Gain PI Controller Research Articles

Adaptive neural network control of a centrifugal chiller system

In this paper, a neuro-adaptive PI control strategy for a water-cooled centrifugal chiller system is developed, and its control performance is examined. The system model consists of a flooded evaporator, a flooded condenser, a centrifugal compressor, and an electronic expansion valve. The overall system consists of three control loops: a compressor speed control loop, an inlet guide vane (IGV) control loop, and a condenser liquid level control loop. A neuro-adaptive control strategy for compressor speed control was designed. The control performance of the chiller was tested by carrying out simulation runs using an integrated building and HVAC (IB-HVAC) system model. The major details of the IB-HVAC model are described in this paper. Results show that the neuro-adaptive controller can adapt to new system dynamics of the IB-HVAC system and give good setpoint tracking responses under a wide range of operating conditions. The results show that the neuro-adaptive controller performs better than the constant gain PI controller in terms of speed of response and setpoint tracking properties.

Power quality improvement in distribution generation with renewable energy sources using hybrid GBDT-BCMO approach

ABSTRACT This paper presents a hybrid control system designed to improve power quality in grid-integrated hybrid renewable energy sources (HRES). The proposed hybrid control scheme is a hybrid approach gradient boosting decision tree and balancing composite motion optimisation, named GBDT-BCMO. The goals outlined above are the focus of GBDT-BCMO. The GBDT machine learning technique is enhanced using the BCMO method. GBDT method is trained on inputs like previous instantaneous energy of obtainable sources and current time required load demand based on target reference power. Based on load variation, GBDT-BCMO control system creates PI controller gain parameters to generate optimal control signal and manage HRES energy. The prediction process of the present method undertakes variations on system parameters, like reactive and real power and DC voltage. The proposed GBDT-BCMO system improves the power system damping and creates line voltage, giving reactive power compensation. The proposed methodology is then carried out in MATLAB/Simulink platform, and the performance is analysed. The behaviour of the proposed system is related with other systems. The proposed method ranges from 0 to 22.1 V. The BCMO system ranges from 0 to 22. The ALO system ranges from 0 to 22 V. The BAT Algorithm ranges from 0 to 22.0 V.

Social Media Data Mining and Mental Health Status Assessment Based on Sentiment Analysis

The usage of the word Power quality in recent times acquired intensified interest due to the complex industrial processes. The usage of intelligent tools to improve power quality is increasing day by day, as assumption of present day power system as a linear model is unsatisfactory. This paper deals with analysis of Differential Evolution (DE), Hybrid Differential Evolution (HDE) and Variable Scaling Hybrid Differential Evolution for harmonic reduction in the source current with optimal tuning of PI controller gain values. Shunt Active power Filter is one of the better solution to suppress the source current harmonics which are induced into power system because of nonlinear loads. Current controller called HBCC is considered for gating operation of switches in Voltage Source Inverter. The Intelligent tuned PQ theory is used for reference current generation. The then obtained compensating currents are injected at point of common coupling for current disturbance mitigation. Simulations of MATLAB/SIMULINK environment of the present work shows the efficacy.

Computer Modeling Analysis of Electric Vehicle's Choice Behavior Considering Latent Variables

At present, there are few researches on the influence of psychological latent variables on the choice behavior of electric vehicles, and lack of consideration of individual heterogeneity. In this study, computer modeling was used to construct not only a traditional discrete choice model that takes into account individual heterogeneity, but also a hybrid choice model,which takes into account psychological latent variables are constructed to explore the mutual effects of observable personal attributes, vehicle attributes and difficult to directly observe psychological latent variables on consumers’ choice behavior of electric vehicles. The estimation results of hybrid choice model with psychological latent variables and the traditional discrete choice model without considering psychological latent variables are compared. The result show that perceived usefulness, perceived risk and purchasing attitude have a significant impact on consumers’ choice behavior of electric vehicles. Compared with traditional discrete choice model, the hybrid choice model, which takes into account psychological latent variables has significantly higher prediction accuracy and has better interpretation ability and fitting effect. The research results can provide theoretical support for further expanding the electric vehicle market and formulating relevant policieshe usage of the word Power quality in recent times acquired intensified interest due to the complex industrial processes. The usage of intelligent tools to improve power quality is increasing day by day, as assumption of present day power system as a linear model is unsatisfactory. This paper deals with analysis of Differential Evolution (DE), Hybrid Differential Evolution (HDE) and Variable Scaling Hybrid Differential Evolution for harmonic reduction in the source current with optimal tuning of PI controller gain values. Shunt Active power Filter is one of the better solution to suppress the source current harmonics which are induced into power system because of nonlinear loads. Current controller called HBCC is considered for gating operation of switches in Voltage Source Inverter. The Intelligent tuned PQ theory is used for reference current generation. The then obtained compensating currents are injected at point of common coupling for current disturbance mitigation. Simulations of MATLAB/SIMULINK environment of the present work shows the efficacy.

Power Quality Improvement based on VSHDE Algorithm Incorporating Shunt Active Power Filter

The usage of the word Power quality in recent times acquired intensified interest due to the complex industrial processes. The usage of intelligent tools to improve power quality is increasing day by day, as assumption of present day power system as a linear model is unsatisfactory. This paper deals with analysis of Differential Evolution (DE), Hybrid Differential Evolution (HDE) and Variable Scaling Hybrid Differential Evolution for harmonic reduction in the source current with optimal tuning of PI controller gain values. Shunt Active power Filter is one of the better solution to suppress the source current harmonics which are induced into power system because of nonlinear loads. Current controller called HBCC is considered for gating operation of switches in Voltage Source Inverter. The Intelligent tuned PQ theory is used for reference current generation. The then obtained compensating currents are injected at point of common coupling for current disturbance mitigation. Simulations of MATLAB/SIMULINK environment of the present work shows the efficacy.

Analysis of electromechanical coupling modal and dynamic response characteristics of permanent magnet gear transmission system considering variable load condition

In order to study the influence of electromagnetic (EM) effect and load change on the modal characteristics and dynamic response of gear transmission system driven by permanent magnet synchronous motor (PMSM), a electromechanical coupling dynamic model is established. The composite air gap permeability coefficient is introduced, and the formula of permanent magnet flux linkage under the influence of space harmonic and cogging effect is derived. The variation laws of gear meshing stiffness and bearing support stiffness under the influence of load change are simulated and analyzed. The natural frequency and vibration modal under different load, flux linkage and PI controller gain are revealed. On this basis, the influence of EM effect and load change on the resonance domain is analyzed through frequency sweep analysis and time domain simulation. Results indicate that the 1st order natural frequency and resonance amplitude will increase with the load, and the influence of PMSM EM excitation will gradually dominate. The increase of the flux linkage and speed loop controller gain Kpω will reduce the 1st order natural frequency. When Kpω =123, a new mode appears, and there is a modal transition between the new mode and mode 1 when Kpω =161. The research results can provide theoretical guidance for improving the transmission performance and structure optimization design of the permanent magnet gear transmission system.

Design and analysis of high-gain DC–DC chopper topologies for PV-fed BLDC motor drive system

PurposeSwitching power converters for photovoltaic (PV) applications with high gain are rapidly expanding. To obtain better voltage gain, low switch stress, low ripple and cost-effective converters, researchers are developing several topologies.Design/methodology/approachIt was decided to use the particle swarm optimization approach for this system in order to compute the precise PI controller gain parameters under steady state and dynamic changing circumstances. A high-gain q- ZS boost converter is used as an intermittent converter between a PV and brushless direct current (BLDC) motor to attain maximum power point tracking, which also reduces the torque ripples. A MATLAB/Simulink environment has been used to build and test the positive output quadratic boost high gain converters (PQBHGC)-1, PQBHGC-8, PQBHGC-4 and PQBHGC-3 topologies to analyse their effectiveness in PV-driven BLDC motor applications. The simulation results show that the PQBHGC-3 topology is effective in comparison with other HG cell DC–DC converters in terms of efficiency, reduced ripples, etc. which is most suitable for PV-driven BLDC applications.FindingsThe simulation results have showed that the PQBHGC-3 gives better performance with minimum voltage ripple of 2V and current ripple of 0.4A which eventually reduces the ripples in the torque in a BLDC motor. Also, the efficiency for the suggested PQBHGC-3 for PV-based BLDC applications is the best with 99%.Originality/valueThis study is the first of its kind comparing the different topologies of PQBHGC-1, PQBHGC-8, PQBHGC-4 and PQBHGC-3 topologies to analyse their effectiveness in PV-driven BLDC motor applications. This study suggests that the PQBHGC-3 topology is most suitable in PV-driven BLDC applications.

An improved weather adaptable P&O MPPT technique under varying irradiation condition

Perturb and Observe algorithm is most familiar due to its wide range of utilization in tracking maximum power point. Besides, being simple and economical, perturb and observe algorithm has the major disadvantage of atmosphere insensitivity, resulting in fluctuation of output characteristics under varying irradiation conditions. An Improved Weather Adaptable perturb and observe maximum power point tracking is projected in this paper to overcome the disadvantages due to weather insensitivity in perturb and observe algorithm. Additionally, in the proposed algorithm, irradiation and temperature sensors are employed in estimating nearest location to maximum power point, resulting in faster response. The system is designed to update the PI controller gain values according to weather variations, resulting in satisfactory operating characteristics at all possible irradiation cases. The proposed Weather Adaptable perturb and observe tracking scheme is developed in MATLAB and hardware cases, the conclusions shows that the system follows good dynamic properties, low oscillations under steady state and better tracking efficiency compared to existing MPPT schemes. Following these advantages, the proposed system is simple with low mathematical burden, leads to easy real time implementation.

A hybrid control technique for small signal stability analysis for microgrids under uncertainty

Distributed generators (DG) with inverter based on renewable sources are generally utilized in microgrids. Most of these sources work in droop control mode to effectively share the load. Higher droop is chosen on these systems to recover dynamic power sharing. This paper proposes a Hybrid Control Technique for Small Signal Stability Analysis for Microgrids under Uncertainty. The proposed topology is to recover the capacity of power system is used to restore the normal operating condition. The proposed hybrid technique is the combination of chaotic Henry gas solubility optimization (CHGSO) and recalling-enhanced recurrent neural network (RENNN) and therefore called the CHGSO-RENNN technique. The proposed technique is used to optimally predict the internal and external current loop control parameters in light and the variety of power and current parameters. The small stability is revealed through the working conditions of the whole machine. The overall stability of the small signal is investigated in a linear model so that both source and load are used to characterize the state matrix of the frame that is used for eigenvalue examination. The PI controller gain parameters are optimally tuned and the controller offers reliable frame operation. The proposed technique is performed on MATLAB/Simulink work platform.

PV and Wind Energy Conversion Exploration based on Grid Integrated Hybrid Generation Using the Cuttlefish Algorithm

This paper focuses on the exploration of grid-integrated hybrid generation comprising Photovoltaic (PV) and Wind Energy Conversion Systems (WECSs) using the Cuttlefish Algorithm (CFA). PV and wind energies are opposite because sunny days are normally calm, and strong winds frequently occur on cloudy days or at night. Hence, a hybrid PV and wind power system is more reliable than either individual source in terms of delivering uninterrupted power. The regulation of the DC voltage is the key issue in this configuration. The conventional PI controller is inaccurate in regulating the DC voltage. The PI controller gain tuning using optimization techniques provides good DC voltage regulation and less Total Harmonic Distortion (THD). Hence, CFA is proposed for the tuning of PI gains. The performance parameters such as DC voltage regulation and THD of CFA are analyzed.

Performance Enhancement of the DPC Control Based on a VGPI Controller Applied to a Grid Connected PV System

Even though the PI controller is among the most widespread controllers in photovoltaic (PV) systems, it presents overshoots and undershoots in the tracking trajectory mode. This major disadvantage remains an open problem. In the current paper, a Direct Power Control (DPC) of a three-phase grid-connected PV system based on a Variable Gain PI (VGPI) controller is developed to remove the overshoots and undershoots in the classical PI controller. The proposed control system has been tested in the Matlab/Simulink environment. The simulation results demonstrate the feasibility and robustness of the proposed method in terms of overshoots, undershoots, and current quality.

Optimised coordinated control of hybrid AC/DC microgrids along PV-wind-battery: a hybrid based model

This work presents a novel coordinated control approach for an MG with hybrid AC/DC loads and energy resources. As a result, power interactions between the DC and AC subgrids are appropriately enabled by distributing power fluctuations in a coordinated manner. Initially, a coordinated control scheme of distributed converters was presented. Then, a model predictive power and voltage control (MPPVC) technique is used for DC/AC interlinking converter that offers high-quality voltages and guarantees the optimal power transfer amongst ac and dc sub-grids. This paper aims to enhance the control structure of the energy storage system (ESS), where the optimised PI controller is insisted. Particularly, the gain of PI controller is optimally tuned by a new hybrid algorithm named as index-based fly-rider combined model (IF-RM) that incorporates both the concepts of rider optimisation algorithm (ROA) and firefly algorithm (FF). Finally, the betterment of the proposed work was validated over other existing models.

Design of Robust Guaranteed Margin Stability Region PI Controller for Automotive LED Lighting With Parameter Uncertainty

In the modern era, automotive light emitting diode (LED) lighting technologies are booming as a result of high luminous intensity, long life, compact size, high energy efficiency, high reliability etc. As the load is sensitive for input parametric variations, it is essential to regulate the load voltage and current with respect to system specifications. Hence, there is a need for fast response robust controller to feed the required voltage and current during abnormal conditions. In this paper, a robust controller is designed for single switch control buck boost converter for automotive LED lighting. A small signal modelling of the converter is developed with perturbed state variables to analyze the dynamic behavior of the system. The system with dynamic controller has a zero in the right-hand side of the s-plane, which results in poor closed loop stability. Hence, a robust controller is designed with Kharitonov’s theorem by considering the uncertain variations in the converter parameters. A robust performance region is obtained by considering guaranteed gain margin and phase margin benchmark. In this region, the optimal PI controller gain values are obtained using Kharitonov’s sixteen plants theorem. The obtained gain values make the system with minimum oscillation, fast settling time, right hand side zero compensation and stability of the system. The performance analysis is compared with the conventional PI controller and to ensure the peak value of sensitivity for robust controller. The simulation of the system is performed in PSIM and validated in real time using dSPACE1103 controller with experimental results.

A PI Controller with a Robust Adaptive Law for a Dielectric Electroactive Polymer Actuator

Dielectric electroactive polymer actuators are new important transducers in control system applications. The design of a high performance controller is a challenging task for these devices. In this work, a PI controller was studied for a dielectric electroactive polymer actuator. The pole placement problem for a closed-loop system with the PI controller was analyzed. The limitations of a PI controller in the pole placement problem are discussed. In this work, the analytic PI controller gain rules were obtained, and therefore extension to adaptive control is possible. To minimize the influence of unmodeled dynamics, the robust adaptive control law is applied. Furthermore, analysis of robust adaptive control was performed in a number of simulations and experiments.

Analysis of High-Efficiency Transformerless Inverter for a Grid-Tied PV Power System with Reactive Power Control

Background: In recent days grid-tied PV power systems play a vital role in the entire energy system. In a grid –tied PV system Transformerless Inverter (TI) topologies are preferred for its reduced price, improved efficiency, lightweight etc. Therefore many transformerless topologies have been proposed and verified with real power injection only. Recently, almost every international standard has imposed that a specified amount of reactive power should be handled by the grid-tied PV inverter. According to the standard VDE-AR-N4105, grid-tied PV inverter of power rating below 3.68kVA, should attain Power Factor (PF) from 0.95 leading to 0.95 lagging. Objective: To address this issue of grid-tied PV system with reactive power control, in this paper Fuzzy gain scheduling controller is proposed as a power controller for High Efficiency Transformeless (HETL) inverter. The performance of the proposed scheme is analyzed and validated with the comparison of a conventional PI controller based active and reactive power controllers. Methods: This paper is with the intention of improvement in the performance of the system, the FGS controller is anticipated as active and reactive power controllers. In conventional PI controller gains are constant for any value of the error, which makes error and delay in optimum value of voltage (Vα and Vß). Hence in this analysis FGS controller tunes PI controller gain with respect to change in active and reactive power error. Results: Comparative performance of PI and FGS based HETL inverter is presented in this paper. It is noted that for any cases either Pref is constant or variable the FGS reduces ripple than PI based HETL inverter system. Compare to constant reference power case variable reference case produces more ripples in both systems. Conclusion: From the analysis FGS based HETL inverter in a grid-tied PV based power system produces the best performance in all aspects such as voltage, active power and reactive power.

Simply structured controllers for vibration suppression in long rotors

In this paper suppression of the transient flexural vibrational disturbances in long rotors, with fluid film bearings, is investigated. The rotor is described by a series of distributed shafts connected by the lumped discs, and the system is mounted on lumped fluid film bearings. Upon determination of the dynamic stiffness matrix of the system, the best approximate transfer function matrix description of the rotor, is determined. Initially vibration suppression by simple diagonal Proportional + Integral (PI) controllers is studied and via direct search optimisation techniques the PI parameters which exhibit fast vibration suppression is found. The resulted high integration rate, and low proportional gain PI controller, theoretically provided fast suppression time. However, it is shown that due to the strong coupling effect in the rotor system, and high rate of integration, the closed loop relative stability is weak, and feasibility of controller is questionable. Therefore, an alternative simple first order controller without integration action, that is named “attenuation filter “is suggested that can produce stronger stability and produces significant (not full) vibration suppression. The closed loop multivariable control of the rotor system comprising two vibration sensors and two magnetic actuators using such attenuation filter, is then simulated. The response to step disturbances, has provided 95% suppression with significantly fast response. It is concluded that although the attenuation filter may not provide 100% suppression, but it more reliable since the integration of the error, that results weak stability is avoided.

An Algorithm for DSTATCOM with Optimized Values of PI Gain Using Adaptive Internal Model

In this article, a control algorithm with Adaptive Internal Model (AIM) frequency identifier has been discussed for three-phase Distribution Static Compensator (DSTATCOM). An AIM motivated method is implicated in the control scheme to extract fundamental in each phase. The reduction of reactive burden on the supply using DSTATCOM and making the supply current sinusoidal is the main theme behind this work. The fundamental extraction and PI controller gain estimation are the two things that bring variant in the proposed work. The fundamental frequency estimation, rejection of harmonics and its components are the main features of this algorithm. The convergent property of the algorithm is not much influenced by the actual disturbed signal and design parameters principally provide the robustness to the algorithm. The PI controller gains are estimated using Grasshopper Optimization Algorithm (GOA). The suggested control scheme with estimated gain values from the GOA optimization technique has controlled issues like reactive power compensation and mitigation of grid current harmonics caused due to an identified harmonic producing non-linear load that is a three-phase ac voltage controller with resistive load. This work provides implementation performance using dSPACE-1104 of the proposed control scheme for DSTATCOM.

Experimental investigation of model-based IMC control of severe slugging

Severe slugging formation has been investigated experimentally in a two-phase flow-loop composed of a downwardly inclined pipe and a vertical riser. In this study, a bifurcation diagram was made to more clearly identify which flow the current system has at each valve opening. A model was made by inputting the dimensions of the flow loop using OLGA, a multiphase flow simulation program, to compare the experimental results. The model-based control logic was constructed by estimating the transfer function utilizing the OLGA model. The estimated transfer function is used to tune the gain of the PI controller, using the method called the Internal Model Control (IMC). Through this method, PI gain can be easily obtained through only one tuning parameter. When the PI controller gain is obtained through the transfer function of the flow loop system, mitigation of severe slugging was achieved while increasing the flow rate than the case with manual choking.

Self-Tuning Two Degree-of-Freedom Proportional–Integral Control System Based on Reinforcement Learning for a Multiple-Input Multiple-Output Industrial Process That Suffers from Spatial Input Coupling

Proportional–integral–derivative (PID) control remains the primary choice for industrial process control problems. However, owing to the increased complexity and precision requirement of current industrial processes, a conventional PID controller may provide only unsatisfactory performance, or the determination of PID gains may become quite difficult. To address these issues, studies have suggested the use of reinforcement learning in combination with PID control laws. The present study aims to extend this idea to the control of a multiple-input multiple-output (MIMO) process that suffers from both physical coupling between inputs and a long input/output lag. We specifically target a thin film production process as an example of such a MIMO process and propose a self-tuning two-degree-of-freedom PI controller for the film thickness control problem. Theoretically, the self-tuning functionality of the proposed control system is based on the actor-critic reinforcement learning algorithm. We also propose a method to compensate for the input coupling. Numerical simulations are conducted under several likely scenarios to demonstrate the enhanced control performance relative to that of a conventional static gain PI controller.

Enhanced PI control and adaptive gain tuning schemes for distributed secondary control of an islanded microgrid

This paper develops an enhanced proportional-integral distributed control scheme (EPI-DCS) to regulate the frequency and voltage of a droop-controlled microgrid and share the power mismatch, simultaneously. The proposed EPI-DCS is designed by using the control Lyapunov function method and adding a new consensus-based term to the integrand dynamic of the conventional PI control. In the proposed distributed EPI-DCS, the distributed generation units intermittently exchange information with the neighbouring distributed generation units, through a communication network. Considering the communication network time delays, the stability of the proposed EPI-DCS is examined using the Lyapunov–Krasovskii linear matrix inequality conditions, and the maximum stable time delay is calculated. In order to stabilise the system for large destabilising time delays, an adaptive gain scheme is proposed. Effectiveness of the proposed adaptive EPI-DCS is validated by numerical simulations with detailed models of the components and the converters, including load change, distributed generation outage, and adaptive gain-scheduling against destabilising communication network time delays.