compared with PI controller in terms of reference tracking, and robustness against DFIG parameters variations. Simulation results are presented under MATLAB/Simulink software show the validity of the proposed control strategies .

Speed and Direction Angle Control of Four Wheel Drive Skid-Steered Mobile Robot by Using Fractional Order PI Controller

In this paper, speed and direction angle control of four-wheel drive skid-steered mobile robot (4WD SSMR) is realized by Fractional-Order Proportional Integral (FOPI) controller. Speed and direction angle of the mobile robot are calculated by using angular velocity of each motors. FOPI controller produces the torques of each motor of mobile robot for trajectory tracking and stabilization in the desired position. A well-tuned conventional PI controller is also applied to mobile robot for comparison with the FOPI. Experimental results prove that the FOPI shows better trajectory tracking performance than PI controller in terms of trajectory tracking accuracy and error levels.DOI: http://dx.doi.org/10.5755/j01.eie.22.5.16337

A new control method based on type-2 fuzzy neural PI controller to improve dynamic performance of a half-bridge DC–DC converter

Due to nonlinear behavior and the uncertainty with converter structure, controller design is difficult and accompanied with complexities. In this paper, a new control method based on Type-2 fuzzy neural PI (T2FN PI) controller is applied to improve the dynamic response of half-bridge DC–DC converters for different operation conditions. The T2FNN PI controller amends the specifications of the converter system by controlling its duty cycle of switching. In addition, proposed controller can property handle the uncertainty which is associated to converter structure, measuring devices and measured control signals.The T2FN PI controller is a combination of type-2 fuzzy linguistic process and neural network learning capability. The back-propagation algorithm is applied to train the parameters of T2FNN PI controller. Furthermore, PSO algorithm is applied to obtain the T2FN PI training pattern.In order to evaluate the performance of the proposed T2FN PI controller, it has been compared with a Fuzzy controller and the conventional PI controller for five different operating conditions. The simulation results show efficiency of the T2FNN PI controller in compare to Fuzzy controller and PI controller in terms of better rejection of disturbances, faster transient response and less peak overshoot.

A new smart charging method for EVs for frequency control of smart grid

Nowadays, due to the shortage of fossil fuels on the one hand and their high prices on the other hand, using electric vehicles (EVs) has been increased. Charging of EVs has imposed new loads on power systems. These new and major loads have faced the frequency control and stability of power systems with new challenges. One way to deal with this new challenge is smart charging of EVs. In this method, grid condition is a key parameter that affects the charging of EV. In other words, in smart charging method, charging is performed with respect to power system parameters such as frequency. In this paper, a smart charging method based on fuzzy controller is proposed, in which charging process is performed with respect to the frequency deviation of grid and state of charge (SOC) of EV battery. To evaluate the performance of the proposed controller in control of grid frequency, IEEE 39-bus system in the presence of renewable energy sources is considered as test system. In order to the frequency analysis, this system is converted into a three-area system and, for each area, several EV categories with different numbers of EVs, battery capacity, start time of charging, and initial SOC are supposed. Moreover performance of proposed method is compared with an optimized PI controller in terms of frequency control. To investigate performance of proposed method in charging of EVs, a two area system is assumed and charging of EVs is verified by applying step loads to both areas. Simulations are carried out in MATLAB/SIMULINK environment. Results of the simulations reveal the good performance of the proposed controller in terms of frequency control of grid and charging of EVs.

MATLAB Simulation of UPQC for Power Quality Mitigation Using an Ant Colony Based Fuzzy Control Technique.

This paper proposes a fuzzy logic based new control scheme for the Unified Power Quality Conditioner (UPQC) for minimizing the voltage sag and total harmonic distortion in the distribution system consequently to improve the power quality. UPQC is a recent power electronic module which guarantees better power quality mitigation as it has both series-active and shunt-active power filters (APFs). The fuzzy logic controller has recently attracted a great deal of attention and possesses conceptually the quality of the simplicity by tackling complex systems with vagueness and ambiguity. In this research, the fuzzy logic controller is utilized for the generation of reference signal controlling the UPQC. To enable this, a systematic approach for creating the fuzzy membership functions is carried out by using an ant colony optimization technique for optimal fuzzy logic control. An exhaustive simulation study using the MATLAB/Simulink is carried out to investigate and demonstrate the performance of the proposed fuzzy logic controller and the simulation results are compared with the PI controller in terms of its performance in improving the power quality by minimizing the voltage sag and total harmonic distortion.

Fuzzy Sliding Mode Control of PEM Fuel Cell System for Residential Application

Proton exchange membrane fuel cells (PEMFCs) are receiving more attention compared with other sources of power generation. Maintaining a fuel cell system requires excellent system control to receive the best operating. Therefore, in this paper a dynamic model of a (PEMFC) for residential power generation is applied. The model proposed includes the fuel cell stack model, power condition unite that consists of the methanol reformer model and DC-AC inverter model. According to power output of (PEM) fuel cell system, a fuzzy sliding mode controller which contains the characteristics of fuzzy control and sliding mode control is addressed, in order to modify the hydrogen flow feedback from the terminal load. In addition, this combined controller is used to improve stability by fuzzy reasoning to control the output variation that reduces chattering and increase the speed of tracking by reasoning of sliding mode control. Consequently, the dynamical behavior of system with FSMC is more improved as compared to the FLC and PI controller in terms of rate of hydrogen flow, output AC voltage and output power of FC and it is shown that the proposed controller can achieve better control effect than other controllers.

Improved PI controller based on predictive functional control for liquid level regulation in a coke fractionation tower

Due to limitations of hardware, cost and so on, the application of proportional-integral-derivative (PID) control is more convenient than predictive control. However, predictive control usually has better performance than traditional PID control, thus it is important to combine the advantages of these two control algorithms. A novel PI controller optimized by predictive functional control (PFC) is proposed and tested on liquid level in the industrial coke fractionation tower in this paper. Since this kind of process always shows the integrating behavior, a P controller is first used for it to generate a self-balancing generalized process, then the PFC based PI control is designed for the generalized process. The resulting controller displays the performance of both PFC and PI control with easy implementation in practice. The performance of the proposed PI controller is compared with traditional PI controller in terms of regulatory/servo set-point tracking, disturbance rejection and measurement noise issues, from which results show that the proposed PI controller provides better performance than traditional PI controller.

Stabilization loop of a two axes gimbal system using self-tuning PID type fuzzy controller

The application of inertial stabilization system is to stabilize the sensor's line of sight toward a target by isolating the sensor from the disturbances induced by the operating environment. The aim of this paper is to present two axes gimbal system. The gimbals torque relationships are derived using Lagrange equation considering the base angular motion and dynamic mass unbalance. The stabilization loops are constructed with cross coupling unit utilizing proposed fuzzy PID type controller. The overall control system is simulated and validated using MATLAB. Then, the performance of proposed controller is evaluated comparing with conventional PI controller in terms of transient response analysis and quantitative study of error analysis. The simulation results obtained in different conditions prove the efficiency of the proposed fuzzy controller which offers a better response than the classical one, and improves further the transient and steady-state performance.

REAL-TIME VELOCITY AND DIRECTION ANGLE CONTROL OF AN AUTOMATED GUIDED VEHICLE

In this paper, an adaptive fuzzy control (AFC) system is applied to velocity and direction angle control of a certain type of wheeled mobile robots called automated guided vehicles (AGVs). The fuzzy control system includes an adaptive model identifier and controller. The gains of fuzzy controller are obtained by using the fuzzy identifier model which is defined by real system outputs and control inputs. The parameters of fuzzy identifier model are adjusted online by using recursive least square algorithm. A PI controller is also applied to AGV to show the robustness of the AFC system. Experimental results prove that the AFC shows better tracking performance than the PI controller in terms of robustness, smoothness and fast dynamics. Results are given for complex references, sudden disturbance and extra load conditions.

Unified Power Quality Conditioner Using a Fuzzy Controller

The paper presents a three-phase unified power quality conditioner using a fuzzy controller. The fuzzy controller replaces the conventional PI controller in this work. The results obtained through the fuzzy controller are found superior to those obtained through conventional PI controller in terms of dynamic response. This is because of the fact that the fuzzy controller is based on a linguistic variable set theory and does not require a mathematical model of the system. Moreover, the tedious method of tuning the PI controller is not required in case of fuzzy controller. Simulations are carried out using MATLAB/Simulink to validate the theoretical findings.