Electronics, Volume 8, Issue 5 (May 2019) – 125 articles

An accelerometer-based gyro drift compensation approach in a dual-axial stabilization platform is introduced in this paper. The stabilization platform consists of platform framework, drive motor, gyro and accelerometer module and contorl board. Gyro is an angular rate detecting element to achieve angular rate and rotation angle of the dynamic platform system. However, the platform system has an unstable factor because of the drift of gyro. The main contribution of this paper is to implement a convenient gyro drift compensation approach by using the accelerometer. In contrast to a kalman filtering method, this approach is simpler and practical due to the high-precision characteristic of the accelerometer. Data filtering algorithm and limit of threshold setting of total acceleration values are applied in this approach. The validity and feasibility of the proposed approach are evaluated by four tests under various conditions. Full article

A broadband receiver front-end with low noise figure and flat conversion gain response is presented in this paper. The receiver front-end is a part of the broadband spectrum sensing receiver and processes 30–40 GHz of broad input spectrum followed by down-conversion to DC-10 GHz of IF signal. The proposed work is comprised of a low noise amplifier (LNA), on-chip passive Balun, down conversion mixer, and output buffer. To achieve front-end target specification over 10 GHz input bandwidth, the stagger-tuned LNA is employed and the down conversion mixer is loaded with a 3rd-order LC ladder low pass filter. The prototype chip was implemented in 45 nm CMOS technology. The chip achieves 10.3–16.5 dB conversion gain, 5.9 dB integrated NF, and −11 dBm IIP3 from 30 to 40 GHz. The chip is realized within 0.42 mm ${}^2$ and consumes 96 mW from a 1.2 V supply. Full article

The k-nearest neighbor (kNN) rule is one of the most popular classification algorithms applied in many fields because it is very simple to understand and easy to design. However, one of the major problems encountered in using the kNN rule is that all of the training samples are considered equally important in the assignment of the class label to the query pattern. In this paper, an evidential editing version of the kNN rule is developed within the framework of belief function theory. The proposal is composed of two procedures. An evidential editing procedure is first proposed to reassign the original training samples with new labels represented by an evidential membership structure, which provides a general representation model regarding the class membership of the training samples. After editing, a classification procedure specifically designed for evidently edited training samples is developed in the belief function framework to handle the more general situation in which the edited training samples are assigned dependent evidential labels. Three synthetic datasets and six real datasets collected from various fields were used to evaluate the performance of the proposed method. The reported results show that the proposal achieves better performance than other considered kNN-based methods, especially for datasets with high imprecision ratios. Full article

In this paper, the dynamics-based high-performance robot motion control technology has been mainly studied, and the overall structure is controlled via dynamics forward, given the nonlinearity, strong coupling and time-variability of robots. Considering the unavailability of precise robot model parameters and the uncertain disturbance in real operation, we put forward an active disturbance rejection control (ADRC) strategy based on dynamic feedforward, aiming to improve the control robustness and combining the simple structure, strong anti- disturbance ability, and no restriction from the control model of ADRC. Given the multi-joint coupling of robots, controlled decoupling is conducted by using dynamic characteristics. The ADRC cascade control structure and algorithm based on dynamic feedforward have been studied and the closed-loop stability of the system is investigated by analyzing the system dynamic linearization compensation and the anti-disturbance ability of the extended state observer. Experiments have shown the new strategy is more robust over uncertain disturbance than the conventional proportional-integral-derivative control strategy. Full article

As cloud service providers are not completely trusted, people are increasingly concerned about security issues such as data confidentiality and user privacy. In many existing schemes, the private key generator (PKG) generates a full private key for each user, which means that the PKG can forge a valid signature or decrypt the ciphertext. To address the issue, we first present a novel certificateless hybrid signcryption (CL-HSC) scheme without pairing, in which the PKG only generates the partial private keys for users. It is provably secure under the Elliptic Curve Computational Diffie-Hellman (EC-CDH) assumption in the random oracle model. Then, we propose a key derivation method by which the data owner only needs to maintain the master key to get rid of the complex key management. By combining our proposed CL-HSC scheme and the key derivation method, we present a secure and efficient data-sharing scheme for cloud storage, which can resist collusion attacks, spoofing attacks, and replay attacks and makes user revocation easier. In addition, compared with some existing schemes, our scheme has a lower computational complexity. Full article

A high-speed, low-power divide-by-3/4 prescaler based on an extended true single-phase clock D-flip flop (E-TSPC DFF) is presented. We added two more transistors and a mode control signal to the conventional E-TSPC based divide-by-4 divider to achieve the function of the divide-by-3/4 dual modulus frequency divider. The designed divide-by-3/4 achieved higher speed and lower power operation with mode control compared with the conventional ones. The prescaler was comprised of sixteen transistors and integrates an inverter in the second DFF to provide output directly. The power consumption was minimized due to the reduced number of stages and transistors. In addition, the prescaler operating speed was also improved due to a reduced critical path. We compared the simulation results with conventional E-TSPC based divide-by-3/4 dividers in the same process, where the figure-of-merit (FoM) of the proposed divider was 17.4–75.5% better than conventional ones. We have also fabricated the prescaler in a 40 nm complementary metal oxide semiconductor (CMOS) process. The measured highest operating frequency was 9 GHz with 0.303 mW power consumption under 1.35 V power supply, which agrees with the simulation well. The measurement results demonstrate that the proposed divider achieves high-speed and low-power operation. Full article

This paper explores a set of learned convolutional kernels which we call Jet Features. Jet Features are efficient to compute in software, easy to implement in hardware and perform well on visual inspection tasks. Because Jet Features can be learned, they can be used in machine learning algorithms. Using Jet Features, we make significant improvements on our previous work, the Evolution Constructed Features (ECO Features) algorithm. Not only do we gain a 3.7× speedup in software without loosing any accuracy on the CIFAR-10 and MNIST datasets, but Jet Features also allow us to implement the algorithm in an FPGA using only a fraction of its resources. We hope to apply the benefits of Jet Features to Convolutional Neural Networks in the future. Full article

We investigate the problem of source detection in information spreading throughout a densely-connected network. Previous works have been developed mostly for tree networks or applied the tree-network results to non-tree networks assuming that the infection occurs in the breadth first manner. However, these approaches result in low detection performance in densely-connected networks, since there is a substantial number of nodes that are infected through the non-shortest path. In this work, we take a two-step approach to the source detection problem in densely-connected networks. By introducing the concept of detour nodes, we first sample trees that the infection process likely follows and effectively compare the probability of the sampled trees. Our solution has low complexity of $O(n^{2}logn)$ , where n denotes the number of infected nodes, and thus can be applied to large-scale networks. Through extensive simulations including practical networks of the Internet autonomous system and power grid, we evaluate our solution in comparison with two well-known previous schemes and show that it achieves the best performance in densely-connected networks. Full article

As the core of electronic system, the switched-mode power supply (SMPS) will lead to serious accidents and catastrophes if it suddenly fails. According to the related research, the monitoring of ripple can acquire the health degree of SMPS indirectly. To realize low-cost, high-precision, and automatic ripple measurement, this paper proposes a new ripple voltage (peak-to-peak value) measuring scheme, utilizing a DAC and two high-speed comparators. Within this scheme, the DC component of SMPS output is blocked by a high-pass filter (HPF). Then, the filtered signal and the reference voltage from a DAC together compose the input of a high-speed comparator. Finally, output pulses of the comparator are captured by a microcontroller unit (MCU), which readjusts the output of the DAC by calculation, and this process is repeated until the DAC output is exactly equal to the peak (or valley) value of ripple. Moreover, in order to accelerate the measurement process, a peak estimation method is specially designed to calculate the output ripple peak (or valley) value of buck topology through merely two measurements. Then the binary search method is utilized to obtain a more exact value on the basis of estimative results. Additionally, an analysis of the measurement error of this ripple measurement system is executed, which shows that the theoretical error is less than 0.5% where the ripple value is larger than 500 mV. Furthermore, appropriate components are selected, and a prototype is manufactured to verify the validity of the proposed theory. Full article

The internet protocol television service (IPTV) has become a key product for internet service providers (ISP), offering several benefits to both ISP and end-users. Because packet networks based on internet protocol have not been prepared for time-sensitive services, such as voice or video, packet networks have had to adopt several mechanisms to secure minimal transmission standards in the form of data stream prioritization. There are two commonly used approaches for video quality assessment. The first approach needs an original source for comparison (full-reference objective metrics), and the second one requires observers for subjective evaluation of video quality. Both approaches are impractical in real-time transmission because it is difficult to transform an objective score into a subjective quality perception, and on the other hand, subjective tests are not able to be performed immediately. Since many countries worldwide put IPTV on the same level as other broadcasting systems (e.g., terrestrial, cable, or satellite), IPTV services are subject to regulation by the national regulation authority. This results in the need to prepare service qualitative criteria and monitoring tools capable of measuring end-user satisfaction levels. Our proposed model combines the principles of both assessment approaches, which results in an effective monitoring solution. Therefore, the main contribution of the created system is to offer a monitoring tool able to analyze the features extracted from the video sequence and transmission system and promptly translate their impact into a subjective point of view. Full article

Content-addressable memory (CAM) is a type of associative memory, which returns the address of a given search input in one clock cycle. Many designs are available to emulate the CAM functionality inside the re-configurable hardware, field-programmable gate arrays (FPGAs), using static random-access memory (SRAM) and flip-flops. FPGA-based CAMs are becoming popular due to the rapid growth in software defined networks (SDNs), which uses CAM for packet classification. Emulated designs of CAM consume much dynamic power owing to a high amount of switching activity and computation involved in finding the address of the search key. In this paper, we present a power and resource efficient binary CAM architecture, Zi-CAM, which consumes less power and uses fewer resources than the available architectures of SRAM-based CAM on FPGAs. Zi-CAM consists of two main blocks. RAM block (RB) is activated when there is a sequence of repeating zeros in the input search word; otherwise, lookup tables (LUT) block (LB) is activated. Zi-CAM is implemented on Xilinx Virtex-6 FPGA for the size 64 × 36 which improved power consumption and hardware cost by 30 and 32%, respectively, compared to the available FPGA-based CAMs. Full article

Relay technology application becomes prevalent nowadays, as it can effectively extend the communication distance, especially for vehicular networks with a limited communication range. Combined with vehicular cloud (VC), transmission efficiency can be improved by offloading partial data. Hence, designing a vehicle relay algorithm and implementation embedded vehicle device is critical. In this paper, VC is considered to deal with the complexity computation in our proposed system model. Without a loss of generality, an end-to-end vehicle communication with one assisted vehicle is analyzed firstly on a transmission link based on VC. Here, the signal-to-noise ratio (SNR) on the receiving end and link outage probability is obtained to enhance the link reliability. The VC computing helps us further simplify computational complexity. Subsequently, an embedded vehicle-enabled device is designed to achieve the optimal path relay selection in realistic vehicular environments. In the functional device framework, we display an optimal path relay selection algorithm according to the link quality. Finally, the performance of the transmission link on the outage probability related with SNR is verified in the simulation results. Meanwhile, the effect of the relay gain is also analyzed. The application of a vehicle-enabled embedded device could improve the performance of vehicular networks. Full article

This paper proposes a control method to improve the energy efficiency and performance of cooling fans used for cooling. In Industry 4.0, a large number of digital data are used, and a large number of data centers are created to handle these data. These data centers consist of information technology (IT) equipment, power systems, and cooling systems. The cooling system is essential to prevent failure and malfunction of the IT equipment, which consumes a considerable amount of energy. This paper proposes a method to reduce the energy used in such cooling systems and to improve the temperature control performance. This paper proposes an fuzzy proportional integral(FPI) controller that controls the input value of the proportional integral(PI) controller by the fuzzy controller according to the operation state, a VFPI (Variable Fuzzy Proportional Integral) controller that adjusts the gain value of the fuzzy controller, and a variable fuzzy proportion integration-variable limit (VFPI-VL) controller that adjusts the limit value of the fuzzy controller’s output value. These controllers control the fan applied to the cooling system and compare the energy consumed and temperature control performance. When the PI controller consumes 100% of the power consumed, the FPI is 50.5%, the VFPI controller is 44.3%, and the VFPI-VL is 32.6%. The power consumption is greatly reduced. In addition, the VFPI-VL controller is the lowest in temperature variation, which improves the energy efficiency and performance of the cooling system using a fan. The methods presented in this paper can not only be applied to fans for cooling, but also to variable speed systems for various purposes and improvement of performance and efficiency can be expected. Full article

A novel quad-state coupled-line microstrip resonator is proposed for compact chipless radio frequency identification (RFID) tags. The proposed resonator can be reconfigured to present one of four possible states: 00, 01, 10, and 11, representing, no resonance, resonance at f₂, resonance at f₁, and resonance at both f₁ and f₂, respectively. The frequency span between f₂ and f₁ can be easily controlled, thereby reducing the required spectrum. Moreover, the proposed technique allows the storage of a large amount of data in a compact size to reduce the cost per bit. A multi-resonator prototype consisting of six resonators is designed, analyzed, and experimentally characterized. This prototype is implemented on the RT Duroid 5880 substrate with a dielectric constant of 2.2, loss tangent of 0.0009, and thickness of 0.79 mm. The designed configuration can be reconfigured for 4⁶ codes. Two complete the RFID tags, including the six resonators and two orthogonally polarized transmitting and receiving antennas, are implemented and tested. The first tag code is designed for all ones, 111111111111, and the second tag is designed as 101010101010 code. Experimental results show good agreement with the simulation. Full article

A novel and compact dual-polarized (DP) chipless radio-frequency identification (RFID) tag is presented in this paper. This tag can read both vertical and horizontal orientations within its frequency band, which improves the robustness and detection capability of the RFID system. The proposed tag makes use of the slot length variation encoding technique to improve the encoding capacity. This technique can duplicate the encoding capacity, thereby reducing the overall tag size by almost 50%. In particular, the proposed tag has an encoding capacity of 20 bits in the 3–8 GHz frequency band and achieves data density of around 15.15 bits/cm². Three prototypes are fabricated and tested outside an anechoic chamber. Furthermore, one tag is tested at different distances (10 cm, 30 cm, and 60 cm) from the reader and the measured results are compared. The simulated and measured results are in reasonable agreement, with acceptable shifts at some frequencies due to fabrication and experimental errors. Full article

Machine learning algorithms have been widely used to deal with a variety of practical problems such as computer vision and speech processing. But the performance of machine learning algorithms is primarily affected by their hyper-parameters, as without good hyper-parameter values the performance of these algorithms will be very poor. Unfortunately, for complex machine learning models like deep neural networks, it is very difficult to determine their hyper-parameters. Therefore, it is of great significance to develop an efficient algorithm for hyper-parameter automatic optimization. In this paper, a novel hyper-parameter optimization methodology is presented to combine the advantages of a Genetic Algorithm and Tabu Search to achieve the efficient search for hyper-parameters of learning algorithms. This method is defined as the Tabu_Genetic Algorithm. In order to verify the performance of the proposed algorithm, two sets of contrast experiments are conducted. The Tabu_Genetic Algorithm and other four methods are simultaneously used to search for good values of hyper-parameters of deep convolutional neural networks. Experimental results show that, compared to Random Search and Bayesian optimization methods, the proposed Tabu_Genetic Algorithm finds a better model in less time. Whether in a low-dimensional or high-dimensional space, the Tabu_Genetic Algorithm has better search capabilities as an effective method for finding the hyper-parameters of learning algorithms. The presented method in this paper provides a new solution for solving the hyper-parameters optimization problem of complex machine learning models, which will provide machine learning algorithms with better performance when solving practical problems. Full article

Community Networks have been around us for decades being initially deployed in the USA and Europe. They were designed by individuals to provide open and free “do it yourself” Internet access to other individuals in the same community and geographic area. In recent years, they have evolved as a viable solution to provide Internet access in developing countries and rural areas. Their social impact is measurable, as the community is provided with the right and opportunity of communication. Community networks combine wired and wireless links, and the nature of the wireless medium is unreliable. This poses several challenges to the routing protocol. For instance, Link-State routing protocols deal with End-to-End Quality tracking to select paths that maximize the delivery rate and minimize traffic congestion. In this work, we focused on End-to-End Quality prediction by means of time-series analysis to foresee which paths are more likely to change their quality. We show that it is possible to accurately predict End-to-End Quality with a small Mean Absolute Error in the routing layer of large-scale, distributed, and decentralized networks. In particular, we analyzed the path ETX behavior and properties to better identify the best prediction algorithm. We also analyzed the End-to-End Quality prediction accuracy some steps ahead in the future, as well as its dependency on the hour of the day. Besides, we quantified the computational cost of the prediction. Finally, we evaluated the impact of the usage for routing of our approach versus a simplified OLSR (ETX + Dijkstra) on an overloaded network. Full article

This paper presents a risk-constrained scheduling optimization model for a grid-connected hybrid microgrid including demand response (DR), electric vehicles (EVs), variable wind power generation and dispatchable generation units. The proposed model determines optimal scheduling of dispatchable units, interactions with the main grid as well as adjustable responsive loads and EVs demand to maximize the expected microgrid operator’s profit under different scenarios. The uncertainties of day-ahead (DA) market prices, wind power production and demands of customers and EVs are considered in this study. To address these uncertainties, conditional value-at-risk (CVaR) as a risk measurement tool is added to the optimization model to evaluate the risk of profit loss and to indicate decision attitudes in different conditions. The proposed method is finally applied to a typical hybrid microgrid with flexible demand-side resources and its applicability and effectives are verified over different working conditions with uncertainties. Full article

In cognitive electronic warfare, when a typical combat vehicle, such as an unmanned combat air vehicle (UCAV), uses radar sensors to explore an unknown space, the target-searching fails due to an inefficient servoing/tracking system. Thus, to solve this problem, we developed an autonomous reasoning search method that can generate efficient decision-making actions and guide the UCAV as early as possible to the target area. For high-dimensional continuous action space, the UCAV’s maneuvering strategies are subject to certain physical constraints. We first record the path histories of the UCAV as a sample set of supervised experiments and then construct a grid cell network using long short-term memory (LSTM) to generate a new displacement prediction to replace the target location estimation. Finally, we enable a variety of continuous-control-based deep reinforcement learning algorithms to output optimal/sub-optimal decision-making actions. All these tasks are performed in a three-dimensional target-searching simulator, i.e., the Explorer game. Please note that we use the behavior angle (BHA) for the first time as the main factor of the reward-shaping of the deep reinforcement learning framework and successfully make the trained UCAV achieve a 99.96% target destruction rate, i.e., the game win rate, in a 0.1 s operating cycle. Full article

Gallium nitride (GaN)-based vertical power Schottky barrier diode (SBD) has demonstrated outstanding features in high-frequency and high-power applications. This paper reviews recent progress on GaN-based vertical power SBDs, including the following sections. First, the benchmark for GaN vertical SBDs with different substrates (Si, sapphire, and GaN) are presented. Then, the latest progress in the edge terminal techniques are discussed. Finally, a typical fabrication flow of vertical GaN SBDs is also illustrated briefly. Full article

In this paper, a novel doping-less tunneling field-effect transistor with Si_0.6Ge_0.4 heterojunction (H-DLTFET) is proposed using TCAD simulation. Unlike conventional doping-less tunneling field-effect transistors (DLTFETs), in H-DLTFETs, germanium and Si_0.6Ge_0.4 are used as source and channel materials, respectively, to provide higher carrier mobility and smaller tunneling barrier width. The energy band and charge carrier tunneling efficiency of the tunneling junction become steeper and higher as a result of the Si_0.6Ge_0.4 heterojunction. In addition, the effects of the source work function, gate oxide dielectric thickness, and germanium content on the performance of the H-DLTFET are analyzed systematically, and the below optimal device parameters are obtained. The simulation results show that the performance parameters of the H-DLTFET, such as the on-state current, on/off current ratio, output current, subthreshold swing, total gate capacitance, cutoff frequency, and gain bandwidth (GBW) product when V_d = 1 V and V_g = 2 V, are better than those of conventional silicon-based DLTFETs. Therefore, the H-DLTFET has better potential for use in ultra-low power devices. Full article

Knowledge of the subsurface structure not only provides useful information on lunar geology, but it also can quantify the potential lunar resources for human beings. The dual-frequency lunar penetrating radar (LPR) aboard the Yutu rover offers a Special opportunity to understand the subsurface structure to a depth of several hundreds of meters using a low-frequency channel (channel 1), as well as layer near-surface stratigraphic structure of the regolith using high-frequency observations (channel 2). The channel 1 data of the LPR has a very low signal-to-noise ratio. However, the extraction of weak signals from the data represents a problem worth exploring. In this article, we propose a weak signal extraction method in view of local correlation to analyze the LPR CH-1 data, to facilitate a study of the lunar regolith structure. First, we build a pre-processing workflow to increase the signal-to-noise ratio (SNR). Second, we apply the K-L transform to separate the horizontal signal and then use the seislet transform (ST) to reserve the continuous signal. Then, the local correlation map is calculated using the two denoising results and a time–space dependent weighting operator is constructed to suppress the noise residuals. The weak signal after noise suppression may provide a new reference for subsequent data interpretation. Finally, in combination with the regional geology and previous research, we provide some speculative interpretations of the LPR CH-1 data. Full article

This paper presents a new frequency compensation approach for three-stage amplifiers driving a pF-to-nF capacitive load. Thanks to the cascode Miller compensation, the non-dominant complex pole frequency is extended effectively, and the physical size of the compensation capacitors is also reduced. A local Q-factor control (LQC) loop is introduced to alter the Q-factor adaptively when loading capacitance C_L varies significantly. This LQC loop decides how much damping current should be injected into the corresponding parasitic node to control the Q-factor of the complex-pole pair, which affects the frequency peak at the gain plot and the settling time of the proposed amplifier in the closed-loop step response. Additionally, a left-half-plane (LHP) zero is created to increase the phase margin and a feed-forward transconductance stage is paralleled to improve the slew rate (SR). Simulated in 0.13-µm CMOS technology, the amplifier is verified to handle a 4-pF-to-1.5-nF (375× drivability) capacitive load with at least 0.88-MHz gain-bandwidth (GBW) product and 42.3° phase margin (PM), while consuming 24.0-µW quiescent power at 1.0-V nominal supply voltage. Full article

The characteristic impedance of a power line is an important parameter in power line communication (PLC) technologies. This parameter is helpful for understanding power line impedance characteristics and achieving impedance matching. In this study, we focused on the characteristic impedance matrices (CIMs) of the medium-voltage (MV) cables. The calculation and characteristics of the CIMs were investigated with special consideration of the grounded shields and armors, which are often neglected in current research. The calculation results were validated through the experimental measurements. The results show that the MV underground cables with multiple grounding points have forward and backward CIMs, which are generally not equal unless the whole cable structure is longitudinally symmetrical. Then, the resonance phenomenon in the CIMs was analyzed. We found that the grounding of the shields and armors not only affected their own characteristic impedances but also those of the cores, and the resonance present in the CIMs should be of concern in the impedance matching of the PLC systems. Finally, the effects of the grounding resistances, cable lengths, grounding point numbers, and cable branch numbers on the CIMs of the MV underground cables were discussed through control experiments. Full article

Despite technical advances in efficiency, devices in standby continue to consume up to 16% of residential electricity. Finding practical, cost-effective reductions is difficult. While the per-unit power consumption has fallen, the number of units continuously drawing power continues to grow. This work reviews a family of technologies that can eliminate standby consumption in many types of electrical plug loads. It also investigates several solutions in detail and develops prototypes. First, burst mode and sleep transistors are established as building blocks for zero-standby solutions. This work then studies the application of two types of wake-up signals. The first is from an optical transmission, and is applicable to remote-controlled devices with a line-of-sight activation, such as set-top boxes, ceiling fans, and motorized curtains. The second is from a wake-up radio, and is applicable to any wireless products. No single technology will address all standby power situations; however, these emerging solutions appear to have broad applicability to save standby energy in miscellaneous plug loads. Full article

Intelligent utilization of resources and improved mission performance in an autonomous agent require consideration of cyber and physical resources. The allocation of these resources becomes more complex when the system expands from one agent to multiple agents, and the control shifts from centralized to decentralized. Consensus is a distributed algorithm that lets multiple agents agree on a shared value, but typically does not leverage mobility. We propose a coupled consensus control strategy that co-regulates computation, communication frequency, and connectivity of the agents to achieve faster convergence times at lower communication rates and computational costs. In this strategy, agents move towards a common location to increase connectivity. Simultaneously, the communication frequency is increased when the shared state error between an agent and its connected neighbors is high. When the shared state converges (i.e., consensus is reached), the agents withdraw to the initial positions and the communication frequency is decreased. Convergence properties of our algorithm are demonstrated under the proposed co-regulated control algorithm. We evaluated the proposed approach through a new set of cyber-physical, multi-agent metrics and demonstrated our approach in a simulation of unmanned aircraft systems measuring temperatures at multiple sites. The results demonstrate that, compared with fixed-rate and event-triggered consensus algorithms, our co-regulation scheme can achieve improved performance with fewer resources, while maintaining high reactivity to changes in the environment and system. Full article

This paper introduces new integrated analog cells fabricated in a C035 I3T25 0.35-μm ON Semiconductor process suitable for a modular design of advanced active elements with multiple terminals and controllable features. We developed and realized five analog cells on a single integrated circuit (IC), namely a voltage differencing differential buffer, a voltage multiplier with current output in full complementary metal–oxide–semiconductor (CMOS) form, a voltage multiplier with current output with a bipolar core, a current-controlled current conveyor of the second generation with four current outputs, and a single-input and single-output adjustable current amplifier. These cells (sub-blocks of the manufactured IC device), designed to operate in a bandwidth of up to tens of MHz, can be used as a construction set for building a variety of advanced active elements, offering up to four independently adjustable internal parameters. The performances of all individual cells were verified by extensive laboratory measurements, and the obtained results were compared to simulations in the Cadence IC6 tool. The definition and assembly of a newly specified advanced active element, namely a current-controlled voltage differencing current conveyor transconductance amplifier (CC-VDCCTA), is shown as an example of modular interconnection of the selected cells. This device was implemented in a newly synthesized topology of an electronically linearly tunable quadrature oscillator. Features of this active element were verified by simulations and experimental measurements. Full article

The purpose of this study was to develop a photovoltaic system that stores energy for use in direct current micro-grid systems or to supply electric power to consumers living in remote areas. If the photovoltaic module array is shaded, the signals of conventional maximum power point trackers (MPPT) may be trapped at the local power maxima. Therefore, this study developed a smart maximum power point tracker to track the maximum power point (MPP). The control method adopted a teaching learning based optimization (TLBO) algorithm. To adjust the energy flow direction of the direct current load terminal, this study proposed an energy accumulation and release strategy that used a high-boost/buck-ratio bidirectional converter to control the battery charge and discharge for energy accumulation and release. In addition, this study developed an inverter to convert direct current into alternating current for alternating current loads. Full article

This paper introduces the near-field detection system of an underwater robot based on the fish lateral line. Inspired by the perception mechanism of fish’s lateral line, the aim is to add near-field detection functionality to an underwater vehicle. To mimic the fish’s lateral line, an array of pressure sensors is developed and installed on the surface of the underwater vehicle. A vibrating sphere is simulated as an underwater pressure source, and the moving mechanism is built to drive the sphere to vibrate at a certain frequency near the lateral line. The calculation of the near-field pressure generated by the vibrating sphere is derived by linearizing the kinematics and dynamics conditions of the free surface wave equation. Structurally, the geometry shape of the detection system is printed by a 3D printer. The pressure data are sent to the computer and analyzed immediately to obtain information of the pressure source. Through the experiment, the variation law of the pressure is generated when the source vibrates near the body, and is consistent with the simulation results of the derived pressure calculation formula. It is found that the direction of the near-field pressure source can distinguished. The pressure amplitude of the sampled signals are extracted to be prepared for the next step to estimate the vertical distance between the center of the pressure source and the lateral line. Full article

This paper presents the fabrication and implementation of novel resistive sensors that were implemented for strain-sensing applications. Some of the critical factors for the development of resistive sensors are addressed in this paper, such as the cost of fabrication, the steps of the fabrication process which make it time-consuming to complete each prototype, and the inability to achieve optimised electrical and mechanical characteristics. The sensors were fabricated via magnetron sputtering of thin-film chromium and gold layer on the thin-film substrates at defined thicknesses. Sticky copper tapes were attached on the two sides of the sensor patches to form the electrodes. The operating principle of the fabricated sensors was based on the change in their responses with respect to the corresponding changes in their relative resistance as a function of the applied strain. The strain-induced characteristics of the patches were studied with different kinds of experiments, such as consecutive bending and pressure application. The sensors with 400 nm thickness of gold layer obtained a sensitivity of 0.0086 Ω/ppm for the pressure ranging between 0 and 400 kPa. The gauge factor of these sensors was between 4.9–6.6 for temperatures ranging between 25 °C and 55 °C. They were also used for tactile sensing to determine their potential as thin-film sensors for industrial applications, like in robotic and pressure-mapping applications. The results were promising in regards to the sensors’ controllable film thickness, easy operation, purity of the films and mechanically sound nature. These sensors can provide a podium to enhance the usage of resistive sensors on a higher scale to develop thin-film sensors for industrial applications. Full article