System Response In Terms Research Articles

Firefly algorithm tuning of PID position control of DC motor using parameter estimator toolbox

This paper aims to design an accurate angular position control for DC motors using a proportional integral derivative (PID) controller. The estimated DC motor parameters have been calculated using the parameter estimator toolbox in MATLAB, Arduino Mega 2560 and speed sensor to build an accurate model in MATLAB. The optimized PID coefficients are found for the DC motor model using the firefly algorithm (FA), which aims to make the actual angle match the desired value without overshooting and oscillations. The PIC16F877A microcontroller was used to implement the code based on optimized PID coefficients found in MATLAB/Simulink to generate the suitable pulse width modulation (PWM) output. In this work, step input was tested to analyze the characteristics of the system response in terms of rise time, settling time and overshoot. It was found that the controller output response curve which is produced from FA-based-PID reached the desired position without overshoot and any oscillations. The findings established that closed-loop control of any system using a system identification toolbox and optimized PID technique can be applied in real applications using low-cost controllers and sensors such as PIC16F877A microcontroller and analog rotary position sensor, respectively.

An Improved Text-Based and Image-Based CAPTCHA Based on Solving and燫esponse Time

CAPTCHA is an acronym that stands for Completely Automated Public Turing Test to tell Computers and Humans Apart (CAPTCHA), it is a good example of an authentication system that can be used to determine the true identity of any user. It serves as a security measure to prevent an attack caused by web bots (automatic programs) during an online transaction. It can come as text-based or image-based depending on the project and the programmer. The usability and robustness, as well as level of security, provided each of the varies and call for the development of an improved system. Hence, this paper studied and improved two different CAPTCHA systems (the text-based CAPTCHA and image-based CAPTCHA). The text-based and image-based CAPTCHA were designed using JavaScript. Response time and solving time are the two metrics used to determine the effectiveness and efficiency of the two CAPTCHA systems. The inclusion of response time and solving time improved the shortfall of the usability and robustness of the existing system. The developed system was tested using 200 students from the Federal College of Animal Health and Production Technology. The results of each of the participants, for the two CAPTCHAs, were extracted from the database and subjected to analysis using SPSS. The result shows that text-based CAPTCHA has the lowest average solving time (21.3333 s) with a 47.8% success rate while image-based CAPTCHA has the highest average solving time was 23.5138 s with a 52.8% success rate. The average response time for the image-based CAPTCHA was 2.1855 s with a 37.9% success rate lower than the text-based CAPTCHA response time (3.5561 s) with a 62.1% success rate. This indicates that the text-based CAPTCHA is more effective in terms of usability tests while image-based CAPTCHA is more efficient in terms of system responsiveness and recommended for potential users.

A flexible Compilation-as-a-Service and Remote-Programming-as-a-Service platform for IoT devices

The Internet-of-Things (IoT) presents itself as an emerging technology, which is able to interconnect a massive number of heterogeneous smart objects. Several complex data-driven applications, such as smart cities applications, home automation, health monitoring, etc., have been realized through the existence of these ubiquitous networks of smart objects. The ability to remotely update the devices forming an IoT network is of paramount importance, as it enables adding new functionality in their firmware, either for resolving software bugs and security vulnerabilities or for application re-purposing, without the need to physically access them. In this work, we present a flexible Compilation-as-a-Service and Remote-Programming-as-a-Service platform that jointly offers cloud-based compilation and Firmware-Over-The-Air (FOTA) update functionalities for deployed IoT devices, in a reliable and secure manner. Our system is capable of easily supporting various embedded operating systems and heterogeneous hardware platforms. We describe the system architecture and elaborate on the implementation details of all system components. In addition, we perform an extensive performance evaluation of a Proof-of-Concept (PoC) deployment of our system and discuss results in terms of system response, scalability and resource utilization.

Tilt Integral Derivative Controller Optimized by Battle Royale Optimization for Wind Generator Connected to Grid

Globally the countries are focusing on reducing the carbon footprint leading to a greater effort for electrical energy generation by renewable energy sources, particularly wind. The wind turbines are invariably using doubly fed asynchronous generator. In this paper a controller has been designed for a doubly fed induction motor. The proposed Tilt Integral Derivate controller for was compared with commonly used PI, PID controllers. Several optimization algorithms were used for tuning of controllers and the best one was selected for each type of controller. The controller has been optimized using battlefield optimization. It had been compared with proportional integral controller, fractional order proportional integral derivative controller. Other controllers were optimized using meta heuristic algorithms. The controller enhanced the system response in terms of settling time, rise time and other parameters. The Tilt controller gave the overall superior performance in terms of parameters like rise time, settling time, settling minimum, peak, and peak time. The results were obtained using MATLAB. This paper discusses operation of doubly fed induction motor operation and optimization methods.

Influence of Pulse Characteristics on Turbocharger Radial Turbine

Abstract Turbocharging has been demonstrated as a key technology to enhance fuel efficiency in the automotive field that faces increasingly stringent emission regulations. Due to the reciprocating engine, pulsating flow feds the turbocharger turbine, which experiences conditions far from a continuous flow scenario. In this work, the effects of the characteristics of the mass flow pulse, parameterized through amplitude, frequency, and temporal gradient, are decoupled and studied via unsteady computational fluid dynamics calculations under on-engine operating conditions. First, the model is validated based on comparisons with experimental data in gas-stand conditions. Then, the effect of each parameter on the exergy budget is assessed by considering a ±10% variation with respect to a baseline pulse. The other factors defining the operating conditions (e.g., mass flow, shaft speed, and inflow exergy) are kept the same as the baseline. The adopted approach enables to completely isolate the effects of each parameter in contrast with previous literature studies. Based on the results observed, pulse amplitude is identified as the primary parameter affecting the hot-side system response in terms of turbine performance, heat transfer, and entropy generation, while frequency and temporal gradient show a smaller influence compared to it. As the pulse amplitude increases, the turbine work is reported to improve up to 9.4%. Smaller variations are otherwise observed for the frequency and temporal gradient analysis. With a 10% increase of the pulse frequency, the turbine work is registered to improve by 5.0%, while the same percentage reduction of the temporal gradient leads to an increase of the turbine work equal to 3.6%.

Design of Anfis based pacemaker controller having improved transient response and its FPGA implementation

This paper presents the design and hardware implementation of an Adaptive Neuro-Fuzzy Inference System (Anfis) based controller for a cardiac pacemaker. Cardiac pacemakers are used for the patients who suffer from bradycardia: heart rate below 60 beats per minute, and pacemaker controllers are required to provide stability between the heart rate and the desired preset profile of the pacemaker. The proposed work aims to design a controller to improve the parameters of cardiovascular system response in terms of stability, steady-state error, transients, etc. The settling time is the major constraint in the design of a pacemaker controller; ideally, it is required to have no delay between the need of heartbeat and the stimulus delivery by the pacemaker. The combination of neural network with fuzzy logic makes the proposed controller more effective concerning ‘learning’ and speed. The membership function of fuzzy logic plays an important role in controller design; the optimal number of membership functions are selected, so as to avoid the controller design complexities. In the proposed scheme, we have designed a pacemaker controller with fifteen membership functions on MATLAB/Simulink. To validate the theoretical results of the proposed methodology, the proposed controller is implemented on the Artix 7 Field Programmable Gate Array (FPGA) board. The simulation results show that the control strategy of the proposed design is more suitable in terms of timing response and the hardware implementation shows that the proposed controller will consume less power. The settling time and the power consumption for the proposed pacemaker controller are found to be 1.3813sec and 8.04 mW respectively.

Modified brain storming optimization technique for transient stability improvement of SVC controller for a two machine system

Purpose Static VAR compensators (SVC) have been recognized to be one of the most important flexible AC transmission systems devices used for mitigating the low-frequency electrochemical oscillations occurring in the system and for reactive power compensation, thereby improving the overall dynamic stability and efficiency of the system. The purpose of this paper is to optimize and dynamically tune the control parameters of the classical proportional integral and derivative (PID) controller of the SVC for a two-machine system by designing a new robust optimization technique. Design/methodology/approach The angular speed deviation between the two machines is used as an auxiliary signal to SVC for generation of the required damping output. To justify the efficacy of the system undertaken, a light load fault at time t = 1 s is projected to the system. The simulation is carried out in MATLAB/Simulink architecture. Findings The proposed technique helps in the enhancement of system efficiency, reliability and controllability and by effectively responding to the non-linearities taking place in a power grid network. The results obtained are indicative of the fact that the proposed modified brain storming optimization (MBSO) technique reduces system disturbances very quickly, increases the system response in terms of better rise time, settling time and peak overshoot and improves the efficiency of the system. Originality/value A detailed comparison of the MBSO technique is compared with the conventional brain storming optimization (BSO) and PID technique. Total harmonic distortion through fast Fourier transform is also compiled to prove that the values of the proposed MBSO method found out to be confined well within the prescribed IEEE-514 boundaries.

Response analysis of the nodes of pipe networks under seismic load.

Transient ground displacement (TGD) that is caused by earthquakes can damage underground pipes. This damage is especially critical for the joints, elbows and tees of the pipes which play an important role in the operation of a pipe network. In this study, a scale pipe network with both elbows and tees, as well as some components of the pipe network with only tees or elbows, has been investigated. The response of the nodes of a pipe network, when installed in non-uniform geology, was analyzed using the shaking table test and ABAQUS finite element simulation. This paper has firstly introduced the preparation of the test and the developed finite element model. Then the system response in terms of strain, the friction, the bending deformation, the node deformation amplification coefficient and the pipe-soil relative displacement along the pipe axis of the pipe network and two pipe network components have been analyzed explaining the correlation between these responses. Finally, the influence of elbows and tees on the pipe network was analyzed, and the conclusions that have been reached about how tees and elbows can change the response of a pipe network during an earthquake can provide theoretical support for the seismic design and layout of an underground pipe network.

Efficient non-stationary random vibration analysis of vehicle-bridge system based on an improved explicit time-domain method

Based on the recently developed explicit time-domain method (ETDM), this paper presents a new efficient computational framework for non-stationary random vibration analysis of the vehicle-bridge system (VBS) subjected to random track irregularity excitation. In this framework, the time-varying VBS equation is discretized using the time-stepping integration method, leading to an explicit expression for the stochastic system response in terms of the track irregularity excitation. Based on this expression, the response moments of the VBS can be easily evaluated in a direct way; the response probability density can also be obtained by using the Gaussian characteristic of the irregularity excitation. To further improve the computational efficiency, an efficient spectral representation-based formulation is proposed to calculate the excitation covariance matrix required in the analysis, which avoids tedious Fourier integrals required in the traditional ETDM. In the numerical application, the accuracy and efficiency of the proposed method are validated by the solutions obtained using the Monte Carlo and pseudo-excitation methods; the effects of several parameters on the stochastic responses of the VBS are investigated.

Using gestural emotions recognised through a neural network as input for an adaptive music system in virtual reality

In this article, a head gesture recognition system is developed in order to identify emotional inputs and provide them to an adaptive music system (LitSens) in virtual reality applications, improving virtual presence in the process. Two iterations of this system, both founded on neural networks, are presented: the first one is based on a multi-layer perceptron, whereas the second one consists of a hybrid one-dimensional convolutional neural network. In both cases, the system is able to recognise fear by analysing head gestures. Whereas the first implementation is quicker when recognising this emotion, the second one is slower, but much more accurate, which makes it a better option overall for soundtrack adaptation. An experiment is then detailed, aimed towards validating the behaviour of a gestural recogniser when detecting fear in players. The results achieved through this validation are generally positive, but evince the need for an improvement in terms of system responsiveness.

A novel identification procedure from ambient vibration data

Ambient vibration modal identification, also known as Operational Modal Analysis, aims to identify the modal properties of a structure based on vibration data collected when the structure is under its operating conditions, i.e., no initial excitation or known artificial excitation. This procedure for testing and/or monitoring historic buildings, is particularly attractive for civil engineers concerned with the safety of complex historic structures. However, since the external force is not recorded, the identification methods have to be more sophisticated and based on stochastic mechanics. In this context, this contribution will introduce an innovative ambient identification method based on applying the Hilbert Transform, to obtain the analytical representation of the system response in terms of the correlation function. In particular, it is worth stressing that the analytical signal is a complex representation of a time domain signal: the real part is the time domain signal itself, while the imaginary part is its Hilbert transform. A 3DOF numerical example will be presented to show the accuracy of the proposed procedure, and comparisons with data from other methods assess the reliability of the approach. Finally, the identification method will be extended to the real case study of the Chiaramonte Palace, a historic building located in Palermo and known as “Steri”.

First-Order Linear Mechatronics Model for Closed-Loop MEMS Disk Resonator Gyroscope.

In this paper, a first-order closed-loop mechatronics model of a micro-electromechanical system (MEMS) disk resonator gyroscope (DRG) with a configurable ASIC is established for closed-loop design and performance analysis. There are usually some nonlinear modules in the gyroscope mechatronics model, and it is difficult to design the closed-loop controllers using classical automatic control theory. An order-reduction method (ORM) based on the Laplace transform and inverse Laplace transform is proposed to linearize the nonlinear modules. The linearized model is proved to show good agreement with the original mechatronics model in terms of system response. The experimental verification was conducted to demonstrate the validation of this method.

An improved response function based stochastic meshless method for problems in elasto-statics

The current study proposes an improved response function (IRF) based stochastic element free Galerkin method (SEFGM) for the analysis of problems in elasto-statics, wherein Young’s modulus is modelled as a homogeneous random field with symmetric distribution characteristics. The proposed SEFGM approximates displacement as the sum of a deterministic part and a stochastic part. The stochastic part is modelled with the help of an IRF, which is a function of discretized set of random variables. Moving least square shape functions are employed to discretize the random field. Utilizing Taylor series expansions of stiffness matrix and force vector and IRF approximation of displacement, explicit expressions for system responses in terms of random variables are derived. Stochastic informations of system responses are evaluated by employing Monte Carlo Simulation (MCS) on the response function, which eliminates the need of construction and simulation of system matrices at each set of sample generation. 1D and 2D numerical examples in elasto-statics are solved using proposed method. Results are validated with those obtained by direct simulation of system of equations using MCS and also compared with other methods like second order perturbation and ad-hoc response function based SEFGM. Normalized computational times required for all the methods are also compared. It is found that the proposed method is computationally efficient and can produce accurate results even for higher coefficient of variation of input random fields.

A control method using adaptive setting of electronic expansion valve for water chiller systems equipped with variable speed compressors

Abstract Efficient control methods are essential for refrigeration systems that utilize variable speed compressors. In this paper, stability and performance of a water chiller system equipped with a variable speed compressor and an electronic expansion valve (EEV) were investigated. We focused on the system response in terms of both the degree of superheat (DS) and the temperature of evaporator water (product water) with three control methods. These methods are single control loop (SCL) with adaptive EEV opening, two-control loops (TCL) with adaptive DS setting, and constant DS setting. The SCL method takes into account the coupling effect between the compressor speed and the EEV opening. For the TCL method, the DS and the product water temperature are separately controlled. We tested a proportional fuzzy (PF) controller with the three methods in addition to conventional PI and PID controllers. The results showed that the application of appropriate control method may have a significant influence on the coefficient of performance (COP) and system stability rather than the type of controller. The operation with fixed superheat setting yields the lower COP compared to the SCL and the TCL method. In comparison to the PI and PID controllers, the PF controller reduces the fluctuation in the DS. The SCL method produces the maximum COP as well as good stability for both the DS and the product water temperature. Compared to the constant DS operation, the SCL method enhanced the COP by 27.5%, 18.3%, and 19.7% for the PF, PID, and PI controllers, respectively.

Performance enhancement of energy extraction capability for fuel cell implementations with improved Cuckoo search algorithm

This paper addresses an improved optimization method to enhance the energy extraction capability of fuel cell implementations. In this study, the proposed method called Dynamic Cuckoo Search Algorithm (DCSA) is tested in a stand-alone fuel cell in order to control the system power under dynamic temperature response. In the operational process, a fuel cell is connected to a load through a dc-dc boost converter, and DCSA is utilized to adjust the switching duration in dc-dc converter by using voltage, current and temperature parameters. In this way, it controls the output voltage to maximize power delivery capability at the demand-side and eliminates the drawback of conventional cuckoo search algorithm (CSA) which cannot change duty cycle under operating temperature variations. In this regard, DCSA shows a significant improvement in terms of system response and achieves a more efficient power extraction than the conventional CSA method. In order to demonstrate the system performance, the stand-alone fuel cell system is constructed in Simulink environment via a processor-in the-loop (PIL) based digital implementation and analyzed by using different optimization methods. In the analysis section, the results of the proposed method are compared with conventional methods (perturb&observe mppt, incremental conductance mppt, and particle swarm optimization). In this context, convergence speed and efficiency analysis for both methods verify that the DCSA gives original results compared to conventional methods.

From Uninterruptible Power Supply to resilient smart micro grid: The case of a battery storage at telecommunication station

Nowadays, resilient grids meet growing interest for their capability of supplying critical load even in case of power fault coming from grid disturbance and natural disasters. To do this, such grids involve redundant apparatus and predictive control schemes.For high value services, unexpected system unavailability is source of economic losses to the providers. Hence, beside the internal energy storage devices, such plants had better to have redundancy of energy sources (e.g. electrical grid and natural gas network) and tailored power flows control strategies still valid even in the case of energy shortage. On the other hand, distributed storage resources is attracting growing interest to support the power networks in terms of both resiliency and flexibility facing the impact of generation from the Renewable Energy Sources.In this work, a power supply system controller based on Artificial Intelligence was developed and simulated to wisely operate the storage resources to serve the ICT equipment as Uninterruptible Power Supply (above all in case of emergency) as fundamental mission. Secondly, the investigation assessed the capability, to offer ancillary services to the power network increasing its resiliency measured system response in terms of survival time during grid faults and restoration transient time to recover initial service level.

Temperature regulation for distillation process using self-tuning fuzzy plus PID controller

This paper presents a self-tuning fuzzy logic controller plus PID controller that applied for essential oil extraction process. The most popular technique in extraction essential oil is using steam distillation. This method is lack to the process requirement and also towards parameter change. In order to regulate the steam distillation at desired extraction condition, the controller needs to integrate to the plant. By using auto regressive model with external input (ARX) model structure, the temperature of steam was successfully modelled with best fit 98.42%. This model was successfully representing the system during controller simulation work. There are several controllers that demonstrated in this project which are self-tuning fuzzy PID controller (STFPID) and conventional PID. Both controller will compare their performance in terms of system response which are percent overshoot (%OS), settling time (Ts) and also rise time (Tr). As the result, the STFPID with seven membership function gives the best performance compared to PID controller.

Pid Controller for Thermal Control in Satellites

The paper gives the application of PID controller in satellite launching; it gives out the different technique which involves PID controller. It involves the temperature control (thermistor) in heater which is situated in the satellite. PID controller is implemented with the use of programmable logic controller. Using Ordinary control techniques, it is very difficult for controlling temperature; hence the purpose of proposed research is implementing PID controller design using programmable logic controller (PLC) in order to control the temperature and maintain the output in such a way that there is zero error between process variable and set point/desired output by closed loop operations in the satellite by avoiding the manual monitoring system. A thorough analysis using various PID parameters is presented in terms of system response. Performance of the controller is examined in terms of duty cycle, average current and power dissipation. Finally, a comparative analysis of PID controller for thermal control in satellite is presented

Asymmetric plucking bistable energy harvester: Modeling and experimental validation

Incorporation of plucking up-conversion and bistable energy harvesting techniques can be solutions to enhance energy harvested from large-amplitude impulsive-type events. This work proposes an asymmetric plucking-based bistable energy harvester with rotary structure and plectrum, to convert the impulsive excitation to plucking force that helps the harvester jump into the high-energy orbit. The bistable configuration is set to be asymmetric in order to achieve repeatable mechanical plucking condition, ensuring the feasibility and stability of the proposed system. Hertzian contact theory is employed to relate different oscillation modes with dynamic plucking force under variations of plucking velocity and overlap length. By considering the deformation and rotational angle of beam tip during vibration, geometrically dipole-dipole model is adopted to calculate the asymmetric magnetic force and study potential well in contrast to the symmetric configuration. With the fact that linear damping model often misses its physical essentials in bistable systems, nonlinear damping model is employed to account for the energy dissipation process. Experiments show qualitative agreement with simulation results in terms of system responses and power output under different velocities, overlap lengths and load resistances. Compared with plucking energy harvester without bi-stability, the proposed system is able to improve the power output by up to 22.9% for single plucking cycle and 29.8% for periodic plucking. Parametric studies based on nondimensionalization are further conducted to investigate the mechanisms that control the energy characteristics of the system, thus providing a foundation to develop an optimal plucking bistable energy harvester.

Aggregate effect on concrete cone capacity

Recently, a large experimental campaign was completed that attempted to establish a link between petrography of the coarse aggregate, the concrete material properties and the system response in terms of concrete cone capacity. The investigation focused on three normal strength concretes having different coarse aggregate types (quartz, limestone, basalt) but otherwise similar mix design. All specimens of each concrete were cast from the same batch, carefully cured following three sets of curing protocols, and systematically characterized. The investigation comprised aggregate and concrete characterization, and structural tests performed at two ages on cast-in headed stud anchors under tensile loading. The aggregate characterization included the determination of Los Angeles coefficient, hardness and Young’s modulus. In order to characterize the concretes, standard compression and indirect tension tests, were performed together with fracture tests. The experimentally obtained material and structural data finally served for the evaluation of current predictive models in terms of concrete compressive strength or concrete fracture properties as well as a correlation study. Aided by photogrammetric analysis, the concrete cone shape was determined for each individual test and analyzed to uncover possible dependencies on the coarse aggregate type.