Search Results (3,982)

Doubly Fed Induction Generators (DFIGs) are widely employed in variable-speed wind turbine systems due to their high efficiency, enhanced controllability, and economic viability. This paper presents an intelligent neural-network-based control strategy aimed at maximizing wind energy extraction while ensuring accurate speed regulation of a DFIG by continuously tracking the maximum power point under fluctuating wind conditions. Two independent control schemes are developed for the decoupled regulation of active and reactive power in a grid-connected DFIG wind turbine. The first scheme is based on conventional field-oriented control using proportional integral regulators (FOC–PI), while the second employs an Artificial Neural Network Controller (ANNC). The effectiveness of both controllers is evaluated through MATLAB/Simulink 2020 Version simulations of a 1.5 MW DFIG-based wind energy conversion system and experimentally validated using a real wind profile implemented on an eZdsp TMS320F28335 digital signal processor. The proposed control approach achieves low output ripple, a steady-state error below 0.16%, total harmonic distortion of 0.38%, and a limited overshoot of 5%. The obtained results confirm the robustness and reliability of the implemented control strategies in enhancing power capture and improving overall system stability under variable wind conditions. Full article

With the active modernization of power facilities and the increasing deployment of maneuverable combined-cycle gas turbines (CCGTs), the selection of rational start-up strategies becomes increasingly important from the perspective of power quality. Excessive acceleration of power ramp-up may lead to undesirable voltage deviations, particularly in transmission networks with limited grid stiffness. This study investigates the impact of CCGT start-up ramp rate on voltage dynamics and power quality indicators at a 110/220 kV grid node. A detailed model of the Almaty power hub was developed in MATLAB/Simulink, taking into account the network structure, generating units, transformers, and aggregated loads. Three start-up scenarios were analyzed: an existing combined heat and power plant, a 504 MW combined-cycle gas turbine unit, and a 560 MW combined-cycle gas turbine unit with fuel afterburning. Voltage dynamics were evaluated using RMS-based indicators and a stabilization criterion incorporating a 5 s sliding time window and an 80% admissibility threshold. The simulation results reveal a nonlinear relationship between the start-up ramp rate and voltage quality. Increasing the ramp rate reduces the voltage stabilization time; however, beyond approximately 0.05 MW/s, further acceleration does not lead to additional improvement in power quality. The results indicate the existence of an optimal range of start-up ramp rates that provides a compromise between start-up speed and voltage quality requirements. The proposed approach can be used in the development of start-up algorithms for modern combined-cycle power plants connected to 110/220 kV transmission networks. Full article

In the context of power electronic interfaces in photovoltaic (PV), fuel cell, battery, and microgrid applications, the low output voltage of the DC source necessitates a voltage-boosting inverter. This paper proposes a single-source seven-level switched-capacitor boost inverter, particularly for low-voltage applications. The proposed inverter has the capability to produce seven different output voltage levels, i.e., intermediate boosted levels, with a total gain of three times the input voltage. The inverter has the advantage of a reduced number of power switches, diodes, and a switched-capacitor unit, which allows for single-stage operation without the need for a second DC-DC converter. The operating principle of the proposed inverter is explained in detail with a complete switching state analysis, conduction path analysis, and output voltage generation. The capacitor size is calculated using a charge balance-based equation. The self-balancing capability is validated for mismatched initial voltages with a bounded steady-state ripple. To evaluate the performance of the proposed inverter in a more realistic scenario, the effects of non-ideal device characteristics are considered, and the efficiency of the inverter is estimated using a loss model. A predictive current control technique is applied to control the output current under inductive load conditions. The simulation results obtained in MATLAB/Simulink software validate the proper seven-level operation of the inverter, the self-balancing capability of the capacitors, improved output waveform quality, and current control. The proposed inverter can be extended to grid-connected applications, where conventional output filters can be applied to meet the harmonic standards. Full article

The integration of renewable energy sources, including photovoltaic (PV) and fuel cell (FC) systems, into AC grids has attracted immense research interest in recent times. Furthermore, incorporating these renewable sources of energy into medium-voltage grids is garnering increased attention because of the obvious benefits of medium-voltage integration at elevated power levels. Photovoltaic applications entail the arrangement of solar panels capable of outputting voltages up to 1.5 kV; nonetheless, fuel cells display restricted output voltage, with a maximum market range of 400 to 700 V. Hence, the efficient integration of renewable energy sources into low-voltage or medium-voltage grids demands the utilization of a step-up direct current (DC–DC) inverter and a converter for connection to the alternating current (AC) grid, in which an efficient step-up converter is critical for the medium-voltage grid. Therefore, this study presents a three-phase buck-boost split-source inverter (BSSI) that resolves the constrained output voltage of the fuel cells. This study focuses on modifying the configuration of a conventional three-phase split-source inverter (SSI) circuit by adding a few components while maintaining the inverter’s modulation. This novel circuit design enables the reduction in voltage strains on the inverter switch components and improves DC-link use in relation to a traditional SSI configuration. For an 800 bus, maximal voltage stress on the primary inverter switches is lowered when compared with the standard SSI that delivers entire DC-bus voltage to switches. A rectifier-based model is employed to simulate the behavior of a renewable energy source. Combining these advantages with the conventional modulation of the inverter offers a more effective design. The buck-boost split-source inverter (BSSI) was analyzed using three distinct modulation techniques: the sinusoidal pulse-width modulation scheme (SPWM), the third-harmonic injected pulse-width modulation (THPWM) scheme, and space vector modulation (SVM). The proposed analysis was validated through MATLAB-SIMULINK and practical outcomes on a 5.0 kW model. The practical and SIMULINK data were found to be closely aligned with the analysis. The circuit developed in this study also ensures efficient DC-to-AC conversion, specifically with regard to low-voltage sources, like fuel cells or photovoltaic (PV) systems. Full article

This paper presents an adaptive virtual oscillator control in coordination with an adaptive filter to mitigate subsynchronous oscillations in grid-forming converters caused by series compensation. Although series compensation enhances power transfer capability and transient stability margins, it can introduce subsynchronous resonance, leading to subsynchronous oscillations. Virtual oscillator control fed with set points is made dispatchable for grid-forming control to ensure the power-sharing, fast-synchronization, and subsynchronous oscillation damping capability of inverters. In this paper, taking advantage of power reserves in grid-forming operation, virtual oscillator control law is modified to dynamically change the set power point during low-resonance conditions to mitigate subsynchronous oscillations. Moreover, to overcome the limited damping capability of adaptive VOC during severe-resonance conditions, a coordinated adaptive adjustment of the grid-side filter inductance based on the modified power set point is designed. The IEEE’s first benchmark model is altered by integration with a 1000 MW grid-forming inverter in a MATLAB R2024b/Simulink environment. The previously proposed dispatchable virtual oscillator control and electronic-based FACT device, i.e., thyristor-controlled series capacitor, are implemented and analyzed under the same test system for the sake of comparison with the designed coordinated strategy. The simulation results are investigated in the time domain and frequency domain, and by calculating performance indices to verify the effectiveness of the proposed scheme. The overall analysis justifies the mitigated, low transient overshoot and high power quality of subsynchronous oscillations by using the designed strategy with varying compensation levels. Full article

Low-voltage grids are undergoing rapid change as rooftop photovoltaics, electric vehicles and other distributed energy resources increase their share of demand. Without new local control, these trends risk more frequent voltage problems and costly reinforcement, which can slow affordable and just energy transitions. This article proposes a MATLAB/Simulink methodology for designing and comparing PID and Mamdani fuzzy volt–var controllers implemented at a single PV inverter in a radial low-voltage feeder. The feeder model aggregates residential demand, two PV units, a small wind unit, battery storage and an EV charging event; controller performance is assessed using time-domain simulations and scalar indices of overshoot, undershoot, settling time, time outside a ±5% voltage band, and reactive power usage. In the studied high-PV scenario, both controllers maintain acceptable voltage quality with limited overshoot and short settling times, while the fuzzy controller yields smoother transients at the expense of slightly higher but still modest reactive power adjustments. The results illustrate how accessible digital tools can help system operators and regulators explore local volt–var strategies that increase renewable hosting capacity and power quality compliance without immediate grid reinforcement, thereby supporting sustainable electrification in the context of the fourth industrial revolution. Full article

Post-combustion CO₂ capture using monoethanolamine (MEA) is a mature mitigation technology, yet its high energy demand and complex dynamics remain major challenges. This study presents a unified dynamic modeling and control framework for an MEA-based absorption–regeneration system, focusing on a comparative evaluation of PID, fuzzy logic control (FLC), and model predictive control (MPC) under realistic operating disturbances. A control-oriented surrogate model was developed in MATLAB R2024b/Simulink and validated against published benchmark trends. The control objective was to maintain CO₂ capture efficiency above 90% while minimizing reboiler energy consumption under ±10% inlet CO₂ concentration and flue gas flow disturbances. Simulation results showed that PID control ensures basic stability but exhibits slow recovery and high energy usage, while FLC improves robustness with limited dynamic improvement. MPC consistently maintained capture efficiency above the target value, reduced the settling time by approximately 37%, and achieved a 12.4% reduction in average reboiler duty compared to PID control. The results demonstrate that a unified, implementation-oriented modeling framework enables the effective assessment of advanced control strategies and supports the energy-efficient operation of industrial MEA-based CO₂ capture systems. Full article

To address the limited capability of conventional hydro-pneumatic suspensions in coordinated damping–stiffness regulation, this paper proposes a new semi-active hydro-pneumatic suspension (SAHPS) system based on a dual-valve shock absorber. A damping valve architecture composed of a spring check valve–solenoid proportional valve–spring check valve is arranged between the rod and rodless chambers of the hydraulic cylinder, enabling coordinated adjustment of suspension damping and equivalent stiffness. Furthermore, a genetic algorithm optimization with model predictive control (GA-MPC) is designed to enhance the overall dynamic performance of the suspension while effectively reducing the operating frequency of the solenoid proportional valve. Finally, AMESim–Simulink co-simulations and hardware-in-the-loop (HIL) experiments are conducted under bumpy road excitation and Class C random road conditions. Under Class C random road conditions, compared with passive hydro-pneumatic suspension and semi-active suspension with conventional MPC, the proposed method achieves maximum reductions of 11%, 25%, and 12.9% in the root mean square values of body acceleration, suspension working space, and dynamic tire load, respectively. The discrepancies between experimental and simulation results remain below 7%, confirming the effectiveness of the proposed system and control strategy. This study provides a new technical guidance for low-frequency vibration suppression in vehicle suspension systems. Full article

Ion-exchange-based wastewater treatment processes exhibit nonlinear and time-varying dynamics, making the control of total dissolved solids (TDS) and water hardness a complex task. Conventional Proportional–Integral–Derivative (PID) controllers often show limited performance under such conditions due to fixed tuning parameters and linear assumptions. To address these limitations, this study presents a comparative evaluation of traditional and intelligent control strategies for regulating TDS and water hardness through influent flow control. A classical PID controller is compared with fuzzy logic and Adaptive neuro-fuzzy inference system (ANFIS) controllers using a unified MATLAB/Simulink simulation framework. The control performance is evaluated based on dynamic response characteristics, including rise time, settling time, and overshoot. For TDS control, the PID controller exhibits a rise time of 15.9 s and a settling time of 50.9 s, while the fuzzy logic controller improves the response with a rise time of 13.6 s and settling time of 44.1 s. The ANFIS controller achieves the fastest response, with a rise time of 8.31 s and a settling time of 27.1 s. Similar trends are observed for water hardness control, where the PID controller shows a rise time of 17.0 s and settling time of 55.8 s, the fuzzy logic controller reduces these values to 12.3 s and 40.4 s, respectively, and the ANFIS controller further improves performance with a rise time of 9.23 s and settling time of 30.3 s. The overshoot values for all controllers remain comparable, within the range of approximately 4.4–5.0%. The results clearly demonstrate that intelligent control strategies, particularly ANFIS, provide significantly faster convergence and improved dynamic performance compared to conventional PID control. The reduced settling time implies lower control effort and decreased energy consumption, highlighting the potential of intelligent controllers for efficient and reliable industrial wastewater treatment applications. Full article

In the airborne environment, radar electronic systems feature diverse operation modes and complex working conditions, which impose stringent requirements on the temperature control accuracy of the cold plate liquid cooling system. The operational stability of radar chips is directly determined by the inlet temperature of the cold plate; thus, optimizing both the structure and control strategy of the liquid cooling system is crucial to ensuring their reliable operation under airborne working conditions. In this paper, a simulation platform for the airborne radar liquid cooling system is constructed based on MATLAB/Simulink (R2023a), on which system-level design and simulation research are carried out under dynamic working conditions. After verifying the model effectiveness through experiments, a comparative analysis of the temperature control performance between feedback control and fuzzy control is conducted. Simulation and experimental verification results demonstrate that under the working conditions with coupled variations in the ambient environment and power, fuzzy control achieves a maximum temperature overshoot of merely 0.14 °C with an overshoot time of 1 s, which is significantly superior to feedback control, whose maximum temperature overshoot and overshoot time reach 6.6 °C and 4 s, respectively. This study realizes the precise and stable control of the cold plate inlet temperature and provides a feasible solution for the thermal management design of airborne liquid cooling systems and their similar counterparts. Full article

This paper presents two new step-up DC–DC converters that have high voltage gains and low voltage stresses across their main switches with respect to their output voltages. These high voltage gains are achieved with the help of voltage multiplier cells (VMCs). By inserting VMCs that are switched inductors (SIs) and switched capacitors (SCs), the voltage gains increased substantially compared to the conventional converters, such as the traditional boost converter (TBC), Luo converter, or Zeta converter. Furthermore, the TBC has a voltage stress across its main switch that equals the output voltage, while the two proposed step-up converters have voltage stresses across their main switches that are lower than their output voltages. An extended converter is obtained from the main topology, which has a higher voltage gain than the main one. This paper investigates both topologies in continuous conduction mode (CCM) operation and shows a detailed analysis deriving the voltage gain and the voltage stress between the switches. In the main topology, when the duty ratio (D) is $0.75$, the output voltage equals around thirty times the input voltage. In the extended topology, when D is $0.75$, the output voltage equals around sixty times the input voltage. The voltage stresses across the main switches in both topologies are half of their output voltages when D is $0.75$. Simulation models using Matlab/Simulink are carried out for both the main and extended topologies, showing how these agree with the theoretical derivations. Full article

In this paper, frequency control of shipboard microgrids is achieved in the presence of measurement noise, dynamic uncertainty, and actuator faults. Measurement noise arises from incorrect signal processing, electromagnetic interference, converter switching dynamics, mechanical vibrations from propulsion and generators, and transients caused by sudden changes in load or generation. Actuator faults are caused by intense mechanical vibrations, temperature-induced stress, degradation of power electronic devices, communication latency, and wear or saturation in fuel injection and governor components. To regulate the frequency deviation under these challenges, a cross-entropy-based fault-tolerant model predictive control method, utilizing a discrete-time linear Kalman filter, is developed. Firstly, the discrete-time linear Kalman filter ensures that uncertain states of the shipboard microgrids are measurable in a noisy environment. Afterward, the model predictive control scheme is employed to obtain an optimal control input based on the measurable states. This controller ensures the frequency regulation of shipboard microgrids in the presence of measurement noise. Furthermore, a fault-tolerant control technique that utilizes the concept of cross-entropy is extended to provide a robust controller that verifies the frequency regulation of shipboard microgrids with actuator faults. To demonstrate the stability of the closed-loop system of the shipboard microgrids based on the proposed controller, considering the effects of measurement noise, state uncertainty, and actuator faults, the Lyapunov stability concept is employed. Finally, simulation results in MATLAB/Simulink R2025b are provided to show that the proposed control method for frequency regulation in renewable shipboard microgrids is both effective and practicable. Full article

With the continuous increase in coal mining depth, rock burst occurs frequently, which poses a serious threat to coal mine safety production. As the key equipment to ensure the stability of coal mine working face, the response characteristics of the hydraulic support safety valve are directly related to the life safety of coal miners and the protection of equipment. To address the problem that the traditional hydraulic support safety valve has a slow response and cannot release pressure rapidly, a new control strategy of a hydraulic support safety valve based on the magnetorheological effect is proposed. The fixed current control strategy and the fuzzy PID strategy based on grey predictive control are studied to improve the response speed and pressure relief efficiency of the safety valve. The effectiveness of the control strategy is verified by AMESim and Simulink co-simulation. The simulation results show that the new control strategy can significantly improve the dynamic response characteristics of the safety valve, shorten the response time and enhance the pressure relief performance. The superiority of the magnetorheological effect safety valve in improving the impact resistance of the coal mine hydraulic support is verified. This study provides a new technical path and theoretical basis for the optimal design of the safety valve of coal mine hydraulic support and the safety protection under rock burst. Full article

The automation of petroleum extraction columns requires robust and adaptive control due to the highly nonlinear nature of the heat and mass transfer processes involved. In this study, a hybrid control system integrating conventional fuzzy logic with quantum-inspired computational optimization is proposed to enhance the control of temperature and flow rates in industrial extraction columns. The hybrid quantum-inspired fuzzy controller is applied to a petroleum extraction column. The controller adopts fuzzy rule weights using a quantum-inspired optimization algorithm. Compared with classical PID and fuzzy controllers, it reduces settling time and solvent consumption. A MATLAB/Simulink-based simulation model of the extraction column was developed to validate the approach. Experimental tests were conducted using synthetic data and varying operational parameters to evaluate control performance. The hybrid controller achieved a 0.7% reduction in phenol consumption and reduced temperature deviations by 2.2% compared to a baseline fuzzy controller. Energy savings ranged from 1% to 2% depending on the operating scenarios. These results were confirmed through repeated simulations and statistical analysis. The proposed system demonstrates the potential of quantum-inspired fuzzy control to enhance process efficiency, reduce energy use, and improve product quality in complex chemical extraction applications. The statistical evaluation was based on repeated simulation runs and comparative performance metrics rather than physical experiments. Full article

With the increasing penetration of inverter-based resources (IBRs), modern power systems are experiencing undesirable dynamics, such as sub-synchronous oscillations in weak grids. Conventional PI control schemes, however, exhibit limited robustness against nonlinearities arising from varying operating points in weak grids, leading to instability. To address this challenge, we propose a robust controller for the outer loop of grid-side converters in IBRs based on robust μ-synthesis control theory. Specifically, this paper utilizes μ-synthesis to handle linearized model parameters associated with operating-point variations. The proposed controller replaces the PI controllers in the outer loop while retaining the established dq-frame control philosophy. Furthermore, during controller synthesis, the controller is optimized with a 2-by-2 multi-input multi-output structure to explicitly account for cross-coupling effects between the d- and q-axes. Finally, the proposed controller was validated using electromagnetic transient simulations of a detailed type-IV wind farm model implemented in MATLAB/Simulink R2025a, and its performance was compared with that of a conventional PI-based outer control loop. The wind farm was tested under very weak grid conditions, and the proposed controller demonstrated robust stability against varying operating points by providing superior damping performance. Full article