Proportional-integral Controller Parameters Research Articles

Improved PR Control Strategy for an LCL Three-Phase Grid-Connected Inverter Based on Active Damping

Aiming at the problem of power coupling and complicated decoupling in the d-q coordinate system of a three-phase grid-connected inverter, a current closed-loop control strategy based on an improved QPIR (quasi-proportional integral resonant) controller in the α-β two-phase static coordinate system is proposed. Firstly, the mathematical model of an LCL three-phase grid-connected inverter is established, and its instantaneous power calculation equation is deduced. Secondly, the frequency method is applied to compare and analyze the proportional resonant, quasi-proportional resonant, and improved current controller, and the appropriate improved controller parameters are obtained according to the traditional proportional integral controller parameter design method and the weight coefficient. Finally, the improved controller is compared with the traditional controller in the simulation model of the LCL three-phase grid-connected inverter based on active damping. The results show that the proposed improved current control strategy has good dynamic response characteristics, can realize the non-static error control of grid-connected current, and realizes the decoupling control of active power and reactive power when the load jumps. At the same time, the results also prove the superiority of the proposed control strategy and verify its effectiveness.

Modeling and Simulation of Three Phase Power Factor Correctors with Fast Dynamic Response based on Fixed PWM and Bang-Bang control Techniques using DC-DC SEPIC Converter Modules

The main concerns of the power supply industry is to obtain a single stage converter with a low-cost for achieving power factor correction (PFC) complying with required harmonic standards and regulated output voltage simultaneously for three-phase applications. This paper presents the modelling and simulation of single stage three phase power factor correctors using DC-DC SEPIC converter modules based on cascade control strategy. It uses outer loop using proportional-integral (PI) controller to regulate the output voltage and three inner fixed PWM/bang-bang controllers to shape the source current. PI controller parameters are determined by using TYREUS-LUYBEN tuning method. Performance analysis has been made for the two proposed approaches by comparing the simulation results. Results reveal that the proposed scheme provides the power factor close to unity, low % total harmonic distortion (THD), regulated output voltage for load variations and effective set point tracking. Experimental results using fixed PWM technique is also presented.

A four-level test system for evaluating pavement compaction performance of autonomous articulated vehicles

This article develops a four-level test system for accurately evaluating pavement compaction performance of autonomous articulated vehicles. In the evaluation layer, various performance indicators are evaluated, including the stability, rapidity and accuracy of trajectory tracking, and the ratio of required compaction to actual compaction once and twice and compaction repeatability index when pavement compaction. The guidance and control layer can be described in terms of theory and application. At the theoretical level, the line of sight guidance algorithm and incremental proportional integral control algorithm are introduced to eliminate system control lag. Among them, the best line of sight guidance and incremental proportional integral control parameters are selected by the Elitist strategies genetic algorithm, and the initial parameters are set according to human driving experience initial control parameters. At the application level, the BECKHOFF controller, a kind of programmable logic controller, acts as the main guidance and control unit in the four-level control system, fixed speed is given to the autonomous articulated vehicle by setting the engine speed and transmission gear, and steering wheel angle is adjusted in real time by the BECKHOFF controller. In the sensor level, a simplified sensor configuration is used to reduce overall cost. The comparative simulation results of no controller, the incremental proportional integral controller, line of sight guidance-incremental proportional integral controller with human driving experience initial control parameters, line of sight guidance-incremental proportional integral controller with random initial control parameters, and elitist strategies genetic algorithm-line of sight guidance-incremental proportional integral controller with human driving experience initial control parameters manifest evidently that the proposed elitist strategies genetic algorithm-line of sight guidance-incremental proportional integral controller with human driving experience initial control parameters has almost no steady-state error, no overshoot, and short settling time. Field results show that ratio of required compaction to actual compaction once achieves 100%, ratio of required compaction to actual compaction twice achieves 94.6%, and compaction repeatability index achieves 35%.

Particle swarm optimization algorithm-based PI inverter controller for a grid-connected PV system.

The lack of control in voltage overshoot, transient response, and steady state error are major issues that are frequently encountered in a grid-connected photovoltaic (PV) system, resulting in poor power quality performance and damages to the overall power system. This paper presents the performance of a control strategy for an inverter in a three-phase grid-connected PV system. The system consists of a PV panel, a boost converter, a DC link, an inverter, and a resistor-inductor (RL) filter and is connected to the utility grid through a voltage source inverter. The main objective of the proposed strategy is to improve the power quality performance of the three-phase grid-connected inverter system by optimising the proportional-integral (PI) controller. Such a strategy aims to reduce the DC link input voltage fluctuation, decrease the harmonics, and stabilise the output current, voltage, frequency, and power flow. The particle swarm optimisation (PSO) technique was implemented to tune the PI controller parameters by minimising the error of the voltage regulator and current controller schemes in the inverter system. The system model and control strategies were implemented using MATLAB/Simulink environment (Version 2020A) Simscape-Power system toolbox. Results show that the proposed strategy outperformed other reported research works with total harmonic distortion (THD) at a grid voltage and current of 0.29% and 2.72%, respectively, and a transient response time of 0.1853s. Compared to conventional systems, the PI controller with PSO-based optimization provides less voltage overshoot by 11.1% while reducing the time to reach equilibrium state by 32.6%. The consideration of additional input parameters and the optimization of input parameters were identified to be the two main factors that contribute to the significant improvements in power quality control. Therefore, the proposed strategy effectively enhances the power quality of the utility grid, and such an enhancement contributes to the efficient and smooth integration of the PV system.

Design and implementation of an LCL grid‐connected inverter based on capacitive current fractional proportional–integral feedback strategy

The capacitive current feedback active damping strategy has a limited damping region. When the grid-side impedance is large, the digital control inductor–capacitor–inductor (LCL) grid-connected inverter system with grid-side current loop control and capacitive current feedback active damping cannot run stably. To address this issue, this study proposes an improved capacitive current feedback active damping strategy, namely the capacitive current fractional proportional–integral feedback strategy (CCFPIFS), which increases the upper-frequency limit of the system damping region and approaches to the Nyquist sampling frequency. Furthermore, this study analyses the constraints of fractional-order proportional–integral controller parameters to ensure the stability of the system. The simulation analysis is performed by Simulink. The experimental results are consistent with theoretical expectations. Consequently, the proposed CCFPIFS can not only achieve better control performance and improve the robustness of the LCL grid-connected inverter system, but also improve the output power quality of the system. This damping strategy can make the LCL grid-connected inverter system work stably under the environment of high grid impedance.

Adaptive Hybrid Fuzzy PI-LQR Optimal Control using Artificial Immune System via Clonal Selection for Two-Area Load Frequency Control

Load frequency control (LFC) problem has been a foremost issue in electrical power system operation and is becoming more important recently with growing size, changing structure, and complexity in interconnected power systems. In general, LFC system utilizes simple proportional integral (PI) controller. However, due to the PI control parameters are commonly adjusted based on classical or trial-error method (TEM), it is incapable of obtaining good dynamic performance for a wide range of operating conditions and various load change scenarios in a multi-area power system. This paper introduces a novel control scheme for load frequency control (LFC) using hybrid fuzzy proportional integral (fuzzy PI) and linear quadratic regulator (LQR) optimal control, where fuzzy logic control (FLC) is used to adjust the gains KP and KI of PI controller which called fuzzy PI in this paper, while the LQR optimal control method is employed to obtain the feedback gain KOP through Algebraic Riccati Equation (ARE). The merit of both control strategies is to tune their control feedback gains, which are KP, KI and KOP, regarding various system operating conditions. Artificial immune system (AIS) via clonal selection is utilized to optimize the membership function (MF) of fuzzy PI and weighting matrices Q and R of LQR optimal control in order to obtain their optimal feedback gains. To examine the efficacy of the proposed method, LFC of two-area power system model is utilized as a test system. The amalgamation of fuzzy PI-LQR is applied to improve the dynamic performance of two-area LFC. Other control schemes such as PI controller, hybrid PI controllerLQR, and hybrid fuzzy PI-LQR are also investigated to the studied a test system. The obtained simulation results show that the proposed method could compress the settling time and decrease the overshoot of LFC which is better than other approaches that are also employed to the tested system in this study.

Simple Tuning Rules for Feedforward Compensators Applied to Greenhouse Daytime Temperature Control Using Natural Ventilation

In this work, simple tuning rules for feedforward compensators were applied to design a control strategy to regulate the inside air temperature of a greenhouse during daytime by means of a natural ventilation system. The developed control strategy is based on a PI (Proportional-Integral) controller combined with feedforward compensators to improve the performance against measurable external disturbances such as outside air temperature, solar radiation, and wind velocity. Since the greenhouse process dynamics is very complex and physical non-linear models are mathematically complicated, a system identification methodology was proposed to obtain simpler models (high-order polynomial and low-order transfer functions). Thus, an easier procedure was completed to tune the PI controller parameters and to obtain the feedforward compensators expressions by following a series of modern and simple tuning rules. Simulations with real data were executed to compare the control performance of a PI controller with or without the addition of feedforward compensators. Moreover, real tests for the developed control strategy were carried out in an experimental greenhouse. Results demonstrate an enhanced control performance with the presence of the feedforward compensators under different weather conditions.

Analysis and Design of a Double Fuzzy PI Controller of a Voltage Outer Loop in a Reversible Three-Phase PWM Converter

Aiming at the application of a reversible three-phase pulse width modulation (PWM) converter with a wide range of AC side voltage and DC side voltage, a double fuzzy proportional integral (PI) controller for voltage outer loop was proposed. The structures of the proposed controller were motivated by the problems that either the traditional PI controller or single fuzzy PI controller cannot achieve high performance in a wide range of AC and DC voltage conditions. The presented double fuzzy controller studied in this paper is a sub fuzzy controller in addition to the traditional fuzzy PI controller; in particular, the sub fuzzy controller can get the auxiliary correction of PI control parameters according to the AC side voltage and the DC side given voltage variation of PWM converter after the reasoning of the sub fuzzy controller, while the traditional fuzzy PI controller outputs the correction of PI control parameters according to the DC voltage error and its error change rate. In this paper, the traditional fuzzy PI controller can be called the main fuzzy controller, and the adaptive adjustment of PI control parameters of the voltage outer loop is the sum of the PI parameter correction output by the main fuzzy controller and the auxiliary PI parameter correction output by the sub fuzzy controller. Finally, the experimental results show that the reversible three-phase PWM converter can achieve excellent dynamic and static performance in a wide range of AC voltage and DC voltage applications by using the proposed double fuzzy PI controller.

Validity of continuous tuning rules in event-based PI controllers using symmetric send-on-delta sampling: An experimental approach

One of the difficulties encountered in the tuning of event-based proportional-integral (PI) controllers using symmetric send-on-delta sampling (SSOD) is the possible appearance of a stable limit cycle, especially when tuning rules designed for continuous control loops are applied. This oscillation is a consequence of the intersection in the Nyquist map of the open loop transfer function (process + controller) with the negative reciprocal of the describing function (DF) of the SSOD sampler. As the DF-based approach is an approximated method and therefore it introduces errors in the locations of the intersections in the Nyquist map, a set of oscillation-free PI controller parameters regions generated by an experimental approach are presented in this paper. The relevant aspect of these regions is that any parameters’ couple located inside them implies a controller that can be applied for the control of first order or integrating processes without generating stable limit cycles. As these regions constitute a resource to check whether a continuous tuning rule can be safely applied in an event-based control loop, a study of the validity of some PI tuning rules is provided in the paper. Also, the regions provide a framework for the design of tuning rules specifically formulated for event-based PI controllers and an example of that is presented in the paper. Finally, it is analyzed whether the classical sensitivity functions can be used as a tool to check and design tuning rules for SSOD-PI controllers instead of the experimental regions.

Adaptive ELM neural computing framework with fuzzy PI controller for speed regulation in permanent magnet synchronous motors

In this work, a new adaptive extreme learning machine (ELM) neural network-based fuzzy controller is designed and simulated for implementing speed regulation in a permanent magnet synchronous motor. ELM is a neural model wherein the number of hidden neurons to be placed in the hidden layer is tuned during the process of neural network training itself. A new adaptive ELM model is developed for placing the number of hidden neurons in the hidden layer, and this new adaptive ELM is tuned with artificial bee colony (ABC) algorithm for optimizing its weight parameters and also the number of hidden neurons. Fuzzy proportional–integral (PI) controller is developed in this work in order to eliminate the steady-state error. The new adaptive ELM neural model optimized with ABC algorithm is applied to tune the input parameters of the fuzzy PI controller and also on optimizing the rules and fuzzy membership functions. The optimized adaptive ELM neural network-based fuzzy PI controller is utilized to investigate the speed regulation of permanent magnet synchronous motor (PMSM) in this work. The developed new PI controller with the PMSM is tested for its performance characteristics and to prove its validity is compared with the traditional controller and other heuristic controllers proposed in earlier literature works.

Simulation of Closed-Loop Deep Brain Stimulation Control Schemes for Suppression of Pathological Beta Oscillations in Parkinson's Disease.

This study presents a computational model of closed-loop control of deep brain stimulation (DBS) for Parkinson’s disease (PD) to investigate clinically viable control schemes for suppressing pathological beta-band activity. Closed-loop DBS for PD has shown promising results in preliminary clinical studies and offers the potential to achieve better control of patient symptoms and side effects with lower power consumption than conventional open-loop DBS. However, extensive testing of algorithms in patients is difficult. The model presented provides a means to explore a range of control algorithms in silico and optimize control parameters before preclinical testing. The model incorporates (i) the extracellular DBS electric field, (ii) antidromic and orthodromic activation of STN afferent fibers, (iii) the LFP detected at non-stimulating contacts on the DBS electrode and (iv) temporal variation of network beta-band activity within the thalamo-cortico-basal ganglia loop. The performance of on-off and dual-threshold controllers for suppressing beta-band activity by modulating the DBS amplitude were first verified, showing levels of beta suppression and reductions in power consumption comparable with previous clinical studies. Proportional (P) and proportional-integral (PI) closed-loop controllers for amplitude and frequency modulation were then investigated. A simple tuning rule was derived for selecting effective PI controller parameters to target long duration beta bursts while respecting clinical constraints that limit the rate of change of stimulation parameters. Of the controllers tested, PI controllers displayed superior performance for regulating network beta-band activity whilst accounting for clinical considerations. Proportional controllers resulted in undesirable rapid fluctuations of the DBS parameters which may exceed clinically tolerable rate limits. Overall, the PI controller for modulating DBS frequency performed best, reducing the mean error by 83% compared to DBS off and the mean power consumed to 25% of that utilized by open-loop DBS. The network model presented captures sufficient physiological detail to act as a surrogate for preclinical testing of closed-loop DBS algorithms using a clinically accessible biomarker, providing a first step for deriving and testing novel, clinically suitable closed-loop DBS controllers.

Design of Load Frequency Control for a Microgrid Using D-partition Method

AbstractThis paper proposes a load frequency control (LFC) scheme for the distributed generation (DG) system of the microgrid (μ-grid) using the D-partition method (DPM). μ-grid is formed with a combination of renewable and non-renewable sources to supply distribution system loads of smaller capacity. In this research paper, μ-grid comprising of a combination of a wind turbine generator (WTG) and Diesel Generator (DG) are taken for investigation of LFC. For the effective control of real power generation of μ-grid, Proportional-integral (PI) controllers are implemented for WTG and DG system so that the frequency deviation is minimized. The PI controller parameters found by using DPM are compared with the conventional Ziegler-Nichols method (ZNM). The main contribution of this work is to provide a single step /simplistic computing method for calculating the PI controller parameters of a dynamic system such as the microgrid system comprising of the renewable energy sources without any further requirements of retuning. Simulation results demonstrate the robustness of the DPM, which is superior in damping frequency oscillations of μ-grid.

Salp swarm algorithm‐based optimal control scheme for LVRT capability improvement of grid‐connected photovoltaic power plants: design and experimental validation

Contribution of Photovoltaic (PV) systems is rapidly growing and great attention is given to the design of PV controllers to enhance both the performance of PV systems and the low voltage ride through (LVRT) capability during abnormal operational conditions. This article presents a novel application of the salp swarm algorithm (SSA) in order to optimally tune the PV controllers to enhance the LVRT of grid-connected PV systems. Enhancement of LVRT is indicated in percentage undershoots or overshoots, settling time and steady-state error of voltage response. A control strategy is applied to the DC-DC converter to obtain a maximum power point tracking operation through a proportional-integral (PI)-based open fractional voltage control. The grid side inverter controls both the point of common coupling voltage and the DC-link voltage through PI-based cascaded-voltage control. To get PI controller parameters that guarantee the optimum design of the controllers, the fitness function is optimized by using the SSA. The proposed optimal control scheme is tested under various fault scenarios and compared with other conventional optimization-based PI controllers to examine its validity under PSCAD environment. The effectiveness of the optimal control scheme is verified by comparing the simulation results with the practical results of the PV system.

A Practical Study of Improved Speed Performance of BLDC Motors Using Conventional PI And Fuzzy-PI Controllers

Brushless Direct Current Motors (BLDC) motors are available for large-scale use and commercially diverse industrial implementation, seeking faster and more efficient control. Proportional-integral (PI) controllers, like traditional controllers, perform better in pre-defined or user-defined motion bands. However, to achieve better performance for applications at wide speeds, they must be re-tuned at each speed change. Therefore, it is inconvenient or in most cases, it is not possible to re-tune the PI controller parameters in each setup to get the correct response from the BLDC motor drive for the entire speed range. Fuzzy-logic based PI controllers can efficiently tune these PI parameters for each phase change of command speed and improve the speed response of electric drives. This paper discusses the implementation plan for the speed control of the BLDC motors using the expensive ATMEGA328P-PU controller, the prosaic PI, and the Fuzzy Logic-Based-PU Controller. In this paper, simulation and hardware results that validate the effectiveness of the control scheme are presented.

Robust PI Control of Interval Plants With Gain and Phase Margin Specifications: Application to a Continuous Stirred Tank Reactor

The paper is focused on robust Proportional-Integral (PI) control of interval plants with gain and phase margin specifications and on the application of this approach to a Continuous Stirred Tank Reactor (CSTR). More specifically, the work aims at the determination of PI controller parameter regions, for which not only robust stability but also some level of robust performance of the closed-loop control system is guaranteed, and this robust performance is represented by the required gain and phase margin that has to be ensured for all potential members of the interval family of controlled plants, even for the worst case. The applied technique is based on the combination of the previously published generalization of stability boundary locus method (for specified gain and phase margin under the assumption of fixed-parameter plants) with the sixteen plant theorem. This extension enables the direct application of the method to design the robustly performing PI controllers for interval plants. The effectiveness of the improved method is demonstrated on a CSTR, modeled as the interval plant, for which the robust stability and robust performance regions are obtained.

Validating Continuous Tuning Rules for Event-Based PI Control of Lag-Dominant Processes

One of the difficulties of the tuning of event-based proportional-integral (PI) controllers using symmetric send-on-delta sampling (SSOD) is the appearance of a stable limit cycle, especially when rules designed for continuous control loops are applied. This oscillation is explained by the intersection in the Nyquist map of the system, that is, of the loop transfer function, with the negative reciprocal of the describing function (DF) of the SSOD sampler. However, as the DF theory is based on neglecting the high-order harmonics in the closed loop system, it introduces errors in the prediction of the oscillations. The paper presents an experimental study that establishes the boundaries of the PI controller parameters (proportional and integral gains) that avoid any limit cycle considering that a lag-dominant first order process model is used for the tuning. By taking into account the boundaries, a safety application in an event-based framework of any tuning rule designed for the classical time-driven case is possible.

Relative Studies of Improved Speed Performance of BLDC Motors Using Conventional PI and Fuzzy-PI Controllers

Brushless Direct Current Motors (BLDC) motors are available for large-scale use and commercially diverse industrial implementation, seeking faster and more efficient control. Proportional-integral (PI) controllers, like traditional controllers, perform better in pre-defined or user-defined motion bands. However, to achieve better performance for applications at wide speeds, they must be re-tuned at each speed change. Therefore, it is inconvenient or in most cases, it is not possible to re-tune the PI controller parameters in each setup to get the correct response from the BLDC motor drive for the entire speed range. Fuzzy-logic based PI controllers can efficiently tune these PI parameters for each phase change of command speed and improve the speed response of electric drives. This paper discusses the implementation plan for the speed control of the BLDC motors using the expensive ATMEGA328P-PU controller, the prosaic PI, and the Fuzzy Logic-Based-PU Controller. In this paper, simulation and hardware results that validate the effectiveness of the control scheme are presented.

A Communication-free Signal Generating Technique for Reactive Power Correction in Islanded Microgrid

The primary function of microgrid (MG) is to share the power accurately among different distributed generation (DG) units according to the load demands. The droop control methods are normally used for appropriate power sharing. However, these control techniques suffer badly due to the feeder impedances and uncontrollable power coupling issues. Many techniques have been proposed to share power accurately, most of them rely on communication link. In this work a localized/communication free signal generating mechanism is proposed. The mechanism injects the transient reactive power in frequency droop characteristics by observing the changes in microgrid. This injection disturbs the actual active power sharing which is helpful for the computation of reactive power sharing errors. These errors are minimized by utilizing the proportional integral (PI) controller. The PI controller modifies the y-intercept and the slop of Q-E (Reactive Power –Voltage) droop characteristic for the correction of reactive power sharing error. Moreover, the parameters of droop and PI controller of inner control loop are optimized by Particle Swarm Optimization (PSO) to obtain high precision and reliability. The proposed technique has the following salient features:1. Accurately shares the reactive power without the information of feeder line impedances2. This accurate reactive power sharing scheme has been started locally without the need of communication signal from the central controller. Thus, there is no delay in monitoring the notable changes in microgrid caused by DGs. 3. The careful selection of PI & droop controller parameters through PSO makes the system more stable as compared to the conventional methods in terms of transients and steady state responses.

Automatic Generation Control of a Two Area Thermal-Thermal Deregulated Power System with HES and TCPS units for Unscheduled Interchange Price Signals

Automatic Generation Control (AGC) plot for two area inter-connected thermal to thermal Deregulated Power System (DPS) utilizing Unscheduled Interchange (UI) price signal, which has an effect on the power markets is proposed in the paper. Unscheduled Interchange price is one of the most important parts of Availability Based Tariff (ABT) which goes about as an optional control system for regulating the grid frequency. These UI price signals vacillate according to change in grid frequencies which can be open by the participants (generator or load) associated with the grid. The customary AGC system, however, attempts to carry the error of frequency to 0, yet it will be an ineffectual answer for taking an interest producing penalty deviations with frequency. This plan additionally gives the system operator adaptability to plan the generation in an ideal way. In this examination, the execution of a Proportional Integral (PI) controller is proposed because beneficial AGC of 2 area thermal and thermal deregulated system works under the impacts of bi-lateral contracts over the dynamics. The tuning of PI controller parameters is illuminated by utilizing a Moth-Flame Optimization (MFO) algorithm. Further to improve the AGC performance, the Hydrogen Energy Storage (HES) units is incorporated into its control area which can adequately moist the electromechanical motions in a power system, as they give guarantee from the storage limit notwithstanding the generator rotors dynamic energy which can share abrupt deviations in power requirement. The Thyristor Controlled Phase Shifter is proposed in arrangement with tie line between any inter-connected areas that may be applied to balance out frequency motions of the area by fast control of power in tie line over the interconnections. Execution of HES-TCPS units' blend captures the underlying frequency fall just as the power deviations in tie line for an abrupt load unsettling influence and the outcomes show that the charges of UI are extensively limited while keeping up at normal frequency worth. Furthermore, proposed strategy yields an eminent decrease in the control input deviation yet, in addition, guarantees superior soundness for the unscheduled interchange price signals therefore, the market participants can get benefit accordingly.

Computation of stability regions for load frequency control systems including incommensurate time delays

This article studies the impact of incommensurate communication time delays on stability regions defined in proportional-integral (PI) controller parameter space for a two-area load frequency control (LFC) system. Distributed power generations and large power plants increase the complexity and control issues of interconnected power systems. In interconnected power systems, LFC systems need to have complex communication networks to exchange data between control center and geographically dispersed generations. The receiving/transmitting of remote measuring data through communication infrastructures causes inevitable time delays, which adversely affect controller performance and stability of the LFC system. Time delays introducing feedback control loops of a multiarea LFC system could exhibit incommensurate characteristics. In this study, a simple graphical method based on extracting a stability boundary locus is implemented to get PI controller parameters responsible for stabilizing the LFC system having incommensurate delay values. The boundaries of the stability regions in the PI controller parameter space are confirmed by time-domain simulations and a numerical algorithm known as the quasipolynomial mapping-based root finder algorithm. Results illustrate that incommensurate delays have remarkable effects on the stability region.