Control in the field (control strategies used in fieldbus field devices) provides increased flexibility and cost efficiency, as well as improved process integrity in industrial plant operations. Despite the benefits listed above, communication delays caused by FOUNDATION™ the most typical issues encountered while adopting fieldbus technology are fieldbus networks and control loops. Using particle swarm optimization, this work proposes an effective tuning solution for cascade control strategies implemented in fieldbus field devices. The proposed optimal tuning approach is compared to the Ziegler-Nichols tuning method using a level-flow cascade control plant model in the Delt V distributed control system. Furthermore, experimental results showed that the proposed tuning strategy improved control loop performance.
This study aims to evaluate the factors influencing customers” intention to use digital banking services. The main theoretical framework is based on the Technology Acceptance Model (TAM)., extended with social image and perceived self-efficacy. This study is able to gather data from 230 respondents using online surveys., which are then subjected to structural equation modeling (SEM) analysis in SMART PLS. The result shows that attitude toward using and perceived self-efficacy are the main drivers of customers” intention to use digital banking. In contrast., perceived usefulness is found to have no significant impact on intention to use. Perceived usefulness., perceived ease of use., and social image are found to positively impact attitude toward using. Lastly., perceived usefulness is found to be influenced by perceived ease of use. Despite its limitations., this study contributes academically to the technology acceptance research through the extension of TAM in the digital banking context and provides managerial insights for future digital banking development in Indonesia.
This paper proposed a simple electronic load controller (ELCr) for a pico hydropower system. The electronic load controller is used to regulate the output power of hydropower generators, thereby maintaining the output voltage and frequency at desired values. Conventionally, the diode bridge rectifier with IGBT ELCr is used in pico hydropower. However, it injects harmonics into the system. The phase regulation technique also suffers from harmonics and is limited by the timing accuracy of the trigger pulse. Hence a single-switch bidirectional AC chopper (SSBAC) - based ELCr is proposed. This SSBAC ELCr uses a single IGBT per phase to switch voltage and current bi-directionally to the dump load. From the simulation studies, the SSBAC ELCr produced excellent voltage regulation with low order harmonics at a value of 3.21%. The SSBAC ELCr maintained the generator's torque constant and provided a balanced distribution of power in each phase.
A piezoelectric energy harvesting (PEH) circuit with a passive rectifier lack in efficiency and performance. The performance and potential of piezoelectric energy-harvesting devices depend strongly on the power conditioning circuit as the circuits are essential for managing and controlling energy flows in these energy collecting devices. In order to overcome this situation, the parallel synchronized switch harvesting on inductor (P-SSHI) and the general model of synchronized multiple bias-flip (SMBF) which are the recent implementation of parallel synchronized triple bias-flip (P-S3BF) and parallel synchronized septuple bias-flip (P-S7BF) are used for further enhancing the PEH performance. In addition, active rectifiers presented distinguished benefits over passive rectifiers, such as the ability to analyze regulation, dynamic response to load changes, output voltage ripple, input current, total harmonic distortion (THD), power factor correction, and wave factor. Furthermore, by using an active rectifier the output voltage can be boosted higher. Thus, it is more efficient than a lower voltage since it experiences less energy loss from resistance. This research investigates the several high efficiency AC-DC active rectifiers as interface circuit plays a crucial role in the energy harvesting capability enhancement in PEH systems. The research methodology is carried out on a piezoelectric structure under the same base circuit with a different type of power conditioning circuit applied to the main circuit using the LTspice software. In conclusion, the input voltage for each different active rectifier circuit were set at 3–5 V and the frequency is set based on the input voltage of the circuit. Based on the results, the P-S7BF shows the higher efficiency with voltage output will have the most efficiency with the estimated voltage output reaching up to 13 V with a net harvesting power of up to 80-90% follow up by the P-S3BF and P-SSHI. There are several recommendations to improve active circuit by investigation the impact of load variation on the efficiency, such as different loads may require different rectification techniques and control strategies to achieve high efficiency.
In recent trends, machine learning in EDA tool features is a hotcake. It covers floorplanning, placement optimization, congestion optimization, routing optimization, as well as design space optimization with artificial intelligence capability. With machine learning capability, the design is expected to converge faster with a higher quality of result in timing, power, and routing utilization. This paper will review the current artificial intelligent state of the arts, in chip design optimization. The paper will discuss the type of artificial model deployed in the field as well as the preferred model in the field. The evaluation is done on commercially supported artificial intelligent features in the EDA tool, at various implementation stages, including stability tests of the commercial artificial intelligent features. From the finding, machine learning does improves the predictability of quality of result however, there is a need for forward looking controller to ensure the optimum quality of result from combined machine learning features. Hopefully, the finding of existing artificial intelligent features supported and limitations will benefit the design community.
