Pole -mounted sonar vibration prediction using CMAC neural networks

The efficiency and accuracy of pole-mounted sonar systems are severely affected by pole vibration, Traditional signal processing techniques are not appropriate for the pole vibration problem due to the nonlinearity of the pole vibration and the lack of a priori knowledge about the statistics of the data to be processed. A novel approach of predicting the pole-mounted sonar vibration using CMAC neural networks is presented. The feasibility of this approach is studied in theory, evaluated by simulation and verified with a real-time laboratory prototype, Analytical bounds of the learning rate of a CMAC neural network are derived which guarantee convergence of the weight vector in the mean. Both simulation and experimental results indicate the CMAC neural network is an effective tool for this vibration prediction problem

A Metric for Evaluating Neural Input Representation in Supervised Learning Networks

Supervised learning has long been attributed to several feed-forward neural circuits within the brain, with particular attention being paid to the cerebellar granular layer. The focus of this study is to evaluate the input activity representation of these feed-forward neural networks. The activity of cerebellar granule cells is conveyed by parallel fibers and translated into Purkinje cell activity, which constitutes the sole output of the cerebellar cortex. The learning process at this parallel-fiber-to-Purkinje-cell connection makes each Purkinje cell sensitive to a set of specific cerebellar states, which are roughly determined by the granule-cell activity during a certain time window. A Purkinje cell becomes sensitive to each neural input state and, consequently, the network operates as a function able to generate a desired output for each provided input by means of supervised learning. However, not all sets of Purkinje cell responses can be assigned to any set of input states due to the network's own limitations (inherent to the network neurobiological substrate), that is, not all input-output mapping can be learned. A key limiting factor is the representation of the input states through granule-cell activity. The quality of this representation (e.g., in terms of heterogeneity) will determine the capacity of the network to learn a varied set of outputs. Assessing the quality of this representation is interesting when developing and studying models of these networks to identify those neuron or network characteristics that enhance this representation. In this study we present an algorithm for evaluating quantitatively the level of compatibility/interference amongst a set of given cerebellar states according to their representation (granule-cell activation patterns) without the need for actually conducting simulations and network training. The algorithm input consists of a real-number matrix that codifies the activity level of every considered granule-cell in each state. The capability of this representation to generate a varied set of outputs is evaluated geometrically, thus resulting in a real number that assesses the goodness of the representation

Evolution of microgrids with converter-interfaced generations: Challenges and opportunities

© 2019 Elsevier Ltd Although microgrids facilitate the increased penetration of distributed generations (DGs) and improve the security of power supplies, they have some issues that need to be better understood and addressed before realising the full potential of microgrids. This paper presents a comprehensive list of challenges and opportunities supported by a literature review on the evolution of converter-based microgrids. The discussion in this paper presented with a view to establishing microgrids as distinct from the existing distribution systems. This is accomplished by, firstly, describing the challenges and benefits of using DG units in a distribution network and then those of microgrid ones. Also, the definitions, classifications and characteristics of microgrids are summarised to provide a sound basis for novice researchers to undertake ongoing research on microgrids

Individual Blade Control for Vibration Reduction of a Helicopter with Dissimilar Blades

A control method is proposed to reduce vibrations in helicopters using active trailing-edge flaps on the rotor blades. The novelty of the method is that each blade is controlled independently, taking into account possible blade dissimilarities. This is different from previous control approaches that assumed blades were identical and generated a single control input, which is applied with adequate phase shift to each blade. The controller is developed in discrete time, with the control inputs updated every rotor revolution. The method consists of performing simultaneous system identification (using Kalman filtering technique) and closed loop control (using a deterministic control law) at each time step. For the system identification, different inputs are applied to each blade, and the relationship between the individual blade inputs and the resulting loads in the fixed frame is estimated on-line, assuming a linear-time-periodic model of the helicopter. A comprehensive rotor analysis, including all blade degrees of freedom and a free wake model for computing the inflow across the rotor disk, was used to investigate the controller performance in detail. The rotor model is based on a modern bearingless rotor that includes detailed modeling of trailing edge flap effects. The controller performance was tested at advance ratios from 0.10 to 0.40, both for a baseline rotor with identical blades and a damaged rotor with dissimilar blades. In the case of the dissimilar rotor, comprehensive analysis predicts that allowing independent control inputs for each blade dramatically improves the vibration reduction compared to restricting the control inputs to be specific phase shifted versions of each other. In order to test the controller experimentally, a Mach-scale rotor model was fabricated. The rotor model consists of 4 blades with piezo-ceramic actuated trailing edge flaps. A new type of hinge using flexures was designed to improve the flap articulation and incorporated in each blade. The smart rotor model is then fitted on a bearingless model-scale hub and tested both on a hover stand and in the Glenn L. Martin wind tunnel. Both rotating-frame as well as fixed-frame vibratory loads were targeted in the closed-loop control tests. These tests demonstrate the controller's ability to account for blade dissimilarities and generate different optimal inputs for each blade. For example, in hover, at 500 RPM, the 1/rev bending moment at the root of three of the blades was simultaneously reduced by 77% using three active blades. In forward flight, the controller could simultaneously reduce the baseline 4/rev fixed frame vibration as well other harmonics of vibration such as 1/rev and 3/rev arising from blade dissimilarities. It was also possible to minimize vibration in the fixed frame for several loads simultaneously. However, for most control tests, increases in other loads (not included in the control objective) were observed. During most closed loop tests, the maximum allowable input to the actuators was reached. It was found that the method used to account for actuator saturation and maintain actuator input within acceptable limits had an important effect on controller performance. The best controller performance was obtained when control inputs are computed by solving the constrained minimization problem. However, this procedure is very time consuming and could not be implemented in real-time with the available computer. It can be concluded that accounting for blade dissimilarities using individual inputs for each blade results in improved vibration reduction. However, to maximize the benefits of this control scheme, an efficient, practical method to limit control inputs needs to be devised

Aeronautical engineering: A continuing bibliography with indexes (supplement 322)

This bibliography lists 719 reports, articles, and other documents introduced into the NASA scientific and technical information system in Oct. 1995. Subject coverage includes: design, construction and testing of aircraft and aircraft engines; aircraft components, equipment, and systems; ground support systems; and theoretical and applied aspects of aerodynamics and general fluid dynamics