Controller For System Research Articles

Solar and Dynamo Powered Ev Using Fingerprint Authentication

Nonrenewable energy sources are already interfering with the availability of electricity. Today, the primary emphasis is on the generation of electricity from renewable sources. This proposal proposes a feasible design solution in the shape of a user-friendly three-wheeler. A fingerprint-accessible electric vehicle. This electric vehicle uses solar power and a self-changing dynamo to charge its battery. The battery serves as the vehicle's power source. A microcontroller serves as the system's primary controller. It is connected to a fingerprint module, a relay, the car ignition, and an LCD. The Microcontroller reads the input from the fingerprint module and, if it is legitimate, grants access to the ignition system. The status will be displayed on the LCD. In addition, we're adding three more sensors: speed, temperature, and voltage. Lithium-ion batteries can be harmful if not used within the safety-operated area (SOA). To avoid this, we calculate the temperature of the lithium-ion battery when it exceeds 49.9?. It will make a sound through the buzzer. This can prevent damage to the battery and the person driving the vehicle. Voltage Sensor is designed to monitor battery charging and discharging time, which is displayed on the LCD. A speed sensor is used to determine the speed of the vehicle.

Precision-controlled ultrafast electron microscope platforms. A case study: Multiple-order coherent phonon dynamics in 1T-TaSe2 probed at 50 fs-10 fm scales.

We report on the first detailed beam tests attesting the fundamental principle behind the development of high-current-efficiency ultrafast electron microscope systems where a radio frequency (RF) cavity is incorporated as a condenser lens in the beam delivery system. To allow for the experiment to be carried out with a sufficient resolution to probe the performance at the emittance floor, a new cascade loop RF controller system is developed to reduce the RF noise floor. Temporal resolution at 50 fs in full-width-at-half-maximum and detection sensitivity better than 1% are demonstrated on exfoliated 1T-TaSe2 system under a moderate repetition rate. To benchmark the performance, multi-terahertz edge-mode coherent phonon excitation is employed as the standard candle. The high temporal resolution and the significant visibility to very low dynamical contrast in diffraction signals via high-precision phase-space manipulation give strong support to the working principle for the new high-brightness femtosecond electron microscope systems.

Hybrid power plant using synchronization controller system to save electricity cost

The application of hybrid energy power plants is one solution to save electricity cost in buildings of government agencies, industries, and universities. The problem with using hybrid power plants that use solar energy sources and paid electricity networks is that sunlight energy cannot produce energy consistently from sunrise to sunset. Maximum energy can only be obtained when the sun is vertically acceptable to the photovoltaic (PV). This results in electrical loads having to be disconnected or switched back to the grid. The application of an electrical power sharing system synchronization controller system (SCS) can automatically regulate the use of electrical energy to low PV energy. The results of research on the application of hybrid PV using the SCS system with a rooftop solar panel system at the Gorontalo State University Building can produce a total electrical power of 600,975 kWh. The need for electrical power from January to September 2022 amounted to 859,151 kWh. The SCS hybrid power plant can reduce the use of paid electrical energy and its costs by 83.60%. The investment, operational, and maintenance cost requirement is IDR 10,747,886,801. The return on investment (ROI) analysis results show that the return on investment can be achieved for up to 34 years.

Implementation of the Smart Car Controller System in Cars Based on the Internet of Things

<em>This research aimed to create innovations in the development of the Internet of Things in car accessories to add system accessories to cars. The type of research used was experimental research. The subjects studied in this research were car users whose hobbies were various types of cars. The use of Internet of Things media in car accessories is very unique and has not been widely used to create innovations in the development of Internet of Things technology. This research aimed to help car users control their cars through the voice control feature, as well as to make car users a second choice to upgrade their car systems compared to buying a sophisticated car at an expensive price. The research results showed that there were still very few car users equipped with control systems compared to luxury car users who had sophisticated systems. Thus, it can be concluded that the idea of a voice control system using the Internet of Things for car accessories could help car users increase the sophistication of the car system and is a good choice.</em>

Simulink and real-time implementation of the E-cycle for measuring the reliability of the model using sensors

Utilization of rechargeable battery based bicycles has been significantly increased in India. In this study, battery powered electric vehicles have been implemented in MATLAB 2013a Simulink and real-time hardware systems. In order to design and integrate a working model of electric cycle, one needs to know about the different components involved in a system, such as lithium-ion batteries, Brushless DC motor (BLDC), and controller systems. The detailed study about the component selection has been described in this study. The drive testing has been implemented in both Simulink and real time respectively. Within a single charging system, the proposed model of electric cycle has been derived up to 25 kilo-meter up to speed of 30 kilo-meter per second respectively. The characteristics of electric vehicles such as torque (N-m) versus time (s), speed (km/h) versus time (s) and distance (km) versus time (s) have been discussed in this study. Based on characteristics study, reliability of the electric vehicle model has been enhanced in electric bicycle system by physical model confirmation.

ControlPULP: A RISC-V On-Chip Parallel Power Controller for Many-Core HPC Processors with FPGA-Based Hardware-In-The-Loop Power and Thermal Emulation

High-performance computing (HPC) processors are nowadays integrated cyber-physical systems demanding complex and high-bandwidth closed-loop power and thermal control strategies. To efficiently satisfy real-time multi-input multi-output (MIMO) optimal power requirements, high-end processors integrate an on-die power controller system (PCS). While traditional PCSs are based on a simple microcontroller (MCU)-class core, more scalable and flexible PCS architectures are required to support advanced MIMO control algorithms for managing the ever-increasing number of cores, power states, and process, voltage, and temperature variability. This paper presents ControlPULP, an open-source, HW/SW RISC-V parallel PCS platform consisting of a single-core MCU with fast interrupt handling coupled with a scalable multi-core programmable cluster accelerator and a specialized DMA engine for the parallel acceleration of real-time power management policies. ControlPULP relies on FreeRTOS to schedule a reactive power control firmware (PCF) application layer. We demonstrate ControlPULP in a power management use-case targeting a next-generation 72-core HPC processor. We first show that the multi-core cluster accelerates the PCF, achieving 4.9x speedup compared to single-core execution, enabling more advanced power management algorithms within the control hyper-period at a shallow area overhead, about 0.1% the area of a modern HPC CPU die. We then assess the PCS and PCF by designing an FPGA-based, closed-loop emulation framework that leverages the heterogeneous SoCs paradigm, achieving DVFS tracking with a mean deviation within 3% the plant’s thermal design power (TDP) against a software-equivalent model-in-the-loop approach. Finally, we show that the proposed PCF compares favorably with an industry-grade control algorithm under computational-intensive workloads.

A hybrid traffic controller system based on flower pollination algorithm and type-2 fuzzy logic optimized with crow search algorithm for signalized intersections

In this study, a hybrid traffic signal control (HTSC) system based on phase and time optimization was developed. The Flower Pollination Algorithm (FPA) approach was used for phase optimization, while Type-2 Fuzzy Logic, optimized with the Crow Search Algorithm (CSA), was utilized for time optimization. The hybrid system's performance was investigated using nine different traffic conditions and four different intersection geometries. The hybrid system was compared with three controller systems which are a fixed-time signal controller, a signal controller based on the FPA approach (FPA_TSC), and the optimized Type-1 fuzzy logic signal controller (Type-1 FL-TSC). The HTSC approach achieved the best performance with about 32% improvement over the fixed-time traffic controller and it showed 5% and 6% better performance than the FPA_TSC and Type-1 FL-TSC, respectively. Considering the performance of the new hybrid system, it is effective in minimizing delays and driver dissatisfaction occurring from signalization. It also contributes to the reduction of emissions and fuel consumption. The HTSC approach can be used as an alternative signal control method in the control of intersections with high traffic volume due to its fast and effective performance.

Online optimal tuning of fuzzy PID controller using grey wolf optimizer for quarter car semi-active suspension system

In order to reduce vibration and increase ride comfort, this article utilizes a system of quarter-car suspension integrated with a Fuzzy PID controller. To build and improve the Fuzzy PID controller for the semi-active suspension system used in quarter cars, using a novel meta-heuristic technique known as Grey Wolf Optimizer (GWO). Here the magnetorheological damper (MR) fluid with the Fuzzy PID controller was examined to optimize using the GWO algorithm. With the GWO technique and the integral of time absolute error (IAE) as a fitness function, the three gain parameters of the Fuzzy PID controller – Kp, Ki, and Kd– have been optimally set. The suggested approach has additional advantages for the optimization of functions with three variables, including simplicity in implementation, quick convergence traits, and superior computational capabilities. This work is significant, to the best of the author’s knowledge there is no optimization method using GWO to online tune a Fuzzy PID controller for a semi-active suspension system. The optimal output parameters of the controller can be updated online in real-time by GWO. The performance of the proposed controller was examined by assessing the root mean square (RMS) values and peak-to-peak (PTP) values of body displacement and body acceleration under various road profiles. To ensure that the intelligent controller was of the highest caliber, an online test rig was constructed. Results from simulations and online experiments demonstrated that the Fuzzy GWO PID controller significantly improved ride comfort under a variety of road conditions when compared to the Fuzzy PID controller and passive suspension system.

Fuzzy logic controller for UAV with gains optimized via genetic algorithm

A gains optimizer of a fuzzy controller system for an Unmanned Aerial Vehicle (UAV) based on a metaheuristic algorithm is developed in the present investigation. The contribution of the work is the adjustment by the Genetic Algorithm (GA) to tune the gains at the input of a fuzzy controller. First, a typical fuzzy controller was modeled, designed, and implemented in a mathematical model obtained by Newton-Euler methodology. Subsequently, the control gains were optimized using a metaheuristic algorithm. The control objective is that the UAV consumes the least amount of energy. With this basis, the Genetic Algorithm finds the necessary gains to meet the design parameters. The tests were performed using the Matlab-Simulink environment. The results indicate an improvement, reducing the error in tracking trajectories from 30% in some tasks and following trajectories that could not be completed without a tuned controller in other tasks.

Pengaruh Pancaran Radio Komunikasi Bali Radar Terhadap Pelayanan Lalu Lintas Penerbangan

The aviation communication system is very important for aviation, especially for pilots and air traffic controllers. The communication system for air traffic controllers and pilots must be adequate in order to create good communication and prevent misunderstandings between pilots and air traffic controllers. Meanwhile, the communication system at the Bali Radar APP/TMA unit cannot cover all of its areas of responsibility and is feared to affect the quality of air traffic services. After coordinating with the technical unit, the authors suggest installing a device that can extend a radio frequency signal called VHF ER (extender range), and specifically for the northern area of Mount Agung which is usually passed by VFR aircraft where the area is a class G airspace, the authors suggest creating a frequency called TIBA (Traffic Information Broadcast by Aircraft).

Collaborative optimization on cooling channel flow resistance and winding temperature for integrated cooling of motor and controller

The efficiency and working performance of the motor and controller system in micro-electric vehicles depends mainly on its thermal performance, which is contingent upon effective and active cooling. The working temperature of the motor and controller may be too high during operation, which properly causes motor power reduction or motor breakdowns. Therefore, it is crucial to design a good cooling channel for better cooling the integrated motor and controller system. This work proposes an integrated cooling channel of motor and controller, and the fluid-solid coupling analysis is applied for analyzing the velocity, pressure distributions of the cooling channel, and temperature distributions of motor solid components. Meanwhile, the collaborative optimization method based on the multi-island genetic algorithm (MIGA) is used to attain optimal design parameters of the integrated cooling channel of the motor and controller for obtaining a better cooling channel design with lower flow resistance and lower winding temperatures. Results show that the original cooling channel’s flow resistance and maximum winding temperature are 31.87 kPa and 120.04°C, respectively. The flow resistance and winding temperature are pretty significant. After optimization, the local vortex flow and zero velocity area in optimal cooling channel design are improved, the coolant flow velocity becomes more uniform, and the flow resistance is significantly reduced. The flow resistance and maximum winding temperature of the optimal cooling channel design are 12.5 kPa and 116.76°C, respectively, which are decreased compared with the original cooling channel structure, with a decrease of 39.4% and 2.7%, respectively. The research findings in this work can provide theoretical reference for solid components temperature evaluation of motor and give valuable data to cooling performance evaluation and optimization of integrated cooling channel for motor and controller system.

Inexpensive short-circuit current limiter and switching device based on one commutation circuit for a three-phase system

The escalating levels of fault currents resulting from short circuits, particularly in the context of distribution generators, have presented a critical need for the widespread implementation of fault current limiters (FCLs) in power systems. Despite their evident advantages, the extensive adoption of FCLs has been hindered by the high production costs associated with these devices. To address this challenge, a comprehensive study was conducted to develop a cost-effective FCL tailored specifically for three-phase power systems. This paper proposes a novel approach based on a single commutation circuit for the FCL and offers detailed insights into the construction of the FCL circuit, with a particular focus on efficient current interruption. Additionally, the study comprehensively discusses the logic controller and measurement system employed in conjunction with the proposed FCL, ensuring precise fault detection and rapid response to disturbances within the power grid. The integration of an artificial zero-crossing circuit within the FCL design further enhances its capability to limit short-circuit currents proactively, even before the occurrence of the first peak, thereby bolstering overall system reliability and stability. The study's significant contribution lies in achieving cost-effectiveness through the simplicity of the FCL's design, eliminating the need for extensive upgrades to various network components.

Fuzzy controller system utilization to increase the hydrogen production bioreactor capacity: toward sustainability and low carbon technology

Abstract The utilization of bio-hydrogen as a fuel source holds immense promise as a renewable energy option, offering compelling economic and environmental advantages. This study investigates the economic and environmental advantages of bio-hydrogen as a renewable energy source compared to fossil fuels, focusing on the reduction of greenhouse gas emissions such as carbon dioxide and carbon monoxide. The enhancement of anaerobic hydrogen production reactor capacity is explored through the application of a fuzzy controller system. Numerical simulations demonstrate that the fuzzy controller outperforms other methods in augmenting biological hydrogen production, effectively addressing the inherent non-linear characteristics of the system. In contrast, limitations in robustness against system uncertainty are observed with the non-linear controller. Exceptional tracking of desired values by the fuzzy controller, even in the presence of model uncertainty, results in a lower integral of time multiplied by squared error (ITSE) performance index compared to non-linear and proportional–integral controllers. Emphasizing the viability of the fuzzy method for regulating hydrogen production processes, potential gains of up to 95% in biological hydrogen production are indicated compared to open-loop configurations. This clean-burning fuel holds promise for industrial applications, contributing to the reduction of harmful gas emissions. The findings underscore the transformative potential of the fuzzy controller system in advancing sustainable hydrogen production and its significant role in addressing environmental concerns.

Fuzzy Logic Controller Based Charging and Discharging Control for Battery in EV Applications

The present research addresses the fuzzy charging and discharge control method for batteries made with lithium-ion utilized in EV applications. The proposed fuzzy-based solution takes into account available parameter to charge or discharge the store within the safe functioning area. To analyses and control battery performance, a variety of controlling methods have been used, but each has its own set of drawbacks, such as the inability to stop two charging conditions, the difficulty of the controller, the lengthy charge time. Due to the lack of mathematical calculations, a fuzzy controller is also simpler to construct, has less additional sensing components, and fewer deep discharging and overcharging protections, making it more efficient in terms of speed and complexity. The effectiveness of the suggested charging-discharging controller system is demonstrated through numerical simulations employing load demand and generation. Performance of the suggested controller is evaluated under simulated load conditions. The model's ability to regulate battery charging and discharging is confirmed by the trial's successful conclusion. The output shows that the battery's state of charge (SOC) never goes above the 20% to 80% safe range for that specific type. A new fuzzy model and an operational real-time system for regulating battery charging and discharging are the major results of this research.

A Centralized Shifted Voltage Control Method for Accurate Power Sharing in DC Islanded Microgrids

Due to line impedance mismatch among renewable energy sources (RESs), it is hard to realize accurate power sharing in the DC microgrid system. To solve this issue, a distributed power sharing strategy for adjusting the RES output voltage is developed by adding shifted output voltage into each local controller. Thanks to the shifted voltage, the influence of voltage drop caused by the droop controller is effectively mitigated, so that the DC bus voltage is constantly balanced regardless of the load changes. The proposed method is realized with a centralized approach, and all the required control variable to determine the reference voltage is transmitted through low-bandwidth communication. The controller design and system stability are analyzed in detail with a simplified microgrid model. Small-scale DC microgrid is simulated to verify the effectiveness of the centralized shifted voltage control method.

SRM drive system of FOPID controller for speed control and torque ripple minimisation

SRM drive system of FOPID controller for speed control and torque ripple minimisation

SRM drive system of FOPID controller for speed control and torque ripple minimisation

SRM drive system of FOPID controller for speed control and torque ripple minimisation

System reliability calculation based on the run-time analysis of ladder program

Programmable logic controller (PLC) system, a typical member in the embedded family, is now widely applied in industry. For safety critical PLC systems, reliability is of top significance. However, due to subcomponents’ temporal correlations caused by the run-time execution of embedded ladder programs, the complexity of reliability analysis is greatly increased. In this paper, we propose a novel probabilistic model to analyze reliability of PLC systems, called run-time reliability model (RRM). RRM is automatically constructed based on the structure and run-time execution of the embedded ladder program. Moreover, it is also a dynamic bayesian network (DBN) capturing full dependencies in a PLC system. Then, according to execution semantics of RRM nodes, we present customized conditional probability distribution (CPD) tables to calculate final reliability of the system, with failure probability of every referenced component as refinement. The strength of this model is that not only does it explicitly specify the correlations between run-time execution of embedded software and system components, but also it serves as a computational mechanism for probabilistic inference. Besides, the proposed approach is superior to previous works in both accuracy and efficiency. Compared to monte carlo based simulation, the average error rate of reliability values inferred from RRM model is small.

Control of complex systems with generalized embedding and empirical dynamic modeling.

Effective control requires knowledge of the process dynamics to guide the system toward desired states. In many control applications this knowledge is expressed mathematically or through data-driven models, however, as complexity grows obtaining a satisfactory mathematical representation is increasingly difficult. Further, many data-driven approaches consist of abstract internal representations that may have no obvious connection to the underlying dynamics and control, or, require extensive model design and training. Here, we remove these constraints by demonstrating model predictive control from generalized state space embedding of the process dynamics providing a data-driven, explainable method for control of nonlinear, complex systems. Generalized embedding and model predictive control are demonstrated on nonlinear dynamics generated by an agent based model of 1200 interacting agents. The method is generally applicable to any type of controller and dynamic system representable in a state space.

Smart Home Automation using IoT: Prototyping and Integration of Home Devices

Smart homes are becoming a reality thanks to the Internet of Things (IoT) technology's quick progress, providing homeowners with never-before-seen levels of efficiency, convenience, and security. This abstract gives a summary of a project that combines prototyping and integration to turn a standard house into a modern smart home. The paper focuses on creating an extensive IoT ecosystem that seamlessly connects diverse household equipment, such as lighting controls, thermostats, and security cameras, to a single, intelligent network. We use cutting-edge IoT communication and protocol technologies to create strong connectivity between these devices, enabling homeowners to remotely monitor and control them from a central hub or their smartphones. Our smart home system's central controller, which includes cutting-edge sensors and AI algorithms, is its brain. To reduce energy usage, improve security, and accommodate resident preferences and routines, this controller gathers and examines data from the linked devices. It learns user patterns through machine learning and suggests automation procedures to make life easier. A smart home system prioritises security and privacy in addition to increasing convenience. We also place a strong emphasis on flexibility and scalability, which enable the incorporation of new hardware and features as the IoT landscape changes. For homeowners, tech enthusiasts, and developers interested in building their own smart houses, our project on prototyping and integration serves as a model. It highlights how IoT technology has the ability to upgrade conventional living quarters into intelligent, networked areas that improve our quality of life while fostering energy efficiency and security. In the end, this project advances the continued development of smart home automation by increasing everyone's access to and ability to customise it.