mobile robots play an enormous role in different fields of daily life applications including military, safety, and logistic multi-tasking capabilities. A new approach is introduced to the market which is the 3 Mecanum...
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Demand response is expected to play a fundamental role in providing flexibility for balancing operations to the grid. On the other hand, the fast electrification of the transportation sector calls for new solutions to...
Demand response is expected to play a fundamental role in providing flexibility for balancing operations to the grid. On the other hand, the fast electrification of the transportation sector calls for new solutions to enforce safe and reliable grid operation. Here we consider an electric vehicle charging station that participates in demand response programs. The demand response program asks for a change of the charging station load profile in exchange for a monetary reward. A stochastic receding horizon scheme that exploits the charging flexibility is then designed to optimally coordinate vehicle charging. Numerical simulations show that the proposed approach ensures substantial cost reduction compared to simpler benchmarks while maintaining the computation time feasible for real-world applications.
Opinion dynamics is a popular process to model the evolution of group opinions, which provides technical support for public opinion-related decision issues. However, most existing works focus on studying the opinions ...
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ISBN:
(数字)9798331508760
ISBN:
(纸本)9798331508777
Opinion dynamics is a popular process to model the evolution of group opinions, which provides technical support for public opinion-related decision issues. However, most existing works focus on studying the opinions evolution in social networks while overlooking the influence of information networks. Besides, in social networks, the rules for filtering authoritative individuals only consider public authorities, failing to consider the individuals' heterogeneity. To tackle the above issues, we propose an opinion evolution model based on collaboration between information networks and social networks (ISOE). Specifically, we first update the individual's opinion by judging the quality of the information obtained by the individual in the information network; then, we filter the trusted neighbor set for the current individual by quantifying the attributes of the individual's authority and closeness and update the individual's opinion after comprehensive weighting analysis of the trusted neighbor set; finally, we conduct information exchange between the social and information networks with the inter-layer information transfer mechanism. The above three steps are repeated until the group opinions reach a steady state. Extensive experiments have been carried out to prove the performance superiority of our proposed model.
This paper introduces the Transient Predictor and describes how it can be used to estimate the Multistep Predictor, which can be applied to applications such as Data-Driven Predictive control (DDPC). The Transient Pre...
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ISBN:
(数字)9798350316339
ISBN:
(纸本)9798350316346
This paper introduces the Transient Predictor and describes how it can be used to estimate the Multistep Predictor, which can be applied to applications such as Data-Driven Predictive control (DDPC). The Transient Predictor has two desirable traits that differentiate it from other methods for estimating the Multistep Predictor, such as the standard Subspace Predictor method: 1) Causality-the Transient Predictor asserts a causal relationship between future inputs and future outputs; and 2) Bias-the Transient Predictor is a consistent predictor of future outputs. This paper provides an easy-toimplement algorithm for estimating the Transient Predictor and in turn the Multistep Predictor, and demonstrates its efficacy for DDPC. In experiments, we find that the Transient Predictorbased DDPC performs remarkably well with small lead-in data lengths, indicating that it is well-suited for tasks in which large amounts of data are not available. In addition, the Transient Predictor is not afflicted by the same bias as subspace-based methods when data is gathered in closed loop.
Batteries are a central component of many complex systems, including mobile devices, sensors, electric vehicles, etc. Keeping the battery working in normal conditions avoids dangerous hazards for the user or the syste...
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ISBN:
(数字)9798331528010
ISBN:
(纸本)9798331528027
Batteries are a central component of many complex systems, including mobile devices, sensors, electric vehicles, etc. Keeping the battery working in normal conditions avoids dangerous hazards for the user or the system itself and helps extend the device’s life. The battery temperature is one of the most delicate aspects of these devices since some dangerous scenarios, like thermal runaway, could occur due to variable conditions. This paper uses a battery model of an electric vehicle from the automotive area as a case study to simulate the thermal response to normal usage. Then, thermal fault scenarios are modeled within equivalent circuital device descriptions and analyzed regarding state-of-charge, temperature, and voltage output. The findings presented offer a valuable starting point for improving the design phase of the batteries in multiple fields by testing fault scenarios already during simulation.
Enriching the robot representation of the operational environment is a challenging task that aims at bridging the gap between low-level sensor readings and high-level semantic understanding. Having a rich representati...
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It has been revealed that in the conditions of small-scale production of discrete-analog filters on switched capacitors and ADC-drivers, it is most advisable to design high-speed operational amplifiers (OAs) based on ...
It has been revealed that in the conditions of small-scale production of discrete-analog filters on switched capacitors and ADC-drivers, it is most advisable to design high-speed operational amplifiers (OAs) based on the CBJT technological route and the MH2XA031 array chip, which allows operation in conditions of low temperatures and exposure to radiation. It has been established that most commercially produced $O A s$ provide an average value of the slew rate (SR, up to $200 \div 300 \mathrm{~V} / \mu \mathrm{s}$). This is largely due to the limitations of the technologies used, and most importantly, to the irrational design of circuits. We study the maximum performance parameters of a CBJT OA with one integrating capacitor, which ensures the stability of the $O A$, and a differentiating transient correction circuit, which is implemented by connecting additional small capacitors to the original circuit. In this case, the $S R$ of the $O A$ increases by more than 500 times (up to $4000 \mathrm{~V} / \mu \mathrm{s}$).
In a recent paper it has been shown that the existence, for a MIMO nonlinear system, of normal forms with a special structure that proves to be useful in the design of feedback laws is implied by an assumption introdu...
In a recent paper it has been shown that the existence, for a MIMO nonlinear system, of normal forms with a special structure that proves to be useful in the design of feedback laws is implied by an assumption introduced a long time ago by Hirschorn in his work on systems invertibility. In this paper, we provide an alternative viewpoint and prove that a necessary and sufficient condition for the existence of such kind of normal forms can be identified in a special feature of the so-called maximal controlled invariant distribution algorithm.
—The computing continuum, a novel paradigm that extends beyond the current silos of cloud and edge computing, can enable the seamless and dynamic deployment of applications across diverse infrastructures. By utilizin...
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This paper presents a novel methodology for closed-loop system identification of unstable nonlinear systems using the Koopman operator with Extended Dynamic Mode Decomposition with control (EDMDc). The study highlight...
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ISBN:
(数字)9798331505400
ISBN:
(纸本)9798331505417
This paper presents a novel methodology for closed-loop system identification of unstable nonlinear systems using the Koopman operator with Extended Dynamic Mode Decomposition with control (EDMDc). The study highlights the critical role of selecting appropriate observable functions to develop accurate and efficient Koopman models. We demonstrate that the resulting Koopman models exhibit excellent fitting and validation properties and retain the stabilizability of the original nonlinear systems. These models are verified through time and frequency responses under closed-loop control using a Linear Quadratic Regulator (LQR), confirming their effectiveness. Future work will extend this framework to more complex systems and incorporate machine learning techniques to refine the selection of observable functions. This approach aims further to enhance the adaptability and robustness of Koopman-based control strategies.
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