56 research outputs found
Lipschitzian Parameterization-Based Approach for Adaptive Controls of Nonlinear Dynamic Systems with Nonlinearly Parameterized Uncertainties: A Theoretical Framework and Its Applications
Contingent and Intermediate Tangent Cones in Hyperbolic Differential Inclusions and Necessary Optimality Conditions
AbstractWe study some properties of the contingent and intermediate cones to the reachable set and the solution set of hyperbolic differential inclusions. These properties allow us to obtain necessary optimality conditions in terminal problems for the corresponding class of inclusions and dynamic systems with feedback controls
Robust H-infinity filtering for 2-D systems with intermittent measurements
This paper is concerned with the problem of robust H∞ filtering for uncertain two-dimensional (2-D) systems with intermittent measurements. The parameter uncertainty is assumed to be of polytopic type, and the measurements transmission is assumed to be imperfect, which is modeled by a stochastic variable satisfying the Bernoulli random binary distribution. Our attention is focused on the design of an H∞ filter such that the filtering error system is stochastically stable and preserves a guaranteed H∞ performance. This problem is solved in the parameter-dependent framework, which is much less conservative than the quadratic approach. By introducing some slack matrix variables, the coupling between the positive definite matrices and the system matrices is eliminated, which greatly facilitates the filter design procedure. The corresponding results are established in terms of linear matrix inequalities, which can be easily tested by using standard numerical software. An example is provided to show the effectiveness of the proposed approac
Investigation of the near-grazing behavior in hard-impact oscillators using model-based TS fuzzy approach
Finite-resolution digital beamforming for multi-user millimeter-wave networks
Recent studies have shown that low-resolution analog-to-digital-converters and digital-to-analog-converters (ADCs and DACs) can make fully-digital beamforming more power efficient than its analog or hybrid beamforming counterpart over wide-band millimeter-wave (mmWave) channels. Inspired by this, we propose a computationally efficient fully-digital beamformer relying on low-resolution ADCs/DACs for multi-user mmWave communication networks. Both a generalized (unstructured) beamformer (GB) and a structured zero-forcing beamformer (ZFB) are proposed. For maintaining fairness among all users in the network, specifically tailored objective functions are considered under sum-power constraints, namely that of maximizing the geometric mean (GM) of users’ rate and their max-min rate. These computationally challenging beamforming design problems are tackled by developing computationally efficient steep ascent algorithms, which have the radical benefit of relying on a closed-form solution at each iteration. Moreover, to facilitate the employment of low-cost amplifiers at each antenna, the GB design problem subject to the equal-gain transmission constraint is considered, which assigns equal transmit power to each transmit antenna. The proposed algorithms promise a user-rate distribution having a reduced deviation among the user-rates, i.e., improved rate-fairness. Our extensive simulation results show an approximately upto 45% reduction for the GM-rate of a 2-bit ADC (4-bin quantization) compared to the -resolution AD
Transmitter-side wireless information- and power-transfer in massive MIMO systems
Both time-switching (TS) and power splitting has been used at the receiver for wireless information and power transfer in the downlink of massive multiple-input-multiple-output systems. By contrast, this correspondence adopts the transmit-TS approach, where the energy and information are transferred over different fractions of a time slot. Our goal is to jointly optimize the transmit-TS factor and power allocation coefficients during energy and information transfer for maximizing the users’ minimum throughput subject to transmit power and minimum harvested energy constraints. This nonconvex problem is solved by our path following algorithm. Our simulation results demonstrate the benefits of the proposed transmit-TS algorithm, which easily doubles the throughput compared to that of the existing techniques.<br/
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