We propose a protocol for quantum adiabatic optimization, whereby an intermediary Hamiltonian that is diagonal in the computational basis is turned on and off during the interpolation. This ‘diagonal catalyst’ serve...
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Avoiding collisions with obstacles is of fundamental importance for the safe navigation of unmanned aerial vehicles (UAVs) and mobile robots. In this paper, we approach the avoidance problem by composing a scalable na...
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ISBN:
(纸本)9781538679012;9781538679265
Avoiding collisions with obstacles is of fundamental importance for the safe navigation of unmanned aerial vehicles (UAVs) and mobile robots. In this paper, we approach the avoidance problem by composing a scalable navigation strategy from multiple stochastic optimal controllers. We consider a scenario with a fixed speed Dubins vehicle, which is tasked to reach a waypoint while avoiding collisions with multiple moving obstacles. Obstacle moving directions are unknown, therefore, we use a random walk stochastic process model to anticipate that uncertainty in the design of navigation feedback control. The proposed navigation is based on a composition of minimum time stochastic optimal controllers. Each optimal controller is the solution to a minimum time problem to reach either the waypoint or a safe configuration with respect to an obstacle. The composition is based on the controller value functions and is scalable, i.e., it can deal with any number of obstacles. Our results are illustrated with a numerical simulation.
Quantum communication complexity studies the efficiency of information communication (that is, the minimum amount of communication required to achieve a certain task) using quantum states. One representative example i...
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In this work, we develop an importance sampling estimator by coupling the reduced-order model and the generative model in a problem setting of uncertainty quantification. The target is to estimate the probability that...
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| The demand for sophisticated tools and approaches in heat management and control has triggered fast development of emerging fields including conductive thermal metamaterials, nanophononics, far-field and near-field ...
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In this article, the problem of designing Active Disturbance Rejection control (ADRC) for a class of second-order mechanical systems, expressed with Euler-Lagrange equations, is studied. A specific and practically mot...
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ISBN:
(数字)9781538682661
ISBN:
(纸本)9781538682678
In this article, the problem of designing Active Disturbance Rejection control (ADRC) for a class of second-order mechanical systems, expressed with Euler-Lagrange equations, is studied. A specific and practically motivated case is considered here, namely trajectory tracking task without the use of signal time-derivatives in the tracking controller. A general solution is proposed showing how to synthesize and tune the observer and the controller parts of the ADRC scheme. A special Extended State Observer is used in the design and here it takes the form of a Generalized Proportional Integral Observer (GPIO), which uses a Taylor series approximation of the total disturbance. A set of experimental results, obtained using a two degree-of-freedom robotic manipulator, shows the effectiveness of the proposed governing scheme in terms of trajectory realization and disturbance rejection without the use of signal time-derivatives in the controller.
"Magneto-optical" effect refers to a rotation of polarization plane, which has been widely studied in traditional ferromagnetic metal and insulator films and scarcely in two-dimensional layered materials. He...
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In the envisioned smart grid, high penetration of uncertain renewables, unpredictable participation of (industrial) customers, and purposeful manipulation of smart meter readings, all highlight the need for accurate, ...
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In the envisioned smart grid, high penetration of uncertain renewables, unpredictable participation of (industrial) customers, and purposeful manipulation of smart meter readings, all highlight the need for accurate, fast, and robust power system state estimation (PSSE). Nonetheless, most real-time data available in the current and upcoming transmission/distribution systems are nonlinear in power system states (i.e., nodal voltage phasors). Scalable approaches to dealing with PSSE tasks undergo a paradigm shift toward addressing the unique modeling and computational challenges associated with those nonlinear measurements. In this study, we provide a contemporary overview of PSSE and describe the current state of the art in the nonlinear weighted least-squares and least-absolutevalue PSSE. To benchmark the performance of unbiased estimators, the Cramer-Rao lower bound is developed. Accounting for cyber attacks, new corruption models are introduced, and robust PSSE approaches are outlined as well. Finally, distribution system state estimation is discussed along with its current challenges. Simulation tests corroborate the effectiveness of the developed algorithms as well as the practical merits of the theory.
The practical use of many types of near-term quantum computers requires accounting for their limited connectivity. One way of overcoming limited connectivity is to insert swaps in the circuit so that logical operation...
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An automated determination of Laguerre-Gaussian (LG) modes benefits cavity tuning and optical communication. In this paper, we employ machine learning techniques to automatically detect the lowest sixteen LG modes of ...
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