Traditional Proportional Integral Controller Research Articles

Frequency stabilization in microgrid with PV system based on maximum power extraction: A sliding mode approach

The article addresses the critical issue of frequency regulation in microgrids (MG) integrated with solar photovoltaic (PV) systems, which rely on maximum power point tracking (MPPT) using sliding mode control (SMC). The frequency stability of MGs is a significant concern due to the inherent variability of renewable energy sources, making frequency regulation challenging. This research proposes a dual-objective control strategy. Firstly, it ensures the solar PV system maximizes power extraction via a buck-boost converter controlled by SMC. Simultaneously, it maintains frequency regulation in the MG under load disturbances using SMC. The SMC technique guarantees precise convergence to the maximum power operating point and minimizes frequency deviations in the MG. The proposed solution demonstrates effective maximum power extraction under varying irradiance levels and reliable frequency regulation despite system parameter uncertainties and nonlinearities such as generation rate constraints (GRC) and governor deadband (GDB). Additionally, the SMC-based design achieves faster convergence compared to traditional proportional-integral (PI) controllers optimized using intelligent techniques. Stability analysis, performed using Bode and Nyquist plots, further confirms the robustness of the proposed system. The model was developed and tested in the MATLAB Simulink environment, showcasing its efficacy and reliability.

Fuzzy Logic Controller-Based STATCOM for Reactive Power Compensation in a Grid-Connected Wind Power Plant

Wind energy is one of the most prevalent renewable sources nowadays, which has been projected to play an immense role in realizing the clean energy transition. This paper dives into one of the critical challenges in the grid integration of wind power plants, which is reactive power compensation. The static synchronous compensator (STATCOM) is commonly used to inject/absorb reactive power in wind power plants where the device is controlled with the traditional proportional-integral (PI) controller. This article investigates the effectiveness of the fuzzy logic controller (FLC) in managing the STATCOM to compensate and regulate the reactive power in a 9 MW grid-connected wind power plant. Due to its faster and malleable response, the FLC allows for greater flexibility in controlling the STATCOM. According to the findings, the voltage profile at the point of common coupling (PCC) is improved considerably in the case of the FLC compared to the PI controller, demonstrating the efficacy of the employed strategy. MATLAB-Simulink has been used to model and analyze the proposed system. We achieved a 6 percent improvement in voltage regulation when FLC was utilized instead of PI controllers. DUJASE Vol. 8 (1) 62-70, 2023 (January)

A Nonlinear Active Disturbance Rejection Feedback Control Method for Proton Exchange Membrane Fuel Cell Air Supply Subsystems

The control strategy of the gas supply subsystem is very important to ensure the performance and stability of the fuel cell system. However, due to the inherent nonlinear characteristics of the fuel cell gas supply subsystem, the traditional control strategy is mainly based on proportional integral (PI) control, which has the disadvantages of large limitation, large error, limited immunity, and inconsistent control performance, which seriously affects its effectiveness. In order to overcome these challenges, this paper proposes an optimal control method for air supply subsystems based on nonlinear active disturbance rejection control (ADRC). Firstly, a seven-order fuel cell system model is established, and then, the nonlinear ADRC and traditional PI control strategies are compared and analyzed. Finally, the two strategies are simulated and compared. The validation results indicate that the integral absolute error (IAE) measure of PI control is 0.502, the integral square error (ISE) measure is 0.1382, and the total variation (TV) measure is 399.1248. Compared with the PI control, the IAE and ISE indexes of ADRC were reduced by 61.31% and 58.03%, respectively. ADRC is superior to PI control strategy in all aspects and realizes the efficient adjustment of the system under different working conditions. ADRC is more suitable for the nonlinear characteristics of the gas supply system and is more suitable for the oxygen excess ratio (OER).

An Output Cooperative Controller for a Hydraulic Support Multi-Cylinder System Based on Neural Network Compensation

The straightness control of a fully mechanized working face is the key technology used in intelligent coal mining, so the position control of a hydraulic support multi-cylinder moving system is of great significance. However, due to the harsh environment of coal mines, complex friction, external disturbances, and the coupling relationship between adjacent cylinders, the accuracy of position control is restricted. Therefore, an output cooperative controller is proposed in this paper for a multi-cylinder system. A high-order sliding mode observer is utilized to estimate the system states with the only available output position signal. A neural network disturbance observer is applied to estimate the lump disturbance of the strict-feedback model, including the system uncertainty, disturbance force and the coupling force between adjacent cylinders. Then, continuous motion position tracking simulation is conducted and the estimation performance of the state observer and neural network is analyzed. Furthermore, a multi-cylinder collaborative control test rig is designed, and experiments based on the actual actions of the hydraulic support are conducted. The results show that the proposed output cooperative controller has an excellent position control performance compared with the traditional proportional–integral controller.

Power optimization of photovoltaic modules under varying environmental conditions based on current equalization collaborating constant voltage control

Abstract The performance of photovoltaic modules is affected by environmental factors such as irradiance and temperature, which can lead to a decrease in output performance or even damage. This study proposes an improved formula for calculating the real maximum power of photovoltaic modules by analyzing the influence of irradiance and temperature. A simulation model is developed using PLECS software to simulate the global maximum power of photovoltaic modules under different environmental conditions, and the results are compared with the calculated real maximum power. A power optimization scheme for photovoltaic modules is then proposed based on current equalization and constant voltage control. This scheme employs a single-switch multi-winding forward-flyback converter to equalize the mismatched currents between cell strings, thereby enhancing the output performance. Traditional proportional integral controllers are utilized to achieve constant voltage control and obtain the real maximum power of photovoltaic modules. Simulation models are built in the PLECS simulation platform to evaluate the performance of a global maximum power point tracking scheme based on the traditional perturb and observe algorithm with current equalization, a segment perturb and observe algorithm without current equalization, and the proposed power optimization scheme. The simulation results demonstrate that the proposed constant voltage control has greater efficiency than the traditional perturb and observe algorithm. The proposed scheme achieves a significant improvement in efficiency, with a 27.87% increase compared to the segment perturb and observe algorithm without current equalization.

Performance improvement of predictive voltage control for interlinking converters of integrated microgrid

Voltage quality in Renewable Energy System may be harmed by varying power demand and fluctuating energy source outputs. The model predictive voltage (MPV) control approach is suggested in this study. The proposed control strategy enables appropriate power interactions between the AC and DC subgrids while sharing power fluctuations in a coordinated way. Both the AC and DC subgrids support each other in accordance with their normalized relative changes in AC frequency and DC voltage, respectively. A typical photovoltaic (PV) wind-battery-based hybrid AC/DC microgrid is modelled and investigated, and the usefulness of the proposed scheme is validated under the renewable energy variations and load perturbations. MATLAB/Simulink has validated the efficacy of the suggested strategy. A set of comparative tests was conducted between conventional Proportional-Integral (PI) control, Sliding Mode Control (SMC) strategies, and a novel Model Predictive Voltage Control (MPV) approach under diverse conditions. The aim was to comprehensively assess the advantages of the proposed MPV method. Results demonstrate that, in contrast to traditional PI and SMC control strategies, the MPV technique exhibits distinct benefits in terms of superior control performance and achieves exceptionally low Total Harmonic Distortion (THD) values. Ultimately, the proposed solution not only raises the performance standard but also ensures the stable operation of the Renewable Energy System (RES).

Investigation of Legendre polynomials expanded adaptive controller with inverse compensation for high frequency tracking of electro-hydraulic force systems

Accurate force tracking of an electro-hydraulic force system (EHFS) is of great significance in various industrial applications. As the EHFS is inevitably confronted with hydraulic nonlinearities, dynamic variations and uncertain disturbances, the real-time force tracking performance is generally unsatisfactory, especially for high frequency command force signals. For reducing the force tracking error with relatively high frequency inputs, a Legendre polynomials expanded adaptive controller with inverse compensation is proposed in this paper. The proposed controller is constructed by introducing an offline designed inverse compensation (IC) controller and an online adaptive controller to the EHFS governed by traditional Proportional Integral (PI) controller, in which the former IC controller is acting as the inner loop controller and the latter adaptive controller is regarded as an outer controller. The inner loop IC controller with fixed control parameters is offline designed on the basis of traditional PI controller by means of the generalized projection identification algorithm and the zero magnitude error tracking technology, focusing on extending the real-time force tracking bandwidth of the EHFS. The outer loop online adaptive controller is developed by Legendre polynomials expanded adaptive filters with nonlinear mapping ability, whose weights are online updated by an adaptive tuning algorithm with the aim of handling system’s dynamic variations, nonlinearities and uncertain disturbances. The proposed controller is implemented on a real EHFS test rig by the xPC/Target rapid prototyping technique, and comparative experimental results demonstrate that the proposed controller can achieve much higher high frequency tracking performance than the traditional PI and IC controller commonly used in industry.

Load frequency and voltage control of two area interconnected power system using covariance matrix adaptation evolution strategy based Aquila optimization optimized fast fuzzy-fractional order tilt integral derivative controller

In this paper, an optimal tuning method is given for a Fast Fuzzy-Fractional Order Tilt Integral Derivative Controller (HFF-FOTIDC) used in the Load Frequency Control (LFC) and Automatic Voltage Regulator (AVR) systems of a two-area interconnected power system. LFC is in charge of managing the frequency and real power flows in the system. AVR is in charge of maintaining the voltage profile and managing the flow of reactive power. In Area 1, a step disturbance is used to study how the system works in a dynamic way. By looking at the system's voltage, power flow through the tie lines, and frequency, the experts can figure out how the system will react. The proposed control techniques combine two well established control logic, which are fast fuzzy control logic and fractional order tilt integral derivative control logic. The main goal is to decrease voltage and frequency changes caused by step disturbances and return them to their normal values. The simulation results show how good the suggested system is by comparing it to systems that use traditional proportional integral controllers and traditional Integral controllers. By using the finest tuning method for the fast fuzzy-fractional order tilt integral derivative controller, the designed system has better performance than standard controllers at reducing fluctuations and getting the desired frequency and voltage responses. The parameters of the proposed controller are optimized by using Covariance Matrix Adaptation Evolution Strategy based Aquila Optimization (CMAESAO) optimization technique.

Enhanced proportional integral controller for DSTATCOM with particle swarm optimization algorithm in power system

Power system expansion planning is supported by using distributed generation (DG) instead of installing new main power system generators. The portability and autonomous operation of the DG make it capable of integrating into the distribution system. Power electronics devices for home loads, mainly electric vehicles, mobile phones, and laptops, introduce harmonics and related power quality issues to the distribution system. This load creates power quality issues like an increase in total harmonic distortion (THD) and a reduction in power factor. This paper uses the DG to supply important power electronics devices for the mitigation of power quality problems in distributed systems with non-linear loads, such as electric vehicles, called the “distributed static compensator (DSTATCOM)”. Wind and photovoltaic (PV) generators supply power to a common DC source. To improve power quality D-STATCOM powered by PV and wind energy systems at the DC link is incorporated. The direct axis/quadrature axis method (DQ method) controls the real and reactive components of the power. Proportional integral (PI) and particle swarm optimization (PSO) based PI controller parameter estimation are developed, and results are compared for power quality performance. In terms of improving power quality, the PSO-based parameter estimate of the PI controller performs better than the traditional PI controller.<br /><div class="extension_reset_css AnnotateNet_widget AnnotateReviewNotesButton" style="display: none; z-index: 2147483644;" data-id="ExtensionWidget"><div class="extension_reset_css AnnotateNet_widget annotateclickable" style="z-index: 8; display: none;" title="Resize" data-id="Widget"> </div></div>

LCC-HVDC Frequency Robust Control Strategy Based on System Parameter Identification in Islanded Operation Mode

To enhance the stability of the frequency at the sending terminal of the HVDC island during operation, a novel DC supplemental frequency robust controller is proposed in this paper. The proposed controller utilizes the fast controllability of a DC power supply to maintain system frequency stability. The identification of a low-order linearized model of the system can be obtained from a high-precision Prony algorithm based on the second derivative method (SDM). Subsequently, utilizing a robust design methodology based on linear matrix inequalities, an additional frequency robust controller is devised, striking a balance between optimal performance and robustness. This supplementary frequency robust controller exhibits a straightforward control structure with a modest order, making it readily implementable. Simulation experiments conducted within the PSCAD/EMTDC framework substantiate that the designed supplemental frequency robust controller significantly enhances the frequency stability of the sending terminal system. Furthermore, when compared with traditional proportional integral (PI) controllers, it demonstrates superior control efficacy and robustness against various types of faults under different operational modes. Even in interconnected operational modes, it continues to operate effectively. The research findings offer valuable insights for practical applications in islanded power systems.

A fast and structurally simple control scheme based on a fuzzy supervisory approach for wireless power transfer systems

AbstractWireless power transfer (WPT) is a promising technology and has attracted many researchers’ attention due to its inherent advantages such as reliability, safety, flexibility, and low maintenance costs. For WPT systems, the output voltage varies according to the variable loads and the coupling coefficient conditions, affecting system stability and efficiency. In this regard, this study is concerned with the tracking control problem of WPT systems based on fuzzy supervisory proportional–integral (PI) controller and a phase shift modulation technique, which is for the first time proposed by this paper. By introducing appropriate fuzzy rules, the proposed control scheme not only can track the desired output voltage but also has better robust behaviour to deal with the problem of variations of circuit elements and coupling coefficients. That is, the proposed fuzzy supervisory PI control scheme can perform better than the traditional PI controller. Analysis of the designed control method and simulation results validate the superiority of the proposed method over the traditional PI controller in all conditions, which can make it a suitable choice for the applications of electric vehicle charging systems. The analysis is supported by experimental measurements.

Improved Compound Vibration Suppression Control for Magnetic Levitation Motor

The magnetic levitation motor is high efficiency, energy saving and environmental protection, which integrates magnetic levitation bearing and permanent magnet motor into the traditional motor. Two key technologies of its stable operation are vibration suppression control of magnetic bearing and speed sensorless chattering suppression control of motor. The innovative research has been studied from the perspective of control systems. First, in order to form the vibration suppression controller, the traditional proportional integral differential control has been improved by adding incomplete differential time constant. In addition, the method using linear variable structure sliding mode observer (SMO) is proposed to achieve speed identification, which can solve the chattering problem caused by the discontinuous high frequency switching signal compared to the traditional SMO. Finally, the experimental platform is built to verify the correctness of the proposed control methods. When the motor operates in speed sensorless mode, the rotor vibration is within the effective range. © 2024 Institute of Electrical Engineer of Japan and Wiley Periodicals LLC.

Exponential super-twisting control for nonlinear systems with unknown polynomial perturbations

The study focuses on the control of nonlinear dynamic systems in the presence of parameter uncertainties, unmodeled dynamics, and external disturbances. The lumped perturbation is assumed to be bounded within a polynomial in the system state with the polynomial parameters and degrees unknown a priori such that it accommodates a quite wider range dynamic systems. Based on the studies in recent super-twisting algorithm designs and the idea from adaptive sliding mode control for nonlinear systems with uncertainties, we propose a novel adaptive super-twisting algorithm with exponential reaching law, or exponential super-twisting algorithm (ESTA), for the high-stability and acceptable accuracy control of the aimed nonlinear dynamics. The stability analysis and practical finite-time (PFT) convergence are proven using Lyapunov theory and an intuitive analysis of the control behaviour. Simulations are performed to compare the proposed ESTA with the existing super-twisting method and the traditional proportional integral differential control. The simulation results demonstrate the effectiveness of the proposed ESTA in terms of the fastest settling time and the smallest overshoot.

Normalized Error-Based PI Controller and Its Application to the DC–DC Buck Converter

In this article, the structure of the normalized error-based proportional-integral (PI) controller is presented and its application to the DC–DC buck converter is discussed. The main motivation is to overcome the drawbacks of saturation and the limited range of controller gains offered by the traditional PI controller. Initially, the theoretical structure and advantages of an improved PI controller are shown. Next, the problem of regulation of the step-down DC–DC converter is addressed using the proposed controller. The objective is to keep the load voltage constant even when the converter parameters vary. The averaged state-space model of the converter is presented and a detailed stability analysis based on the Lypunov indirect method is carried out. The results show an improved range of controller parameters when the proposed controller is employed. Finally, some simulation results are shown to illustrate the effect of controller parameter variations on the output response. These results also verify the ability of the proposed controller to handle the changes in the load, input voltage, and reference voltage of the converter. Moreover, a comparative simulation study validates the superior transient response of the proposed normalized error-based PI controller over the traditional PI controller.

Neural Network Model-Based Reinforcement Learning Control for AUV 3-D Path Following

Autonomous underwater vehicles (AUVs) have become important tools in the ocean exploration and have drawn considerable attention. Precise control for AUVs is the prerequisite to effectively execute underwater tasks. However, the classical control methods such as model predictive control (MPC) rely heavily on the dynamics model of the controlled system which is difficult to obtain for AUVs. To address this issue, a new reinforcement learning (RL) framework for AUV path-following control is proposed in this paper. Specifically, we propose a novel actor-model-critic (AMC) architecture integrating a neural network model with the traditional actor-critic architecture. The neural network model is designed to learn the state transition function to explore the spatio-temporal change patterns of the AUV as well as the surrounding environment. Based on the AMC architecture, a RL-based controller agent named ModelPPO is constructed to control the AUV. With the required sailing speed achieved by a traditional proportional-integral (PI) controller, ModelPPO can control the rudder and elevator fins so that the AUV follows the desired path. Finally, a simulation platform is built to evaluate the performance of the proposed method that is compared with MPC and other RL-based methods. The obtained results demonstrate that the proposed method can achieve better performance than other methods, which demonstrate the great potential of the advanced artificial intelligence methods in solving the traditional motion control problems for intelligent vehicles.

A Composite Super-Twisting Sliding Mode Approach for Platform Motion Suppression and Power Regulation of Floating Offshore Wind Turbine

The floating platform motion of an offshore wind turbine system can exacerbate output power fluctuations and increase fatigue loads. This paper proposes a new scheme based on a fast second-order sliding mode (SOSM) control and an adaptive super-twisting extended state observer to suppress the platform motion and power fluctuation. Firstly, an affine nonlinear model of the floating wind turbine pitch system is constructed. Then, a fast SOSM pitch control law is adopted to adjust the blade pitch angle, and a new adaptive super-twisting extended state observer is constructed to achieve total disturbance observation. Finally, simulations are conducted under two cases of wind and wave conditions based on FAST (fatigue, aerodynamics, structures, and turbulence) and MATLAB/Simulink. Compared with the traditional proportional integral (PI) control scheme and standard super-twisting control scheme, the platform roll under the proposed scheme is reduced by 13% and 4%, and pitch is reduced by 16% and 3% in Case 1. Correspondingly, the roll is reduced by 9% and 15%, and pitch is reduced by 7% and 1% in Case 2. For the tower top pitch and yaw moment, load reductions of 7% and 3% or more are achievable compared with those under the PI control scheme. It is indicated that the proposed scheme is more effective in suppressing floating platform motion, stabilizing output power of the wind turbine system, and reducing tower loads.

Reduced switch cascaded asymmetrical 27 level inverter-STATCOMwith fuzzy logic controller

<p>In this study, a 27-levelinverter with a reduced switch asymmetrical cascaded H-bridge (CHB) with fuzzy logic controller (FLC) is proposed. With series connections, a low voltage converter, a middle level voltage converter, and a high voltage converter make up the static synchronous compensator (STATCOM). The configuration of the asymmetrical inverter uses trinary DCsources. To acquire switching signals for the trinary inverter-based STATCOM to compensate for real power, load voltage, reactive power, load current, and power factor under load changing conditions, FLC is constructed. With fewer switches, the suggested arrangement produces greater voltage levels. The performance of the reduced switch asymmetrical cascaded H-bridge inverter-STATCOM with FLCis simulated using the MATLAB Simulink platform under both static and dynamic load conditions. When compared to reduced switch asymmetrical cascaded H-bridge inverter-STATCOM with traditional proportional integral (PI) controller, the FLC result demonstrates efficient unbalanced load compensation. The FLC in the proposed inverter also lowers the total harmonic distortion.</p>

Novel Composite Speed Control of Permanent Magnet Synchronous Motor Using Integral Sliding Mode Approach

Permanent magnet synchronous motors (PMSMs) are widely applied in industry, and proportional integral (PI) controllers are often used to control PMSMs. Aiming at the characteristics of the poor anti-disturbance ability and speed ripple of traditional PI controllers, a novel composite speed controller for PMSMs is proposed in this paper that uses a novel sliding mode control (SMC). To improve the chattering problem of traditional SMC, a high-order approaching law super-twisting algorithm (STA) is applied. Considering the internal and external disturbance of motor driver systems, such as motor parameter drifts and load torque changes, a disturbance estimator based on an extended state observer (ESO) is proposed, and it is used for the feed-forward compensation of the current. The composite super-twisting integral sliding mode controller (ST-ISMC) with a nonlinear ESO is tested by simulations and experiments, and the comparative results verify that the proposed controller has the higher control accuracy, smaller speed ripple and stronger robustness.

Model Predictive Control Strategies for Turbine Electrified Energy Management

Abstract The increasing electrification of aircraft propulsion systems is leading to new control architectures being developed to address integration between electric machines and gas-based turbine engines. For hybrid-electric propulsion systems, current conceptual architectures often couple electric machines with the shafts of gas turbine engines and introduce energy storage. Leveraging the electrical power system of hybridized engines, Turbine Electrified Energy Management (TEEM) is a recent control approach that improves transient operability in an effort to enable more efficient and lighter weight turbomachinery. This study seeks to expand TEEM's application beyond traditional proportional-integral (PI) control by presenting linear model predictive control (MPC) schemes to execute the TEEM concept. Through constraint selection and cost function design, transient operability goals for TEEM are considered with no external logic or saturation. Unique to the designs are the use of a washout filter, which simplifies transient detection and motor activation logic. The proposed architectures are implemented with both centralized MPC and distributed MPC approaches, and comparisons are drawn to a benchmark PI controller simulated on a nonlinear turbofan engine model at one ground condition and one cruise condition. Performance is evaluated using compressor maps, stall margin performance, and two novel metrics: transient stack usage and transient excursion integral. Results reveal the linear MPC scheme performs comparably to the baseline controller and can be implemented in at least two distinct configurations with potential for further modifications, thus establishing the groundwork for future investigations.

Extended State Observer-Based Predictive Current Control for Dual Three-Phase PMSM with High Dynamic Performance

Model predictive controllers are widely discussed in the field of dual three-phase permanent magnet synchronous motor control. However, conventional predictive current controllers usually suffer from parameter inaccuracies or model uncertainties, resulting in prediction errors and deterioration of control performance. Therefore, in this paper, an extended state observer-based (ESO) model predictive current controller is proposed to effectively improve the dynamic performance of the motor and its robustness to parameters or disturbances. Parameter inaccuracies or model uncertainties are considered to be lumped disturbances and expressed in the modified mathematical model of the motor. Then, with the designed observer estimating the external disturbances in real time, the prediction error is compensated and corrected periodically. Additionally, the parameter design method of the observer is presented to simplify the controller design. Finally, comparative experiments are implemented to sufficiently demonstrate the effectiveness of the proposed method for dynamic performance improvement as well as for parameter robustness. The results show that the proposed method takes only 17μs of computation time with a closed-loop bandwidth of 1839rad/s. In addition, the maximum d-axis following error of the proposed method is only 0.10A in the load dynamics experiments, which is a significant improvement compared to the 0.79A of the traditional proportional-integral controller.