A multiple-actuator fault isolation approach for overactuated electric vehicles (EVs) is designed with a minimal ℓ1-norm solution. As the numbers of driving motors and steering actuators increase ...beyond the number of controlled variables, an EV becomes an overactuated system, which exhibits actuator redundancy and enables the possibility of fault-tolerant control (FTC). On the other hand, an increase in the number of actuators also increases the possibility of simultaneously occurring multiple faults. To ensure EV reliability while driving, exact and fast fault isolation is required; however, the existing fault isolation methods demand high computational power or complicated procedures because the overactuated systems have many actuators, and the number of simultaneous fault occurrences is increased. The method proposed in this paper exploits the concept of sparsity. The underdetermined linear system is defined from the parity equation, and fault isolation is achieved by obtaining the sparsest nonzero component of the residuals from the minimal ℓ1-norm solution. Therefore, the locations of the faults can be obtained in a sequence, and only a consistently low computational load is required regardless of the isolated number of faults. The experimental results obtained with a scaled-down overactuated EV support the effectiveness of the proposed method, and a quantitative index of the sparsity condition for the target EV is discussed with a CarSim-connected MATLAB/Simulink simulation.
Blockchain is a technology that can ensure data integrity in a distributed network, and it is actively applied in various fields. Recently, blockchain is gaining attention due to combining with the ...Internet of Things (IoT) technology in the industrial field. Moreover, many researchers have proposed the Industrial IoT (IIoT) architecture with blockchain for data integrity and efficient management. The IIoT network consists of many heterogeneous devices (e.g., sensors, actuators, and programmable logic controllers (PLC)) with resources-constrained, and the availability of the network must be preferentially considered. Therefore, applying the existed blockchain technology is still challenging. There are some results about the technique of constructing blockchain lightly to solve this challenge. However, in these results, the analysis in perspective of cryptographic performance (area, throughput, and power consumption) has not been considered sufficiently, or only focused on the architecture of the blockchain network. The blockchain technology is based on cryptographic techniques, and the main part is a cryptographic hash function. Therefore, if we construct the blockchain-based IIoT architecture, we have to consider the performance of the hash function. Many lightweight hash functions have been proposed recently for the resource-constrained environment, and it can also be used to the blockchain. Therefore, in this paper, we analyze the considerations of lightweight blockchain for IIoT. Also, we conduct an analysis of lightweight hash for blockchain, and propose a new lightweight hash-based blockchain architecture that can change the hash algorithm used for mining adjust to network traffic.
The design of optimal input for fault identification in electric ground vehicles (EGVs) that use four independent in-wheel motors and four-wheel steering is presented in this paper. As the number of ...motors and steering actuators increases beyond the number of controlled variables, an EGV becomes an overactuated system, which provides actuator redundancy and the possibility of fault-tolerant control in the case of faults that occur in vehicle elements, such as its sensors and actuators. To ensure the reliability of the EGV during driving, online fault identification is needed, and its performance is directly dependent on the input signals. The input can be designed using the control allocation method, which is one approach to manage actuator redundancy. The proposed control allocation maximizes the sensitivity of the system output to parameters related to the fault position, while the system output is simultaneously controlled to maintain stability and follow the desired vehicle motions, even when faults occur. Simulations using the commercial software CarSim are performed to show the effectiveness of the proposed optimal input design method for fault identification; the performance of the system is compared with the conventional white noise perturbation input with equal power.
The experimental verification of the optimal input design method for fault identification is performed using a scaled-down overactuated electric vehicle. In the previous study, online fault ...identification was achieved by utilizing all the characteristics of an overactuated system (Park and Park, 2016). The perturbation input signal for the actuator fault identification can be applied to the faulty actuators to suppress most of the control performance loss. The scaled-down vehicle contains four independent driving motors and four independent wheel steering motors to model an extremely overactuated system. The lateral velocity and yaw rate are estimated using the state observer to realize feedback control, and the cornering stiffness is determined based on the estimated values. Experimental verification is performed using steady state cornering maneuvers with sudden actuator faults. The experiments with the scaled-down vehicle support the performance of the optimal input design method. When sensor noise and modeling uncertainties exist, the results from our method were much more precise than the results obtained using the conventional white noise perturbation input signal.
Although deep learning models have exhibited excellent performance in various domains, recent studies have discovered that they are highly vulnerable to adversarial attacks. In the audio domain, ...malicious audio examples generated by adversarial attacks can cause significant performance degradation and system malfunctions, resulting in security and safety concerns. However, compared to recent developments in the audio domain, the properties of the adversarial audio examples and defenses against them still remain largely unexplored. In this study, to provide a deeper understanding of the adversarial robustness in the audio domain, we first investigate traditional and recent feature extractions in terms of adversarial attacks. We show that adversarial audio examples generated from different feature extractions exhibit different noise patterns, and thus can be distinguished by a simple classifier. Based on the observation, we extend existing adversarial detection methods by proposing a new detection method that detects adversarial audio examples using an ensemble of diverse feature extractions. By combining the frequency and self-supervised feature representations, the proposed method provides a high detection rate against both white-box and black-box adversarial attacks. Our empirical results demonstrate the effectiveness of the proposed method in speech command classification and speaker recognition.
A novel design of a magnetic levitation (maglev) ropeless elevator for semiconductor wafer vertical transport is newly presented. To satisfy high cleanliness during vertical transport of the wafer, ...linear motor lifting and maglev guiding are desirable instead of the conventional rope lifting and wheel-based guiding method. Owing to the physically noncontact maglev guiding, particle-free and high-speed operation can be achieved with remarkable ride quality. In this paper, practical challenges for wafer transport, such as the eccentricity of the mass center from the actuating axis, severe acceleration/deceleration conditions as well as periodic large disturbances from normal forces of the linear motor, resonance of the elevator, and manufacturing tolerance of the guide rail, are further considered to satisfy the ride performance in wafer transport by designing a robust feedback controller with a loop shaping technique. A full-scale maglev ropeless elevator was constructed to experimentally validate the effectiveness of the proposed method. The experimental results demonstrated excellent magnetic levitation guiding performance in 5 degrees of freedom, with a maximum airgap fluctuation of 227 μm under harsh lifting conditions ( V max = 2600 mm/s).
Magnetic levitation can reduce particulate contamination that occurs during wafer transportation in the semiconductor manufacturing process. This technology radically eliminates contact between the ...wafer and the transport system, reducing friction, wear, and particle generation. Therefore, it is suitable for achieving high cleanliness in the ultra-fine line-width semiconductor production process and solving the need for particle removal in a vacuum environment. In this study, the roller and linear motion guide components of the wafer transfer system were replaced with a magnetic levitation module, and a robot arm was installed on top to transport a single wafer. A posture controller and a current controller were designed, and test equipment simulating the wafer transfer system was also manufactured and tested. Regarding mover and system identification, a sine sweep test was performed on the motion axis of the five degrees of freedom. Through the obtained system identification, it was possible to design the posture controller more precisely. Moreover, through levitation in standstill experiments and high-speed operation experiments, the wafer transport system can be used to verify dust-free high-speed transport and accurate positioning performance.
•FePc/SWNT heterojunction nanowires are prepared via a self-assembly approach.•FePc/SWNT performs much better than Pt/C in the ORR in alkaline media.•DFT and experimental results are combined to ...understand the ORR at FePc/SWNT.•The O2–FePc interaction is facilitated with fast electron transfer to the surface.
A self-assembly approach to preparing iron phthalocyanine/single-walled carbon nanotube (FePc/SWNT) heterojunction nanowires as a new oxygen reduction reaction (ORR) electrocatalyst has been developed by virtue of water-adjusted dispersing in 1-cyclohexyl-pyrrolidone (CHP) of the two components. The FePc/SWNT nanowires have a higher Fermi level compared to pure FePc (d-band center, DFT=−0.69eV versus −0.87eV, respectively). Consequently, an efficient channel for transferring electron to the FePc surface is readily created, facilitating the interaction between FePc and oxygen, so enhancing the ORR kinetics. This heterojunction-determined activity in ORR illustrates a new stratagem to preparing non-noble ORR electrocatalysts of significant importance in constructing real-world fuel cells.
•Speech classification systems are vulnerable to adversarial attacks.•Transferability of audio adversarial examples is related to noise sensitivity.•A new transferable adversarial attack is developed ...based on noise injection.•Proposed method outperforms other adversarial attacks in terms of transferability.
Despite the success of deep neural networks, the existence of adversarial attacks has revealed the vulnerability of neural networks in terms of security. Adversarial attacks add subtle noise to the original example, resulting in a false prediction. Although adversarial attacks have been mainly studied in the image domain, a recent line of research has discovered that speech classification systems are also exposed to adversarial attacks. By adding inaudible noise, an adversary can deceive speech classification systems and cause fatal issues in various applications, such as speaker identification and command recognition tasks. However, research on the transferability of audio adversarial examples is still limited. Thus, in this study, we first investigate the transferability of audio adversarial examples with different structures and conditions. Through extensive experiments, we discover that the transferability of audio adversarial examples is related to their noise sensitivity. Based on the analyses, we present a new adversarial attack called noise injected attack that generates highly transferable audio adversarial examples by injecting additive noise during the gradient ascent process. Our experimental results demonstrate that the proposed method outperforms other adversarial attacks in terms of transferability.
Mixtures of refractory oxides and transition metal oxides for yttrium–aluminum–manganese–iron–nickel–chromium–oxygen (Y–Al–Mn–Fe–Ni–Cr–O) systems were prepared using normal ceramic processes, for use ...as negative temperature coefficient (NTC) thermistors to measure a wide temperature range. Platinum–rhodium (Pt–Rh) alloy electrodes were inserted into the body during the formation process to increase the reliability at high temperatures and decrease the contact resistance. The properties of the thermistors were analyzed by X-ray diffraction (XRD), scanning electron microscopy (SEM), and resistance measurements. The shrinkage rate, grain size, and density of the specimens doped with Cr2O3 were higher than those of non-doped specimens. The crystallinity of the grains decreased with the addition of 0.006mol of Cr2O3. The grain size increased with Cr2O3. The resistance behaviors were similar for the two specimens, but the values were higher with the Cr2O3. The B constant value (the coefficient of temperature sensitivity) was 3636K for the non-doped specimen and 3876K for the specimen doped with 0.006mol of Cr2O3 across a temperature range of 0–600°C. The specimens exhibited a linear relationship between their electrical resistance and reciprocal temperature over a wide temperature range, indicating NTC thermistor characteristics. The mixtures of refractory oxides and transition metal oxides extended the measurement range from 0°C to 600°C, and the addition of Cr2O3 increased the resistance and the B constant in the doped sample.
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