This paper presents an event-based asymptotic tracking control scheme designed for strict feedback systems with unknown control directions. The control directions directly determine how the controller acts on the syst...
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Nowadays, the optimally developed system design has been important with the improvement of the technology. The mathematical model approach with the proper controller design provides a more efficient system with its ou...
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Path planning and seeking is one of the most challenging and interesting problems in the field of artificial intelligence. In this article, we propose a new image-based path planning algorithm to overcome traditional ...
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Nowadays, gimbal systems have been a very critical role to obtain some important information related to live images photos and target detection in unmanned aerial vehicles. The most basic performance criterion of gimb...
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1 Quantum information technology Quantum information technology utilizes physical systems at the microscopic level, such as photon, atom, ion, and superconducting, to accomplish information-processing tasks that are i...
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1 Quantum information technology Quantum information technology utilizes physical systems at the microscopic level, such as photon, atom, ion, and superconducting, to accomplish information-processing tasks that are impossible for the classical macroscopic world. During the past decade, significant process has been achieved in the pursuit of quantum technology into practical applications,generating great research interest from various domains, with the potential to radically change our information infrastructure [1–3].
In the noisy intermediate-scale quantum (NISQ) era, the capabilities of variational quantum algorithms are greatly constrained due to a limited number of qubits and the shallow depth of quantum circuits. We may view t...
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In the noisy intermediate-scale quantum (NISQ) era, the capabilities of variational quantum algorithms are greatly constrained due to a limited number of qubits and the shallow depth of quantum circuits. We may view these variational quantum algorithms as weak learners in supervised learning. Ensemble methods are general approaches to combining weak learners to construct a strong one in machine learning. In this paper, by focusing on classification, we theoretically establish and numerically verify a learning guarantee for quantum adaptive boosting (AdaBoost). The supervised-learning risk bound describes how the prediction error of quantum AdaBoost on binary classification decreases as the number of boosting rounds and sample size increase. We further empirically demonstrate the advantages of quantum AdaBoost by focusing on a 4-class classification. The quantum AdaBoost not only outperforms several other ensemble methods, but in the presence of noise it can also surpass the ideally noiseless but unboosted primitive classifier after only a few boosting rounds. Our work indicates that in the current NISQ era, introducing appropriate ensemble methods is particularly valuable in improving the performance of quantum machine learning algorithms.
In this paper, we extend a constraint-based coverage control for robotic sensor networks based on control barrier functions (CBFs) for environments with known obstacles and different types of unmanned vehicles (UV). T...
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In this paper, we extend a constraint-based coverage control for robotic sensor networks based on control barrier functions (CBFs) for environments with known obstacles and different types of unmanned vehicles (UV). To this end, we use a sensing function that considers the vertices of the obstacles to compute the route and the distance regarding the UVs. This way, obstacle avoidance becomes intrinsic to the CBF ensuring the coverage performance. Moreover, we consider different obstacles and speeds for each type of UV. Finally, the proposed algorithm is illustrated with a heterogeneous fleet of UVs and obstacles in a simulated thermosolar power plant.
In this paper, the attack detection problem is investigated for a class of closed-loop systems subjected to unknownbutbounded noises in the presence of stealthy attacks. The measurement outputs from the sensors are qu...
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In this paper, the attack detection problem is investigated for a class of closed-loop systems subjected to unknownbutbounded noises in the presence of stealthy attacks. The measurement outputs from the sensors are quantized before transmission.A specific type of perfect stealthy attack, which meets certain rather stringent conditions, is taken into account. Such attacks could be injected by adversaries into both the sensor-toestimator and controller-to-actuator channels, with the aim of disrupting the normal data flow. For the purpose of defending against these perfect stealthy attacks, a novel scheme based on watermarks is developed. This scheme includes the injection of watermarks(applied to data prior to quantization) and the recovery of data(implemented before the data reaches the estimator).The watermark-based scheme is designed to be both timevarying and hidden from adversaries through incorporating a time-varying and bounded watermark signal. Subsequently, a watermark-based attack detection strategy is proposed which thoroughly considers the characteristics of perfect stealthy attacks,thereby ensuring that an alarm is activated upon the occurrence of such attacks. An example is provided to demonstrate the efficacy of the proposed mechanism for detecting attacks.
This work presents the architecture and development of the Serious Game (SG) Memô which is aimed at exercising the Short-Term Memory (STM) of children with Autism Spectrum Disorder (ASD). This serious game propos...
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The three single-phase combined (TSC) topology has been ruling the power converter industries for many years. In this research, TSC topology with Lithium Battery DC source is proposed for 400Hz Ground Power Unit (GPU)...
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