Order PI Controller Research Articles

Optimized cascaded controller for frequency stabilization of marine microgrid system

The trend towards reducing greenhouse gas emissions by dipping the use of traditional sources of energy in marine power grids, as well as the rapid expansion of renewable energy sources (RESs), were the driving forces behind the incorporation of RESs in maritime microgrid systems and enquiry of the ensuing prevalent control mechanism. The frequency stability of a Marine Microgrid System (MMGS) is a critical aspect that directly affects its reliable and efficient operation. This study describes a method for frequency stabilization in independent maritime microgrids consists of diverse renewable energy resources including wind turbine generators, sea wave energy/tidal power generation, solar generation, bio-diesel generator and energy storage systems. This paper aims to develop a new optimal cascaded order proportional integral based proportional derivative for marine load frequency control. Due to the fact that the performance of the controller is highly dependent on the parameters of the controller, optimizing these coefficients can have a significant impact on the output performance of the LFC control. In light of this, this paper presents the sewing training-based optimization (STBO), a new human-based metaheuristic algorithm to optimize the coefficient of the suggested controller. The essential stimulation of STBO is the teaching procedure of sewing to beginner tailors. By utilizing a population of candidate solutions, the algorithm iteratively refines the control parameters to find the optimal set that minimizes frequency deviations and enhances system stability. The responses of the cascaded PI-PD controller are linked to those of the PID and PI controllers in order to demonstrate its superiority. To evaluate the efficiency of STBO, it is compared to well-established recent techniques such as fitness dependent optimization, grey wolf optimization and Jellyfish search optimization. From the results, it is observed that our proposed approach improved the settling time by 25.35%, 45.89%, and 29.35%, reduced peak overshoot by 78.34%, 67.71%, and 78.23%, and similarly reduced undershoot by 81.56%, 56.22% and 76.56% as compared to FDO, GWO and JSO techniques respectively. Finally, the sensitivity analysis is performed under ±50% load variation and ± 40% power system parameters to prove the robustness of the proposed controller.

Improved current control loops in wind side converter with the support of wild horse optimizer for enhancing the dynamic performance of PMSG-based wind generation system

ABSTRACT The creation of optimization methods is relatively common and popular today for solving issues in engineering areas. In this paper, a new wild horse optimizer (WHO) method is adopted to design an optimal controller for a permanent-magnet synchronous generator (PMSG)-based wind turbine system (WTS). A control method consisting of two current control loops of the optimized controller is proposed for the control of the machine-side converter. The dynamic performance of PMSG can be improved during the different normal and abnormal conditions through effective tuning of the PI controller gains which enhances the overall response of the system parameters. This enhancement consequently results in the realization of the maximal power tracking during wind speed changes and the fault ride-through capability during faults and large-signal events. Furthermore, the power fluctuations due to the incoming wind speed variants can be smoothed by using the suggested controller. In addition, the proposed controller system employs an optimal torque control method and braking chopper system to help in achieving such tasks. MATLAB simulations of a 1.5 MW PMSG-WTS have been carried out and compared with the Ziegler Nichols-based PI controller in order to validate the feasibility and efficacy of the proposed controller.

Finite-Dimensional Observer-Based PI Regulation Control of a Reaction–Diffusion Equation

This article investigates the output feedback setpoint regulation control of a reaction–diffusion equation by means of boundary control. The considered reaction–diffusion plant may be open-loop unstable. The proposed control strategy consists of the coupling of a finite-dimensional observer and a PI controller in order to achieve the boundary setpoint regulation control of various system outputs such as the Dirichlet and Neumann traces. In this context, it is shown that the order of the finite-dimensional observer can always be selected large enough, with an explicit criterion, to achieve both the stabilization of the plant and the setpoint regulation of the system output.

Wind Power System for Grid-connection Based on PMSG and PI Controlling under Variable Wind Speed

Wind power is an important part of sustainable energy development and plays a pivotal role in the background of the ‘Dual Carbon’ goal. In this paper, a wind power grid-connected model based on Permanent Magnetic Synchronous Generator(PMSG) is proposed. The pitch angle of the wind turbine and the waveform of the grid-side currents are controlled by the PI controller in order to realize the tracking of the power frequency and phase of the grid voltages, and eventually achieve the purpose of grid-connection. By utilizing MATLAB/Simulink, the simulation results reveal that the final output currents’ frequency and phase meet the requirements of grid-connection, and the Total Harmonic Distortion(THD) of the current waveform is less than 2%, which represents a high power quality. It can provide reference for efficient and convenient grid-connection of wind power generation.

Design of PSO-tuned FOPI & Smith predictor controller for nonlinear polymer electrolyte membrane fuel cell

ABSTRACT The polymer electrolyte membrane (PEM) fuel cell or proton exchange membrane fuel cell (PEMFC) has sparked a lot of interest in renewable electricity generation due to high efficiency, quick start up time, and low operating temperature. However, they exhibit highly nonlinear behavior with degraded power quality under uncertain input conditions. The hydrogen, oxygen, and air feed determine the PEMFC system’s performance. Controlling the manifold pressure at the cathode side is essential in preventing the problem of oxygen starvation. In this paper, a nonlinear dynamic model of the PEMFC is considered to control the supply manifold pressure. The performance of the nonlinear PEMFC with various classical controllers (PI, PD, PID, and PID with filter derivative), Smithpredictor, and Fractional Order PI (FOPI) controllers are compared. The optimization of classical controllers is performed by PID tuner. On the other hand, Smith predictor and FOPI controller are tuned by artificial intelligence technique, namely, Particle Swarm Optimization (PSO). The FOPI controller is also tuned with Genetic Algorithm (GA). The PEMFC output is compared in terms of performance evaluation parameters, i.e. settling time, overshoot, and steady state error. The computer simulations suggest that in comparison with GA-FOPI [settling time (ts) = 1.374 s, overshoot (Mp) = 18.452%, steady state error (ess) = 0.1%] and PSO-Smith predictor (ts = 1.262 s, Mp = 5.581%, ess = 0%), the PSO-FOPI controller results in much better settling time (ts = 1.008 s), overshoot (Mp = 2.577%), and steady state error (ess = 0%). Thus, PSO-optimized FOPI controller with nonlinear PEMFC outperforms the classical, PSO-Smith predictor, and GA-FOPI control schemes.

Modelling, control and supervisory optimization of generalized predictive control in catalytic cracking reactor

Abstract As gasoline demand increases, the efficiency of operation of Fluidized Catalytic Cracking Unit (FCCU) becomes paramount importance. In this paper, a dynamic model for FCCU is simulated and integrated with yield model in order to estimate the yield of products namely gasoline, light gases and coke. Conventional PI controllers are designed for the control of reactor and regenerator temperature. Since, the complete reaction occurs in a very short duration, the controllers are tuned so as to achieve shorter settling time and minimum overshot. Further in order to increase the yield, optimization of FCCU using Generalized Predictive Controller (GPC) at supervisory level is attempted. Through optimization of objective function, the GPC will provide optimized set point for the PI controller in order to maintain maximum gasoline yield.

Robust Frequency Control of an Islanded AC Micro Grid using BDA Optimized 3DOF Controller under Plug in Electric Vehicle

The article presents the effectiveness of a Binary Dragonfly Algorithm (BDA) based 3-DOF controller for robust frequency control in an islanded AC micro-grid system under different uncertainties. A micro-grid is incorporated with the integration of various renewable energy based distributed generations (DG). The proposed micro-grid system is structured with wind turbine generator (WTG), Photo voltaic (PV) system, Diesel engine generator (DEG), Micro-turbines (MT), Aqua electrolyzer based Fuel Cells(FC) and with few energy storage devices i.e Battery energy storage (BES) and Flywheel energy storage (FES). Moreover a chargeable plug in electric vehicle is effected as load side demand while obtaining frequency control mechanism in micro-grid system. However large dynamics, low inertia and incurred uncertainties of most DG system affects system performance especially on system frequency seriously. In view of this to obtain robust control mechanism in islanded micro-grid system the article proposes a novel Binary Dragonfly Algorithm based 3-DOF controller to ensure servicing of good quality power to remote consumers. The performances of proposed BDA optimized 3-DOF controller is compared with conventional PSO, GA technique based PID and PI controller in order to justify supremacy of proposed approaches. Finally it has been suggested that the proposed BDA optimized 3-DOF controller is more effectiveness over other optimized controllers.

Novel DTC induction machine drive improvement using controlled rectifier for DC voltage tuning

<span lang="EN-US">The application of the direct torque control strategy for induction machine drives is mainly characterized by torque and flux distortions caused by voltage vector limitation. The goal of this paper is to perform the conventional DTC induction machine drives and reduce ripples of both flux and torque response. The proposed contribution is based on the control of the DC output side of the rectifier feeding the voltage source inverter by means of PI controller in order to adapt the voltage vector used in typical DTC switching table. Mathematic models are built using MATLAB Simulink and programming environment; the simulation results show the difference between the proposed method and classical DTC.</span>

Reduction of Power Quality Issues in Micro-Grid using GA Tuned PI Controller Based DVR

In the present energy scenario, one of major problems is with Power quality. Power quality came to more relevant, focused, with the addition of suitable equipment, where its behavior is very much important to the power supply quality. Power quality issue is a phenomenon noted as a not usual standard current, frequency or voltage which may results in a failure of sophiscated devices. The main issue focuses at the power swell & sag. In the paper, authors present a novel methodology for the prevention of voltage sag & swell. To rectify this issue, customized power equipments are adopted. Among them, Dynamic Voltage Restorer (DVR), the best as well as right advanced customized power equipment used in power distribution networks. The advantages include reduced price, low size, and its good transient response to the interferences. This work explain the MATLAB results of a Dynamic Voltage Restorer (DVR) modeling and analysis. Here, conventional controller like PI type and GA Tuned PI controller are used for comparison. In the offered method, PI controller parameters using GA Tuned implemented is being replaced by the traditional PI controller in order to develop the performance of the plant. The aim of the controller is made faster than conventional technique based controller. By MATLAB simulation tool, the performance can be studied.

State‐space modelling of an interconnected system of renewable energy sources and grid for rural electrification

This study deals with the development of a state-space model for an interconnected system of renewable energy sources (RES) with grid. The RES technologies considered for power generation in the interconnected system are doubly fed induction generator (DFIG) based wind energy conversion system and biogas genset. A linearised model for DFIG has been developed for the system. For biogas genset, the control of frequency and voltage is taken care by the electronic speed governor and IEEE type-I excitation system, respectively. The interconnected system takes a fixed feed of power supply from the grid and the rest of the consumer load is taken care by the RES. Finally, state feedback controllers have been developed for this interconnected system which maintains the active and reactive power balance between different sources of RES when small signal perturbations are given in load and input wind power. The comparative analysis has also been performed with the conventional PI controllers in order to demonstrate the superiority of proposed feedback controllers for the interconnected power system.

A simple constant switching frequency of direct torque control of brushless DC motor

This paper discusses about direct torque control of Brushless DC motor by injecting the triangular waveform and using PI controller in order to reduce the torque and obtain constant switching frequency. Brushless DC motor are widely used in applications which require wide range of speed and torque control because of robust, longer lifespan, faster torque response and able to operate at high speed. Unlike conventional three phase DTC of induction machine (IM),the proposed DTC approach introduces two phase conduction mode. Besides that, the magnitude flux is considered constant in which the results only gains from constant torque region. Thus, the flux control loop is eliminated while implement this scheme. Using the triangular waveform that will be compare with actual torque, the proper switching pattern can be selected to control the generated torque and reducing commutation torque ripple. The torque response depends on the speed of the stator flux linkage which is directly controlled by selecting appropriate voltage space vectors from a look-up table to make sure the torque error within the band. The validity of the proposed control scheme for constant switching frequency and reduce torque ripple are verified through simulation and experimental results.

Artificial Neural Networks Based Maximum Power Point Tracking Photovoltaic System for Remote Park LED Lighting Applications

Due to the difficulty of electricity supplying to the remote locations by the grid, the standalone photovoltaic solar systems are playing a major role instead of the grid connected systems for the mentioned purpose. Remote or rural parks are daily visited locations; for this reason, this paper focuses on guaranteeing the maximum power point tracking(MPPT) conditions during day hours weather fluctuations through the artificial neural network (ANN) technique. ANN is adopted in this study due to its accuracy and fast tracking response by directly estimating the instantaneous values of MPP compared to the conventional techniques. A park lighting of total rated power 1.8 kW based on LED lamps is ,in this study, considered in order to remove the complexity of alternating system requirements such as an inverter, an insulating transformer, and a power filter. MATLAB/Simulink software is adopted in order to evaluate the proposed PV system. The presented study includes PV matrix design based on PV module of MPP power 150 W, an efficient ANN algorithm is working with PI controller in order to have accurate reference voltages and consequently producing the desired PWM drive pulses. A buck-boost DC-DC converter is designed to control the output load power. The collected and analyzed results are promising an effective practical standalone system for park lighting applications.

Active & reactive powers control of DFIG placed with wind energy system by using hybrid controller

Here paper presents around the Active power along with Reactive power clout of a grid allied doubly fed Induction Generator (DFIG) with wind energy system (WES) employing PI & ANFIS controller. DFIG is formed adapting a d-q revolving allusion cage circuit with stator flux oriented, field oriented clout approach. By using a coterminous converter of Variable speed constant Frequency (VSCF) along with active the reactive power and DC tie voltage are controlled at sub and super synchronous speeds. An ANFIS has been coupled by a conventional PI controller in order to enhance the power controlling capability at steady state and voltage dip conditions

Fractional PID controller design for nonlinear systems based on singular perturbation technique

This paper deals with the output regulation of nonlinear control systems in order to guarantee desired performances in the presence of plant parameters variations and external disturbances. The proposed control law structures are based on the fractional order PI (FOPI) and PID (FOPID) control schemes. By introducing the two-time-scale notions in the closed-loop system, the presented design methodology of fractional PID control guarantees desired transients. Then, the singular perturbations technique is used to analyse the closed-loop system properties and to get explicit expressions for evaluation of the controller parameters. The tuning of the controller parameters is based on a constrained optimisation algorithm. Simulation examples are presented to show the effectiveness of the proposed method.

Neuro-Fuzzy control for four Wheels electric vehicle safety

This paper present novel approach for traction control of four wheel electric propulsion system for each wheel. This algorithm is necessary to improve the vehicle safety, the independent Machine Control philosophy is employed using an intelligent controller for torque and speed estimation, the proposed system replace the classical PI controller in order to improve vehicle dynamic performances. When the classical proposed control can't ensure the electric vehicle stability in several road topology situation's. The electronic differential system using adaptive fuzzy logic controller permit to vehicle to achieve intelligent driving. To show the efficiency of vehicle system control both of classical and intelligent controller are tested on Matlab Simulink environment ,the results obtained present satisfactory and show clearly the best response of the intelligent control during driving trajectory. The obtained data prove clearly that the worst performances of driving using PI comparing with adaptive fuzzy logic controller with no overshoot and no speed error and less estimated current ,and optimized autonomy.

An Improved PI-MultiStart Control Algorithm for Standalone PV Inverter System

This paper proposes an improved voltage controller using MultiStart optimization (MS) algorithm based PI (MS-PI) to control the modulation index for stand-alone PV inverter under different load conditions. In this proposed control algorithm (MS-PI), and parameters are automatically tuned to avoid the trial and error procedure in the classical PI controller in order to minimize the output voltage error. To do so, the mean square error (MSE) is used as an objective function with the MultiStart algorithm code. MATLAB models (Simulink and Code) for a PV inverter and the proposed control algorithm are developed. In order to get the desired output voltage of the inverter, a statistical evaluation for the proposed controller (MS-PI) is investigated and compared with that one’s obtained by particle swarm optimization (PSO) algorithm based PI approach (PSO-PI). Based on the results, the proposed controller has proven that its performance is robust and efficient in terms of total harmonic distortion (THD), regulated voltage amplitude in term of oscillation, and the minimum value of mean square error (MSE) as compared to the PSO-PI algorithm.

Modeling and Control of Low Frequency Dynamics of a Smart System

Background/Objectives: Active vibration control is an important aspect in mechatronic system dynamics and control. The objective of this manuscript is to present a classical PI controller in order to control the vibrations of a piezoelectric laminate flexible cantilever beam when excited by various signals. Methods/Statistical analysis: Finite element modeling techniques are employed to analytically develop the mathematical model of the smart system which replicates the low frequency system dynamics. The sensor, exciter and control actuator dynamics are modeled as well. The programming platform selected for developing the math model is MATLAB. The developed model was exported to SIMULINK platform for the controller design wherein classical PI control technique is implemented. Findings: The developed model is verified for its accuracy from its frequency response to free vibration condition which showed a close match between the resonant frequencies of the model with that derived from theory of vibrations. PI controller is the most commonly used controller worldwide due to its ease in computation as well as cost effectiveness. Its efficiency is proved in this manuscript when the system was subjected to free vibration in open loop as well as with the controller in loop. Further, as in practical cases, the system was also subjected to harmonic excitations at the dominant resonant frequencies and here as well, the controller was highly efficient in damping out the vibrations. Application/Improvements: The work presented in this manuscript can be extrapolated to any fixed-free system in aerospace, defence as well as heavy industries. The performance of the active controller can be further improved by opting for math intensive robust control strategies.

Optimized sensor and sensorless control of PMSM modeled in discrete mode: a comparison of KH and PSO algorithms

Purpose The purpose of this paper is to improve dynamic performance of the permanent magnet synchronous motor (PMSM) field oriented control by means of optimizing its PI controller’s coefficients. Design/methodology/approach In this paper, Krill Herd (KH) optimization algorithm is proposed to optimize PI controller coefficients. Moreover, drive control system and steady state estimator are implemented in discrete mode. In order to evaluate the performance of the proposed algorithm, a comparison is carried out between KH and PSO algorithms. It is noteworthy that PSO algorithm has presented the best dynamic response among the studied approaches in literature. Findings By using the proposed optimization algorithm, the system tracks the reference speed with a very low error. In addition, the discrete mode simulations do not require initiating integrators. Moreover, it significantly increases the processing speed. The proposed approach is carried out in both sensor and sensorless drive systems. The simulation results indicate lower torque ripple, shorter settling time, lower overshoot, faster dynamic response and higher robustness against speed, torque and machine parameter changes. Practical implications The PI controller is extensively used in practical drive systems, due to its simple structure and implementation as well as its acceptable performance. On the other hand, PMSM benefits from high power density, high efficiency, low torque ripple, low inertia, and high performance in a wide speed range. This paper presents an efficient approach to optimize PI coefficients of the PMSM drive system. Originality/value This paper proposes a new algorithm (KH algorithm) to determine the coefficients of PI controllers in order to improve dynamic performance of the PMSM drive system.

Nonlinear Speed Control of Permanent Magnet Synchronous Motor with Salient Poles

This paper presents the speed control of permanent magnet synchronous motor with salient poles based on two-step linearization method. In the first step, the direct compensation of the nonlinearities in the equations of current is used. In the second step, the input-output linearization in the state space is used for the decoupling of flux and torque axis. Simulated results are compared to the field oriented vector control structure with PI controllers in order to show differences in the performance of both approaches. ��Keywords:nonlinear control, permanent magnet synchronous machine, feedback linearization, transformation matrix, nonlinear canonical form

Particle swarm optimization based PI controller of VSC-HVDC system connected to a wind farm

This paper, explores the connection of a wind farm to the grid through high voltage direct current system on voltage source converter VSC-HVDC. 12 MW wind farm consisting of 6 individual 2 MW permanent magnet synchronous generators is presented. In this paper we proposed a new particle swarm optimization algorithm (PSO) based PI controller in order to optimize the gains of PI controller of VSC-HVDC link, which consequently improve the stability of the link after a strict faults. Different results are obtained to show the efficiency of the proposed PSO algorithm for the conception of optimal controller for a VSC-HVDC link connected to a wind farm. MATLAB/Similink simulations are provided to illustrate the performance of the proposed approach under serious perturbation as single AC fault and DC fault.