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In this article, the outlier production mechanism of the conventional Multiple Signal Classification (MUSIC) and the g-MUSIC Direction-of-Arrival (DoA) estimation technique is investigated using tools from Random Matrix Theory (RMT). A general Central Limit Theorem (CLT) is derived that allows to analyze the asymptotic stochastic behavior of eigenvector-based cost functions in the asymptotic regime where the number of snapshots and the number of antennas increase without bound at the same rate. Furthermore, this CLT is used to provide an accurate prediction of the resolution capabilities of the MUSIC and the g-MUSIC DoA estimation method. The finite dimensional distribution of the MUSIC and the g-MUSIC cost function is shown to be asymptotically jointly Gaussian distributed in the asymptotic regime., Comment: This work has been accepted for publication in the IEEE Transactions on Signal Processing. Copyright may be transferred without notice, after which this version may no longer be accessible

The paper deals with a well-known extremum seeking scheme by proving uniformity properties with respect to the amplitudes of the dither signal and of the cost function. Those properties are then used to show that the scheme guarantees the global minimiser to be semi-global practically stable despite the presence of local saddle points. To achieve these results, we analyse the average system associated with the extremum seeking scheme via arguments based on the Fourier series.

Dataset and analyses for article on PNAS with Josh Solomon and Mike Morgan. https://doi.org/10.1073/pnas.1901963116

This paper presents the development of an indirect adaptive state-feedback controller to improve the disturbance-rejection capability of under-actuated multivariable systems. The ubiquitous Linear-Quadratic-Regulator (LQR) is employed as the baseline state-feedback controller. Despite its optimality, the LQR lacks robustness against parametric uncertainties. Hence, the main contribution of this paper is to devise and retrofit the LQR with a stable online gain-adjustment mechanism that dynamically adjusts the state weighting-coefficients of LQR's quadratic cost-function via state-error dependent nonlinear-scaling functions. An original self-mutating phase-based adaptive modulation scheme is systematically formulated in this paper to self-adjust the state weighting-coefficients. The scheme employs pre-calibrated secant-hyperbolic-functions whose waveforms are dynamically reconfigured online based on the variations in magnitude and polarity of state-error variables. This augmentation dynamically alters the solution of the Riccati-Equation which modifies the state-feedback gains online. The proposed adaptation flexibly manipulates the system's control effort as the response converges to or diverges from the reference. The efficacy of proposed adaptive controller is validated by conducting hardware-in-the-loop experiments to vertically stabilize the QNET 2.0 Rotary Pendulum system. As compared to the standard LQR, the proposed adaptive controller renders rapid transits in system's response with improved damping against oscillations, while maintaining its asymptotic-stability, under bounded exogenous disturbances.

In this article, the outlier production mechanism of the conventional Multiple Signal Classification (MUSIC) and the g-MUSIC Direction-of-Arrival (DoA) estimation technique is investigated using tools from Random Matrix Theory (RMT). A general Central Limit Theorem (CLT) is derived that allows to analyze the asymptotic stochastic behavior of eigenvector-based cost functions in the asymptotic regime where the number of snapshots and the number of antennas increase without bound at the same rate. Furthermore, this CLT is used to provide an accurate prediction of the resolution capabilities of the MUSIC and the g-MUSIC DoA estimation method. The finite dimensional distribution of the MUSIC and the g-MUSIC cost function is shown to be asymptotically jointly Gaussian distributed in this asymptotic regime. IEEE

Optimal percolation concerns the identification of the minimum-cost strategy for the destruction of any extensive connected components in a network. Solutions of such a dismantling problem are important for the design of optimal strategies of disease containment based either on immunization or social distancing. Depending on the specific variant of the problem considered, network dismantling is performed via the removal of nodes or edges, and different cost functions are associated to the removal of these microscopic elements. In this paper, we show that network representations in geometric space can be used to solve several variants of the network dismantling problem in a coherent fashion. Once a network is embedded, dismantling is implemented using intuitive geometric strategies. We demonstrate that the approach well suits both Euclidean and hyperbolic network embeddings. Our systematic analysis on synthetic and real networks demonstrates that the performance of embedding-aided techniques is comparable to, if not better than, the one of the best dismantling algorithms currently available on the market., Comment: 13 pages, 5 figures, 1 table + SM available at https://cgi.luddy.indiana.edu/~filiradi/Mypapers/SM_geo_percolation.pdf

7th IEEE International Symposium on Electrical and Electronics Engineering, ISEEE 2021 -- 28 October 2021 through 30 October 2021 -- -- 175357, L. Zadeh came up with the idea of Z-number to reflect human decision-making ability in environments where information is uncertain. According to his idea, a Z-number consists of a classical fuzzy part and its reliability. Although there are linguistic based studies exist in the literature, designing the reliability part is still an open issue. In this paper, Logistic Regression is used to determine reliability part. Since the reliability part contains probability information and fuzzy granular information, both statistical and probability based methods must be proposed. The features such as giving probabilistic output, being optimization based via a cost function makes the Logistic Regression one of the best methods for generating Z-number. According to the proposed method, Z-numbers and Z-number based fuzzy if-then rules are written. We tried the Z-number based classifier on Fisher Iris Dataset. The results showed us the more reliable fuzzy membership functions give the more accurate outputs as expected. Another important issue is the reliability of input information, i.e. sensor data, was not known, so the reliability based calculations could not be performed. The reliability of input data can be calculated via proposed method. © 2021 IEEE.

The commonly reported measures of the predictive accuracy are evaluated in this paper. Absolute, squared, percentage, and integral errors methods are implemented, to reduce the objective function, which employed in model predictive control. These methods are usually investigated for dc source inverter, which controlled by finite set model predictive current control system, with three phase induction motor load. In this paper, the evaluation includes different aspects, accuracy, complexity, system harmonics content, and execution time. A vital criterion in this process is the performance of the inverter, and the matching between the reference and the measured machine currents. The evaluation shows that for one term objective function, absolute and square errors give similar results with less execution time for the absolute error, but if multi terms objective function the square error is better.

International audience; When a high power output is required in cycling, a spontaneous transition by the cyclist from a seated to a standing position generally occurs. In this study, by varying the cadence and cyclist bodyweight, we tested whether the transition is better explained by the greater power economy of a standing position or by the emergence of mechanical constraints that force cyclists to stand. Ten males participated in five experimental sessions corresponding to different bodyweights (80%, 100%, or 120%) and cadences (50 RPM, 70 RPM, or 90 RPM). In each session, we first determined the seat-to-stand transition power (SSTP) in an incremental test. The participants then cycled at 20%, 40%, 60%, 80%, 100%, or 120% of the SSTP in the seated and standing positions, for which we recorded the saddle forces and electromyogram (EMG) signals of eight lower limb muscles. We estimated the cycling cost using an EMG cost function (ECF) and the minimal saddle forces in the seated position as an indicator of the mechanical constraints.Our results show the SSTP to vary with respect to both cadence and bodyweight. The ECF was lower in the standing position above the SSTP value (i.e., at 120%) in all experimental sessions. The minimal saddle forces varied significantly with respect to both cadence and bodyweight.These results suggest that optimization of the muscular cost function, rather than mechanical constraints, explain the seat-to-stand transition in cycling.

This is the final version of the article. It first appeared from Springer via http://dx.doi.org/10.1007/s11095-016-1992-3, PURPOSE: For passive dry powder inhalers (DPIs) entrainment and emission of the aerosolized drug dose depends strongly on device geometry and the patient's inhalation manoeuvre. We propose a computational method for optimizing the entrainment part of a DPI. The approach assumes that the pulmonary delivery location of aerosol can be determined by the timing of dose emission into the tidal airstream. METHODS: An optimization algorithm was used to iteratively perform computational fluid dynamic (CFD) simulations of the drug emission of a DPI. The algorithm seeks to improve performance by changing the device geometry. Objectives were to achieve drug emission that was: A) independent of inhalation manoeuvre; B) similar to a target profile. The simulations used complete inhalation flow-rate profiles generated dependent on the device resistance. The CFD solver was OpenFOAM with drug/air flow simulated by the Eulerian-Eulerian method. RESULTS: To demonstrate the method, a 2D geometry was optimized for inhalation independence (comparing two breath profiles) and an early-bolus delivery. Entrainment was both shear-driven and gas-assisted. Optimization for a delay in the bolus delivery was not possible with the chosen geometry. CONCLUSIONS: Computational optimization of a DPI geometry for most similar drug delivery has been accomplished for an example entrainment geometry.

DC microgrids are gaining interest due to higher efficiencies of DC distribution compared with AC. The benefits of DC systems have been widely researched for data centers, IT facilities and residential applications. The research focus, however, has been more on system architecture and optimal voltage level, less on optimized operation and control of generation sources. The latter theme is perused in this paper, where cost-based droop scheme is proposed for distributed generators (DGs) in DC microgrids. Unlike traditional proportional power sharing based droop scheme, the proposed scheme considers the generation costs of DGs and dynamically tunes their droop gradients to produce more power from less costly DGs and vice versa. The proposed scheme is fully autonomous, simple to implement in dispatchable and non-dispatchable sources coupled with storage, support islanded and grid-connected operation. Most importantly, the proposed scheme can reduce overall total generation cost in DC microgrids without centralized controller and communication links. The performance of the proposed scheme has been verified under different load conditions.

The aim of this paper is to present a communication synthesis approach stated as an allocation problem. In the proposed approach, communication synthesis allows to transform a system composed of processes that communicate via high-level primitives through abstract channels into a set of processes executed by interconnected processors that communicate via signals and share communication control. The proposed communication synthesis approach deals with both protocol selection and interface generation and is based on binding/allocation of communication units. This approach allows a wide design space exploration through automatic selection of communication protocols. We present a new algorithm that performs binding/allocation of communication units. This algorithm makes use of a cost function to evaluate different allocation alternatives. We illustrate through an example the usefulness of the algorithm for allocating automatically different protocols within the same application system.

A hierarchical high level synthesis (HHLS) system, such as AMICAL, allows the obtaining of an architecture for a circuit from its behavioral description, written as a hierarchy of procedures and function calls, proper of large circuits. When specific modules are synthesized and reused as basic hardware modules in another HLS session, the resulting architecture may be inefficient due to operations overlap among the allocated hardware modules. This paper presents the structure of a CAD system that treats this problem by generating new hardware modules through a set of transformations to be applied to existing modules in an original library. We call the procedure of generating and reusing these new modules recursive high level synthesis (RHLS) which leads to a more efficient architecture. We propose a cost function that evaluates the quality of each architecture, taking into account area and time, and we present criteria to select the most promising transformation. The methodology is applied to a motor controller example (PID), showing its feasibility.

International audience; Communication synthesis aims to transform a system with processes that communicate via high level primitives through channels into interconnected processes that communicate via signals and share communication control. We present a new algorithm that performs binding/allocation of communication units. This algorithm makes use of a cost function to evaluate different allocation alternatives. The proposed communication synthesis approach deals with both protocol selection and interface synthesis and is based on binding/allocation of communication units. We illustrate through an example the usefulness of the algorithm for allocating automatically different protocols within the same system.