Special Issue on Selected Papers from IEEE ICKII 2018

1. Introduction

Electronic Engineering and Design Innovations are both academic and practical engineering fields that involve systematic technological materialization through scientific principles and engineering designs. Technological innovation via Electronic Engineering includes electrical circuits and devices, computer science and engineering, communications and information processing, and electrical engineering communications. The Special Issue on “Selected Papers from IEEE ICKII 2018” was expected to select excellent papers presented at the International Conference on Knowledge Innovation and Invention 2018 (IEEE ICKII 2018) on the topics of electronics and its applications. This conference was held on Jeju Island, South Korea, 23–27 July, 2018, and it provided a unified communication platform for researchers from all of the world. The main goal of this Special Issue on “Selected Papers from IEEE ICKII 2018” is to discover new scientific knowledge relevant to the topic of electronics and its applications.

2. The Topic of Electronics and Its Applications

This special issue selected 5 excellent papers from 120 papers presented at IEEE ICKII 2018. The published papers are introduced as follows:

Chang et al. reported on “Robust Stable Control Design for AC Power Supply Applications” [1] and proposed an improved feedback algorithm by binary particle swarm optimization (BPSO)-based nonsingular terminal sliding mode control (NTSMC) for DC–AC converters. The NTSMC can create limited system state convergence time and allow singularity avoidance. The BPSO is capable of finding the global best solution in real-world applications, thus optimizing NTSMC parameters during digital implementation. The association of NTSMC and BPSO extends the design of the classical terminal sliding mode to converge to non-singular points more quickly and introduce optimal methodology to avoid falling into local extremum and low convergence precision. Simulation results show that the improved technique can achieve low total harmonic distortion (THD) and fast transients with both plant parameter variations and sudden step load changes. Experimental results of a DC–AC converter prototype controlled by an algorithm based on digital signal processing have been shown to confirm mathematical analysis and enhanced performance under transient and steady-state load conditions. Since the improved DC–AC converter system has significant advantages in tracking accuracy and solution quality over classical terminal sliding mode DC–AC converter systems, this paper will be applicable to designers of relevant robust control and optimal control techniques.

Jiang et al. reported on “A Mixed Deep Recurrent Neural Network for MEMS Gyroscope Noise Suppressing” [2] to improve the navigation accuracy of inertial navigation systems, where one effective approach is to model the raw signal noise and suppress it. Commonly, an inertial measurement unit is composed of three gyroscopes and three accelerometers, and among them, the gyroscopes play an important role in the accuracy of the inertial navigation system’s navigation solutions. Motivated by this problem, in this paper, an advanced deep recurrent neural network was employed and evaluated in noise modeling of a micromechanics system gyroscope. Specifically, a deep long short-term memory recurrent neural network and a deep-gated recurrent unit–recurrent neural network were combined together to construct a two-layer recurrent neural network for noise modeling. In this method, the gyroscope data were treated as a time series, and a real dataset from a micromechanics system inertial measurement unit was employed in the experiments. The results showed that, compared to the two-layer long short-term memory, the three-axis attitude errors of the mixed long short-term memory–gated recurrent unit decreased by 7.8%, 20.0%, and 5.1%. When compared with the two-layer gated recurrent unit, the proposed method showed 15.9%, 14.3%, and 10.5% improvement. These results supported a positive conclusion on the performance of the designed method, specifically, the mixed deep recurrent neural networks outperformed the two-layer gated recurrent unit and the two-layer long short-term memory recurrent neural networks.

Wang et al. reported on “Operational Improvement of Interior Permanent Magnet Synchronous Motor Using Fuzzy Field-Weakening Control” [3] and proposed that the fuzzy control design of maximum torque per ampere (MTPA) and maximum torque per voltage (MTPV) for the interior permanent magnet synchronous motor (IPMSM) control system is capable of reducing computation burden, improving torque output, and widening the speed range. In the entire motor speed range, three control methods, i.e., the MTPA, flux weakening, and MTPV methods may be applied depending on current and voltage statuses. The simulation using MATLAB/Simulink is first conducted and then in order to speed up the development, hardware-in-the-loop (HIL) is adopted to verify the effectiveness of the proposed fuzzy MTPA and MTPV control for the IPMSM system.

Zhang et al. reported on “Hardware Implementation for an Improved Full-Pixel Search Algorithm Based on Normalized Cross Correlation Method” [4] to propose an improved full pixel search algorithm based on the normalized cross correlation (NCC) method considering hardware implementation. According to the field programmable gate array (FPGA) simulation results, the speed of hardware design proposed in this paper is 2000 times faster than that of software in single-point matching, and 600 times faster than software in multi-point matching. The speed of the presented algorithm shows an increasing trend with the increase of the template size when performing multipoint matching.

Lee et al. reported on “Design and Realization of a Compact High-Frequency Band-Pass Filter with Low Insertion Loss Based on a Combination of a Circular-Shaped Spiral Inductor, Spiral Capacitor and Interdigital Capacitor” [5] to propose bandpass filter (BPF) is connecting an interdigital and a spiral capacitor in series between the two symmetrical halves of a circular intertwined spiral inductor. For the mass production of devices, and to achieve a higher accuracy and a better performance compared with other passive technologies, we used integrated passive device (IPD) technology. IPD has been widely used to realize compact BPFs and achieve the abovementioned. The center frequency of the proposed BPF is 1.96 GHz, and the return loss, insertion loss, and transmission zero are 26.77 dB, 0.27 dB, and 38.12 dB, respectively. The overall dimensions of BPFs manufactured using IPD technology are 984 × 800 μm², which is advantageous for miniaturization and integration.