Simulink Environment Research Articles

The Effect of Sample Size on the Interpolation Algorithm of Frequency Estimation

Fast and accurate frequency estimation is essential in various engineering applications, including control systems, communications, and resonance sensing systems. This study investigates the effect of sample size on the interpolation algorithm of frequency estimation. In order to enhance the accuracy of frequency estimation and performance, we describe a novel method that provides a number of approaches for calculating and defending the sample size for of the window function designs, whereas, the correct choice of the type and the size of the window function makes it possible to reduce the error. Computer simulation using Matlab / Simulink environment is performed to investigate the proposed procedure's performance and feasibility. This study performs the comparison of the interpolation algorithm of frequency estimation strategies that can be applied to improve the accuracy of the frequency estimation. Simulation results shown that the proposed strategy with the Parzen and Flat-top gave remarkable change in the maximum error of frequency estimation. They perform better than the conventional windows at a sample size equal to 64 samples, where the maximum error of frequency estimation is 2.13e-2, and 2.15e-2 for Parzen and Flat-top windows, respectively. Moreover, the efficiency and performance of the Nuttall window also perform better than other windows, where the maximum error is 7.76×10-5 at a sample size equal to 8192. The analysis of simulation result showed that when using the proposed strategy to improve the accuracy of the frequency estimation, it is first essential to evaluate what is the maximum number of samples that can be obtained, how many spectral lines should be used in the calculations, and only after that choose a suitable window.

Neuroadaptive Control of a Continuum Robot for Finger Rehabilitation

This study has designed an easy-to-wear parallel continuum robot-based hand rehabilitation system that supports and enhances the finger’s flexion, extension, abduction, and adduction movements. The primary novelty of the proposed system lies in its ability to focus therapeutic exercises on a single joint, a feature not commonly found in existing rehabilitation robots. A kinematic model of the system was developed, and to perform both kinematic and dynamic analyses, a multibody model was constructed in the MATLAB Simulink environment. Joint angle control was implemented using a nominal controller, and to account for individual uncertainties in joint dynamics, a neuroadaptive controller was integrated with the nominal controller. This approach aims for the neural network architecture to learn these uncertainties during control iterations and incorporate them into the control, resulting in a robust controller. Thus, a model reference control approach was proposed for active and passive rehabilitation processes. The system model was tested in a simulation environment, and then all tests were repeated in the physical system. The simulation and real system results include the real system’s open-loop responses, nominal controller responses for each joint, responses, and the results for active, passive, and assistive control modes.

Implementation of sensorless indirect vector control of induction motor with closed-loop current control

Abstract The paper focuses on the development and testing of an advanced induction motor control method. This method, known as indirect rotor flux-oriented vector control, allows independent control of motor torque and flux, providing high dynamic performance similar to that of a DC motor. Additionally, the implemented system is sensorless, eliminating physical rotor position sensors, which reduces complexity and cost while increasing system reliability. The proposed system uses a rotor flux estimation algorithm, based on mathematical models, which provides the necessary information for vector orientation in the absence of a sensor. Additionally, closed-loop current control improves stability and accuracy of the control by correcting output current deviations from reference values. Thus, the system provides fast and accurate response in the presence of load variations and external disturbances. Simulations and experimental tests were carried out in the Simulink environment, where the proposed model was evaluated under various operating conditions. The results demonstrate the efficiency of the system and the validity of the method for industrial applications where precise and robust induction motor control is required.

A GWO-Based Indirect IMC-PID Controller for DC-DC Boost Converter

A PID controller design using an internal model control (IMC) approach is a well-established method for controller tuning in a DC-DC boost converter. This study introduces an innovative implementation of a novel indirect Internal Model Control (IMC) strategy for PID controller design, tailored specifically for a DC-DC boost converter. While the indirect IMC approach has been documented in prior research, its application to boost converters signifies a substantial contribution to the field. The proposed method simplifies the tuning process by focusing exclusively on the plant shifting parameter ψ, thereby eliminating the need for an IMC filter. Optimal tuning is achieved through the Grey Wolf Optimization (GWO) method, which enhances the controller’s stability, robustness, and transient response in the presence of disturbances commonly encountered in boost converter operation. Extensive simulations are performed in a MATLAB Simulink environment to compare the performance of the GWO-based indirect IMC-PID controller with traditional PID and IMC-PID designs. Performance is assessed based on transient response parameters and performance indices, such as IAE, ISE, ITAE, and ITSE. Results reveal that the GWO-optimized indirect IMC-PID controller significantly outperforms conventional controllers, demonstrating enhanced servo and regulatory behaviors.

A switched model predictive control with parametric weights-based mode transition strategy for a novel parallel hybrid electric vehicle

In a novel parallel hybrid electric vehicle (HEV) configuration, the transition from pure electric mode to hybrid mode encompasses critical operations such as engine startup, coordinated control of motor and engine torque, and engagement of the clutch. Addressing the intricate challenges associated with enhancing speed tracking performance during and after mode transition, mitigating jerk during mode transition, and minimizing mode transition time, this paper conducts a meticulous analysis of the vehicle configuration and mode transition process. The mode transition process is systematically delineated into four stages, with each stage characterized by the establishment of dynamic models. Subsequently, a mode transition strategy is proposed, leveraging switched model predictive control with parametric weights (SMPC-PW). This controller framework includes the design of two model predictive controllers (MPC) tailored for two pivotal stages, the formulation of a parametric weights pattern based on pre-transition acceleration, and the development of a stage switching strategy to ensure seamless switches between controllers. The efficacy of the proposed strategy is validated through co-simulations in the Simulink and GT-Power environment. The fine-tuning of MPC parameters is grounded in multiple sets of prediction horizons and sampling time simulation results. In comparison to strategies based on MPC and PID under various acceleration scenarios, the SMPC-PW strategy consistently maintains acceleration control below 10 m/s3. It not only achieves superior speed tracking during and after mode transition but also reduces mode switch time by 0.1 s-0.3 s. These compelling results unequivocally demonstrate that the proposed mode transition strategy significantly elevates the quality of mode transition for this specific parallel HEV configuration.

Defect diagnosis of high contact ratio spur gear system with increasing level of fault

Breakage of tooth is common in power transmission gear systems with continuous running. Model of a system (virtual prototype) serves as a tool for generating large amount of data and can replace expensive experimentation. Dependability of a model depends on the purpose for which the data is generated. Two models of spur gear system are considered in this work: (1) block diagram-based planer kinematics model of spur gear system developed in Simulink environment which does not consider the support and torsional effects and (2) detailed CAD based multibody dynamics model (includes bearings, drive, coupling, connecting rod and supports) that considers backlash, axial and torsional effects developed using MBS ADAMS software. A custom-made high contact ratio gear system is fabricated for experiments. The time and frequency domain characteristics of experimental and simulated signals are compared to draw the conclusions of fault related symptom of the systems with increasing level of faults and the utility of models.

Construction of the Automatic Control System of a Single-Screw Extruder

The purpose of the work is to build the rational system for regulating technological parameters of the single-screw extruder using the frequency-regulated electric drive with limited use of sensors. This goal is achieved by the way of solving the following problems: development the method for controlling the technological parameters of the extruder with a controllable electric drive; development of a structural diagram of a model for estimating the speed of rotation a rotor of the engine without the use of velocity-type transducers; development of a functional diagram of the vector frequency-regulated electric drive with an observer that is built on the basis of a voltage equation corresponding to the main magnetic flux; development of a simulation model of the system of adjustable electric drive of the extruder and carrying out simulations with using the Matlab software package in the environment of Simulink. The most significant results of the researches are: the proposed algorithm for controlling the technological parameters (dynamic viscosity and pressure) by the way of calculating of the electrical power parameters of the adjustable electric drive of the extruder without the use velocity-type transducers; the functional diagram of the vector frequency-regulated electric drive of the single-screw extruder with the observer that was built on the basis of balance of the reactive capacity provides the necessary values of the technological parameters of the extruder. Changes in dynamic viscosity and pressure in the material, provides flexible adjustment without the use of speed sensors and rational use of electricity.

FUZZY LOGIC-BASED POWER MANAGEMENT IN GRID-CONNECTED SOLAR ENERGY SYSTEMS

With the ever-increasing application of photovoltaic systems on the power grid, energy flow management and grid stability have become a key factor, especially under varying conditions like variable cloud cover and fluctuating load demands. The paper looks forward to proposing a fuzzy logic approach to the management of energy regarding a solar energy system connected to a grid, aiming at obtaining an optimised power distribution among PV generation, the grid, and battery storage. The proposed system will be driven by five input parameters, PV value, grid availability, load demand, battery state of charge, and tariff rate, to regulate the energy flow activity within different scenarios. The simulation results developed in the MATLAB Simulink environment proved the effectiveness of the applied controller in maintaining energy stability and fulfilling the requirements of a load within seven case studies for a 24-hour duration. The work points out the potential of fuzzy logic, besides reliability, in enhancing the efficiency of various renewable energy systems integrated with conventional energy supply grids.<p> </p><p><strong> Article visualizations:</strong></p><p><img src="/-counters-/soc/0799/a.php" alt="Hit counter" /></p>

Comparison of passive and semi-active piezoelectric transducer damping of cantilever oscillation

The aim of this work is the analysis of passive and semi-active damping methods on the model woven beam with a piezoelectric (PZ) layer. The mathematical model of the PZ layer on cantilever beam is derived. For modeling, real product parameters of PZ layer are used, and through simulation find the optimal values to dampen it. The resistive-inductance passive model, and State-Switch Damping SSD semi-active model are used in this work. The models are processed in the MATLAB Simulink environment and the results of the behavior of the models compared to each other. The program involving passive and semi-active systems, where analyze the behavior of the model for different parameters and the damping capabilities of individual methods are compared. The simulation results show the effectiveness of the semi-active system in comparison with the passive systems, also it shows the passive method is not so effective at low frequency as it in high frequency, and the semi-active method is not optimal for high frequency vibration.

Determining Watterson model time delays using adaptive filters

Short radio waves have the property of being reflected from the ionosphere, which is why data transmission via HF communication channels can be carried out over many kilometers without additional transmitting devices. The use of broadband communication channels increases the data transmission speed, but at the same time leads to severe distortion of the received signal. Using the Watterson model, the HF communication channel was simulated in Matlab in the Simulink environment. For various possible values of the model parameters, least mean squares (LMS) equalizer algorithms were used to determine these coefficients.

Implementation of NLC‐SHM based novel PWM scheme on packed U‐cell multilevel inverter

AbstractThis article introduces a novel integrated nearest level controller (NLC) combined with selective harmonic mitigation (SHM) control approach aimed at efficiently suppressing lower‐order harmonics has been introduced. The proposed methodology is implemented on the PUC‐7 inverter topology, leveraging the combined benefits offered by both NLC and SHM controllers through a hybrid model. The proposed method demonstrates the capability to reduce lower‐order harmonics up to the 49th harmonic from the load voltage. The particle swarm optimization algorithm is employed to determine optimal switching angles and their corresponding nearest levels, thereby reducing implementation time, computational complexity, and overall system intricacy. The performance analysis of the proposed control strategy across various scenarios, including fluctuations in modulation index and monitoring diverse parameters such as load dynamics has been performed. This approach yields a significant reduction in total harmonic distortion in both load voltage and current. A comparative analysis between NLC, selective harmonic mitigation (SHM), and the integrated NLC‐SHM approach is carried out on the PUC‐7 inverter. The integrated SHM‐NLC control is implemented and validated using the MATLAB Simulink environment, complemented by hardware‐based experimentation, to ascertain its effectiveness.

Experimental validation of a novel hybrid Equilibrium Slime Mould Optimization for solar photovoltaic system

Maximizing Power Point Tracking (MPPT) is an essential technique in photovoltaic (PV) systems that guarantees the highest potential conversion of sunlight energy under any irradiance changes. Efficient and reliable MPPT technique is a challenge faced by researchers due to factors such as fluctuations in irradiance and the presence of partial shading. This paper introduced a novel hybrid Equilibrium Slime Mould Optimization (ESMO) MPPT-based algorithm combining the advantages of two recent algorithms, Slime Mould Optimization (SMO) and Equilibrium Optimizer (EO). The ESMO algorithm is compared with highly efficient MPPT-based techniques such as SMO, EO, Particle Swarm Optimization (PSO), Grey Wolf Optimization (GWO), and Whale Optimization Algorithm (WOA), both under a Simulink environment and a real-time experimental laboratory setup using a Dspace1104 controller and PV emulator. The comparison focuses on performance under several irradiance cases, including instant irradiance change, partial shading, complex partial shading, and dynamic partial shading. The key advantage of ESMO is the fact that it has a single tunable parameter, which makes implementation much easier and, at the same time, reduces the computational resources that are required by the control system. Extensive testing proves the superiority of ESMO over all other techniques, the average efficiency of which is 99.98% under all conditions. Additionally, ESMO provides fast average tracking times of 244 ms under simulation experiments and 200 ms for real-time experiments. These results show that ESMO can be very important for future implementation in large-scale solar PV systems.

A novel dual hysteresis controller for the management of a three phase dynamic voltage restorer

In this work a novel control scheme for the three-phase dynamic voltage restorer has been proposed and validated. The proposed control strategy guarantees the source current waveform to be sinusoidal and at near unity power factor. Further, the voltage sag and swell occurring in the source are overcome and the load gets a smooth power supply at a voltage closer to the rated voltage even in the face of voltage sag or swell occurring in the source. The proposed system uses a power factor corrected front end rectifier that regulates a defined voltage in a DC link. The DVR derives power from the DC link. The PFC rectifier and the DVR converter both are controlled by individual PI and hysteresis current controllers. Further the control system has been adopted in per phase method with actual current estimation system for each phase of the rectifier and the DVR sides done individually. The main advantage of the proposed system is that it does not require the usually required DQ transformation scheme. The proposed idea has been proved to be suitable for balanced and unbalanced loads. The proposed idea has been validated with dynamic simulations carried out in the MATLAB SIMULINK environment and with a scaled down experimental prototype.

Intelligent Efficient Routing and Localization in the Underwater Wireless Sensor Network to Improve Network Lifetime

The inefficiency of the localization process mostly causes delays and operational difficulties in wireless sensor network (WSN) topologies. When localization is suboptimal, the time required for path creation significantly increases, leading to reduced network lifetime and diminished routing efficiency. To address these critical issues, our research focuses on developing a novel procedure that optimizes routing and localization. In this context, localization is the initial step for reaching sensor terminals, followed by activating the routing mechanism. To tackle these issues in Underwater Wireless Sensor Networks (UWSN), the proposed work presents the Elman Bat-based Hello Routing (EBbHR). The primary objective of our research is to locate wireless sensor nodes within the designed UWSN effectively. The process is initiated to achieve this by creating the necessary wireless sensor hubs within the MATLAB Simulink environment. Subsequently, the novel EBbHR function is activated to facilitate the precise localization of all sensor hubs, thereby enhancing the overall data transmission. The success of the designed EBbHR is assessed by considering UWSN factors, and a comparison with current approaches is carried out to show the advancements made by the model.

Optimal Control Strategy to Analyse the Networked Control System Stability

It is crucial to preserve the networked control systems (NCS) transient performance and stability because adding uncertain parameters degrades system performance and introduces instability. Thus, the analysis of NCS system performance under uncertain conditions, such as disturbance, is the focus of this paper. The performance of NCS is demonstrated using control action and some appropriate stability conditions. The simulation diagram in result section displays effectiveness of proposed methodology and shows a comparative analysis of the response signal with and without control action along with disturbance in NCS. Experiments conducted in the MATLAB Simulink environment demonstrate the efficacy of the suggested methodology.

A novel differential protection scheme for AC microgrid based on loss function

Differential protection stands out as the optimal choice for protecting AC microgrids, compared to overcurrent and distance-based schemes, because of its adaptability to different network topologies, ability to manage bi-directional power flow, and better selectivity for system transients and variable fault current. However, high impedance faults, time synchronization error, and high bandwidth communication requirements are significant challenges faced by differential protection schemes. Considering such issues, this paper has proposed a novel differential protection scheme based on loss function (Percentage Bias Error), evaluated by using line's both end superimposed positive and negative sequential currents magnitude, which enhances the sensitivity in identifying internal fault that occurs in either grid-connected or islanded microgrid mode of operation. Its effectiveness is validated on ring and radial distribution networks with high impedance fault (500 Ω) at different fault locations. Additionally, the relaying scheme is stable under different system transients, CT error in noisy environments, and robust for time synchronization error. Moreover, the proposed scheme is compared with the existing techniques to illustrate its high sensitivity, fast operation (within one cycle), and high accuracy. The proposed scheme is simulated in a MATLAB Simulink environment, and results are validated using a laboratory-level hardware setup.

Rule‐based energy management system for autonomous voltage stabilization in standalone DC microgrid

AbstractThis paper presents a rule‐based energy management system (EMS) designed for a standalone DC microgrid incorporating solar photovoltaic (PV), fuel cell, battery energy storage system (BESS), and electric vehicle. The unpredictable nature of renewable energy sources and the instability of loads pose challenges for maintaining DC bus voltages and power‐sharing arrangements, impacting the microgrid's smooth operation. The proposed EMS aims to ensure power balance between generation and demand, mitigating vulnerabilities of the DC bus to voltage instability caused by fluctuations from both the load and source sides. This is achieved through an autonomous DC bus voltage stabilization strategy, involving the maintenance of a nominal state of energy (SoE) for the BESS and hydrogen fuel consumption for the fuel cell within predefined lower and upper limits. By regulating these two factors, the EMS algorithm facilitates optimal performance of the PV, battery, and fuel cell components. Consequently, the EMS provides decision‐making instructions to each individual energy source, ensuring efficient operation under various conditions. The effectiveness of the proposed EMS is evaluated through hardware‐based testing on a DC microgrid and simulations in the MATLAB Simulink environment across multiple operating scenarios.

A new solution for tackling mismatching losses in solar PV array via image encryption

Solar photovoltaic systems may undergo changes in power generation due to environmental factors such as partial shadowing, resulting in losses due to mismatch. This can ultimately lead to a decrease in the efficiency of the system's power conversion. While current solutions are both cost-effective and efficient, there is potential for novel approaches to further enhance system performance by improving consistency, power production, and minimizing mismatch losses. To address these limitations, this paper proposes the utilization of a highly efficient generalized Arnold's cat Map technique, commonly used in the image encryption process, to reconfigure the PV array. The effectiveness of these proposed approaches is evaluated in a MATLAB Simulink environment, specifically for a symmetrical (8x8) PV array, under various benchmark conditions such as Long wide; Short wide, Long Narrow, and Short Narrow shading conditions. The results obtained from these evaluations are then compared to prominent strategies such as Total-cross-tied and the recently reported Chaotic Baker's Map reconfiguration techniques. Furthermore, extensive analysis is conducted using different performance indices to gain a comprehensive understanding of the proposed approaches.

Accurate design, simulation and implementation of AC/DC inductors for power electronic converters

AbstractThis article proposes a holistic and improved methodology for the inductors' design in power electronic circuits operating at high frequencies. This methodology includes an analytical design, a finite element modeling of the electromagnetic behavior with JMAG software, a simulation analysis in a Simulink environment, and experimental verification of the effectiveness of inductor design in a laboratory‐scale step‐up boost power converter prototype. The holistic approach allowed us to achieve all target specifications such as maximum power (300 W), minimum voltage (60 V), inductance (1.77 mH), and maximum current ripple (1 A). It guarantees the losses' minimization in core and copper (21.47 W), and marginal errors below 4% between the analytical, simulated, and experimental values.

Review and modeling on hydrogen fuel cells electric vehicle (HFCEV), in comparison with battery electrical vehicle (BEV) using MATLAB environment. Case study: Postal car

This research puts forward the modeling of a Hydrogen Fuel Cell Electric Vehicle (HFCEV) and its validation, in comparison with battery electrical vehicle (BEV) based on a postal vehicle and its subsystems. The main investigation parameters are the amount of hydrogen consumed, and the change in the state of charging of the battery. For the profile of the same speed route, an HFCEV model and a BEV model, consisting of multiple subsystems, were developed, and simulated in the MATLAB® Simulink environment. We make use of various sources of drive cycles to obtain our outcomes such as the New European Diving Cycle (NEDC). By running simulations for different stages, we are able to generate simulation results. The discrepancies in the graphs and the visual demonstrations guided us to variable conclusions on how different factors affect an electric vehicle’s performance and efficiency. The simulation result shows that the (BEV) is 30% more effective for NEDC drive cycle comparing with (HFCEV).