NASA Technical Reports Server (NTRS)
Griffin, Brian Joseph; Burken, John J.; Xargay, Enric
2010-01-01
This paper presents an L(sub 1) adaptive control augmentation system design for multi-input multi-output nonlinear systems in the presence of unmatched uncertainties which may exhibit significant cross-coupling effects. A piecewise continuous adaptive law is adopted and extended for applicability to multi-input multi-output systems that explicitly compensates for dynamic cross-coupling. In addition, explicit use of high-fidelity actuator models are added to the L1 architecture to reduce uncertainties in the system. The L(sub 1) multi-input multi-output adaptive control architecture is applied to the X-29 lateral/directional dynamics and results are evaluated against a similar single-input single-output design approach.
Self-tuning multivariable pole placement control of a multizone crystal growth furnace
NASA Technical Reports Server (NTRS)
Batur, C.; Sharpless, R. B.; Duval, W. M. B.; Rosenthal, B. N.
1992-01-01
This paper presents the design and implementation of a multivariable self-tuning temperature controller for the control of lead bromide crystal growth. The crystal grows inside a multizone transparent furnace. There are eight interacting heating zones shaping the axial temperature distribution inside the furnace. A multi-input, multi-output furnace model is identified on-line by a recursive least squares estimation algorithm. A multivariable pole placement controller based on this model is derived and implemented. Comparison between single-input, single-output and multi-input, multi-output self-tuning controllers demonstrates that the zone-to-zone interactions can be minimized better by a multi-input, multi-output controller design. This directly affects the quality of crystal grown.
A multi-GHz chaotic optoelectronic oscillator based on laser terminal voltage
DOE Office of Scientific and Technical Information (OSTI.GOV)
Chang, C. Y., E-mail: cychang@gatech.edu; UMI 2958 Georgia Tech-CNRS, Georgia Tech Lorraine, 2 Rue Marconi, F-57070 Metz; Choi, Daeyoung
2016-05-09
A multi-GHz chaotic optoelectronic oscillator based on an external cavity semiconductor laser (ECL) is demonstrated. Unlike the standard optoelectronic oscillators for microwave applications, we do not employ the dynamic light output incident on a photodiode to generate the microwave signal, but instead generate the microwave signal directly by measuring the terminal voltage V(t) of the laser diode of the ECL under constant-current operation, thus obviating the photodiode entirely.
Tahoun, A H
2017-01-01
In this paper, the stabilization problem of actuators saturation in uncertain chaotic systems is investigated via an adaptive PID control method. The PID control parameters are auto-tuned adaptively via adaptive control laws. A multi-level augmented error is designed to account for the extra terms appearing due to the use of PID and saturation. The proposed control technique uses both the state-feedback and the output-feedback methodologies. Based on Lyapunov׳s stability theory, new anti-windup adaptive controllers are proposed. Demonstrative examples with MATLAB simulations are studied. The simulation results show the efficiency of the proposed adaptive PID controllers. Copyright © 2016 ISA. Published by Elsevier Ltd. All rights reserved.
Information encoder/decoder using chaotic systems
Miller, Samuel Lee; Miller, William Michael; McWhorter, Paul Jackson
1997-01-01
The present invention discloses a chaotic system-based information encoder and decoder that operates according to a relationship defining a chaotic system. Encoder input signals modify the dynamics of the chaotic system comprising the encoder. The modifications result in chaotic, encoder output signals that contain the encoder input signals encoded within them. The encoder output signals are then capable of secure transmissions using conventional transmission techniques. A decoder receives the encoder output signals (i.e., decoder input signals) and inverts the dynamics of the encoding system to directly reconstruct the original encoder input signals.
Information encoder/decoder using chaotic systems
Miller, S.L.; Miller, W.M.; McWhorter, P.J.
1997-10-21
The present invention discloses a chaotic system-based information encoder and decoder that operates according to a relationship defining a chaotic system. Encoder input signals modify the dynamics of the chaotic system comprising the encoder. The modifications result in chaotic, encoder output signals that contain the encoder input signals encoded within them. The encoder output signals are then capable of secure transmissions using conventional transmission techniques. A decoder receives the encoder output signals (i.e., decoder input signals) and inverts the dynamics of the encoding system to directly reconstruct the original encoder input signals. 32 figs.
Evaluating Multi-Input/Multi-Output Digital Control Systems
NASA Technical Reports Server (NTRS)
Pototzky, Anthony S.; Wieseman, Carol D.; Hoadley, Sherwood T.; Mukhopadhyay, Vivek
1994-01-01
Controller-performance-evaluation (CPE) methodology for multi-input/multi-output (MIMO) digital control systems developed. Procedures identify potentially destabilizing controllers and confirm satisfactory performance of stabilizing ones. Methodology generic and used in many types of multi-loop digital-controller applications, including digital flight-control systems, digitally controlled spacecraft structures, and actively controlled wind-tunnel models. Also applicable to other complex, highly dynamic digital controllers, such as those in high-performance robot systems.
QFT Multi-Input, Multi-Output Design with Non-Diagonal, Non-Square Compensation Matrices
NASA Technical Reports Server (NTRS)
Hess, R. A.; Henderson, D. K.
1996-01-01
A technique for obtaining a non-diagonal compensator for the control of a multi-input, multi-output plant is presented. The technique, which uses Quantitative Feedback Theory, provides guaranteed stability and performance robustness in the presence of parametric uncertainty. An example is given involving the lateral-directional control of an uncertain model of a high-performance fighter aircraft in which redundant control effectors are in evidence, i.e. more control effectors than output variables are used.
Adaptive Control for Uncertain Nonlinear Multi-Input Multi-Output Systems
NASA Technical Reports Server (NTRS)
Cao, Chengyu (Inventor); Hovakimyan, Naira (Inventor); Xargay, Enric (Inventor)
2014-01-01
Systems and methods of adaptive control for uncertain nonlinear multi-input multi-output systems in the presence of significant unmatched uncertainty with assured performance are provided. The need for gain-scheduling is eliminated through the use of bandwidth-limited (low-pass) filtering in the control channel, which appropriately attenuates the high frequencies typically appearing in fast adaptation situations and preserves the robustness margins in the presence of fast adaptation.
Experimental validation of wireless communication with chaos.
Ren, Hai-Peng; Bai, Chao; Liu, Jian; Baptista, Murilo S; Grebogi, Celso
2016-08-01
The constraints of a wireless physical media, such as multi-path propagation and complex ambient noises, prevent information from being communicated at low bit error rate. Surprisingly, it has only recently been shown that, from a theoretical perspective, chaotic signals are optimal for communication. It maximises the receiver signal-to-noise performance, consequently minimizing the bit error rate. This work demonstrates numerically and experimentally that chaotic systems can in fact be used to create a reliable and efficient wireless communication system. Toward this goal, we propose an impulsive control method to generate chaotic wave signals that encode arbitrary binary information signals and an integration logic together with the match filter capable of decreasing the noise effect over a wireless channel. The experimental validation is conducted by inputting the signals generated by an electronic transmitting circuit to an electronic circuit that emulates a wireless channel, where the signals travel along three different paths. The output signal is decoded by an electronic receiver, after passing through a match filter.
Experimental validation of wireless communication with chaos
NASA Astrophysics Data System (ADS)
Ren, Hai-Peng; Bai, Chao; Liu, Jian; Baptista, Murilo S.; Grebogi, Celso
2016-08-01
The constraints of a wireless physical media, such as multi-path propagation and complex ambient noises, prevent information from being communicated at low bit error rate. Surprisingly, it has only recently been shown that, from a theoretical perspective, chaotic signals are optimal for communication. It maximises the receiver signal-to-noise performance, consequently minimizing the bit error rate. This work demonstrates numerically and experimentally that chaotic systems can in fact be used to create a reliable and efficient wireless communication system. Toward this goal, we propose an impulsive control method to generate chaotic wave signals that encode arbitrary binary information signals and an integration logic together with the match filter capable of decreasing the noise effect over a wireless channel. The experimental validation is conducted by inputting the signals generated by an electronic transmitting circuit to an electronic circuit that emulates a wireless channel, where the signals travel along three different paths. The output signal is decoded by an electronic receiver, after passing through a match filter.
Experimental validation of wireless communication with chaos
DOE Office of Scientific and Technical Information (OSTI.GOV)
Ren, Hai-Peng; Bai, Chao; Liu, Jian
The constraints of a wireless physical media, such as multi-path propagation and complex ambient noises, prevent information from being communicated at low bit error rate. Surprisingly, it has only recently been shown that, from a theoretical perspective, chaotic signals are optimal for communication. It maximises the receiver signal-to-noise performance, consequently minimizing the bit error rate. This work demonstrates numerically and experimentally that chaotic systems can in fact be used to create a reliable and efficient wireless communication system. Toward this goal, we propose an impulsive control method to generate chaotic wave signals that encode arbitrary binary information signals and anmore » integration logic together with the match filter capable of decreasing the noise effect over a wireless channel. The experimental validation is conducted by inputting the signals generated by an electronic transmitting circuit to an electronic circuit that emulates a wireless channel, where the signals travel along three different paths. The output signal is decoded by an electronic receiver, after passing through a match filter.« less
Coordination of heterogeneous nonlinear multi-agent systems with prescribed behaviours
NASA Astrophysics Data System (ADS)
Tang, Yutao
2017-10-01
In this paper, we consider a coordination problem for a class of heterogeneous nonlinear multi-agent systems with a prescribed input-output behaviour which was represented by another input-driven system. In contrast to most existing multi-agent coordination results with an autonomous (virtual) leader, this formulation takes possible control inputs of the leader into consideration. First, the coordination was achieved by utilising a group of distributed observers based on conventional assumptions of model matching problem. Then, a fully distributed adaptive extension was proposed without using the input of this input-output behaviour. An example was given to verify their effectiveness.
A comparative study of linear and nonlinear MIMO feedback configurations
NASA Technical Reports Server (NTRS)
Desoer, C. A.; Lin, C. A.
1984-01-01
In this paper, a comparison is conducted of several feedback configurations which have appeared in the literature (e.g. unity-feedback, model-reference, etc.). The linear time-invariant multi-input multi-output case is considered. For each configuration, the stability conditions are specified, the relation between achievable I/O maps and the achievable disturbance-to-output maps is examined, and the effect of various subsystem perturbations on the system performance is studied. In terms of these considerations, it is demonstrated that one of the configurations considered is better than all the others. The results are then extended to the nonlinear multi-input multi-output case.
Zhou, Ping; Ahmad, Bashir; Ren, Guodong; Wang, Chunni
2018-01-01
In this paper, a new four-variable dynamical system is proposed to set chaotic circuit composed of memristor and Josephson junction, and the dependence of chaotic behaviors on nonlinearity is investigated. A magnetic flux-controlled memristor is used to couple with the RCL-shunted junction circuit, and the dynamical behaviors can be modulated by changing the coupling intensity between the memristor and the RCL-shunted junction. Bifurcation diagram and Lyapunov exponent are calculated to confirm the emergence of chaos in the improved dynamical system. The outputs and dynamical behaviors can be controlled by the initial setting and external stimulus as well. As a result, chaos can be suppressed and spiking occurs in the sampled outputs under negative feedback, while applying positive feedback type via memristor can be effective to trigger chaos. Furthermore, it is found that the number of multi-attractors in the Jerk circuit can be modulated when memristor coupling is applied on the circuit. These results indicate that memristor coupling can be effective to control chaotic circuits and it is also useful to reproduce dynamical behaviors for neuronal activities. PMID:29342178
Ma, Jun; Zhou, Ping; Ahmad, Bashir; Ren, Guodong; Wang, Chunni
2018-01-01
In this paper, a new four-variable dynamical system is proposed to set chaotic circuit composed of memristor and Josephson junction, and the dependence of chaotic behaviors on nonlinearity is investigated. A magnetic flux-controlled memristor is used to couple with the RCL-shunted junction circuit, and the dynamical behaviors can be modulated by changing the coupling intensity between the memristor and the RCL-shunted junction. Bifurcation diagram and Lyapunov exponent are calculated to confirm the emergence of chaos in the improved dynamical system. The outputs and dynamical behaviors can be controlled by the initial setting and external stimulus as well. As a result, chaos can be suppressed and spiking occurs in the sampled outputs under negative feedback, while applying positive feedback type via memristor can be effective to trigger chaos. Furthermore, it is found that the number of multi-attractors in the Jerk circuit can be modulated when memristor coupling is applied on the circuit. These results indicate that memristor coupling can be effective to control chaotic circuits and it is also useful to reproduce dynamical behaviors for neuronal activities.
Multi-Target Regression via Robust Low-Rank Learning.
Zhen, Xiantong; Yu, Mengyang; He, Xiaofei; Li, Shuo
2018-02-01
Multi-target regression has recently regained great popularity due to its capability of simultaneously learning multiple relevant regression tasks and its wide applications in data mining, computer vision and medical image analysis, while great challenges arise from jointly handling inter-target correlations and input-output relationships. In this paper, we propose Multi-layer Multi-target Regression (MMR) which enables simultaneously modeling intrinsic inter-target correlations and nonlinear input-output relationships in a general framework via robust low-rank learning. Specifically, the MMR can explicitly encode inter-target correlations in a structure matrix by matrix elastic nets (MEN); the MMR can work in conjunction with the kernel trick to effectively disentangle highly complex nonlinear input-output relationships; the MMR can be efficiently solved by a new alternating optimization algorithm with guaranteed convergence. The MMR leverages the strength of kernel methods for nonlinear feature learning and the structural advantage of multi-layer learning architectures for inter-target correlation modeling. More importantly, it offers a new multi-layer learning paradigm for multi-target regression which is endowed with high generality, flexibility and expressive ability. Extensive experimental evaluation on 18 diverse real-world datasets demonstrates that our MMR can achieve consistently high performance and outperforms representative state-of-the-art algorithms, which shows its great effectiveness and generality for multivariate prediction.
A Hierarchical multi-input and output Bi-GRU Model for Sentiment Analysis on Customer Reviews
NASA Astrophysics Data System (ADS)
Zhang, Liujie; Zhou, Yanquan; Duan, Xiuyu; Chen, Ruiqi
2018-03-01
Multi-label sentiment classification on customer reviews is a practical challenging task in Natural Language Processing. In this paper, we propose a hierarchical multi-input and output model based bi-directional recurrent neural network, which both considers the semantic and lexical information of emotional expression. Our model applies two independent Bi-GRU layer to generate part of speech and sentence representation. Then the lexical information is considered via attention over output of softmax activation on part of speech representation. In addition, we combine probability of auxiliary labels as feature with hidden layer to capturing crucial correlation between output labels. The experimental result shows that our model is computationally efficient and achieves breakthrough improvements on customer reviews dataset.
NASA Astrophysics Data System (ADS)
Lai, Qiang; Zhao, Xiao-Wen; Rajagopal, Karthikeyan; Xu, Guanghui; Akgul, Akif; Guleryuz, Emre
2018-01-01
This paper considers the generation of multi-butterfly chaotic attractors from a generalised Sprott C system with multiple non-hyperbolic equilibria. The system is constructed by introducing an additional variable whose derivative has a switching function to the Sprott C system. It is numerically found that the system creates two-, three-, four-, five-butterfly attractors and any other multi-butterfly attractors. First, the dynamic analyses of multi-butterfly chaotic attractors are presented. Secondly, the field programmable gate array implementation, electronic circuit realisation and random number generator are done with the multi-butterfly chaotic attractors.
Ngeo, Jimson; Tamei, Tomoya; Shibata, Tomohiro
2014-01-01
Surface electromyographic (EMG) signals have often been used in estimating upper and lower limb dynamics and kinematics for the purpose of controlling robotic devices such as robot prosthesis and finger exoskeletons. However, in estimating multiple and a high number of degrees-of-freedom (DOF) kinematics from EMG, output DOFs are usually estimated independently. In this study, we estimate finger joint kinematics from EMG signals using a multi-output convolved Gaussian Process (Multi-output Full GP) that considers dependencies between outputs. We show that estimation of finger joints from muscle activation inputs can be improved by using a regression model that considers inherent coupling or correlation within the hand and finger joints. We also provide a comparison of estimation performance between different regression methods, such as Artificial Neural Networks (ANN) which is used by many of the related studies. We show that using a multi-output GP gives improved estimation compared to multi-output ANN and even dedicated or independent regression models.
Performance of Multi-chaotic PSO on a shifted benchmark functions set
DOE Office of Scientific and Technical Information (OSTI.GOV)
Pluhacek, Michal; Senkerik, Roman; Zelinka, Ivan
2015-03-10
In this paper the performance of Multi-chaotic PSO algorithm is investigated using two shifted benchmark functions. The purpose of shifted benchmark functions is to simulate the time-variant real-world problems. The results of chaotic PSO are compared with canonical version of the algorithm. It is concluded that using the multi-chaotic approach can lead to better results in optimization of shifted functions.
NASA Astrophysics Data System (ADS)
Xie, Yi-Yuan; Li, Jia-Chao; He, Chao; Zhang, Zhen-Dong; Song, Ting-Ting; Xu, Chang-Jun; Wang, Gui-Jin
2016-10-01
A novel long-distance multi-channel bidirectional chaos communication system over multiple paths based on two synchronized 1550 nm vertical-cavity surface-emitting lasers (VCSELs) is proposed and studied theoretically. These two responding VCSELs (R-VCSELs) can output similar chaotic signals served as chaotic carrier in two linear polarization (LP) modes with identical signal injection from a driving VCSEL (D-VCSEL), which is subject to optical feedback and optical injection, simultaneously. Through the numerical simulations, high quality chaos synchronization between the two R-VCSELs can be obtained. Besides, the effects of varied qualities of chaos synchronization on communication performances in 20 km single mode fiber (SMF) channels are investigated by regulating different internal parameters mismatch after adopting chaos masking (CMS) technique. With the decrease of the maximum cross correlation coefficient (Max-C) between the two R-VCSELs, the bit error rate (BER) of decoded message increase. Meanwhile, the BER can still be less than 10-9 when the Max-C degrades to 0.982. Based on high quality synchronization, when the dispersion compensating fiber (DCF) links are introduced, 4n messages of 10 Gbit/s can transmit in 180 km SMF channels over n coupling paths, bidirectionally and simultaneously. Thorough tests are carried out with detailed analysis, demonstrating long-distance, multi-channel, bidirectional chaos communication based on VCSELs with chaotic signal injection.
2010-01-01
Multi-Disciplinary, Multi-Output Sensitivity Analysis ( MIMOSA ) .........29 3.1 Introduction to Research Thrust 1...39 3.3 MIMOSA Approach ..........................................................................................41 3.3.1...Collaborative Consistency of MIMOSA .......................................................41 3.3.2 Formulation of MIMOSA
A multi-channel isolated power supply in non-equipotential circuit
NASA Astrophysics Data System (ADS)
Li, Xiang; Zhao, Bo-Wen; Zhang, Yan-Chi; Xie, Da
2018-04-01
A multi-channel isolation power supply is designed for the problems of different MOSFET or IGBT in the non-equipotential circuit in this paper. It mainly includes the square wave generation circuit, the high-frequency transformer and the three-terminal stabilized circuit. The first part is used to generate the 24V square wave, and as the input of the magnetic ring transformer. In the second part, the magnetic ring transformer consists of one input and three outputs to realize multi-channel isolation output. The third part can output different potential and realize non-equal potential function through the three-terminal stabilized chip. In addition, the multi-channel isolation power source proposed in this paper is Small size, high reliability and low price, and it is convenient for power electronic switches that operate on multiple different potentials. Therefore, the research on power supply of power electronic circuit has practical significance.
NASA Technical Reports Server (NTRS)
Pototzky, Anthony; Wieseman, Carol; Hoadley, Sherwood Tiffany; Mukhopadhyay, Vivek
1991-01-01
Described here is the development and implementation of on-line, near real time controller performance evaluation (CPE) methods capability. Briefly discussed are the structure of data flow, the signal processing methods used to process the data, and the software developed to generate the transfer functions. This methodology is generic in nature and can be used in any type of multi-input/multi-output (MIMO) digital controller application, including digital flight control systems, digitally controlled spacecraft structures, and actively controlled wind tunnel models. Results of applying the CPE methodology to evaluate (in near real time) MIMO digital flutter suppression systems being tested on the Rockwell Active Flexible Wing (AFW) wind tunnel model are presented to demonstrate the CPE capability.
MIMO system identification using frequency response data
NASA Technical Reports Server (NTRS)
Medina, Enrique A.; Irwin, R. D.; Mitchell, Jerrel R.; Bukley, Angelia P.
1992-01-01
A solution to the problem of obtaining a multi-input, multi-output statespace model of a system from its individual input/output frequency responses is presented. The Residue Identification Algorithm (RID) identifies the system poles from a transfer function model of the determinant of the frequency response data matrix. Next, the residue matrices of the modes are computed guaranteeing that each input/output frequency response is fitted in the least squares sense. Finally, a realization of the system is computed. Results of the application of RID to experimental frequency responses of a large space structure ground test facility are presented and compared to those obtained via the Eigensystem Realization Algorithm.
Lu, Bin [Kenosha, WI; Luebke, Charles John [Sussex, WI; Habetler, Thomas G [Snellville, GA; Zhang, Pinjia [Atlanta, GA; Becker, Scott K [Oak Creek, WI
2011-12-27
A system and method for measuring and controlling stator winding temperature in an AC motor while idling is disclosed. The system includes a circuit having an input connectable to an AC source and an output connectable to an input terminal of a multi-phase AC motor. The circuit further includes a plurality of switching devices to control current flow and terminal voltages in the multi-phase AC motor and a controller connected to the circuit. The controller is configured to activate the plurality of switching devices to create a DC signal in an output of the motor control device corresponding to an input to the multi-phase AC motor, determine or estimate a stator winding resistance of the multi-phase AC motor based on the DC signal, and estimate a stator temperature from the stator winding resistance. Temperature can then be controlled and regulated by DC injection into the stator windings.
Low-carbon building assessment and multi-scale input-output analysis
NASA Astrophysics Data System (ADS)
Chen, G. Q.; Chen, H.; Chen, Z. M.; Zhang, Bo; Shao, L.; Guo, S.; Zhou, S. Y.; Jiang, M. M.
2011-01-01
Presented as a low-carbon building evaluation framework in this paper are detailed carbon emission account procedures for the life cycle of buildings in terms of nine stages as building construction, fitment, outdoor facility construction, transportation, operation, waste treatment, property management, demolition, and disposal for buildings, supported by integrated carbon intensity databases based on multi-scale input-output analysis, essential for low-carbon planning, procurement and supply chain design, and logistics management.
Deadbeat Predictive Controllers
NASA Technical Reports Server (NTRS)
Juang, Jer-Nan; Phan, Minh
1997-01-01
Several new computational algorithms are presented to compute the deadbeat predictive control law. The first algorithm makes use of a multi-step-ahead output prediction to compute the control law without explicitly calculating the controllability matrix. The system identification must be performed first and then the predictive control law is designed. The second algorithm uses the input and output data directly to compute the feedback law. It combines the system identification and the predictive control law into one formulation. The third algorithm uses an observable-canonical form realization to design the predictive controller. The relationship between all three algorithms is established through the use of the state-space representation. All algorithms are applicable to multi-input, multi-output systems with disturbance inputs. In addition to the feedback terms, feed forward terms may also be added for disturbance inputs if they are measurable. Although the feedforward terms do not influence the stability of the closed-loop feedback law, they enhance the performance of the controlled system.
A Generalized Mixture Framework for Multi-label Classification
Hong, Charmgil; Batal, Iyad; Hauskrecht, Milos
2015-01-01
We develop a novel probabilistic ensemble framework for multi-label classification that is based on the mixtures-of-experts architecture. In this framework, we combine multi-label classification models in the classifier chains family that decompose the class posterior distribution P(Y1, …, Yd|X) using a product of posterior distributions over components of the output space. Our approach captures different input–output and output–output relations that tend to change across data. As a result, we can recover a rich set of dependency relations among inputs and outputs that a single multi-label classification model cannot capture due to its modeling simplifications. We develop and present algorithms for learning the mixtures-of-experts models from data and for performing multi-label predictions on unseen data instances. Experiments on multiple benchmark datasets demonstrate that our approach achieves highly competitive results and outperforms the existing state-of-the-art multi-label classification methods. PMID:26613069
Expanded all-optical programmable logic array based on multi-input/output canonical logic units.
Lei, Lei; Dong, Jianji; Zou, Bingrong; Wu, Zhao; Dong, Wenchan; Zhang, Xinliang
2014-04-21
We present an expanded all-optical programmable logic array (O-PLA) using multi-input and multi-output canonical logic units (CLUs) generation. Based on four-wave mixing (FWM) in highly nonlinear fiber (HNLF), two-input and three-input CLUs are simultaneously achieved in five different channels with an operation speed of 40 Gb/s. Clear temporal waveforms and wide open eye diagrams are successfully observed. The effectiveness of the scheme is validated by extinction ratio and optical signal-to-noise ratio measurements. The computing capacity, defined as the total amount of logic functions achieved by the O-PLA, is discussed in detail. For a three-input O-PLA, the computing capacity of the expanded CLUs-PLA is more than two times as large as that of the standard CLUs-PLA, and this multiple will increase to more than three and a half as the idlers are individually independent.
Berger, Theodore W.; Song, Dong; Chan, Rosa H. M.; Marmarelis, Vasilis Z.; LaCoss, Jeff; Wills, Jack; Hampson, Robert E.; Deadwyler, Sam A.; Granacki, John J.
2012-01-01
This paper describes the development of a cognitive prosthesis designed to restore the ability to form new long-term memories typically lost after damage to the hippocampus. The animal model used is delayed nonmatch-to-sample (DNMS) behavior in the rat, and the “core” of the prosthesis is a biomimetic multi-input/multi-output (MIMO) nonlinear model that provides the capability for predicting spatio-temporal spike train output of hippocampus (CA1) based on spatio-temporal spike train inputs recorded presynaptically to CA1 (e.g., CA3). We demonstrate the capability of the MIMO model for highly accurate predictions of CA1 coded memories that can be made on a single-trial basis and in real-time. When hippocampal CA1 function is blocked and long-term memory formation is lost, successful DNMS behavior also is abolished. However, when MIMO model predictions are used to reinstate CA1 memory-related activity by driving spatio-temporal electrical stimulation of hippocampal output to mimic the patterns of activity observed in control conditions, successful DNMS behavior is restored. We also outline the design in very-large-scale integration for a hardware implementation of a 16-input, 16-output MIMO model, along with spike sorting, amplification, and other functions necessary for a total system, when coupled together with electrode arrays to record extracellularly from populations of hippocampal neurons, that can serve as a cognitive prosthesis in behaving animals. PMID:22438335
Self tuning control of wind-diesel power systems
DOE Office of Scientific and Technical Information (OSTI.GOV)
Mufti, M.D.; Balasubramanian, R.; Tripathy, S.C.
1995-12-31
This paper proposes some effective self-tuning control strategies for isolated Wind-Diesel power generation systems. Detailed modeling and studies on both single-input single-output (SISO) as well as multi-input multi-output (MIMO) self tuning regulators, applied to a typical system, are reported. Further, the effect of introducing a Super-conducting Magnetic Energy Storage (SMES) unit on the system performance has been investigated. The MIMO self-tuning regulator controlling the hybrid system and the SMES in a coordinated manner exhibits the best performance.
NASA Astrophysics Data System (ADS)
Abdul, M.; Farooq, U.; Akbar, Jehan; Saif, F.
2018-06-01
We transform the semi-classical laser equation for single mode homogeneously broadened lasers to a one-dimensional nonlinear map by using the discrete dynamical approach. The obtained mapping, referred to as laser logistic mapping (LLM), characteristically exhibits convergent, cyclic and chaotic behavior depending on the control parameter. Thus, the so obtained LLM explains stable, bistable, multi-stable, and chaotic solutions for output field intensity. The onset of bistability takes place at a critical value of the effective gain coefficient. The obtained analytical results are confirmed through numerical calculations.
Wang, Chunhua; Liu, Xiaoming; Xia, Hu
2017-03-01
In this paper, two kinds of novel ideal active flux-controlled smooth multi-piecewise quadratic nonlinearity memristors with multi-piecewise continuous memductance function are presented. The pinched hysteresis loop characteristics of the two memristor models are verified by building a memristor emulator circuit. Using the two memristor models establish a new memristive multi-scroll Chua's circuit, which can generate 2N-scroll and 2N+1-scroll chaotic attractors without any other ordinary nonlinear function. Furthermore, coexisting multi-scroll chaotic attractors are found in the proposed memristive multi-scroll Chua's circuit. Phase portraits, Lyapunov exponents, bifurcation diagrams, and equilibrium point analysis have been used to research the basic dynamics of the memristive multi-scroll Chua's circuit. The consistency of circuit implementation and numerical simulation verifies the effectiveness of the system design.
Statistical linearization for multi-input/multi-output nonlinearities
NASA Technical Reports Server (NTRS)
Lin, Ching-An; Cheng, Victor H. L.
1991-01-01
Formulas are derived for the computation of the random input-describing functions for MIMO nonlinearities; these straightforward and rigorous derivations are based on the optimal mean square linear approximation. The computations involve evaluations of multiple integrals. It is shown that, for certain classes of nonlinearities, multiple-integral evaluations are obviated and the computations are significantly simplified.
NASA Astrophysics Data System (ADS)
Cui, Guozeng; Xu, Shengyuan; Ma, Qian; Li, Yongmin; Zhang, Zhengqiang
2018-05-01
In this paper, the problem of prescribed performance distributed output consensus for higher-order non-affine nonlinear multi-agent systems with unknown dead-zone input is investigated. Fuzzy logical systems are utilised to identify the unknown nonlinearities. By introducing prescribed performance, the transient and steady performance of synchronisation errors are guaranteed. Based on Lyapunov stability theory and the dynamic surface control technique, a new distributed consensus algorithm for non-affine nonlinear multi-agent systems is proposed, which ensures cooperatively uniformly ultimately boundedness of all signals in the closed-loop systems and enables the output of each follower to synchronise with the leader within predefined bounded error. Finally, simulation examples are provided to demonstrate the effectiveness of the proposed control scheme.
NASA Technical Reports Server (NTRS)
Siwakosit, W.; Hess, R. A.; Bacon, Bart (Technical Monitor); Burken, John (Technical Monitor)
2000-01-01
A multi-input, multi-output reconfigurable flight control system design utilizing a robust controller and an adaptive filter is presented. The robust control design consists of a reduced-order, linear dynamic inversion controller with an outer-loop compensation matrix derived from Quantitative Feedback Theory (QFT). A principle feature of the scheme is placement of the adaptive filter in series with the QFT compensator thus exploiting the inherent robustness of the nominal flight control system in the presence of plant uncertainties. An example of the scheme is presented in a pilot-in-the-loop computer simulation using a simplified model of the lateral-directional dynamics of the NASA F18 High Angle of Attack Research Vehicle (HARV) that included nonlinear anti-wind up logic and actuator limitations. Prediction of handling qualities and pilot-induced oscillation tendencies in the presence of these nonlinearities is included in the example.
Flexible and multi-directional piezoelectric energy harvester for self-powered human motion sensor
NASA Astrophysics Data System (ADS)
Kim, Min-Ook; Pyo, Soonjae; Oh, Yongkeun; Kang, Yunsung; Cho, Kyung-Ho; Choi, Jungwook; Kim, Jongbaeg
2018-03-01
A flexible piezoelectric strain energy harvester that is responsive to multi-directional input forces produced by various human motions is proposed. The structure of the harvester, which includes a polydimethylsiloxane (PDMS) bump, facilitates the effective conversion of strain energy, produced by input forces applied in random directions, into electrical energy. The structural design of the PDMS bump and frame as well as the slits in the piezoelectric polyvinylidene fluoride (PVDF) film provide mechanical flexibility and enhance the strain induced in the PVDF film under input forces applied at various angles. The amount and direction of the strain induced in PVDF can be changed by the direction of the applied force; thus, the generated output power can be varied. The measured maximum output peak voltage is 1.75, 1.29, and 0.98 V when an input force of 4 N (2 Hz) is applied at angles of 0°, 45°, and 90°, and the corresponding maximum output power is 0.064, 0.026, and 0.02 μW, respectively. Moreover, the harvester stably generates output voltage over 1.4 × 104 cycles. Thus, the proposed harvester successfully identifies and converts strain energy produced by multi-directional input forces by various human motions into electrical energy. We demonstrate the potential utility of the proposed flexible energy harvester as a self-powered human motion sensor for wireless healthcare systems.
Optimized System Identification
NASA Technical Reports Server (NTRS)
Juang, Jer-Nan; Longman, Richard W.
1999-01-01
In system identification, one usually cares most about finding a model whose outputs are as close as possible to the true system outputs when the same input is applied to both. However, most system identification algorithms do not minimize this output error. Often they minimize model equation error instead, as in typical least-squares fits using a finite-difference model, and it is seen here that this distinction is significant. Here, we develop a set of system identification algorithms that minimize output error for multi-input/multi-output and multi-input/single-output systems. This is done with sequential quadratic programming iterations on the nonlinear least-squares problems, with an eigendecomposition to handle indefinite second partials. This optimization minimizes a nonlinear function of many variables, and hence can converge to local minima. To handle this problem, we start the iterations from the OKID (Observer/Kalman Identification) algorithm result. Not only has OKID proved very effective in practice, it minimizes an output error of an observer which has the property that as the data set gets large, it converges to minimizing the criterion of interest here. Hence, it is a particularly good starting point for the nonlinear iterations here. Examples show that the methods developed here eliminate the bias that is often observed using any system identification methods of either over-estimating or under-estimating the damping of vibration modes in lightly damped structures.
A comparison of two multi-variable integrator windup protection schemes
NASA Technical Reports Server (NTRS)
Mattern, Duane
1993-01-01
Two methods are examined for limit and integrator wind-up protection for multi-input, multi-output linear controllers subject to actuator constraints. The methods begin with an existing linear controller that satisfies the specifications for the nominal, small perturbation, linear model of the plant. The controllers are formulated to include an additional contribution to the state derivative calculations. The first method to be examined is the multi-variable version of the single-input, single-output, high gain, Conventional Anti-Windup (CAW) scheme. Except for the actuator limits, the CAW scheme is linear. The second scheme to be examined, denoted the Modified Anti-Windup (MAW) scheme, uses a scalar to modify the magnitude of the controller output vector while maintaining the vector direction. The calculation of the scalar modifier is a nonlinear function of the controller outputs and the actuator limits. In both cases the constrained actuator is tracked. These two integrator windup protection methods are demonstrated on a turbofan engine control system with five measurements, four control variables, and four actuators. The closed-loop responses of the two schemes are compared and contrasted during limit operation. The issue of maintaining the direction of the controller output vector using the Modified Anti-Windup scheme is discussed and the advantages and disadvantages of both of the IWP methods are presented.
Wide bandgap matrix switcher, amplifier and oscillator
Sampayan, Stephen
2016-08-16
An electronic device comprising an optical gate, an electrical input an electrical output and a wide bandgap material positioned between the electrical input and the electrical output to control an amount of current flowing between the electrical input and the electrical output in response to a stimulus received at the optical gate can be used in wideband telecommunication applications in transmission of multi-channel signals.
Single- and multi-channel underwater acoustic communication channel capacity: a computational study.
Hayward, Thomas J; Yang, T C
2007-09-01
Acoustic communication channel capacity determines the maximum data rate that can be supported by an acoustic channel for a given source power and source/receiver configuration. In this paper, broadband acoustic propagation modeling is applied to estimate the channel capacity for a time-invariant shallow-water waveguide for a single source-receiver pair and for vertical source and receiver arrays. Without bandwidth constraints, estimated single-input, single-output (SISO) capacities approach 10 megabitss at 1 km range, but beyond 2 km range they decay at a rate consistent with previous estimates by Peloquin and Leinhos (unpublished, 1997), which were based on a sonar equation calculation. Channel capacities subject to source bandwidth constraints are approximately 30-90% lower than for the unconstrained case, and exhibit a significant wind speed dependence. Channel capacity is investigated for single-input, multi-output (SIMO) and multi-input, multi-output (MIMO) systems, both for finite arrays and in the limit of a dense array spanning the entire water column. The limiting values of the SIMO and MIMO channel capacities for the modeled environment are found to be about four times higher and up to 200-400 times higher, respectively, than for the SISO case. Implications for underwater acoustic communication systems are discussed.
Kasnakoğlu, Coşku
2016-01-01
Some level of uncertainty is unavoidable in acquiring the mass, geometry parameters and stability derivatives of an aerial vehicle. In certain instances tiny perturbations of these could potentially cause considerable variations in flight characteristics. This research considers the impact of varying these parameters altogether. This is a generalization of examining the effects of particular parameters on selected modes present in existing literature. Conventional autopilot designs commonly assume that each flight channel is independent and develop single-input single-output (SISO) controllers for every one, that are utilized in parallel for actual flight. It is demonstrated that an attitude controller built like this can function flawlessly on separate nominal cases, but can become unstable with a perturbation no more than 2%. Two robust multi-input multi-output (MIMO) design strategies, specifically loop-shaping and μ-synthesis are outlined as potential substitutes and are observed to handle large parametric changes of 30% while preserving decent performance. Duplicating the loop-shaping procedure for the outer loop, a complete flight control system is formed. It is confirmed through software-in-the-loop (SIL) verifications utilizing blade element theory (BET) that the autopilot is capable of navigation and landing exposed to high parametric variations and powerful winds.
Kasnakoğlu, Coşku
2016-01-01
Some level of uncertainty is unavoidable in acquiring the mass, geometry parameters and stability derivatives of an aerial vehicle. In certain instances tiny perturbations of these could potentially cause considerable variations in flight characteristics. This research considers the impact of varying these parameters altogether. This is a generalization of examining the effects of particular parameters on selected modes present in existing literature. Conventional autopilot designs commonly assume that each flight channel is independent and develop single-input single-output (SISO) controllers for every one, that are utilized in parallel for actual flight. It is demonstrated that an attitude controller built like this can function flawlessly on separate nominal cases, but can become unstable with a perturbation no more than 2%. Two robust multi-input multi-output (MIMO) design strategies, specifically loop-shaping and μ-synthesis are outlined as potential substitutes and are observed to handle large parametric changes of 30% while preserving decent performance. Duplicating the loop-shaping procedure for the outer loop, a complete flight control system is formed. It is confirmed through software-in-the-loop (SIL) verifications utilizing blade element theory (BET) that the autopilot is capable of navigation and landing exposed to high parametric variations and powerful winds. PMID:27783706
Multi-service highly sensitive rectifier for enhanced RF energy scavenging.
Shariati, Negin; Rowe, Wayne S T; Scott, James R; Ghorbani, Kamran
2015-05-07
Due to the growing implications of energy costs and carbon footprints, the need to adopt inexpensive, green energy harvesting strategies are of paramount importance for the long-term conservation of the environment and the global economy. To address this, the feasibility of harvesting low power density ambient RF energy simultaneously from multiple sources is examined. A high efficiency multi-resonant rectifier is proposed, which operates at two frequency bands (478-496 and 852-869 MHz) and exhibits favorable impedance matching over a broad input power range (-40 to -10 dBm). Simulation and experimental results of input reflection coefficient and rectified output power are in excellent agreement, demonstrating the usefulness of this innovative low-power rectification technique. Measurement results indicate an effective efficiency of 54.3%, and an output DC voltage of 772.8 mV is achieved for a multi-tone input power of -10 dBm. Furthermore, the measured output DC power from harvesting RF energy from multiple services concurrently exhibits a 3.14 and 7.24 fold increase over single frequency rectification at 490 and 860 MHz respectively. Therefore, the proposed multi-service highly sensitive rectifier is a promising technique for providing a sustainable energy source for low power applications in urban environments.
Multi-Service Highly Sensitive Rectifier for Enhanced RF Energy Scavenging
Shariati, Negin; Rowe, Wayne S. T.; Scott, James R.; Ghorbani, Kamran
2015-01-01
Due to the growing implications of energy costs and carbon footprints, the need to adopt inexpensive, green energy harvesting strategies are of paramount importance for the long-term conservation of the environment and the global economy. To address this, the feasibility of harvesting low power density ambient RF energy simultaneously from multiple sources is examined. A high efficiency multi-resonant rectifier is proposed, which operates at two frequency bands (478–496 and 852–869 MHz) and exhibits favorable impedance matching over a broad input power range (−40 to −10 dBm). Simulation and experimental results of input reflection coefficient and rectified output power are in excellent agreement, demonstrating the usefulness of this innovative low-power rectification technique. Measurement results indicate an effective efficiency of 54.3%, and an output DC voltage of 772.8 mV is achieved for a multi-tone input power of −10 dBm. Furthermore, the measured output DC power from harvesting RF energy from multiple services concurrently exhibits a 3.14 and 7.24 fold increase over single frequency rectification at 490 and 860 MHz respectively. Therefore, the proposed multi-service highly sensitive rectifier is a promising technique for providing a sustainable energy source for low power applications in urban environments. PMID:25951137
Circuit for high resolution decoding of multi-anode microchannel array detectors
NASA Technical Reports Server (NTRS)
Kasle, David B. (Inventor)
1995-01-01
A circuit for high resolution decoding of multi-anode microchannel array detectors consisting of input registers accepting transient inputs from the anode array; anode encoding logic circuits connected to the input registers; midpoint pipeline registers connected to the anode encoding logic circuits; and pixel decoding logic circuits connected to the midpoint pipeline registers is described. A high resolution algorithm circuit operates in parallel with the pixel decoding logic circuit and computes a high resolution least significant bit to enhance the multianode microchannel array detector's spatial resolution by halving the pixel size and doubling the number of pixels in each axis of the anode array. A multiplexer is connected to the pixel decoding logic circuit and allows a user selectable pixel address output according to the actual multi-anode microchannel array detector anode array size. An output register concatenates the high resolution least significant bit onto the standard ten bit pixel address location to provide an eleven bit pixel address, and also stores the full eleven bit pixel address. A timing and control state machine is connected to the input registers, the anode encoding logic circuits, and the output register for managing the overall operation of the circuit.
NASA Technical Reports Server (NTRS)
Neilson, Jeffrey M. (Inventor)
2002-01-01
A horn has an input aperture and an output aperture, and comprises a conductive inner surface formed by rotating a curve about a central axis. The curve comprises a first arc having an input aperture end and a transition end, and a second arc having a transition end and an output aperture end. When rotated about the central axis, the first arc input aperture end forms an input aperture, and the second arc output aperture end forms an output aperture. The curve is then optimized to provide a mode conversion which maximizes the power transfer of input energy to the Gaussian mode at the output aperture.
Johnson, Steve A.
1990-01-01
An arrangement especially suitable for use in a laser apparatus for converting a plurality of different input light beams, for example copper vapor laser beams, into a plurality of substantially identical light beams is disclosed herein. This arrangement utilizes an optical mixing bar which is preferably integrally formed as a single unit and which includes a main body for mixing light therein, a flat input surface on one end of the main body, and a multi-faceted output face on the opposite end of the main body. This arrangement also includes means for directing the plurality of different input light beams onto the input face of the mixing base, whereby to cause the different beams to mix within the main body of the mixing bar and exit the latter from its multi-faceted output face as the desired plurality of substantially identical output beams.
Multi-output differential technologies
NASA Astrophysics Data System (ADS)
Bidare, Srinivas R.
1997-01-01
A differential is a very old and proven mechanical device that allows a single input to be split into two outputs having equal torque irrespective of the output speeds. A standard differential is capable of providing only two outputs from a single input. A recently patented multi-output differential technology known as `Plural-Output Differential' allows a single input to be split into many outputs. This new technology is the outcome of a systematic study of complex gear trains (Bidare 1992). The unique feature of a differential (equal torque at different speeds) can be applied to simplify the construction and operation of many complex mechanical devices that require equal torque's or forces at multiple outputs. It is now possible to design a mechanical hand with three or more fingers with equal torque. Since these finger are powered via a differential they are `mechanically intelligent'. A prototype device is operational and has been used to demonstrate the utility and flexibility of the design. In this paper we shall review two devices that utilize the new technology resulting in increased performance, robustness with reduced complexity and cost.
Continuous-Time Bilinear System Identification
NASA Technical Reports Server (NTRS)
Juang, Jer-Nan
2003-01-01
The objective of this paper is to describe a new method for identification of a continuous-time multi-input and multi-output bilinear system. The approach is to make judicious use of the linear-model properties of the bilinear system when subjected to a constant input. Two steps are required in the identification process. The first step is to use a set of pulse responses resulting from a constant input of one sample period to identify the state matrix, the output matrix, and the direct transmission matrix. The second step is to use another set of pulse responses with the same constant input over multiple sample periods to identify the input matrix and the coefficient matrices associated with the coupling terms between the state and the inputs. Numerical examples are given to illustrate the concept and the computational algorithm for the identification method.
Dynamic analysis of a buckled asymmetric piezoelectric beam for energy harvesting
DOE Office of Scientific and Technical Information (OSTI.GOV)
Van Blarigan, Louis, E-mail: louis01@umail.ucsb.edu; Moehlis, Jeff
2016-03-15
A model of a buckled beam energy harvester is analyzed to determine the phenomena behind the transition between high and low power output levels. It is shown that the presence of a chaotic attractor is a sufficient condition to predict high power output, though there are relatively small areas where high output is achieved without a chaotic attractor. The chaotic attractor appears as a product of a period doubling cascade or a boundary crisis. Bifurcation diagrams provide insight into the development of the chaotic region as the input power level is varied, as well as the intermixed periodic windows.
Dynamic modeling and parameter estimation of a radial and loop type distribution system network
DOE Office of Scientific and Technical Information (OSTI.GOV)
Jun Qui; Heng Chen; Girgis, A.A.
1993-05-01
This paper presents a new identification approach to three-phase power system modeling and model reduction taking power system network as multi-input, multi-output (MIMO) processes. The model estimate can be obtained in discrete-time input-output form, discrete- or continuous-time state-space variable form, or frequency-domain impedance transfer function matrix form. An algorithm for determining the model structure of this MIMO process is described. The effect of measurement noise on the approach is also discussed. This approach has been applied on a sample system and simulation results are also presented in this paper.
Wireless Sensor Network Optimization: Multi-Objective Paradigm.
Iqbal, Muhammad; Naeem, Muhammad; Anpalagan, Alagan; Ahmed, Ashfaq; Azam, Muhammad
2015-07-20
Optimization problems relating to wireless sensor network planning, design, deployment and operation often give rise to multi-objective optimization formulations where multiple desirable objectives compete with each other and the decision maker has to select one of the tradeoff solutions. These multiple objectives may or may not conflict with each other. Keeping in view the nature of the application, the sensing scenario and input/output of the problem, the type of optimization problem changes. To address different nature of optimization problems relating to wireless sensor network design, deployment, operation, planing and placement, there exist a plethora of optimization solution types. We review and analyze different desirable objectives to show whether they conflict with each other, support each other or they are design dependent. We also present a generic multi-objective optimization problem relating to wireless sensor network which consists of input variables, required output, objectives and constraints. A list of constraints is also presented to give an overview of different constraints which are considered while formulating the optimization problems in wireless sensor networks. Keeping in view the multi facet coverage of this article relating to multi-objective optimization, this will open up new avenues of research in the area of multi-objective optimization relating to wireless sensor networks.
Li, Yongming; Tong, Shaocheng
2017-12-01
In this paper, an adaptive fuzzy output constrained control design approach is addressed for multi-input multioutput uncertain stochastic nonlinear systems in nonstrict-feedback form. The nonlinear systems addressed in this paper possess unstructured uncertainties, unknown gain functions and unknown stochastic disturbances. Fuzzy logic systems are utilized to tackle the problem of unknown nonlinear uncertainties. The barrier Lyapunov function technique is employed to solve the output constrained problem. In the framework of backstepping design, an adaptive fuzzy control design scheme is constructed. All the signals in the closed-loop system are proved to be bounded in probability and the system outputs are constrained in a given compact set. Finally, the applicability of the proposed controller is well carried out by a simulation example.
Zhong, Dongzhou; Xu, Geliang; Luo, Wei; Xiao, Zhenzhen
2017-09-04
According to the principle of complete chaos synchronization and the theory of Hilbert phase transformation, we propose a novel real-time multi-target ranging scheme by using chaotic polarization laser radar in the drive-response vertical-cavity surface-emitting lasers (VCSELs). In the scheme, to ensure each polarization component (PC) of the master VCSEL (MVCSEL) to be synchronized steadily with that of the slave VCSEL, the output x-PC and y-PC from the MVCSEL in the drive system and those in the response system are modulated by the linear electro-optic effect simultaneously. Under this condition, by simulating the influences of some key parameters of the system on the synchronization quality and the relative errors of the two-target ranging, related operating parameters can be optimized. The x-PC and the y-PC, as two chaotic radar sources, are used to implement the real-time ranging for two targets. It is found that the measured distances of the two targets at arbitrary position exhibit strong real-time stability and only slight jitter. Their resolutions are up to millimeters, and their relative errors are very small and less than 2.7%.
Life Cycle Assessment of Mixed Municipal Solid Waste: Multi-input versus multi-output perspective.
Fiorentino, G; Ripa, M; Protano, G; Hornsby, C; Ulgiati, S
2015-12-01
This paper analyses four strategies for managing the Mixed Municipal Solid Waste (MMSW) in terms of their environmental impacts and potential advantages by means of Life Cycle Assessment (LCA) methodology. To this aim, both a multi-input and a multi-output approach are applied to evaluate the effect of these perspectives on selected impact categories. The analyzed management options include direct landfilling with energy recovery (S-1), Mechanical-Biological Treatment (MBT) followed by Waste-to-Energy (WtE) conversion (S-2), a combination of an innovative MBT/MARSS (Material Advanced Recovery Sustainable Systems) process and landfill disposal (S-3), and finally a combination of the MBT/MARSS process with WtE conversion (S-4). The MARSS technology, developed within an European LIFE PLUS framework and currently implemented at pilot plant scale, is an innovative MBT plant having the main goal to yield a Renewable Refined Biomass Fuel (RRBF) to be used for combined heat and power production (CHP) under the regulations enforced for biomass-based plants instead of Waste-to-Energy systems, for increased environmental performance. The four scenarios are characterized by different resource investment for plant and infrastructure construction and different quantities of matter, heat and electricity recovery and recycling. Results, calculated per unit mass of waste treated and per unit exergy delivered, under both multi-input and multi-output LCA perspectives, point out improved performance for scenarios characterized by increased matter and energy recovery. Although none of the investigated scenarios is capable to provide the best performance in all the analyzed impact categories, the scenario S-4 shows the best LCA results in the human toxicity and freshwater eutrophication categories, i.e. the ones with highest impacts in all waste management processes. Copyright © 2015 Elsevier Ltd. All rights reserved.
A single-layer platform for Boolean logic and arithmetic through DNA excision in mammalian cells
Weinberg, Benjamin H.; Hang Pham, N. T.; Caraballo, Leidy D.; Lozanoski, Thomas; Engel, Adrien; Bhatia, Swapnil; Wong, Wilson W.
2017-01-01
Genetic circuits engineered for mammalian cells often require extensive fine-tuning to perform their intended functions. To overcome this problem, we present a generalizable biocomputing platform that can engineer genetic circuits which function in human cells with minimal optimization. We used our Boolean Logic and Arithmetic through DNA Excision (BLADE) platform to build more than 100 multi-input-multi-output circuits. We devised a quantitative metric to evaluate the performance of the circuits in human embryonic kidney and Jurkat T cells. Of 113 circuits analysed, 109 functioned (96.5%) with the correct specified behavior without any optimization. We used our platform to build a three-input, two-output Full Adder and six-input, one-output Boolean Logic Look Up Table. We also used BLADE to design circuits with temporal small molecule-mediated inducible control and circuits that incorporate CRISPR/Cas9 to regulate endogenous mammalian genes. PMID:28346402
Control design methods for floating wind turbines for optimal disturbance rejection
NASA Astrophysics Data System (ADS)
Lemmer, Frank; Schlipf, David; Cheng, Po Wen
2016-09-01
An analysis of the floating wind turbine as a multi-input-multi-output system investigating the effect of the control inputs on the system outputs is shown. These effects are compared to the ones of the disturbances from wind and waves in order to give insights for the selection of the control layout. The frequencies with the largest impact on the outputs due to limited effect of the controlled variables are identified. Finally, an optimal controller is designed as a benchmark and compared to a conventional PI-controller using only the rotor speed as input. Here, the previously found system properties, especially the difficulties to damp responses to wave excitation, are confirmed and verified through a spectral analysis with realistic environmental conditions. This comparison also assesses the quality of the employed simplified linear simulation model compared to the nonlinear model and shows that such an efficient frequency-domain evaluation for control design is feasible.
Genetics-based control of a mimo boiler-turbine plant
DOE Office of Scientific and Technical Information (OSTI.GOV)
Dimeo, R.M.; Lee, K.Y.
1994-12-31
A genetic algorithm is used to develop an optimal controller for a non-linear, multi-input/multi-output boiler-turbine plant. The algorithm is used to train a control system for the plant over a wide operating range in an effort to obtain better performance. The results of the genetic algorithm`s controller designed from the linearized plant model at a nominal operating point. Because the genetic algorithm is well-suited to solving traditionally difficult optimization problems it is found that the algorithm is capable of developing the controller based on input/output information only. This controller achieves a performance comparable to the standard linear quadratic regulator.
Tunable single-photon multi-channel quantum router based on an optomechanical system
NASA Astrophysics Data System (ADS)
Ma, Peng-Cheng; Yan, Lei-Lei; Zhang, Jian; Chen, Gui-Bin; Li, Xiao-Wei; Zhan, You-Bang
2018-01-01
Routing of photons plays a key role in optical communication networks and quantum networks. Although the quantum routing of signals has been investigated for various systems, both in theory and experiment, the general form of a quantum router with multi-output terminals still needs to be explored. Here, we propose an experimentally accessible tunable single-photon multi-channel routing scheme using an optomechanics cavity which is Coulomb coupled to a nanomechanical resonator. The router can extract single photons from the coherent input signal and directly modulate them into three different output channels. More importantly, the two output signal frequencies can be selected by adjusting the Coulomb coupling strength. For application purposes, we justify that there is insignificant influence from the vacuum and thermal noises on the performance of the router under cryogenic conditions. Our proposal may pave a new avenue towards multi-channel routers and quantum networks.
Optimizing Indicator Choosing for Canal Control System and Simulation Study
USDA-ARS?s Scientific Manuscript database
One Key problem for canal system control is how to select appropriate performance indicators and how to tune the controller with these indicators. A canal system is a multi-input and multi-output (MIMO) system. The judging of control performance can be extremely complicated. In this paper, frequentl...
Fuzzy Neuron: Method and Hardware Realization
NASA Technical Reports Server (NTRS)
Krasowski, Michael J.; Prokop, Norman F.
2014-01-01
This innovation represents a method by which single-to-multi-input, single-to-many-output system transfer functions can be estimated from input/output data sets. This innovation can be run in the background while a system is operating under other means (e.g., through human operator effort), or may be utilized offline using data sets created from observations of the estimated system. It utilizes a set of fuzzy membership functions spanning the input space for each input variable. Linear combiners associated with combinations of input membership functions are used to create the output(s) of the estimator. Coefficients are adjusted online through the use of learning algorithms.
Wireless Sensor Network Optimization: Multi-Objective Paradigm
Iqbal, Muhammad; Naeem, Muhammad; Anpalagan, Alagan; Ahmed, Ashfaq; Azam, Muhammad
2015-01-01
Optimization problems relating to wireless sensor network planning, design, deployment and operation often give rise to multi-objective optimization formulations where multiple desirable objectives compete with each other and the decision maker has to select one of the tradeoff solutions. These multiple objectives may or may not conflict with each other. Keeping in view the nature of the application, the sensing scenario and input/output of the problem, the type of optimization problem changes. To address different nature of optimization problems relating to wireless sensor network design, deployment, operation, planing and placement, there exist a plethora of optimization solution types. We review and analyze different desirable objectives to show whether they conflict with each other, support each other or they are design dependent. We also present a generic multi-objective optimization problem relating to wireless sensor network which consists of input variables, required output, objectives and constraints. A list of constraints is also presented to give an overview of different constraints which are considered while formulating the optimization problems in wireless sensor networks. Keeping in view the multi facet coverage of this article relating to multi-objective optimization, this will open up new avenues of research in the area of multi-objective optimization relating to wireless sensor networks. PMID:26205271
MURI: Impact of Oceanographic Variability on Acoustic Communications
2011-09-01
multiplexing ( OFDM ), multiple- input/multiple-output ( MIMO ) transmissions, and multi-user single-input/multiple-output (SIMO) communications. Lastly... MIMO - OFDM communications: Receiver design for Doppler distorted underwater acoustic channels,” Proc. Asilomar Conf. on Signals, Systems, and... MIMO ) will be of particular interest. Validating experimental data will be obtained during the ONR acoustic communications experiment in summer 2008
Analysis of the performance of a wireless optical multi-input to multi-output communication system.
Bushuev, Denis; Arnon, Shlomi
2006-07-01
We investigate robust optical wireless communication in a highly scattering propagation medium using multielement optical detector arrays. The communication setup consists of synchronized multiple transmitters that send information to a receiver array and an atmospheric propagation channel. The mathematical model that best describes this scenario is multi-input to multi-output communication through stochastic slow changing channels. In this model, signals from m transmitters are received by n receiver-detectors. The channel transfer function matrix is G, and its size is n x m. G(i,j) is the transfer function from transmitter i to detector j, and m > or = n. We adopt a quasi-stationary approach in which the channel time variation has a negligible effect on communication performance over a burst. The G matrix is calculated on the basis of the optical transfer function of the atmospheric channel (composed of aerosol and turbulence elements) and the receiver's optics. In this work we derive a performance model using environmental data, such as documented turbulence and aerosol models and noise statistics. We also present the results of simulations conducted for the proposed detection algorithm.
Validation of a new modal performance measure for flexible controllers design
DOE Office of Scientific and Technical Information (OSTI.GOV)
Simo, J.B.; Tahan, S.A.; Kamwa, I.
1996-05-01
A new modal performance measure for power system stabilizer (PSS) optimization is proposed in this paper. The new method is based on modifying the square envelopes of oscillating modes, in order to take into account their damping ratios while minimizing the performance index. This criteria is applied to flexible controllers optimal design, on a multi-input-multi-output (MIMO) reduced-order model of a prototype power system. The multivariable model includes four generators, each having one input and one output. Linear time-response simulation and transient stability analysis with a nonlinear package confirm the superiority of the proposed criteria and illustrate its effectiveness in decentralizedmore » control.« less
Design and implementation of grid multi-scroll fractional-order chaotic attractors
DOE Office of Scientific and Technical Information (OSTI.GOV)
Chen, Liping, E-mail: lip-chenhut@126.com; Pan, Wei; Wu, Ranchao
2016-08-15
This paper proposes a novel approach for generating multi-scroll chaotic attractors in multi-directions for fractional-order (FO) systems. The stair nonlinear function series and the saturated nonlinear function are combined to extend equilibrium points with index 2 in a new FO linear system. With the help of stability theory of FO systems, stability of its equilibrium points is analyzed, and the chaotic behaviors are validated through phase portraits, Lyapunov exponents, and Poincaré section. Choosing the order 0.96 as an example, a circuit for generating 2-D grid multiscroll chaotic attractors is designed, and 2-D 9 × 9 grid FO attractors are observed at most.more » Numerical simulations and circuit experimental results show that the method is feasible and the designed circuit is correct.« less
Automatic insulation resistance testing apparatus
Wyant, Francis J.; Nowlen, Steven P.; Luker, Spencer M.
2005-06-14
An apparatus and method for automatic measurement of insulation resistances of a multi-conductor cable. In one embodiment of the invention, the apparatus comprises a power supply source, an input measuring means, an output measuring means, a plurality of input relay controlled contacts, a plurality of output relay controlled contacts, a relay controller and a computer. In another embodiment of the invention the apparatus comprises a power supply source, an input measuring means, an output measuring means, an input switching unit, an output switching unit and a control unit/data logger. Embodiments of the apparatus of the invention may also incorporate cable fire testing means. The apparatus and methods of the present invention use either voltage or current for input and output measured variables.
2012-03-22
Power Amplifier (7). A power amplifier was required to drive the actuators. For this research a Trek , Inc. Model PZD 700 Dual Channel Amplifier was used...while the flight test amplifier was being built. The Trek amplifier was capable of amplifying 32 Figure 3.19: dSpace MicroAutoBox II Digital...averaging of 25% was used to reduce the errors caused by noise but still maintain accuracy. For the laboratory Trek amplifier, a 100 millivolt input
Texas two-step: a framework for optimal multi-input single-output deconvolution.
Neelamani, Ramesh; Deffenbaugh, Max; Baraniuk, Richard G
2007-11-01
Multi-input single-output deconvolution (MISO-D) aims to extract a deblurred estimate of a target signal from several blurred and noisy observations. This paper develops a new two step framework--Texas Two-Step--to solve MISO-D problems with known blurs. Texas Two-Step first reduces the MISO-D problem to a related single-input single-output deconvolution (SISO-D) problem by invoking the concept of sufficient statistics (SSs) and then solves the simpler SISO-D problem using an appropriate technique. The two-step framework enables new MISO-D techniques (both optimal and suboptimal) based on the rich suite of existing SISO-D techniques. In fact, the properties of SSs imply that a MISO-D algorithm is mean-squared-error optimal if and only if it can be rearranged to conform to the Texas Two-Step framework. Using this insight, we construct new wavelet- and curvelet-based MISO-D algorithms with asymptotically optimal performance. Simulated and real data experiments verify that the framework is indeed effective.
Multi input single output model predictive control of non-linear bio-polymerization process
DOE Office of Scientific and Technical Information (OSTI.GOV)
Arumugasamy, Senthil Kumar; Ahmad, Z.
This paper focuses on Multi Input Single Output (MISO) Model Predictive Control of bio-polymerization process in which mechanistic model is developed and linked with the feedforward neural network model to obtain a hybrid model (Mechanistic-FANN) of lipase-catalyzed ring-opening polymerization of ε-caprolactone (ε-CL) for Poly (ε-caprolactone) production. In this research, state space model was used, in which the input to the model were the reactor temperatures and reactor impeller speeds and the output were the molecular weight of polymer (M{sub n}) and polymer polydispersity index. State space model for MISO created using System identification tool box of Matlab™. This state spacemore » model is used in MISO MPC. Model predictive control (MPC) has been applied to predict the molecular weight of the biopolymer and consequently control the molecular weight of biopolymer. The result shows that MPC is able to track reference trajectory and give optimum movement of manipulated variable.« less
Globally linearized control on diabatic continuous stirred tank reactor: a case study.
Jana, Amiya Kumar; Samanta, Amar Nath; Ganguly, Saibal
2005-07-01
This paper focuses on the promise of globally linearized control (GLC) structure in the realm of strongly nonlinear reactor system control. The proposed nonlinear control strategy is comprised of: (i) an input-output linearizing state feedback law (transformer), (ii) a state observer, and (iii) an external linear controller. The synthesis of discrete-time GLC controller for single-input single-output diabatic continuous stirred tank reactor (DCSTR) has been studied first, followed by the synthesis of feedforward/feedback controller for the same reactor having dead time in process as well as in disturbance. Subsequently, the multivariable GLC structure has been designed and then applied on multi-input multi-output DCSTR system. The simulation study shows high quality performance of the derived nonlinear controllers. The better-performed GLC in conjunction with reduced-order observer has been compared with the conventional proportional integral controller on the example reactor and superior performance has been achieved by the proposed GLC control scheme.
Synchronization and an application of a novel fractional order King Cobra chaotic system
DOE Office of Scientific and Technical Information (OSTI.GOV)
Muthukumar, P., E-mail: muthukumardgl@gmail.com; Balasubramaniam, P., E-mail: balugru@gmail.com; Ratnavelu, K., E-mail: kuru052001@gmail.com
2014-09-01
In this paper, we design a new three dimensional King Cobra face shaped fractional order chaotic system. The multi-scale synchronization scheme of two fractional order chaotic systems is described. The necessary conditions for the multi-scale synchronization of two identical fractional order King Cobra chaotic systems are derived through feedback control. A new cryptosystem is proposed for an image encryption and decryption by using synchronized fractional order King Cobra chaotic systems with the supports of multiple cryptographic assumptions. The security of the proposed cryptosystem is analyzed by the well known algebraic attacks. Numerical simulations are given to show the effectiveness ofmore » the proposed theoretical results.« less
Design and Implementation of Collaborative Research Approaches
NASA Technical Reports Server (NTRS)
Venti, Mike W.; Berger, David E.
2009-01-01
This poster reviews the collarborative research approaches that NASA has been designing and implementing for the Integrated Vehicle Health Management (IVHM) Project. The inputs for the technical plan are reviewed, the Research Test and Integration Plan (RTIP) WIKI, is used to create and propose a multi-themed and multi-partner research testing opportunities. The outputs are testing opportunities.
Generating multi-double-scroll attractors via nonautonomous approach.
Hong, Qinghui; Xie, Qingguo; Shen, Yi; Wang, Xiaoping
2016-08-01
It is a common phenomenon that multi-scroll attractors are realized by introducing the various nonlinear functions with multiple breakpoints in double scroll chaotic systems. Differently, we present a nonautonomous approach for generating multi-double-scroll attractors (MDSA) without changing the original nonlinear functions. By using the multi-level-logic pulse excitation technique in double scroll chaotic systems, MDSA can be generated. A Chua's circuit, a Jerk circuit, and a modified Lorenz system are given as designed example and the Matlab simulation results are presented. Furthermore, the corresponding realization circuits are designed. The Pspice results are in agreement with numerical simulation results, which verify the availability and feasibility of this method.
BaTMAn: Bayesian Technique for Multi-image Analysis
NASA Astrophysics Data System (ADS)
Casado, J.; Ascasibar, Y.; García-Benito, R.; Guidi, G.; Choudhury, O. S.; Bellocchi, E.; Sánchez, S. F.; Díaz, A. I.
2016-12-01
Bayesian Technique for Multi-image Analysis (BaTMAn) characterizes any astronomical dataset containing spatial information and performs a tessellation based on the measurements and errors provided as input. The algorithm iteratively merges spatial elements as long as they are statistically consistent with carrying the same information (i.e. identical signal within the errors). The output segmentations successfully adapt to the underlying spatial structure, regardless of its morphology and/or the statistical properties of the noise. BaTMAn identifies (and keeps) all the statistically-significant information contained in the input multi-image (e.g. an IFS datacube). The main aim of the algorithm is to characterize spatially-resolved data prior to their analysis.
Pure JavaScript Storyline Layout Algorithm
DOE Office of Scientific and Technical Information (OSTI.GOV)
This is a JavaScript library for a storyline layout algorithm. Storylines are adept at communicating complex change by encoding time on the x-axis and using the proximity of lines in the y direction to represent interaction between entities. The library in this disclosure takes as input a list of objects containing an id, time, and state. The output is a data structure that can be used to conveniently render a storyline visualization. Most importantly, the library computes the y-coordinate of the entities over time that decreases layout artifacts including crossings, wiggles, and whitespace. This is accomplished through multi-objective, multi-stage optimizationmore » problem, where the output of one stage produces input and constraints for the next stage.« less
Adaptive nonlinear control for autonomous ground vehicles
NASA Astrophysics Data System (ADS)
Black, William S.
We present the background and motivation for ground vehicle autonomy, and focus on uses for space-exploration. Using a simple design example of an autonomous ground vehicle we derive the equations of motion. After providing the mathematical background for nonlinear systems and control we present two common methods for exactly linearizing nonlinear systems, feedback linearization and backstepping. We use these in combination with three adaptive control methods: model reference adaptive control, adaptive sliding mode control, and extremum-seeking model reference adaptive control. We show the performances of each combination through several simulation results. We then consider disturbances in the system, and design nonlinear disturbance observers for both single-input-single-output and multi-input-multi-output systems. Finally, we show the performance of these observers with simulation results.
Time series modeling of human operator dynamics in manual control tasks
NASA Technical Reports Server (NTRS)
Biezad, D. J.; Schmidt, D. K.
1984-01-01
A time-series technique is presented for identifying the dynamic characteristics of the human operator in manual control tasks from relatively short records of experimental data. Control of system excitation signals used in the identification is not required. The approach is a multi-channel identification technique for modeling multi-input/multi-output situations. The method presented includes statistical tests for validity, is designed for digital computation, and yields estimates for the frequency responses of the human operator. A comprehensive relative power analysis may also be performed for validated models. This method is applied to several sets of experimental data; the results are discussed and shown to compare favorably with previous research findings. New results are also presented for a multi-input task that has not been previously modeled to demonstrate the strengths of the method.
Time Series Modeling of Human Operator Dynamics in Manual Control Tasks
NASA Technical Reports Server (NTRS)
Biezad, D. J.; Schmidt, D. K.
1984-01-01
A time-series technique is presented for identifying the dynamic characteristics of the human operator in manual control tasks from relatively short records of experimental data. Control of system excitation signals used in the identification is not required. The approach is a multi-channel identification technique for modeling multi-input/multi-output situations. The method presented includes statistical tests for validity, is designed for digital computation, and yields estimates for the frequency response of the human operator. A comprehensive relative power analysis may also be performed for validated models. This method is applied to several sets of experimental data; the results are discussed and shown to compare favorably with previous research findings. New results are also presented for a multi-input task that was previously modeled to demonstrate the strengths of the method.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Luh, G.C.
1994-01-01
This thesis presents the application of advanced modeling techniques to construct nonlinear forward and inverse models of internal combustion engines for the detection and isolation of incipient faults. The NARMAX (Nonlinear Auto-Regressive Moving Average modeling with eXogenous inputs) technique of system identification proposed by Leontaritis and Billings was used to derive the nonlinear model of a internal combustion engine, over operating conditions corresponding to the I/M240 cycle. The I/M240 cycle is a standard proposed by the United States Environmental Protection Agency to measure tailpipe emissions in inspection and maintenance programs and consists of a driving schedule developed for the purposemore » of testing compliance with federal vehicle emission standards for carbon monoxide, unburned hydrocarbons, and nitrogen oxides. The experimental work for model identification and validation was performed on a 3.0 liter V6 engine installed in an engine test cell at the Center for Automotive Research at The Ohio State University. In this thesis, different types of model structures were proposed to obtain multi-input multi-output (MIMO) nonlinear NARX models. A modification of the algorithm proposed by He and Asada was used to estimate the robust orders of the derived MIMO nonlinear models. A methodology for the analysis of inverse NARX model was developed. Two methods were proposed to derive the inverse NARX model: (1) inversion from the forward NARX model; and (2) direct identification of inverse model from the output-input data set. In this thesis, invertibility, minimum-phase characteristic of zero dynamics, and stability analysis of NARX forward model are also discussed. Stability in the sense of Lyapunov is also investigated to check the stability of the identified forward and inverse models. This application of inverse problem leads to the estimation of unknown inputs and to actuator fault diagnosis.« less
On codes with multi-level error-correction capabilities
NASA Technical Reports Server (NTRS)
Lin, Shu
1987-01-01
In conventional coding for error control, all the information symbols of a message are regarded equally significant, and hence codes are devised to provide equal protection for each information symbol against channel errors. However, in some occasions, some information symbols in a message are more significant than the other symbols. As a result, it is desired to devise codes with multilevel error-correcting capabilities. Another situation where codes with multi-level error-correcting capabilities are desired is in broadcast communication systems. An m-user broadcast channel has one input and m outputs. The single input and each output form a component channel. The component channels may have different noise levels, and hence the messages transmitted over the component channels require different levels of protection against errors. Block codes with multi-level error-correcting capabilities are also known as unequal error protection (UEP) codes. Structural properties of these codes are derived. Based on these structural properties, two classes of UEP codes are constructed.
A Novel Degradation Identification Method for Wind Turbine Pitch System
NASA Astrophysics Data System (ADS)
Guo, Hui-Dong
2018-04-01
It’s difficult for traditional threshold value method to identify degradation of operating equipment accurately. An novel degradation evaluation method suitable for wind turbine condition maintenance strategy implementation was proposed in this paper. Based on the analysis of typical variable-speed pitch-to-feather control principle and monitoring parameters for pitch system, a multi input multi output (MIMO) regression model was applied to pitch system, where wind speed, power generation regarding as input parameters, wheel rotation speed, pitch angle and motor driving currency for three blades as output parameters. Then, the difference between the on-line measurement and the calculated value from the MIMO regression model applying least square support vector machines (LSSVM) method was defined as the Observed Vector of the system. The Gaussian mixture model (GMM) was applied to fitting the distribution of the multi dimension Observed Vectors. Applying the model established, the Degradation Index was calculated using the SCADA data of a wind turbine damaged its pitch bearing retainer and rolling body, which illustrated the feasibility of the provided method.
Multi-muscle FES force control of the human arm for arbitrary goals.
Schearer, Eric M; Liao, Yu-Wei; Perreault, Eric J; Tresch, Matthew C; Memberg, William D; Kirsch, Robert F; Lynch, Kevin M
2014-05-01
We present a method for controlling a neuroprosthesis for a paralyzed human arm using functional electrical stimulation (FES) and characterize the errors of the controller. The subject has surgically implanted electrodes for stimulating muscles in her shoulder and arm. Using input/output data, a model mapping muscle stimulations to isometric endpoint forces measured at the subject's hand was identified. We inverted the model of this redundant and coupled multiple-input multiple-output system by minimizing muscle activations and used this inverse for feedforward control. The magnitude of the total root mean square error over a grid in the volume of achievable isometric endpoint force targets was 11% of the total range of achievable forces. Major sources of error were random error due to trial-to-trial variability and model bias due to nonstationary system properties. Because the muscles working collectively are the actuators of the skeletal system, the quantification of errors in force control guides designs of motion controllers for multi-joint, multi-muscle FES systems that can achieve arbitrary goals.
Extreme multistability in a memristor-based multi-scroll hyper-chaotic system.
Yuan, Fang; Wang, Guangyi; Wang, Xiaowei
2016-07-01
In this paper, a new memristor-based multi-scroll hyper-chaotic system is designed. The proposed memristor-based system possesses multiple complex dynamic behaviors compared with other chaotic systems. Various coexisting attractors and hidden coexisting attractors are observed in this system, which means extreme multistability arises. Besides, by adjusting parameters of the system, this chaotic system can perform single-scroll attractors, double-scroll attractors, and four-scroll attractors. Basic dynamic characteristics of the system are investigated, including equilibrium points and stability, bifurcation diagrams, Lyapunov exponents, and so on. In addition, the presented system is also realized by an analog circuit to confirm the correction of the numerical simulations.
Improved disturbance rejection for predictor-based control of MIMO linear systems with input delay
NASA Astrophysics Data System (ADS)
Shi, Shang; Liu, Wenhui; Lu, Junwei; Chu, Yuming
2018-02-01
In this paper, we are concerned with the predictor-based control of multi-input multi-output (MIMO) linear systems with input delay and disturbances. By taking the future values of disturbances into consideration, a new improved predictive scheme is proposed. Compared with the existing predictive schemes, our proposed predictive scheme can achieve a finite-time exact state prediction for some smooth disturbances including the constant disturbances, and a better disturbance attenuation can also be achieved for a large class of other time-varying disturbances. The attenuation of mismatched disturbances for second-order linear systems with input delay is also investigated by using our proposed predictor-based controller.
NASA Technical Reports Server (NTRS)
Craig, Roy R., Jr.
1987-01-01
The major accomplishments of this research are: (1) the refinement and documentation of a multi-input, multi-output modal parameter estimation algorithm which is applicable to general linear, time-invariant dynamic systems; (2) the development and testing of an unsymmetric block-Lanzcos algorithm for reduced-order modeling of linear systems with arbitrary damping; and (3) the development of a control-structure-interaction (CSI) test facility.
ERIC Educational Resources Information Center
Perelman, Sergio; Santin, Daniel
2011-01-01
The aim of the present paper is to examine the observed differences in Students' test performance across public and private-voucher schools in Spain. For this purpose, we explicitly consider that education is a multi-input multi-output production process subject to inefficient behaviors, which can be identified at student level using a parametric…
Real-Time Analysis of a Sensor's Data for Automated Decision Making in an IoT-Based Smart Home.
Khan, Nida Saddaf; Ghani, Sayeed; Haider, Sajjad
2018-05-25
IoT devices frequently generate large volumes of streaming data and in order to take advantage of this data, their temporal patterns must be learned and identified. Streaming data analysis has become popular after being successfully used in many applications including forecasting electricity load, stock market prices, weather conditions, etc. Artificial Neural Networks (ANNs) have been successfully utilized in understanding the embedded interesting patterns/behaviors in the data and forecasting the future values based on it. One such pattern is modelled and learned in the present study to identify the occurrence of a specific pattern in a Water Management System (WMS). This prediction aids in making an automatic decision support system, to switch OFF a hydraulic suction pump at the appropriate time. Three types of ANN, namely Multi-Input Multi-Output (MIMO), Multi-Input Single-Output (MISO), and Recurrent Neural Network (RNN) have been compared, for multi-step-ahead forecasting, on a sensor's streaming data. Experiments have shown that RNN has the best performance among three models and based on its prediction, a system can be implemented to make the best decision with 86% accuracy.
Solar System Chaos and its climatic and biogeochemical consequences
NASA Astrophysics Data System (ADS)
Ikeda, M.; Tada, R.; Ozaki, K.; Olsen, P. E.
2017-12-01
Insolation changes caused by changes in Earth's orbital parameters are the main driver of climatic variations, whose pace has been used for astronomically-calibrated geologic time scales of high accuracy to understand Earth system dynamics. However, the astrophysical models beyond several tens of million years ago have large uncertainty due to chaotic behavior of the Solar System, and its impact on amplitude modulation of multi-Myr-scale orbital variations and consequent climate changes has become the subject of debate. Here we show the geologic constraints on the past chaotic behavior of orbital cycles from early Mesozoic monsoon-related records; the 30-Myr-long lake level records of the lacustrine sequence in Newark-Hartford basins (North America) and 70-Myr-long biogenic silica (BSi) burial flux record of pelagic deep-sea chert sequence in Inuyama area (Japan). BSi burial flux of chert could be considered as proportional to the dissolved Si (DSi) input from chemical weathering on timescales longer than the residence time of DSi ( 100 kyr), because chert could represent a major sink for oceanic dissolved silica (Ikeda et al., 2017).These geologic records show multi-Myr cycles with similar frequency modulations of eccentricity solution of astronomical model La2010d (Laskar et al., 2011) compared with other astronomical solutions, but not exactly same. Our geologic records provide convincing evidence for the past chaotic dynamical behaviour of the Solar System and new and challenging additional constraints for astrophysical models. In addition, we find that ˜10 Myr cycle detected in monsoon proxies and their amplitude modulation of ˜2 Myr cycle may be related to the amplitude modulation of ˜2 Myr eccentricity cycle through non-linear process(es) of Earth system dynamics, suggesting possible impact of the chaotic behavior of Solar planets on climate change. Further impact of multi-Myr orbital cycles on global biogeochemical cycles will be discussed.
Feedback linearizing control of a MIMO power system
NASA Astrophysics Data System (ADS)
Ilyes, Laszlo
Prior research has demonstrated that either the mechanical or electrical subsystem of a synchronous electric generator may be controlled using single-input single-output (SISO) nonlinear feedback linearization. This research suggests a new approach which applies nonlinear feedback linearization to a multi-input multi-output (MIMO) model of the synchronous electric generator connected to an infinite bus load model. In this way, the electrical and mechanical subsystems may be linearized and simultaneously decoupled through the introduction of a pair of auxiliary inputs. This allows well known, linear, SISO control methods to be effectively applied to the resulting systems. The derivation of the feedback linearizing control law is presented in detail, including a discussion on the use of symbolic math processing as a development tool. The linearizing and decoupling properties of the control law are validated through simulation. And finally, the robustness of the control law is demonstrated.
Decentralised fixed modes of networked MIMO systems
NASA Astrophysics Data System (ADS)
Hao, Yuqing; Duan, Zhisheng; Chen, Guanrong
2018-04-01
In this paper, decentralised fixed modes (DFMs) of a networked system are studied. The network topology is directed and weighted and the nodes are higher-dimensional linear time-invariant (LTI) dynamical systems. The effects of the network topology, the node-system dynamics, the external control inputs, and the inner interactions on the existence of DFMs for the whole networked system are investigated. A necessary and sufficient condition for networked multi-input/multi-output (MIMO) systems in a general topology to possess no DFMs is derived. For networked single-input/single-output (SISO) LTI systems in general as well as some typical topologies, some specific conditions for having no DFMs are established. It is shown that the existence of DFMs is an integrated result of the aforementioned relevant factors which cannot be decoupled into individual DFMs of the node-systems and the properties solely determined by the network topology.
Quantized Synchronization of Chaotic Neural Networks With Scheduled Output Feedback Control.
Wan, Ying; Cao, Jinde; Wen, Guanghui
In this paper, the synchronization problem of master-slave chaotic neural networks with remote sensors, quantization process, and communication time delays is investigated. The information communication channel between the master chaotic neural network and slave chaotic neural network consists of several remote sensors, with each sensor able to access only partial knowledge of output information of the master neural network. At each sampling instants, each sensor updates its own measurement and only one sensor is scheduled to transmit its latest information to the controller's side in order to update the control inputs for the slave neural network. Thus, such communication process and control strategy are much more energy-saving comparing with the traditional point-to-point scheme. Sufficient conditions for output feedback control gain matrix, allowable length of sampling intervals, and upper bound of network-induced delays are derived to ensure the quantized synchronization of master-slave chaotic neural networks. Lastly, Chua's circuit system and 4-D Hopfield neural network are simulated to validate the effectiveness of the main results.In this paper, the synchronization problem of master-slave chaotic neural networks with remote sensors, quantization process, and communication time delays is investigated. The information communication channel between the master chaotic neural network and slave chaotic neural network consists of several remote sensors, with each sensor able to access only partial knowledge of output information of the master neural network. At each sampling instants, each sensor updates its own measurement and only one sensor is scheduled to transmit its latest information to the controller's side in order to update the control inputs for the slave neural network. Thus, such communication process and control strategy are much more energy-saving comparing with the traditional point-to-point scheme. Sufficient conditions for output feedback control gain matrix, allowable length of sampling intervals, and upper bound of network-induced delays are derived to ensure the quantized synchronization of master-slave chaotic neural networks. Lastly, Chua's circuit system and 4-D Hopfield neural network are simulated to validate the effectiveness of the main results.
A new chaotic multi-verse optimization algorithm for solving engineering optimization problems
NASA Astrophysics Data System (ADS)
Sayed, Gehad Ismail; Darwish, Ashraf; Hassanien, Aboul Ella
2018-03-01
Multi-verse optimization algorithm (MVO) is one of the recent meta-heuristic optimization algorithms. The main inspiration of this algorithm came from multi-verse theory in physics. However, MVO like most optimization algorithms suffers from low convergence rate and entrapment in local optima. In this paper, a new chaotic multi-verse optimization algorithm (CMVO) is proposed to overcome these problems. The proposed CMVO is applied on 13 benchmark functions and 7 well-known design problems in the engineering and mechanical field; namely, three-bar trust, speed reduce design, pressure vessel problem, spring design, welded beam, rolling element-bearing and multiple disc clutch brake. In the current study, a modified feasible-based mechanism is employed to handle constraints. In this mechanism, four rules were used to handle the specific constraint problem through maintaining a balance between feasible and infeasible solutions. Moreover, 10 well-known chaotic maps are used to improve the performance of MVO. The experimental results showed that CMVO outperforms other meta-heuristic optimization algorithms on most of the optimization problems. Also, the results reveal that sine chaotic map is the most appropriate map to significantly boost MVO's performance.
Generating multi-double-scroll attractors via nonautonomous approach
DOE Office of Scientific and Technical Information (OSTI.GOV)
Hong, Qinghui; Xie, Qingguo, E-mail: qgxie@mail.hust.edu.cn; Shen, Yi
It is a common phenomenon that multi-scroll attractors are realized by introducing the various nonlinear functions with multiple breakpoints in double scroll chaotic systems. Differently, we present a nonautonomous approach for generating multi-double-scroll attractors (MDSA) without changing the original nonlinear functions. By using the multi-level-logic pulse excitation technique in double scroll chaotic systems, MDSA can be generated. A Chua's circuit, a Jerk circuit, and a modified Lorenz system are given as designed example and the Matlab simulation results are presented. Furthermore, the corresponding realization circuits are designed. The Pspice results are in agreement with numerical simulation results, which verify themore » availability and feasibility of this method.« less
Evolution of Bow-Tie Architectures in Biology
Friedlander, Tamar; Mayo, Avraham E.; Tlusty, Tsvi; Alon, Uri
2015-01-01
Bow-tie or hourglass structure is a common architectural feature found in many biological systems. A bow-tie in a multi-layered structure occurs when intermediate layers have much fewer components than the input and output layers. Examples include metabolism where a handful of building blocks mediate between multiple input nutrients and multiple output biomass components, and signaling networks where information from numerous receptor types passes through a small set of signaling pathways to regulate multiple output genes. Little is known, however, about how bow-tie architectures evolve. Here, we address the evolution of bow-tie architectures using simulations of multi-layered systems evolving to fulfill a given input-output goal. We find that bow-ties spontaneously evolve when the information in the evolutionary goal can be compressed. Mathematically speaking, bow-ties evolve when the rank of the input-output matrix describing the evolutionary goal is deficient. The maximal compression possible (the rank of the goal) determines the size of the narrowest part of the network—that is the bow-tie. A further requirement is that a process is active to reduce the number of links in the network, such as product-rule mutations, otherwise a non-bow-tie solution is found in the evolutionary simulations. This offers a mechanism to understand a common architectural principle of biological systems, and a way to quantitate the effective rank of the goals under which they evolved. PMID:25798588
NASA Astrophysics Data System (ADS)
Koten, V. K.; Tanamal, C. E.
2017-03-01
Manufacturing agricultural products by the farmers, people or person who involve in medium industry, small industry, and households industry still be done in separately. Although the power on primemover is enough, in operations, primemover was only to move one of several agricultural products machine. This study attempts to design and construct power transmition multi output with single primemover; a single construction that allows primemover move some agricultur products machine in the same or not. This study begins with the determination of production capacity and the power to destroy products, the determination of resources and rotation, normalization of resources and rotation, the determination of the type material used, the size determination of each machine elements, construction machine elements, and assemble machine elements into a construction multi output power transmition with single primemover on agricultural products machine. The results show that with a input normalization 4 PK (2984 Watt), rotation 2000 rpm, the strength of material 60 kg/mm2, and several operating consideration, thus obtained size of machine elements through calculation. Based on the size, the machine elements is made through the use of some machine tools and assembled to form a multi output power transmition with single primemover.
NASA Astrophysics Data System (ADS)
Mohammad, Yasir K.; Pavlova, Olga N.; Pavlov, Alexey N.
2016-04-01
We discuss the problem of quantifying chaotic dynamics at the input of the "integrate-and-fire" (IF) model from the output sequences of interspike intervals (ISIs) for the case when the fluctuating threshold level leads to the appearance of noise in ISI series. We propose a way to detect an ability of computing dynamical characteristics of the input dynamics and the level of noise in the output point processes. The proposed approach is based on the dependence of the largest Lyapunov exponent from the maximal orientation error used at the estimation of the averaged rate of divergence of nearby phase trajectories.
GPC-Based Stable Reconfigurable Control
NASA Technical Reports Server (NTRS)
Soloway, Don; Shi, Jian-Jun; Kelkar, Atul
2004-01-01
This paper presents development of multi-input multi-output (MIMO) Generalized Pre-dictive Control (GPC) law and its application to reconfigurable control design in the event of actuator saturation. A Controlled Auto-Regressive Integrating Moving Average (CARIMA) model is used to describe the plant dynamics. The control law is derived using input-output description of the system and is also related to the state-space form of the model. The stability of the GPC control law without reconfiguration is first established using Riccati-based approach and state-space formulation. A novel reconfiguration strategy is developed for the systems which have actuator redundancy and are faced with actuator saturation type failure. An elegant reconfigurable control design is presented with stability proof. Several numerical examples are presented to demonstrate the application of various results.
Extreme multistability in a memristor-based multi-scroll hyper-chaotic system
DOE Office of Scientific and Technical Information (OSTI.GOV)
Yuan, Fang, E-mail: yf210yf@163.com; Wang, Guangyi, E-mail: wanggyi@163.com; Wang, Xiaowei
In this paper, a new memristor-based multi-scroll hyper-chaotic system is designed. The proposed memristor-based system possesses multiple complex dynamic behaviors compared with other chaotic systems. Various coexisting attractors and hidden coexisting attractors are observed in this system, which means extreme multistability arises. Besides, by adjusting parameters of the system, this chaotic system can perform single-scroll attractors, double-scroll attractors, and four-scroll attractors. Basic dynamic characteristics of the system are investigated, including equilibrium points and stability, bifurcation diagrams, Lyapunov exponents, and so on. In addition, the presented system is also realized by an analog circuit to confirm the correction of the numericalmore » simulations.« less
Yu, Xue; Lian, Wenjing; Zhang, Jiannan; Liu, Hongyun
2016-06-15
Herein, poly(N-isopropylacrylamide-co-N,N'-dimethylaminoethylmethacrylate) copolymer films were polymerized on electrode surface with a simple one-step method, and the enzyme horseradish peroxidase (HRP) was embedded in the films simultaneously, which were designated as P(NiPAAm-co-DMEM)-HRP. The films exhibited a reversible structure change with the external stimuli, such as pH, CO2, temperature and SO4(2-), causing the cyclic voltammetric (CV) response of electroactive K3Fe(CN)6 at the film electrodes to display the corresponding multi-stimuli sensitive ON-OFF behavior. Based on the switchable CV property of the system and the electrochemical reduction of H2O2 catalyzed by HRP in the films and mediated by Fe(CN)6(3-) in solution, a 5-input/3-output logic gate was established. To further increase the complexity of the logic system, another enzyme glucose oxidase (GOD) was added into the films, designated as P(NiPAAm-co-DMEM)-HRP-GOD. In the presence of oxygen, the oxidation of glucose in the solution was catalyzed by GOD in the films, and the produced H2O2 in situ was recognized and electrocatalytically reduced by HRP and mediated by Fe(CN)6(3-). Based on the bienzyme films, a cascaded or concatenated 4-input/3-output logic gate system was proposed. The present work combined the multi-responsive interface with bioelectrocatalysis to construct cascaded logic circuits, which might open a new avenue to develop biocomputing elements with more sophisticated functions and design novel glucose biosensors. Copyright © 2016 Elsevier B.V. All rights reserved.
NASA Astrophysics Data System (ADS)
vellaichamy, Lakshmanan; Paulraj, Sathiya
2018-02-01
The dissimilar welding of Incoloy 800HT and P91 steel using Gas Tungsten arc welding process (GTAW) This material is being used in the Nuclear Power Plant and Aerospace Industry based application because Incoloy 800HT possess good corrosion and oxidation resistance and P91 possess high temperature strength and creep resistance. This work discusses on multi-objective optimization using gray relational analysis (GRA) using 9CrMoV-N filler materials. The experiment conducted L9 orthogonal array. The input parameter are current, voltage, speed. The output response are Tensile strength, Hardness and Toughness. To optimize the input parameter and multiple output variable by using GRA. The optimal parameter is combination was determined as A2B1C1 so given input parameter welding current at 120 A, voltage at 16 V and welding speed at 0.94 mm/s. The output of the mechanical properties for best and least grey relational grade was validated by the metallurgical characteristics.
Devaney chaos, Li-Yorke chaos, and multi-dimensional Li-Yorke chaos for topological dynamics
NASA Astrophysics Data System (ADS)
Dai, Xiongping; Tang, Xinjia
2017-11-01
Let π : T × X → X, written T↷π X, be a topological semiflow/flow on a uniform space X with T a multiplicative topological semigroup/group not necessarily discrete. We then prove: If T↷π X is non-minimal topologically transitive with dense almost periodic points, then it is sensitive to initial conditions. As a result of this, Devaney chaos ⇒ Sensitivity to initial conditions, for this very general setting. Let R+↷π X be a C0-semiflow on a Polish space; then we show: If R+↷π X is topologically transitive with at least one periodic point p and there is a dense orbit with no nonempty interior, then it is multi-dimensional Li-Yorke chaotic; that is, there is a uncountable set Θ ⊆ X such that for any k ≥ 2 and any distinct points x1 , … ,xk ∈ Θ, one can find two time sequences sn → ∞ ,tn → ∞ with Moreover, let X be a non-singleton Polish space; then we prove: Any weakly-mixing C0-semiflow R+↷π X is densely multi-dimensional Li-Yorke chaotic. Any minimal weakly-mixing topological flow T↷π X with T abelian is densely multi-dimensional Li-Yorke chaotic. Any weakly-mixing topological flow T↷π X is densely Li-Yorke chaotic. We in addition construct a completely Li-Yorke chaotic minimal SL (2 , R)-acting flow on the compact metric space R ∪ { ∞ }. Our various chaotic dynamics are sensitive to the choices of the topology of the phase semigroup/group T.
NASA Astrophysics Data System (ADS)
Huang, Ya; Ferguson, Neil S.
2018-04-01
The study implements a classic signal analysis technique, typically applied to structural dynamics, to examine the nonlinear characteristics seen in the apparent mass of a recumbent person during whole-body horizontal random vibration. The nonlinearity in the present context refers to the amount of 'output' that is not correlated or coherent to the 'input', usually indicated by values of the coherence function that are less than unity. The analysis is based on the longitudinal horizontal inline and vertical cross-axis apparent mass of twelve human subjects exposed to 0.25-20 Hz random acceleration vibration at 0.125 and 1.0 ms-2 r.m.s. The conditioned reverse path frequency response functions (FRF) reveal that the uncorrelated 'linear' relationship between physical input (acceleration) and outputs (inline and cross-axis forces) has much greater variation around the primary resonance frequency between 0.5 and 5 Hz. By reversing the input and outputs of the physical system, it is possible to assemble additional mathematical inputs from the physical output forces and mathematical constructs (e.g. square root of inline force). Depending on the specific construct, this can improve the summed multiple coherence at frequencies where the response magnitude is low. In the present case this is between 6 and 20 Hz. The statistical measures of the response force time histories of each of the twelve subjects indicate that there are potential anatomical 'end-stops' for the sprung mass in the inline axis. No previous study has applied this reverse path multi-input-single-output approach to human vibration kinematic and kinetic data before. The implementation demonstrated in the present study will allow new and existing data to be examined using this different analytical tool.
Observer-Based Discrete-Time Nonnegative Edge Synchronization of Networked Systems.
Su, Housheng; Wu, Han; Chen, Xia
2017-10-01
This paper studies the multi-input and multi-output discrete-time nonnegative edge synchronization of networked systems based on neighbors' output information. The communication relationship among the edges of networked systems is modeled by well-known line graph. Two observer-based edge synchronization algorithms are designed, for which some necessary and sufficient synchronization conditions are derived. Moreover, some computable sufficient synchronization conditions are obtained, in which the feedback matrix and the observer matrix are computed by solving the linear programming problems. We finally design several simulation examples to demonstrate the validity of the given nonnegative edge synchronization algorithms.
Revised Multi-Node Well (MNW2) Package for MODFLOW Ground-Water Flow Model
Konikow, Leonard F.; Hornberger, George Z.; Halford, Keith J.; Hanson, Randall T.; Harbaugh, Arlen W.
2009-01-01
Wells that are open to multiple aquifers can provide preferential pathways to flow and solute transport that short-circuit normal fluid flowlines. Representing these features in a regional flow model can produce a more realistic and reliable simulation model. This report describes modifications to the Multi-Node Well (MNW) Package of the U.S. Geological Survey (USGS) three-dimensional ground-water flow model (MODFLOW). The modifications build on a previous version and add several new features, processes, and input and output options. The input structure of the revised MNW (MNW2) is more well-centered than the original verion of MNW (MNW1) and allows the user to easily define hydraulic characteristics of each multi-node well. MNW2 also allows calculations of additional head changes due to partial penetration effects, flow into a borehole through a seepage face, changes in well discharge related to changes in lift for a given pump, and intraborehole flows with a pump intake located at any specified depth within the well. MNW2 also offers an improved capability to simulate nonvertical wells. A new output option allows selected multi-node wells to be designated as 'observation wells' for which changes in selected variables with time will be written to separate output files to facilitate postprocessing. MNW2 is compatible with the MODFLOW-2000 and MODFLOW-2005 versions of MODFLOW and with the version of MODFLOW that includes the Ground-Water Transport process (MODFLOW-GWT).
NASA Astrophysics Data System (ADS)
Zhang, Jiancheng; Zhu, Fanglai
2018-03-01
In this paper, the output consensus of a class of linear heterogeneous multi-agent systems with unmatched disturbances is considered. Firstly, based on the relative output information among neighboring agents, we propose an asymptotic sliding-mode based consensus control scheme, under which, the output consensus error can converge to zero by removing the disturbances from output channels. Secondly, in order to reach the consensus goal, we design a novel high-order unknown input observer for each agent. It can estimate not only each agent's states and disturbances, but also the disturbances' high-order derivatives, which are required in the control scheme aforementioned above. The observer-based consensus control laws and the convergence analysis of the consensus error dynamics are given. Finally, a simulation example is provided to verify the validity of our methods.
Multi-diversity combining and selection for relay-assisted mixed RF/FSO system
NASA Astrophysics Data System (ADS)
Chen, Li; Wang, Weidong
2017-12-01
We propose and analyze multi-diversity combining and selection to enhance the performance of relay-assisted mixed radio frequency/free-space optics (RF/FSO) system. We focus on a practical scenario for cellular network where a single-antenna source is communicating to a multi-apertures destination through a relay equipped with multiple receive antennas and multiple transmit apertures. The RF single input multiple output (SIMO) links employ either maximal-ratio combining (MRC) or receive antenna selection (RAS), and the FSO multiple input multiple output (MIMO) links adopt either repetition coding (RC) or transmit laser selection (TLS). The performance is evaluated via an outage probability analysis over Rayleigh fading RF links and Gamma-Gamma atmospheric turbulence FSO links with pointing errors where channel state information (CSI) assisted amplify-and-forward (AF) scheme is considered. Asymptotic closed-form expressions at high signal-to-noise ratio (SNR) are also derived. Coding gain and diversity order for different combining and selection schemes are further discussed. Numerical results are provided to verify and illustrate the analytical results.
NASA Technical Reports Server (NTRS)
Kolaini, Ali R.; Doty, Benjamin; Chang, Zensheu
2012-01-01
Loudspeakers have been used for acoustic qualification of spacecraft, reflectors, solar panels, and other acoustically responsive structures for more than a decade. Limited measurements from some of the recent speaker tests used to qualify flight hardware have indicated significant spatial variation of the acoustic field within the test volume. Also structural responses have been reported to differ when similar tests were performed using reverberant chambers. To address the impact of non-uniform acoustic field on structural responses, a series of acoustic tests were performed using a flat panel and a 3-ft cylinder exposed to the field controlled by speakers and repeated in a reverberant chamber. The speaker testing was performed using multi-input-single-output (MISO) and multi-input-multi-output (MIMO) control schemes with and without the test articles. In this paper the spatial variation of the acoustic field due to acoustic standing waves and their impacts on the structural responses in RAT and DFAT (both using MISO and MIMO controls for DFAT) are discussed in some detail.
Research in Applied Mathematics Related to Mathematical System Theory.
1977-06-01
This report deals with research results obtained in the field of mathematical system theory . Special emphasis was given to the following areas: (1...Linear system theory over a field: parametrization of multi-input, multi-output systems and the geometric structure of classes of systems of...constant dimension. (2) Linear systems over a ring: development of the theory for very general classes of rings. (3) Nonlinear system theory : basic
2012-09-30
Estimation Methods for Underwater OFDM 5) Two Iterative Receivers for Distributed MIMO - OFDM with Large Doppler Deviations. 6) Asynchronous Multiuser...multi-input multi-output ( MIMO ) OFDM is also pursued, where it is shown that the proposed hybrid initialization enables drastically improved receiver...are investigated. 5) Two Iterative Receivers for Distributed MIMO - OFDM with Large Doppler Deviations. This work studies a distributed system with
Vibration suppression of a piezo-equipped cylindrical shell in a broad-band frequency domain
NASA Astrophysics Data System (ADS)
Loghmani, Ali; Danesh, Mohammad; Kwak, Moon K.; Keshmiri, Mehdi
2017-12-01
This paper focuses on the dynamic modeling of a cylindrical shell equipped with piezoceramic sensors and actuators, as well as the design of a broad band multi-input and multi-output linear quadratic Gaussian controller for the suppression of vibrations. The optimal locations of actuators are derived by Genetic Algorithm (GA) to effectively control the specific structural modes of the cylinder. The dynamic model is derived based on the Sanders shell theory and the energy approach for both the cylinder and the piezoelectric transducers, all of which reflect the piezoelectric effect. The natural vibration characteristics of the cylindrical shell are investigated both theoretically and experimentally. The theoretical predictions are in good agreement with the experimental results. Then, the broad band multi-input and multi-output linear quadratic Gaussian controller was designed and applied to the test article. An active vibration control experiment is carried out on the cylindrical shell and the digital control system is used to implement the proposed control algorithm. The experimental results show that vibrations of the cylindrical shell can be suppressed by the piezoceramic sensors and actuators along with the proposed controller. The optimal location of the actuators makes the proposed control system more efficient than other configurations.
Multi-valued logic gates based on ballistic transport in quantum point contacts.
Seo, M; Hong, C; Lee, S-Y; Choi, H K; Kim, N; Chung, Y; Umansky, V; Mahalu, D
2014-01-22
Multi-valued logic gates, which can handle quaternary numbers as inputs, are developed by exploiting the ballistic transport properties of quantum point contacts in series. The principle of a logic gate that finds the minimum of two quaternary number inputs is demonstrated. The device is scalable to allow multiple inputs, which makes it possible to find the minimum of multiple inputs in a single gate operation. Also, the principle of a half-adder for quaternary number inputs is demonstrated. First, an adder that adds up two quaternary numbers and outputs the sum of inputs is demonstrated. Second, a device to express the sum of the adder into two quaternary digits [Carry (first digit) and Sum (second digit)] is demonstrated. All the logic gates presented in this paper can in principle be extended to allow decimal number inputs with high quality QPCs.
Efficiency of static core turn-off in a system-on-a-chip with variation
Cher, Chen-Yong; Coteus, Paul W; Gara, Alan; Kursun, Eren; Paulsen, David P; Schuelke, Brian A; Sheets, II, John E; Tian, Shurong
2013-10-29
A processor-implemented method for improving efficiency of a static core turn-off in a multi-core processor with variation, the method comprising: conducting via a simulation a turn-off analysis of the multi-core processor at the multi-core processor's design stage, wherein the turn-off analysis of the multi-core processor at the multi-core processor's design stage includes a first output corresponding to a first multi-core processor core to turn off; conducting a turn-off analysis of the multi-core processor at the multi-core processor's testing stage, wherein the turn-off analysis of the multi-core processor at the multi-core processor's testing stage includes a second output corresponding to a second multi-core processor core to turn off; comparing the first output and the second output to determine if the first output is referring to the same core to turn off as the second output; outputting a third output corresponding to the first multi-core processor core if the first output and the second output are both referring to the same core to turn off.
NASA Astrophysics Data System (ADS)
Wang, Hongyan
2017-04-01
This paper addresses the waveform optimization problem for improving the detection performance of multi-input multioutput (MIMO) orthogonal frequency division multiplexing (OFDM) radar-based space-time adaptive processing (STAP) in the complex environment. By maximizing the output signal-to-interference-and-noise-ratio (SINR) criterion, the waveform optimization problem for improving the detection performance of STAP, which is subjected to the constant modulus constraint, is derived. To tackle the resultant nonlinear and complicated optimization issue, a diagonal loading-based method is proposed to reformulate the issue as a semidefinite programming one; thereby, this problem can be solved very efficiently. In what follows, the optimized waveform can be obtained to maximize the output SINR of MIMO-OFDM such that the detection performance of STAP can be improved. The simulation results show that the proposed method can improve the output SINR detection performance considerably as compared with that of uncorrelated waveforms and the existing MIMO-based STAP method.
NASA Astrophysics Data System (ADS)
Radac, Mircea-Bogdan; Precup, Radu-Emil; Roman, Raul-Cristian
2017-04-01
This paper proposes the combination of two model-free controller tuning techniques, namely linear virtual reference feedback tuning (VRFT) and nonlinear state-feedback Q-learning, referred to as a new mixed VRFT-Q learning approach. VRFT is first used to find stabilising feedback controller using input-output experimental data from the process in a model reference tracking setting. Reinforcement Q-learning is next applied in the same setting using input-state experimental data collected under perturbed VRFT to ensure good exploration. The Q-learning controller learned with a batch fitted Q iteration algorithm uses two neural networks, one for the Q-function estimator and one for the controller, respectively. The VRFT-Q learning approach is validated on position control of a two-degrees-of-motion open-loop stable multi input-multi output (MIMO) aerodynamic system (AS). Extensive simulations for the two independent control channels of the MIMO AS show that the Q-learning controllers clearly improve performance over the VRFT controllers.
Overview of multi-input frequency domain modal testing methods with an emphasis on sine testing
NASA Technical Reports Server (NTRS)
Rost, Robert W.; Brown, David L.
1988-01-01
An overview of the current state of the art multiple-input, multiple-output modal testing technology is discussed. A very brief review of the current time domain methods is given. A detailed review of frequency and spatial domain methods is presented with an emphasis on sine testing.
A fully dynamic model of a multi-layer piezoelectric actuator incorporating the power amplifier
NASA Astrophysics Data System (ADS)
Zhu, Wei; Yang, Fufeng; Rui, Xiaoting
2017-12-01
The dynamic input-output characteristics of the multi-layer piezoelectric actuator (PA) are intrinsically rate-dependent and hysteresis. Meanwhile, aiming at the strong capacitive impedance of multi-layer PA, the power amplifier of the actuator can greatly affect the dynamic performances of the actuator. In this paper, a novel dynamic model that includes a model of the electric circuit providing voltage to the actuator, an inverse piezoelectric effect model describing the hysteresis and creep behavior of the actuator, and a mechanical model, in which the vibration characteristics of the multi-layer PA is described, is put forward. Validation experimental tests are conducted. Experimental results show that the proposed dynamic model can accurately predict the fully dynamic behavior of the multi-layer PA with different driving power.
NASA Technical Reports Server (NTRS)
Meyn, Larry A.
2018-01-01
One of the goals of NASA's Revolutionary Vertical Lift Technology Project (RVLT) is to provide validated tools for multidisciplinary design, analysis and optimization (MDAO) of vertical lift vehicles. As part of this effort, the software package, RotorCraft Optimization Tools (RCOTOOLS), is being developed to facilitate incorporating key rotorcraft conceptual design codes into optimizations using the OpenMDAO multi-disciplinary optimization framework written in Python. RCOTOOLS, also written in Python, currently supports the incorporation of the NASA Design and Analysis of RotorCraft (NDARC) vehicle sizing tool and the Comprehensive Analytical Model of Rotorcraft Aerodynamics and Dynamics II (CAMRAD II) analysis tool into OpenMDAO-driven optimizations. Both of these tools use detailed, file-based inputs and outputs, so RCOTOOLS provides software wrappers to update input files with new design variable values, execute these codes and then extract specific response variable values from the file outputs. These wrappers are designed to be flexible and easy to use. RCOTOOLS also provides several utilities to aid in optimization model development, including Graphical User Interface (GUI) tools for browsing input and output files in order to identify text strings that are used to identify specific variables as optimization input and response variables. This paper provides an overview of RCOTOOLS and its use
NASA Technical Reports Server (NTRS)
Polotzky, Anthony S.; Wieseman, Carol; Hoadley, Sherwood Tiffany; Mukhopadhyay, Vivek
1990-01-01
The development of a controller performance evaluation (CPE) methodology for multiinput/multioutput digital control systems is described. The equations used to obtain the open-loop plant, controller transfer matrices, and return-difference matrices are given. Results of applying the CPE methodology to evaluate MIMO digital flutter suppression systems being tested on an active flexible wing wind-tunnel model are presented to demonstrate the CPE capability.
NASA Astrophysics Data System (ADS)
Zheng, Guangdi; Pan, Mingbo; Liu, Wei; Wu, Xuetong
2018-03-01
The target identification of the sea battlefield is the prerequisite for the judgment of the enemy in the modern naval battle. In this paper, a collaborative identification method based on convolution neural network is proposed to identify the typical targets of sea battlefields. Different from the traditional single-input/single-output identification method, the proposed method constructs a multi-input/single-output co-identification architecture based on optimized convolution neural network and weighted D-S evidence theory. The simulation results show that
The Correlation of Human Capital on Costs of Air Force Acquisition Programs
2009-03-01
6.78 so our model does not exhibit the presence of multi-collinearity. We empirically tested for heteroskedasticity using the Breusch - Pagan -Godfrey...inputs to outputs. The output in this study is the average cost overrun of Aeronautical Systems Center research, development, test , and evaluation...32 Pre-Estimation Specification Tests ............................................................................34 Post
Advanced information processing system: Local system services
NASA Technical Reports Server (NTRS)
Burkhardt, Laura; Alger, Linda; Whittredge, Roy; Stasiowski, Peter
1989-01-01
The Advanced Information Processing System (AIPS) is a multi-computer architecture composed of hardware and software building blocks that can be configured to meet a broad range of application requirements. The hardware building blocks are fault-tolerant, general-purpose computers, fault-and damage-tolerant networks (both computer and input/output), and interfaces between the networks and the computers. The software building blocks are the major software functions: local system services, input/output, system services, inter-computer system services, and the system manager. The foundation of the local system services is an operating system with the functions required for a traditional real-time multi-tasking computer, such as task scheduling, inter-task communication, memory management, interrupt handling, and time maintenance. Resting on this foundation are the redundancy management functions necessary in a redundant computer and the status reporting functions required for an operator interface. The functional requirements, functional design and detailed specifications for all the local system services are documented.
Identification and control of a multizone crystal growth furnace
NASA Technical Reports Server (NTRS)
Batur, C.; Sharpless, R. B.; Duval, W. M. B.; Rosenthal, B. N.; Singh, N. B.
1992-01-01
This paper presents an intelligent adaptive control system for the control of a solid-liquid interface of a crystal while it is growing via directional solidification inside a multizone transparent furnace. The task of the process controller is to establish a user-specified axial temperature profile and to maintain a desirable interface shape. Both single-input-single-output and multi-input-multi-output adaptive pole placement algorithms have been used to control the temperature. Also described is an intelligent measurement system to assess the shape of the crystal while it is growing. A color video imaging system observes the crystal in real time and determines the position and the shape of the interface. This information is used to evaluate the crystal growth rate, and to analyze the effects of translational velocity and temperature profiles on the shape of the interface. Creation of this knowledge base is the first step to incorporate image processing into furnace control.
NASA Technical Reports Server (NTRS)
Guo, Tong-Yi; Hwang, Chyi; Shieh, Leang-San
1994-01-01
This paper deals with the multipoint Cauer matrix continued-fraction expansion (MCFE) for model reduction of linear multi-input multi-output (MIMO) systems with various numbers of inputs and outputs. A salient feature of the proposed MCFE approach to model reduction of MIMO systems with square transfer matrices is its equivalence to the matrix Pade approximation approach. The Cauer second form of the ordinary MCFE for a square transfer function matrix is generalized in this paper to a multipoint and nonsquare-matrix version. An interesting connection of the multipoint Cauer MCFE method to the multipoint matrix Pade approximation method is established. Also, algorithms for obtaining the reduced-degree matrix-fraction descriptions and reduced-dimensional state-space models from a transfer function matrix via the multipoint Cauer MCFE algorithm are presented. Practical advantages of using the multipoint Cauer MCFE are discussed and a numerical example is provided to illustrate the algorithms.
Development of a compact and cost effective multi-input digital signal processing system
NASA Astrophysics Data System (ADS)
Darvish-Molla, Sahar; Chin, Kenrick; Prestwich, William V.; Byun, Soo Hyun
2018-01-01
A prototype digital signal processing system (DSP) was developed using a microcontroller interfaced with a 12-bit sampling ADC, which offers a considerably inexpensive solution for processing multiple detectors with high throughput. After digitization of the incoming pulses, in order to maximize the output counting rate, a simple algorithm was employed for pulse height analysis. Moreover, an algorithm aiming at the real-time pulse pile-up deconvolution was implemented. The system was tested using a NaI(Tl) detector in comparison with a traditional analogue and commercial digital systems for a variety of count rates. The performance of the prototype system was consistently superior to the analogue and the commercial digital systems up to the input count rate of 61 kcps while was slightly inferior to the commercial digital system but still superior to the analogue system in the higher input rates. Considering overall cost, size and flexibility, this custom made multi-input digital signal processing system (MMI-DSP) was the best reliable choice for the purpose of the 2D microdosimetric data collection, or for any measurement in which simultaneous multi-data collection is required.
Engelken, Rainer; Farkhooi, Farzad; Hansel, David; van Vreeswijk, Carl; Wolf, Fred
2016-01-01
Neuronal activity in the central nervous system varies strongly in time and across neuronal populations. It is a longstanding proposal that such fluctuations generically arise from chaotic network dynamics. Various theoretical studies predict that the rich dynamics of rate models operating in the chaotic regime can subserve circuit computation and learning. Neurons in the brain, however, communicate via spikes and it is a theoretical challenge to obtain similar rate fluctuations in networks of spiking neuron models. A recent study investigated spiking balanced networks of leaky integrate and fire (LIF) neurons and compared their dynamics to a matched rate network with identical topology, where single unit input-output functions were chosen from isolated LIF neurons receiving Gaussian white noise input. A mathematical analogy between the chaotic instability in networks of rate units and the spiking network dynamics was proposed. Here we revisit the behavior of the spiking LIF networks and these matched rate networks. We find expected hallmarks of a chaotic instability in the rate network: For supercritical coupling strength near the transition point, the autocorrelation time diverges. For subcritical coupling strengths, we observe critical slowing down in response to small external perturbations. In the spiking network, we found in contrast that the timescale of the autocorrelations is insensitive to the coupling strength and that rate deviations resulting from small input perturbations rapidly decay. The decay speed even accelerates for increasing coupling strength. In conclusion, our reanalysis demonstrates fundamental differences between the behavior of pulse-coupled spiking LIF networks and rate networks with matched topology and input-output function. In particular there is no indication of a corresponding chaotic instability in the spiking network.
Radac, Mircea-Bogdan; Precup, Radu-Emil; Roman, Raul-Cristian
2018-02-01
This paper proposes a combined Virtual Reference Feedback Tuning-Q-learning model-free control approach, which tunes nonlinear static state feedback controllers to achieve output model reference tracking in an optimal control framework. The novel iterative Batch Fitted Q-learning strategy uses two neural networks to represent the value function (critic) and the controller (actor), and it is referred to as a mixed Virtual Reference Feedback Tuning-Batch Fitted Q-learning approach. Learning convergence of the Q-learning schemes generally depends, among other settings, on the efficient exploration of the state-action space. Handcrafting test signals for efficient exploration is difficult even for input-output stable unknown processes. Virtual Reference Feedback Tuning can ensure an initial stabilizing controller to be learned from few input-output data and it can be next used to collect substantially more input-state data in a controlled mode, in a constrained environment, by compensating the process dynamics. This data is used to learn significantly superior nonlinear state feedback neural networks controllers for model reference tracking, using the proposed Batch Fitted Q-learning iterative tuning strategy, motivating the original combination of the two techniques. The mixed Virtual Reference Feedback Tuning-Batch Fitted Q-learning approach is experimentally validated for water level control of a multi input-multi output nonlinear constrained coupled two-tank system. Discussions on the observed control behavior are offered. Copyright © 2018 ISA. Published by Elsevier Ltd. All rights reserved.
Simulation requirements for the Large Deployable Reflector (LDR)
NASA Technical Reports Server (NTRS)
Soosaar, K.
1984-01-01
Simulation tools for the large deployable reflector (LDR) are discussed. These tools are often the transfer function variety equations. However, transfer functions are inadequate to represent time-varying systems for multiple control systems with overlapping bandwidths characterized by multi-input, multi-output features. Frequency domain approaches are the useful design tools, but a full-up simulation is needed. Because of the need for a dedicated computer for high frequency multi degree of freedom components encountered, non-real time smulation is preferred. Large numerical analysis software programs are useful only to receive inputs and provide output to the next block, and should be kept out of the direct loop of simulation. The following blocks make up the simulation. The thermal model block is a classical heat transfer program. It is a non-steady state program. The quasistatic block deals with problems associated with rigid body control of reflector segments. The steady state block assembles data into equations of motion and dynamics. A differential raytrace is obtained to establish a change in wave aberrations. The observation scene is described. The focal plane module converts the photon intensity impinging on it into electron streams or into permanent film records.
DOE Office of Scientific and Technical Information (OSTI.GOV)
FINSTERLE, STEFAN; JUNG, YOOJIN; KOWALSKY, MICHAEL
2016-09-15
iTOUGH2 (inverse TOUGH2) provides inverse modeling capabilities for TOUGH2, a simulator for multi-dimensional, multi-phase, multi-component, non-isothermal flow and transport in fractured porous media. iTOUGH2 performs sensitivity analyses, data-worth analyses, parameter estimation, and uncertainty propagation analyses in geosciences and reservoir engineering and other application areas. iTOUGH2 supports a number of different combinations of fluids and components (equation-of-state (EOS) modules). In addition, the optimization routines implemented in iTOUGH2 can also be used for sensitivity analysis, automatic model calibration, and uncertainty quantification of any external code that uses text-based input and output files using the PEST protocol. iTOUGH2 solves the inverse problem bymore » minimizing a non-linear objective function of the weighted differences between model output and the corresponding observations. Multiple minimization algorithms (derivative-free, gradient-based, and second-order; local and global) are available. iTOUGH2 also performs Latin Hypercube Monte Carlo simulations for uncertainty propagation analyses. A detailed residual and error analysis is provided. This upgrade includes (a) global sensitivity analysis methods, (b) dynamic memory allocation (c) additional input features and output analyses, (d) increased forward simulation capabilities, (e) parallel execution on multicore PCs and Linux clusters, and (f) bug fixes. More details can be found at http://esd.lbl.gov/iTOUGH2.« less
Early Examples from the Integrated Multi-Satellite Retrievals for GPM (IMERG)
NASA Astrophysics Data System (ADS)
Huffman, George; Bolvin, David; Braithwaite, Daniel; Hsu, Kuolin; Joyce, Robert; Kidd, Christopher; Sorooshian, Soroosh; Xie, Pingping
2014-05-01
The U.S. GPM Science Team's Day-1 algorithm for computing combined precipitation estimates as part of GPM is the Integrated Multi-satellitE Retrievals for GPM (IMERG). The goal is to compute the best time series of (nearly) global precipitation from "all" precipitation-relevant satellites and global surface precipitation gauge analyses. IMERG is being developed as a unified U.S. algorithm drawing on strengths in the three contributing groups, whose previous work includes: 1) the TRMM Multi-satellite Precipitation Analysis (TMPA); 2) the CPC Morphing algorithm with Kalman Filtering (K-CMORPH); and 3) the Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks using a Cloud Classification System (PERSIANN-CCS). We review the IMERG design and development, plans for testing, and current status. Some of the lessons learned in running and reprocessing the previous data sets include the importance of quality-controlling input data sets, strategies for coping with transitions in the various input data sets, and practical approaches to retrospective analysis of multiple output products (namely the real- and post-real-time data streams). IMERG output will be illustrated using early test data, including the variety of supporting fields, such as the merged-microwave and infrared estimates, and the precipitation type. We end by considering recent changes in input data specifications, the transition from TRMM-based calibration to GPM-based, and further "Day 2" development.
Salgado, Iván; Mera-Hernández, Manuel; Chairez, Isaac
2017-11-01
This study addresses the problem of designing an output-based controller to stabilize multi-input multi-output (MIMO) systems in the presence of parametric disturbances as well as uncertainties in the state model and output noise measurements. The controller design includes a linear state transformation which separates uncertainties matched to the control input and the unmatched ones. A differential neural network (DNN) observer produces a nonlinear approximation of the matched perturbation and the unknown states simultaneously in the transformed coordinates. This study proposes the use of the Attractive Ellipsoid Method (AEM) to optimize the gains of the controller and the gain observer in the DNN structure. As a consequence, the obtained control input minimizes the convergence zone for the estimation error. Moreover, the control design uses the estimated disturbance provided by the DNN to obtain a better performance in the stabilization task in comparison with a quasi-minimal output feedback controller based on a Luenberger observer and a sliding mode controller. Numerical results pointed out the advantages obtained by the nonlinear control based on the DNN observer. The first example deals with the stabilization of an academic linear MIMO perturbed system and the second example stabilizes the trajectories of a DC-motor into a predefined operation point. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.
Convolutional neural network for road extraction
NASA Astrophysics Data System (ADS)
Li, Junping; Ding, Yazhou; Feng, Fajie; Xiong, Baoyu; Cui, Weihong
2017-11-01
In this paper, the convolution neural network with large block input and small block output was used to extract road. To reflect the complex road characteristics in the study area, a deep convolution neural network VGG19 was conducted for road extraction. Based on the analysis of the characteristics of different sizes of input block, output block and the extraction effect, the votes of deep convolutional neural networks was used as the final road prediction. The study image was from GF-2 panchromatic and multi-spectral fusion in Yinchuan. The precision of road extraction was 91%. The experiments showed that model averaging can improve the accuracy to some extent. At the same time, this paper gave some advice about the choice of input block size and output block size.
1990-12-01
methods are implemented in MATRIXx with the programs SISOTF and MIMOTF respectively. Following the mathe - matical development, the application of these...intent is not to teach any of the methods , it has been written in a manner to significantly assist an individual attempting follow on work. I would...equivalent plant models. A detailed mathematical development of the method used to develop these equivalent LTI plant models is provided. After this inner
2012-03-01
0-486-41183-4. 15. Brown , Robert G. and Patrick Y. C. Hwang . Introduction to Random Signals and Applied Kalman Filtering. Wiley, New York, 1996. ISBN...stability and perfor- mance criteria. In the 1960’s, Kalman introduced the Linear Quadratic Regulator (LQR) method using an integral performance index...feedback of the state variables and was able to apply this method to time-varying and Multi-Input Multi-Output (MIMO) systems. Kalman further showed
Rapid rotational/translational maneuvering experiments of a flexible steel beam
NASA Technical Reports Server (NTRS)
Juang, Jer-Nan; Yang, Li-Farn; Huanag, Jen-Kuang; Macauley, Richard
1989-01-01
Future space manipulators may need translational base motion to expand the access region of a manipulator. An experiment was conducted to demonstrate slewing of flexible structures with coupled rotational and translational axes while simultaneously suppressing vibrational motion during the maneuver. In the experiment, a flexible steel beam carried by a translational cart was maneuvered by an active controller to perform position-control tasks. Experimental results are presented to show how the flexibility of the steel beam influences the multi-input multi-output feedback controller.
NASA Astrophysics Data System (ADS)
Hahn, S. J.; Fawley, W. M.; Kim, K. J.; Edighoffer, J. A.
1994-12-01
The authors examine the performance of the so-called electron output scheme recently proposed by the Novosibirsk group. In this scheme, the key role of the FEL oscillator is to induce bunching, while an external undulator, called the radiator, then outcouples the bunched electron beam to optical energy via coherent emission. The level of the intracavity power in the oscillator is kept low by employing a transverse optical klystron (TOK) configuration, thus avoiding excessive thermal loading on the cavity mirrors. Time-dependent effects are important in the operation of the electron output scheme because high gain in the TOK oscillator leads to sideband instabilities and chaotic behavior. The authors have carried out an extensive simulation study by using 1D and 2D time-dependent codes and find that proper control of the oscillator cavity detuning and cavity loss results in high output bunching with a narrow spectral bandwidth. Large cavity detuning in the oscillator and tapering of the radiator undulator is necessary for the optimum output power.
Mechanical System Analysis/Design Tool (MSAT) Quick Guide
NASA Technical Reports Server (NTRS)
Lee, HauHua; Kolb, Mark; Madelone, Jack
1998-01-01
MSAT is a unique multi-component multi-disciplinary tool that organizes design analysis tasks around object-oriented representations of configuration components, analysis programs and modules, and data transfer links between them. This creative modular architecture enables rapid generation of input stream for trade-off studies of various engine configurations. The data transfer links automatically transport output from one application as relevant input to the next application once the sequence is set up by the user. The computations are managed via constraint propagation - the constraints supplied by the user as part of any optimization module. The software can be used in the preliminary design stage as well as during the detail design of product development process.
Multi-channel detector readout method and integrated circuit
Moses, William W.; Beuville, Eric; Pedrali-Noy, Marzio
2006-12-12
An integrated circuit which provides multi-channel detector readout from a detector array. The circuit receives multiple signals from the elements of a detector array and compares the sampled amplitudes of these signals against a noise-floor threshold and against one another. A digital signal is generated which corresponds to the location of the highest of these signal amplitudes which exceeds the noise floor threshold. The digital signal is received by a multiplexing circuit which outputs an analog signal corresponding the highest of the input signal amplitudes. In addition a digital control section provides for programmatic control of the multiplexer circuit, amplifier gain, amplifier reset, masking selection, and test circuit functionality on each input thereof.
Multi-channel detector readout method and integrated circuit
Moses, William W.; Beuville, Eric; Pedrali-Noy, Marzio
2004-05-18
An integrated circuit which provides multi-channel detector readout from a detector array. The circuit receives multiple signals from the elements of a detector array and compares the sampled amplitudes of these signals against a noise-floor threshold and against one another. A digital signal is generated which corresponds to the location of the highest of these signal amplitudes which exceeds the noise floor threshold. The digital signal is received by a multiplexing circuit which outputs an analog signal corresponding the highest of the input signal amplitudes. In addition a digital control section provides for programmatic control of the multiplexer circuit, amplifier gain, amplifier reset, masking selection, and test circuit functionality on each input thereof.
Alternative to Ritt's pseudodivision for finding the input-output equations of multi-output models.
Meshkat, Nicolette; Anderson, Chris; DiStefano, Joseph J
2012-09-01
Differential algebra approaches to structural identifiability analysis of a dynamic system model in many instances heavily depend upon Ritt's pseudodivision at an early step in analysis. The pseudodivision algorithm is used to find the characteristic set, of which a subset, the input-output equations, is used for identifiability analysis. A simpler algorithm is proposed for this step, using Gröbner Bases, along with a proof of the method that includes a reduced upper bound on derivative requirements. Efficacy of the new algorithm is illustrated with several biosystem model examples. Copyright © 2012 Elsevier Inc. All rights reserved.
Modelling innovation performance of European regions using multi-output neural networks
Henriques, Roberto
2017-01-01
Regional innovation performance is an important indicator for decision-making regarding the implementation of policies intended to support innovation. However, patterns in regional innovation structures are becoming increasingly diverse, complex and nonlinear. To address these issues, this study aims to develop a model based on a multi-output neural network. Both intra- and inter-regional determinants of innovation performance are empirically investigated using data from the 4th and 5th Community Innovation Surveys of NUTS 2 (Nomenclature of Territorial Units for Statistics) regions. The results suggest that specific innovation strategies must be developed based on the current state of input attributes in the region. Thus, it is possible to develop appropriate strategies and targeted interventions to improve regional innovation performance. We demonstrate that support of entrepreneurship is an effective instrument of innovation policy. We also provide empirical support that both business and government R&D activity have a sigmoidal effect, implying that the most effective R&D support should be directed to regions with below-average and average R&D activity. We further show that the multi-output neural network outperforms traditional statistical and machine learning regression models. In general, therefore, it seems that the proposed model can effectively reflect both the multiple-output nature of innovation performance and the interdependency of the output attributes. PMID:28968449
Modelling innovation performance of European regions using multi-output neural networks.
Hajek, Petr; Henriques, Roberto
2017-01-01
Regional innovation performance is an important indicator for decision-making regarding the implementation of policies intended to support innovation. However, patterns in regional innovation structures are becoming increasingly diverse, complex and nonlinear. To address these issues, this study aims to develop a model based on a multi-output neural network. Both intra- and inter-regional determinants of innovation performance are empirically investigated using data from the 4th and 5th Community Innovation Surveys of NUTS 2 (Nomenclature of Territorial Units for Statistics) regions. The results suggest that specific innovation strategies must be developed based on the current state of input attributes in the region. Thus, it is possible to develop appropriate strategies and targeted interventions to improve regional innovation performance. We demonstrate that support of entrepreneurship is an effective instrument of innovation policy. We also provide empirical support that both business and government R&D activity have a sigmoidal effect, implying that the most effective R&D support should be directed to regions with below-average and average R&D activity. We further show that the multi-output neural network outperforms traditional statistical and machine learning regression models. In general, therefore, it seems that the proposed model can effectively reflect both the multiple-output nature of innovation performance and the interdependency of the output attributes.
Bastian, Nathaniel D; Ekin, Tahir; Kang, Hyojung; Griffin, Paul M; Fulton, Lawrence V; Grannan, Benjamin C
2017-06-01
The management of hospitals within fixed-input health systems such as the U.S. Military Health System (MHS) can be challenging due to the large number of hospitals, as well as the uncertainty in input resources and achievable outputs. This paper introduces a stochastic multi-objective auto-optimization model (SMAOM) for resource allocation decision-making in fixed-input health systems. The model can automatically identify where to re-allocate system input resources at the hospital level in order to optimize overall system performance, while considering uncertainty in the model parameters. The model is applied to 128 hospitals in the three services (Air Force, Army, and Navy) in the MHS using hospital-level data from 2009 - 2013. The results are compared to the traditional input-oriented variable returns-to-scale Data Envelopment Analysis (DEA) model. The application of SMAOM to the MHS increases the expected system-wide technical efficiency by 18 % over the DEA model while also accounting for uncertainty of health system inputs and outputs. The developed method is useful for decision-makers in the Defense Health Agency (DHA), who have a strategic level objective of integrating clinical and business processes through better sharing of resources across the MHS and through system-wide standardization across the services. It is also less sensitive to data outliers or sampling errors than traditional DEA methods.
Multi-dimensional simulations of core-collapse supernova explosions with CHIMERA
NASA Astrophysics Data System (ADS)
Messer, O. E. B.; Harris, J. A.; Hix, W. R.; Lentz, E. J.; Bruenn, S. W.; Mezzacappa, A.
2018-04-01
Unraveling the core-collapse supernova (CCSN) mechanism is a problem that remains essentially unsolved despite more than four decades of effort. Spherically symmetric models with otherwise high physical fidelity generally fail to produce explosions, and it is widely accepted that CCSNe are inherently multi-dimensional. Progress in realistic modeling has occurred recently through the availability of petascale platforms and the increasing sophistication of supernova codes. We will discuss our most recent work on understanding neutrino-driven CCSN explosions employing multi-dimensional neutrino-radiation hydrodynamics simulations with the Chimera code. We discuss the inputs and resulting outputs from these simulations, the role of neutrino radiation transport, and the importance of multi-dimensional fluid flows in shaping the explosions. We also highlight the production of 48Ca in long-running Chimera simulations.
A joint swarm intelligence algorithm for multi-user detection in MIMO-OFDM system
NASA Astrophysics Data System (ADS)
Hu, Fengye; Du, Dakun; Zhang, Peng; Wang, Zhijun
2014-11-01
In the multi-input multi-output orthogonal frequency division multiplexing (MIMO-OFDM) system, traditional multi-user detection (MUD) algorithms that usually used to suppress multiple access interference are difficult to balance system detection performance and the complexity of the algorithm. To solve this problem, this paper proposes a joint swarm intelligence algorithm called Ant Colony and Particle Swarm Optimisation (AC-PSO) by integrating particle swarm optimisation (PSO) and ant colony optimisation (ACO) algorithms. According to simulation results, it has been shown that, with low computational complexity, the MUD for the MIMO-OFDM system based on AC-PSO algorithm gains comparable MUD performance with maximum likelihood algorithm. Thus, the proposed AC-PSO algorithm provides a satisfactory trade-off between computational complexity and detection performance.
Subwavelength Sensing Using Nonlinear Feedback in a Wave-Chaotic Cavity
2013-01-01
r̃in and r̃in are the Fourier transforms of the input pulse and output pulse response, respectively. The magnitude and phase of Hcavity( f ) are plotted...function between its input and output voltages. But, as f increases (beyond ∼ 500 MHz), the amplitudes of the output signals decrease and the phase delay...coupled to free space where it is directed along two paths via a beam splitter (BS), where it is reflected of of mirrors (M1 and M2) that are attached to
A Scheme for Obtaining Secure S-Boxes Based on Chaotic Baker's Map
NASA Astrophysics Data System (ADS)
Gondal, Muhammad Asif; Abdul Raheem; Hussain, Iqtadar
2014-09-01
In this paper, a method for obtaining cryptographically strong 8 × 8 substitution boxes (S-boxes) is presented. The method is based on chaotic baker's map and a "mini version" of a new block cipher with block size 8 bits and can be easily and efficiently performed on a computer. The cryptographic strength of some 8 × 8 S-boxes randomly produced by the method is analyzed. The results show (1) all of them are bijective; (2) the nonlinearity of each output bit of them is usually about 100; (3) all of them approximately satisfy the strict avalanche criterion and output bits independence criterion; (4) they all have an almost equiprobable input/output XOR distribution.
Multi-level emulation of complex climate model responses to boundary forcing data
NASA Astrophysics Data System (ADS)
Tran, Giang T.; Oliver, Kevin I. C.; Holden, Philip B.; Edwards, Neil R.; Sóbester, András; Challenor, Peter
2018-04-01
Climate model components involve both high-dimensional input and output fields. It is desirable to efficiently generate spatio-temporal outputs of these models for applications in integrated assessment modelling or to assess the statistical relationship between such sets of inputs and outputs, for example, uncertainty analysis. However, the need for efficiency often compromises the fidelity of output through the use of low complexity models. Here, we develop a technique which combines statistical emulation with a dimensionality reduction technique to emulate a wide range of outputs from an atmospheric general circulation model, PLASIM, as functions of the boundary forcing prescribed by the ocean component of a lower complexity climate model, GENIE-1. Although accurate and detailed spatial information on atmospheric variables such as precipitation and wind speed is well beyond the capability of GENIE-1's energy-moisture balance model of the atmosphere, this study demonstrates that the output of this model is useful in predicting PLASIM's spatio-temporal fields through multi-level emulation. Meaningful information from the fast model, GENIE-1 was extracted by utilising the correlation between variables of the same type in the two models and between variables of different types in PLASIM. We present here the construction and validation of several PLASIM variable emulators and discuss their potential use in developing a hybrid model with statistical components.
Optical frequency comb based multi-band microwave frequency conversion for satellite applications.
Yang, Xinwu; Xu, Kun; Yin, Jie; Dai, Yitang; Yin, Feifei; Li, Jianqiang; Lu, Hua; Liu, Tao; Ji, Yuefeng
2014-01-13
Based on optical frequency combs (OFC), we propose an efficient and flexible multi-band frequency conversion scheme for satellite repeater applications. The underlying principle is to mix dual coherent OFCs with one of which carrying the input signal. By optically channelizing the mixed OFCs, the converted signal in different bands can be obtained in different channels. Alternatively, the scheme can be configured to generate multi-band local oscillators (LO) for widely distribution. Moreover, the scheme realizes simultaneous inter- and intra-band frequency conversion just in a single structure and needs only three frequency-fixed microwave sources. We carry out a proof of concept experiment in which multiple LOs with 2 GHz, 10 GHz, 18 GHz, and 26 GHz are generated. A C-band signal of 6.1 GHz input to the proposed scheme is successfully converted to 4.1 GHz (C band), 3.9 GHz (C band) and 11.9 GHz (X band), etc. Compared with the back-to-back (B2B) case measured at 0 dBm input power, the proposed scheme shows a 9.3% error vector magnitude (EVM) degradation at each output channel. Furthermore, all channels satisfy the EVM limit in a very wide input power range.
HCP: A Flexible CNN Framework for Multi-label Image Classification.
Wei, Yunchao; Xia, Wei; Lin, Min; Huang, Junshi; Ni, Bingbing; Dong, Jian; Zhao, Yao; Yan, Shuicheng
2015-10-26
Convolutional Neural Network (CNN) has demonstrated promising performance in single-label image classification tasks. However, how CNN best copes with multi-label images still remains an open problem, mainly due to the complex underlying object layouts and insufficient multi-label training images. In this work, we propose a flexible deep CNN infrastructure, called Hypotheses-CNN-Pooling (HCP), where an arbitrary number of object segment hypotheses are taken as the inputs, then a shared CNN is connected with each hypothesis, and finally the CNN output results from different hypotheses are aggregated with max pooling to produce the ultimate multi-label predictions. Some unique characteristics of this flexible deep CNN infrastructure include: 1) no ground-truth bounding box information is required for training; 2) the whole HCP infrastructure is robust to possibly noisy and/or redundant hypotheses; 3) the shared CNN is flexible and can be well pre-trained with a large-scale single-label image dataset, e.g., ImageNet; and 4) it may naturally output multi-label prediction results. Experimental results on Pascal VOC 2007 and VOC 2012 multi-label image datasets well demonstrate the superiority of the proposed HCP infrastructure over other state-of-the-arts. In particular, the mAP reaches 90.5% by HCP only and 93.2% after the fusion with our complementary result in [44] based on hand-crafted features on the VOC 2012 dataset.
Integrating Ecological and Water Footprint Accounting in a Multi-Regional Input-Output Framework
Carbon, ecological, and water footprints (CF, EF, and WF) are accounting tools that can be used to understand the connection between consumption activities and environmental pressures on the Earth?s atmosphere, bioproductive areas, and freshwater resources. These indicators have ...
A method to stabilize linear systems using eigenvalue gradient information
NASA Technical Reports Server (NTRS)
Wieseman, C. D.
1985-01-01
Formal optimization methods and eigenvalue gradient information are used to develop a stabilizing control law for a closed loop linear system that is initially unstable. The method was originally formulated by using direct, constrained optimization methods with the constraints being the real parts of the eigenvalues. However, because of problems in trying to achieve stabilizing control laws, the problem was reformulated to be solved differently. The method described uses the Davidon-Fletcher-Powell minimization technique to solve an indirect, constrained minimization problem in which the performance index is the Kreisselmeier-Steinhauser function of the real parts of all the eigenvalues. The method is applied successfully to solve two different problems: the determination of a fourth-order control law stabilizes a single-input single-output active flutter suppression system and the determination of a second-order control law for a multi-input multi-output lateral-directional flight control system. Various sets of design variables and initial starting points were chosen to show the robustness of the method.
Wu, Sanmang; Li, Shantong; Lei, Yalin
2016-01-01
This paper developed an estimation model for the contribution of exports to a country's regional economy based on the Chenery-Moses model and conducted an empirical analysis using China's multi-regional input-output tables for 1997, 2002, and 2007. The results indicated that China's national exports make significantly different contributions to the provincial economy in various regions, with the greatest contribution being observed in the eastern region and the smallest in the central region. The provinces are also subjected to significantly different export spillover effects. The boosting effect for the eastern provinces is primarily generated from local exports, whereas the western provinces primarily benefit from the export spillover effect from the eastern provinces. The eastern provinces, such as Guangdong, Zhejiang, Jiangsu, and Shanghai, are the primary sources of export spillover effects, and Guangdong is the largest source of export spillover effects for almost all of the provinces in China.
Design of feedback control systems for stable plants with saturating actuators
NASA Technical Reports Server (NTRS)
Kapasouris, Petros; Athans, Michael; Stein, Gunter
1988-01-01
A systematic control design methodology is introduced for multi-input/multi-output stable open loop plants with multiple saturations. This new methodology is a substantial improvement over previous heuristic single-input/single-output approaches. The idea is to introduce a supervisor loop so that when the references and/or disturbances are sufficiently small, the control system operates linearly as designed. For signals large enough to cause saturations, the control law is modified in such a way as to ensure stability and to preserve, to the extent possible, the behavior of the linear control design. Key benefits of the methodology are: the modified compensator never produces saturating control signals, integrators and/or slow dynamics in the compensator never windup, the directional properties of the controls are maintained, and the closed loop system has certain guaranteed stability properties. The advantages of the new design methodology are illustrated in the simulation of an academic example and the simulation of the multivariable longitudinal control of a modified model of the F-8 aircraft.
Modeling and control for vibration suppression of a flexible smart structure
NASA Technical Reports Server (NTRS)
Dosch, J.; Leo, D.; Inman, D.
1993-01-01
Theoretical and experimental results of the modeling and control of a flexible ribbed antenna are presented. The antenna consists of eight flexible ribs which constitutes a smart antenna in the sense that the actuator and sensors are an integral part of the structure. The antenna exhibits closely space and repeated modes, thus multi-input multi-output (MIMO) control is necessary for controllability and observability of the structure. The structure also exhibits mode localization phenomenon and contains post buckled members making an accurate finite element model of the structure difficult to obtain. An identified MIMO minimum order model of the antenna is synthesized from identified single-input single-output (SISO) transfer functions curve fit in the frequency domain. The identified model is used to design a positive position feedback (PPF) controller that increases damping in all of the modes in the targeted frequency range. Due to the accuracy of the open loop model of the antenna, the closed loop response predicted by the identified model correlates well wtih experimental results.
Nonlinear aeroservoelastic analysis of a controlled multiple-actuated-wing model with free-play
NASA Astrophysics Data System (ADS)
Huang, Rui; Hu, Haiyan; Zhao, Yonghui
2013-10-01
In this paper, the effects of structural nonlinearity due to free-play in both leading-edge and trailing-edge outboard control surfaces on the linear flutter control system are analyzed for an aeroelastic model of three-dimensional multiple-actuated-wing. The free-play nonlinearities in the control surfaces are modeled theoretically by using the fictitious mass approach. The nonlinear aeroelastic equations of the presented model can be divided into nine sub-linear modal-based aeroelastic equations according to the different combinations of deflections of the leading-edge and trailing-edge outboard control surfaces. The nonlinear aeroelastic responses can be computed based on these sub-linear aeroelastic systems. To demonstrate the effects of nonlinearity on the linear flutter control system, a single-input and single-output controller and a multi-input and multi-output controller are designed based on the unconstrained optimization techniques. The numerical results indicate that the free-play nonlinearity can lead to either limit cycle oscillations or divergent motions when the linear control system is implemented.
A superconducting large-angle magnetic suspension
NASA Technical Reports Server (NTRS)
Downer, James; Goldie, James; Torti, Richard
1991-01-01
The component technologies were developed required for an advanced control moment gyro (CMG) type of slewing actuator for large payloads. The key component of the CMG is a large-angle magnetic suspension (LAMS). The LAMS combines the functions of the gimbal structure, torque motors, and rotor bearings of a CMG. The LAMS uses a single superconducting source coil and an array of cryoresistive control coils to produce a specific output torque more than an order of magnitude greater than conventional devices. The designed and tested LAMS system is based around an available superconducting solenoid, an array of twelve room-temperature normal control coils, and a multi-input, multi-output control system. The control laws were demonstrated for stabilizing and controlling the LAMS system.
Zhang, Lijia; Liu, Bo; Xin, Xiangjun
2015-06-15
A secure enhanced coherent optical multi-carrier system based on Stokes vector scrambling is proposed and experimentally demonstrated. The optical signal with four-dimensional (4D) modulation space has been scrambled intra- and inter-subcarriers, where a multi-layer logistic map is adopted as the chaotic model. An experiment with 61.71-Gb/s encrypted multi-carrier signal is successfully demonstrated with the proposed method. The results indicate a promising solution for the physical secure optical communication.
NASA Astrophysics Data System (ADS)
Tang, Jian; Qiao, Junfei; Wu, ZhiWei; Chai, Tianyou; Zhang, Jian; Yu, Wen
2018-01-01
Frequency spectral data of mechanical vibration and acoustic signals relate to difficult-to-measure production quality and quantity parameters of complex industrial processes. A selective ensemble (SEN) algorithm can be used to build a soft sensor model of these process parameters by fusing valued information selectively from different perspectives. However, a combination of several optimized ensemble sub-models with SEN cannot guarantee the best prediction model. In this study, we use several techniques to construct mechanical vibration and acoustic frequency spectra of a data-driven industrial process parameter model based on selective fusion multi-condition samples and multi-source features. Multi-layer SEN (MLSEN) strategy is used to simulate the domain expert cognitive process. Genetic algorithm and kernel partial least squares are used to construct the inside-layer SEN sub-model based on each mechanical vibration and acoustic frequency spectral feature subset. Branch-and-bound and adaptive weighted fusion algorithms are integrated to select and combine outputs of the inside-layer SEN sub-models. Then, the outside-layer SEN is constructed. Thus, "sub-sampling training examples"-based and "manipulating input features"-based ensemble construction methods are integrated, thereby realizing the selective information fusion process based on multi-condition history samples and multi-source input features. This novel approach is applied to a laboratory-scale ball mill grinding process. A comparison with other methods indicates that the proposed MLSEN approach effectively models mechanical vibration and acoustic signals.
A User''s Guide to the Zwikker-Kosten Transmission Line Code (ZKTL)
NASA Technical Reports Server (NTRS)
Kelly, J. J.; Abu-Khajeel, H.
1997-01-01
This user's guide documents updates to the Zwikker-Kosten Transmission Line Code (ZKTL). This code was developed for analyzing new liner concepts developed to provide increased sound absorption. Contiguous arrays of multi-degree-of-freedom (MDOF) liner elements serve as the model for these liner configurations, and Zwikker and Kosten's theory of sound propagation in channels is used to predict the surface impedance. Transmission matrices for the various liner elements incorporate both analytical and semi-empirical methods. This allows standard matrix techniques to be employed in the code to systematically calculate the composite impedance due to the individual liner elements. The ZKTL code consists of four independent subroutines: 1. Single channel impedance calculation - linear version (SCIC) 2. Single channel impedance calculation - nonlinear version (SCICNL) 3. Multi-channel, multi-segment, multi-layer impedance calculation - linear version (MCMSML) 4. Multi-channel, multi-segment, multi-layer impedance calculation - nonlinear version (MCMSMLNL) Detailed examples, comments, and explanations for each liner impedance computation module are included. Also contained in the guide are depictions of the interactive execution, input files and output files.
Robust Stability Analysis of the Space Launch System Control Design: A Singular Value Approach
NASA Technical Reports Server (NTRS)
Pei, Jing; Newsome, Jerry R.
2015-01-01
Classical stability analysis consists of breaking the feedback loops one at a time and determining separately how much gain or phase variations would destabilize the stable nominal feedback system. For typical launch vehicle control design, classical control techniques are generally employed. In addition to stability margins, frequency domain Monte Carlo methods are used to evaluate the robustness of the design. However, such techniques were developed for Single-Input-Single-Output (SISO) systems and do not take into consideration the off-diagonal terms in the transfer function matrix of Multi-Input-Multi-Output (MIMO) systems. Robust stability analysis techniques such as H(sub infinity) and mu are applicable to MIMO systems but have not been adopted as standard practices within the launch vehicle controls community. This paper took advantage of a simple singular-value-based MIMO stability margin evaluation method based on work done by Mukhopadhyay and Newsom and applied it to the SLS high-fidelity dynamics model. The method computes a simultaneous multi-loop gain and phase margin that could be related back to classical margins. The results presented in this paper suggest that for the SLS system, traditional SISO stability margins are similar to the MIMO margins. This additional level of verification provides confidence in the robustness of the control design.
NASA Astrophysics Data System (ADS)
Li, Yong; Li, Wang; He, Kai-Yu; Li, Pei; Huang, Yan; Nie, Zhou; Yao, Shou-Zhuo
2016-04-01
In natural biological systems, proteins exploit various functional peptide motifs to exert target response and activity switch, providing a functional and logic basis for complex cellular activities. Building biomimetic peptide-based bio-logic systems is highly intriguing but remains relatively unexplored due to limited logic recognition elements and complex signal outputs. In this proof-of-principle work, we attempted to address these problems by utilizing multi-functional peptide probes and the peptide-mediated nanoparticle assembly system. Here, the rationally designed peptide probes function as the dual-target responsive element specifically responsive to metal ions and enzymes as well as the mediator regulating the assembly of gold nanoparticles (AuNPs). Taking advantage of Zn2+ ions and chymotrypsin as the model inputs of metal ions and enzymes, respectively, we constructed the peptide logic system computed by the multi-functional peptide probes and outputted by the readable colour change of AuNPs. In this way, the representative binary basic logic gates (AND, OR, INHIBIT, NAND, IMPLICATION) have been achieved by delicately coding the peptide sequence, demonstrating the versatility of our logic system. Additionally, we demonstrated that the three-input combinational logic gate (INHIBIT-OR) could also be successfully integrated and applied as a multi-tasking biosensor for colorimetric detection of dual targets. This nanoparticle-based peptide logic system presents a valid strategy to illustrate peptide information processing and provides a practical platform for executing peptide computing or peptide-related multiplexing sensing, implying that the controllable nanomaterial assembly is a promising and potent methodology for the advancement of biomimetic bio-logic computation.In natural biological systems, proteins exploit various functional peptide motifs to exert target response and activity switch, providing a functional and logic basis for complex cellular activities. Building biomimetic peptide-based bio-logic systems is highly intriguing but remains relatively unexplored due to limited logic recognition elements and complex signal outputs. In this proof-of-principle work, we attempted to address these problems by utilizing multi-functional peptide probes and the peptide-mediated nanoparticle assembly system. Here, the rationally designed peptide probes function as the dual-target responsive element specifically responsive to metal ions and enzymes as well as the mediator regulating the assembly of gold nanoparticles (AuNPs). Taking advantage of Zn2+ ions and chymotrypsin as the model inputs of metal ions and enzymes, respectively, we constructed the peptide logic system computed by the multi-functional peptide probes and outputted by the readable colour change of AuNPs. In this way, the representative binary basic logic gates (AND, OR, INHIBIT, NAND, IMPLICATION) have been achieved by delicately coding the peptide sequence, demonstrating the versatility of our logic system. Additionally, we demonstrated that the three-input combinational logic gate (INHIBIT-OR) could also be successfully integrated and applied as a multi-tasking biosensor for colorimetric detection of dual targets. This nanoparticle-based peptide logic system presents a valid strategy to illustrate peptide information processing and provides a practical platform for executing peptide computing or peptide-related multiplexing sensing, implying that the controllable nanomaterial assembly is a promising and potent methodology for the advancement of biomimetic bio-logic computation. Electronic supplementary information (ESI) available: Additional figures (Tables S1-S3 and Fig. S1-S6). See DOI: 10.1039/c6nr01072e
Multi-dimensional simulations of core-collapse supernova explosions with CHIMERA
DOE Office of Scientific and Technical Information (OSTI.GOV)
Messer, Bronson; Harris, James Austin; Hix, William Raphael
Unraveling the core-collapse supernova (CCSN) mechanism is a problem that remains essentially unsolved despite more than four decades of effort. Spherically symmetric models with otherwise high physical fidelity generally fail to produce explosions, and it is widely accepted that CCSNe are inherently multi-dimensional. Progress in realistic modeling has occurred recently through the availability of petascale platforms and the increasing sophistication of supernova codes. We will discuss our most recent work on understanding neutrino-driven CCSN explosions employing multi-dimensional neutrino-radiation hydrodynamics simulations with the Chimera code. We discuss the inputs and resulting outputs from these simulations, the role of neutrino radiation transport,more » and the importance of multi-dimensional fluid flows in shaping the explosions. We also highlight the production of 48Ca in long-running Chimera simulations.« less
NASA Astrophysics Data System (ADS)
Abaza, Mohamed; Mesleh, Raed; Mansour, Ali; Aggoune, el-Hadi
2015-01-01
The performance analysis of a multi-hop decode and forward relaying free-space optical (FSO) communication system is presented in this paper. The considered FSO system uses intensity modulation and direct detection as means of transmission and reception. Atmospheric turbulence impacts are modeled as a log-normal channel, and different weather attenuation effects and geometric losses are taken into account. It is shown that multi-hop is an efficient technique to mitigate such effects in FSO communication systems. A comparison with direct link and multiple-input single-output (MISO) systems considering correlation effects at the transmitter is provided. Results show that MISO multi-hop FSO systems are superior than their counterparts over links exhibiting high attenuation. Monte Carlo simulation results are provided to validate the bit error rate (BER) analyses and conclusions.
NASA Astrophysics Data System (ADS)
Mata-Machuca, Juan L.; Aguilar-López, Ricardo
2018-01-01
This work deals with the adaptative synchronization of complex dynamical networks with fractional-order nodes and its application in secure communications employing chaotic parameter modulation. The complex network is composed of multiple fractional-order systems with mismatch parameters and the coupling functions are given to realize the network synchronization. We introduce a fractional algebraic synchronizability condition (FASC) and a fractional algebraic identifiability condition (FAIC) which are used to know if the synchronization and parameters estimation problems can be solved. To overcome these problems, an adaptative synchronization methodology is designed; the strategy consists in proposing multiple receiver systems which tend to follow asymptotically the uncertain transmitters systems. The coupling functions and parameters of the receiver systems are adjusted continually according to a convenient sigmoid-like adaptative controller (SLAC), until the measurable output errors converge to zero, hence, synchronization between transmitter and receivers is achieved and message signals are recovered. Indeed, the stability analysis of the synchronization error is based on the fractional Lyapunov direct method. Finally, numerical results corroborate the satisfactory performance of the proposed scheme by means of the synchronization of a complex network consisting of several fractional-order unified chaotic systems.
NASA Astrophysics Data System (ADS)
Chen, Jing; Qiu, Xiaojie; Yin, Cunyi; Jiang, Hao
2018-02-01
An efficient method to design the broadband gain-flattened Raman fiber amplifier with multiple pumps is proposed based on least squares support vector regression (LS-SVR). A multi-input multi-output LS-SVR model is introduced to replace the complicated solving process of the nonlinear coupled Raman amplification equation. The proposed approach contains two stages: offline training stage and online optimization stage. During the offline stage, the LS-SVR model is trained. Owing to the good generalization capability of LS-SVR, the net gain spectrum can be directly and accurately obtained when inputting any combination of the pump wavelength and power to the well-trained model. During the online stage, we incorporate the LS-SVR model into the particle swarm optimization algorithm to find the optimal pump configuration. The design results demonstrate that the proposed method greatly shortens the computation time and enhances the efficiency of the pump parameter optimization for Raman fiber amplifier design.
Deep multi-spectral ensemble learning for electronic cleansing in dual-energy CT colonography
NASA Astrophysics Data System (ADS)
Tachibana, Rie; Näppi, Janne J.; Hironaka, Toru; Kim, Se Hyung; Yoshida, Hiroyuki
2017-03-01
We developed a novel electronic cleansing (EC) method for dual-energy CT colonography (DE-CTC) based on an ensemble deep convolution neural network (DCNN) and multi-spectral multi-slice image patches. In the method, an ensemble DCNN is used to classify each voxel of a DE-CTC image volume into five classes: luminal air, soft tissue, tagged fecal materials, and partial-volume boundaries between air and tagging and those between soft tissue and tagging. Each DCNN acts as a voxel classifier, where an input image patch centered at the voxel is generated as input to the DCNNs. An image patch has three channels that are mapped from a region-of-interest containing the image plane of the voxel and the two adjacent image planes. Six different types of spectral input image datasets were derived using two dual-energy CT images, two virtual monochromatic images, and two material images. An ensemble DCNN was constructed by use of a meta-classifier that combines the output of multiple DCNNs, each of which was trained with a different type of multi-spectral image patches. The electronically cleansed CTC images were calculated by removal of regions classified as other than soft tissue, followed by a colon surface reconstruction. For pilot evaluation, 359 volumes of interest (VOIs) representing sources of subtraction artifacts observed in current EC schemes were sampled from 30 clinical CTC cases. Preliminary results showed that the ensemble DCNN can yield high accuracy in labeling of the VOIs, indicating that deep learning of multi-spectral EC with multi-slice imaging could accurately remove residual fecal materials from CTC images without generating major EC artifacts.
Multi-Layered Feedforward Neural Networks for Image Segmentation
1991-12-01
the Gram-Schmidt Network ...................... 80 xi Preface WILLIAM SHAKESPEARE 1564-1616 Is this a dagger which I see before me, The handle toward...any input-output mapping with a single hidden layer of non-linear nodes, the result may be like proving that a monkey could write Hamlet . Certainly it
Abstract Environmental models are frequently used within regulatory and policy frameworks to estimate environmental metrics that are difficult or impossible to physically measure. As important decision tools, the uncertainty associated with the model outputs should impact their ...
Analysis of continuous beams with joint slip
L. A. Soltis
1981-01-01
A computer analysis with user guidelines to analyze partially continuous multi-span beams is presented. Partial continuity is due to rotational slip which occurs at spliced joints at the supports of continuous beams such as floor joists. Beam properties, loads, and joint slip are input; internal forces, reactions, and deflections are output.
Multiple-function multi-input/multi-output digital control and on-line analysis
NASA Technical Reports Server (NTRS)
Hoadley, Sherwood T.; Wieseman, Carol D.; Mcgraw, Sandra M.
1992-01-01
The design and capabilities of two digital controller systems for aeroelastic wind-tunnel models are described. The first allowed control of flutter while performing roll maneuvers with wing load control as well as coordinating the acquisition, storage, and transfer of data for on-line analysis. This system, which employs several digital signal multi-processor (DSP) boards programmed in high-level software languages, is housed in a SUN Workstation environment. A second DCS provides a measure of wind-tunnel safety by functioning as a trip system during testing in the case of high model dynamic response or in case the first DCS fails. The second DCS uses National Instruments LabVIEW Software and Hardware within a Macintosh environment.
Kwon, Osung; Ra, Young-Sik; Kim, Yoon-Ho
2009-07-20
Coherence properties of the photon pair generated via spontaneous parametric down-conversion pumped by a multi-mode cw diode laser are studied with a Mach-Zehnder interferometer. Each photon of the pair enters a different input port of the interferometer and the biphoton coherence properties are studied with a two-photon detector placed at one output port. When the photon pair simultaneously enters the interferometer, periodic recurrence of the biphoton de Broglie wave packet is observed, closely resembling the coherence properties of the pump diode laser. With non-zero delays between the photons at the input ports, biphoton interference exhibits the same periodic recurrence but the wave packet shapes are shown to be dependent on both the input delay as well as the interferometer delay. These properties could be useful for building engineered entangled photon sources based on diode laser-pumped spontaneous parametric down-conversion.
Shi, Wuxi; Luo, Rui; Li, Baoquan
2017-01-01
In this study, an adaptive fuzzy prescribed performance control approach is developed for a class of uncertain multi-input and multi-output (MIMO) nonlinear systems with unknown control direction and unknown dead-zone inputs. The properties of symmetric matrix are exploited to design adaptive fuzzy prescribed performance controller, and a Nussbaum-type function is incorporated in the controller to estimate the unknown control direction. This method has two prominent advantages: it does not require the priori knowledge of control direction and only three parameters need to be updated on-line for this MIMO systems. It is proved that all the signals in the resulting closed-loop system are bounded and that the tracking errors converge to a small residual set with the prescribed performance bounds. The effectiveness of the proposed approach is validated by simulation results. Copyright © 2016 ISA. Published by Elsevier Ltd. All rights reserved.
Russell, J.A.G.
1958-01-01
An electronic trigger circuit is described of the type where an output pulse is obtained only after an input voltage has cqualed or exceeded a selected reference voltage. In general, the invention comprises a source of direct current reference voltage in series with an impedance and a diode rectifying element. An input pulse of preselected amplitude causes the diode to conduct and develop a signal across the impedance. The signal is delivered to an amplifier where an output pulse is produced and part of the output is fed back in a positive manner to the diode so that the amplifier produces a steep wave front trigger pulsc at the output. The trigger point of the described circuit is not subject to variation due to the aging, etc., of multi-electrode tabes, since the diode circuit essentially determines the trigger point.
A Novel Approach to Develop the Lower Order Model of Multi-Input Multi-Output System
NASA Astrophysics Data System (ADS)
Rajalakshmy, P.; Dharmalingam, S.; Jayakumar, J.
2017-10-01
A mathematical model is a virtual entity that uses mathematical language to describe the behavior of a system. Mathematical models are used particularly in the natural sciences and engineering disciplines like physics, biology, and electrical engineering as well as in the social sciences like economics, sociology and political science. Physicists, Engineers, Computer scientists, and Economists use mathematical models most extensively. With the advent of high performance processors and advanced mathematical computations, it is possible to develop high performing simulators for complicated Multi Input Multi Ouptut (MIMO) systems like Quadruple tank systems, Aircrafts, Boilers etc. This paper presents the development of the mathematical model of a 500 MW utility boiler which is a highly complex system. A synergistic combination of operational experience, system identification and lower order modeling philosophy has been effectively used to develop a simplified but accurate model of a circulation system of a utility boiler which is a MIMO system. The results obtained are found to be in good agreement with the physics of the process and with the results obtained through design procedure. The model obtained can be directly used for control system studies and to realize hardware simulators for boiler testing and operator training.
Zhang, Zhen; Ma, Cheng; Zhu, Rong
2016-10-14
High integration of multi-functional instruments raises a critical issue in temperature control that is challenging due to its spatial-temporal complexity. This paper presents a multi-input multi-output (MIMO) self-tuning temperature sensing and control system for efficiently modulating the temperature environment within a multi-module instrument. The smart system ensures that the internal temperature of the instrument converges to a target without the need of a system model, thus making the control robust. The system consists of a fully-connected proportional-integral-derivative (PID) neural network (FCPIDNN) and an on-line self-tuning module. The experimental results show that the presented system can effectively control the internal temperature under various mission scenarios, in particular, it is able to self-reconfigure upon actuator failure. The system provides a new scheme for a complex and time-variant MIMO control system which can be widely applied for the distributed measurement and control of the environment in instruments, integration electronics, and house constructions.
Gaussian functional regression for output prediction: Model assimilation and experimental design
NASA Astrophysics Data System (ADS)
Nguyen, N. C.; Peraire, J.
2016-03-01
In this paper, we introduce a Gaussian functional regression (GFR) technique that integrates multi-fidelity models with model reduction to efficiently predict the input-output relationship of a high-fidelity model. The GFR method combines the high-fidelity model with a low-fidelity model to provide an estimate of the output of the high-fidelity model in the form of a posterior distribution that can characterize uncertainty in the prediction. A reduced basis approximation is constructed upon the low-fidelity model and incorporated into the GFR method to yield an inexpensive posterior distribution of the output estimate. As this posterior distribution depends crucially on a set of training inputs at which the high-fidelity models are simulated, we develop a greedy sampling algorithm to select the training inputs. Our approach results in an output prediction model that inherits the fidelity of the high-fidelity model and has the computational complexity of the reduced basis approximation. Numerical results are presented to demonstrate the proposed approach.
Li, Yong; Li, Wang; He, Kai-Yu; Li, Pei; Huang, Yan; Nie, Zhou; Yao, Shou-Zhuo
2016-04-28
In natural biological systems, proteins exploit various functional peptide motifs to exert target response and activity switch, providing a functional and logic basis for complex cellular activities. Building biomimetic peptide-based bio-logic systems is highly intriguing but remains relatively unexplored due to limited logic recognition elements and complex signal outputs. In this proof-of-principle work, we attempted to address these problems by utilizing multi-functional peptide probes and the peptide-mediated nanoparticle assembly system. Here, the rationally designed peptide probes function as the dual-target responsive element specifically responsive to metal ions and enzymes as well as the mediator regulating the assembly of gold nanoparticles (AuNPs). Taking advantage of Zn2+ ions and chymotrypsin as the model inputs of metal ions and enzymes, respectively, we constructed the peptide logic system computed by the multi-functional peptide probes and outputted by the readable colour change of AuNPs. In this way, the representative binary basic logic gates (AND, OR, INHIBIT, NAND, IMPLICATION) have been achieved by delicately coding the peptide sequence, demonstrating the versatility of our logic system. Additionally, we demonstrated that the three-input combinational logic gate (INHIBIT-OR) could also be successfully integrated and applied as a multi-tasking biosensor for colorimetric detection of dual targets. This nanoparticle-based peptide logic system presents a valid strategy to illustrate peptide information processing and provides a practical platform for executing peptide computing or peptide-related multiplexing sensing, implying that the controllable nanomaterial assembly is a promising and potent methodology for the advancement of biomimetic bio-logic computation.
RF waveguide phase-directed power combiners
DOE Office of Scientific and Technical Information (OSTI.GOV)
Nantista, Christopher D.; Dolgashev, Valery A.; Tantawi, Sami G.
2017-05-02
High power RF phase-directed power combiners include magic H hybrid and/or superhybrid circuits oriented in orthogonal H-planes and connected using E-plane bends and/or twists to produce compact 3D waveguide circuits, including 8.times.8 and 16.times.16 combiners. Using phase control at the input ports, RF power can be directed to a single output port, enabling fast switching between output ports for applications such as multi-angle radiation therapy.
Variable Neural Adaptive Robust Control: A Switched System Approach
DOE Office of Scientific and Technical Information (OSTI.GOV)
Lian, Jianming; Hu, Jianghai; Zak, Stanislaw H.
2015-05-01
Variable neural adaptive robust control strategies are proposed for the output tracking control of a class of multi-input multi-output uncertain systems. The controllers incorporate a variable-structure radial basis function (RBF) network as the self-organizing approximator for unknown system dynamics. The variable-structure RBF network solves the problem of structure determination associated with fixed-structure RBF networks. It can determine the network structure on-line dynamically by adding or removing radial basis functions according to the tracking performance. The structure variation is taken into account in the stability analysis of the closed-loop system using a switched system approach with the aid of the piecewisemore » quadratic Lyapunov function. The performance of the proposed variable neural adaptive robust controllers is illustrated with simulations.« less
A joint precoding scheme for indoor downlink multi-user MIMO VLC systems
NASA Astrophysics Data System (ADS)
Zhao, Qiong; Fan, Yangyu; Kang, Bochao
2017-11-01
In this study, we aim to improve the system performance and reduce the implementation complexity of precoding scheme for visible light communication (VLC) systems. By incorporating the power-method algorithm and the block diagonalization (BD) algorithm, we propose a joint precoding scheme for indoor downlink multi-user multi-input-multi-output (MU-MIMO) VLC systems. In this scheme, we apply the BD algorithm to eliminate the co-channel interference (CCI) among users firstly. Secondly, the power-method algorithm is used to search the precoding weight for each user based on the optimal criterion of signal to interference plus noise ratio (SINR) maximization. Finally, the optical power restrictions of VLC systems are taken into account to constrain the precoding weight matrix. Comprehensive computer simulations in two scenarios indicate that the proposed scheme always has better bit error rate (BER) performance and lower computation complexity than that of the traditional scheme.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Hernandez-Solis, A.; Demaziere, C.; Ekberg, C.
2012-07-01
In this paper, multi-group microscopic cross-section uncertainty is propagated through the DRAGON (Version 4) lattice code, in order to perform uncertainty analysis on k{infinity} and 2-group homogenized macroscopic cross-sections predictions. A statistical methodology is employed for such purposes, where cross-sections of certain isotopes of various elements belonging to the 172 groups DRAGLIB library format, are considered as normal random variables. This library is based on JENDL-4 data, because JENDL-4 contains the largest amount of isotopic covariance matrixes among the different major nuclear data libraries. The aim is to propagate multi-group nuclide uncertainty by running the DRAGONv4 code 500 times, andmore » to assess the output uncertainty of a test case corresponding to a 17 x 17 PWR fuel assembly segment without poison. The chosen sampling strategy for the current study is Latin Hypercube Sampling (LHS). The quasi-random LHS allows a much better coverage of the input uncertainties than simple random sampling (SRS) because it densely stratifies across the range of each input probability distribution. Output uncertainty assessment is based on the tolerance limits concept, where the sample formed by the code calculations infers to cover 95% of the output population with at least a 95% of confidence. This analysis is the first attempt to propagate parameter uncertainties of modern multi-group libraries, which are used to feed advanced lattice codes that perform state of the art resonant self-shielding calculations such as DRAGONv4. (authors)« less
Cerina, Federica; Zhu, Zhen; Chessa, Alessandro; Riccaboni, Massimo
2015-01-01
Production systems, traditionally analyzed as almost independent national systems, are increasingly connected on a global scale. Only recently becoming available, the World Input-Output Database (WIOD) is one of the first efforts to construct the global multi-regional input-output (GMRIO) tables. By viewing the world input-output system as an interdependent network where the nodes are the individual industries in different economies and the edges are the monetary goods flows between industries, we analyze respectively the global, regional, and local network properties of the so-called world input-output network (WION) and document its evolution over time. At global level, we find that the industries are highly but asymmetrically connected, which implies that micro shocks can lead to macro fluctuations. At regional level, we find that the world production is still operated nationally or at most regionally as the communities detected are either individual economies or geographically well defined regions. Finally, at local level, for each industry we compare the network-based measures with the traditional methods of backward linkages. We find that the network-based measures such as PageRank centrality and community coreness measure can give valuable insights into identifying the key industries. PMID:26222389
Deep Convolutional Neural Networks for Multi-Modality Isointense Infant Brain Image Segmentation
Zhang, Wenlu; Li, Rongjian; Deng, Houtao; Wang, Li; Lin, Weili; Ji, Shuiwang; Shen, Dinggang
2015-01-01
The segmentation of infant brain tissue images into white matter (WM), gray matter (GM), and cerebrospinal fluid (CSF) plays an important role in studying early brain development in health and disease. In the isointense stage (approximately 6–8 months of age), WM and GM exhibit similar levels of intensity in both T1 and T2 MR images, making the tissue segmentation very challenging. Only a small number of existing methods have been designed for tissue segmentation in this isointense stage; however, they only used a single T1 or T2 images, or the combination of T1 and T2 images. In this paper, we propose to use deep convolutional neural networks (CNNs) for segmenting isointense stage brain tissues using multi-modality MR images. CNNs are a type of deep models in which trainable filters and local neighborhood pooling operations are applied alternatingly on the raw input images, resulting in a hierarchy of increasingly complex features. Specifically, we used multimodality information from T1, T2, and fractional anisotropy (FA) images as inputs and then generated the segmentation maps as outputs. The multiple intermediate layers applied convolution, pooling, normalization, and other operations to capture the highly nonlinear mappings between inputs and outputs. We compared the performance of our approach with that of the commonly used segmentation methods on a set of manually segmented isointense stage brain images. Results showed that our proposed model significantly outperformed prior methods on infant brain tissue segmentation. In addition, our results indicated that integration of multi-modality images led to significant performance improvement. PMID:25562829
Frankel, Mitchell A; Dowden, Brett R; Mathews, V John; Normann, Richard A; Clark, Gregory A; Meek, Sanford G
2011-06-01
Although asynchronous intrafascicular multi-electrode stimulation (IFMS) can evoke fatigue-resistant muscle force, a priori determination of the necessary stimulation parameters for precise force production is not possible. This paper presents a proportionally-modulated, multiple-input single-output (MISO) controller that was designed and experimentally validated for real-time, closed-loop force-feedback control of asynchronous IFMS. Experiments were conducted on anesthetized felines with a Utah Slanted Electrode Array implanted in the sciatic nerve, either acutely or chronically ( n = 1 for each). Isometric forces were evoked in plantar-flexor muscles, and target forces consisted of up to 7 min of step, sinusoidal, and more complex time-varying trajectories. The controller was successful in evoking steps in force with time-to-peak of less than 0.45 s, steady-state ripple of less than 7% of the mean steady-state force, and near-zero steady-state error even in the presence of muscle fatigue, but with transient overshoot of near 20%. The controller was also successful in evoking target sinusoidal and complex time-varying force trajectories with amplitude error of less than 0.5 N and time delay of approximately 300 ms. This MISO control strategy can potentially be used to develop closed-loop asynchronous IFMS controllers for a wide variety of multi-electrode stimulation applications to restore lost motor function.
R-parametrization and its role in classification of linear multivariable feedback systems
NASA Technical Reports Server (NTRS)
Chen, Robert T. N.
1988-01-01
A classification of all the compensators that stabilize a given general plant in a linear, time-invariant multi-input, multi-output feedback system is developed. This classification, along with the associated necessary and sufficient conditions for stability of the feedback system, is achieved through the introduction of a new parameterization, referred to as R-Parameterization, which is a dual of the familiar Q-Parameterization. The classification is made to the stability conditions of the compensators and the plant by themselves; and necessary and sufficient conditions are based on the stability of Q and R themselves.
Concurrent design of an RTP chamber and advanced control system
DOE Office of Scientific and Technical Information (OSTI.GOV)
Spence, P.; Schaper, C.; Kermani, A.
1995-12-31
A concurrent-engineering approach is applied to the development of an axisymmetric rapid-thermal-processing (RTP) reactor and its associated temperature controller. Using a detailed finite-element thermal model as a surrogate for actual hardware, the authors have developed and tested a multi-input multi-output (MIMO) controller. Closed-loop simulations are performed by linking the control algorithm with the finite-element code. Simulations show that good temperature uniformity is maintained on the wafer during both steady and transient conditions. A numerical study shows the effect of ramp rate, feedback gain, sensor placement, and wafer-emissivity patterns on system performance.
Optical switch using Risley prisms
Sweatt, William C.; Christenson, Todd R.
2003-04-15
An optical switch using Risley prisms and rotary microactuators to independently rotate the wedge prisms of each Risley prism pair is disclosed. The optical switch comprises an array of input Risley prism pairs that selectively redirect light beams from a plurality of input ports to an array of output Risley prism pairs that similarly direct the light beams to a plurality of output ports. Each wedge prism of each Risley prism pair can be independently rotated by a variable-reluctance stepping rotary microactuator that is fabricated by a multi-layer LIGA process. Each wedge prism can be formed integral to the annular rotor of the rotary microactuator by a DXRL process.
Optical Switch Using Risley Prisms
Sweatt, William C.; Christenson, Todd R.
2005-02-22
An optical switch using Risley prisms and rotary microactuators to independently rotate the wedge prisms of each Risley prism pair is disclosed. The optical switch comprises an array of input Risley prism pairs that selectively redirect light beams from a plurality of input ports to an array of output Risley prism pairs that similarly direct the light beams to a plurality of output ports. Each wedge prism of each Risley prism pair can be independently rotated by a variable-reluctance stepping rotary microactuator that is fabricated by a multi-layer LIGA process. Each wedge prism can be formed integral to the annular rotor of the rotary microactuator by a DXRL process.
NASA Astrophysics Data System (ADS)
Li, Chuang; Min, Fuhong; Jin, Qiusen; Ma, Hanyuan
2017-12-01
An active charge-controlled memristive Chua's circuit is implemented, and its basic properties are analyzed. Firstly, with the system trajectory starting from an equilibrium point, the dynamic behavior of multiple coexisting attractors depending on the memristor initial value and the system parameter is studied, which shows the coexisting behaviors of point, period, chaos, and quasic-period. Secondly, with the system motion starting from a non-equilibrium point, the dynamics of extreme multistability in a wide initial value domain are easily conformed by new analytical methods. Furthermore, the simulation results indicate that some strange chaotic attractors like multi-wing type and multi-scroll type are observed when the observed signals are extended from voltage and current to power and energy, respectively. Specially, when different initial conditions are taken, the coexisting strange chaotic attractors between the power and energy signals are exhibited. Finally, the chaotic sequences of the new system are used for encrypting color image to protect image information security. The encryption performance is analyzed by statistic histogram, correlation, key spaces and key sensitivity. Simulation results show that the new memristive chaotic system has high security in color image encryption.
Conceptualizing Indicator Domains for Evaluating Action Research
ERIC Educational Resources Information Center
Piggot-Irvine, Eileen; Rowe, Wendy; Ferkins, Lesley
2015-01-01
The focus of this paper is to share thinking about meta-level evaluation of action research (AR), and to introduce indicator domains for assessing and measuring inputs, outputs and outcomes. Meta-level and multi-site evaluation has been rare in AR beyond project implementation and participant satisfaction. The paper is the first of several…
NASA Technical Reports Server (NTRS)
Kvaternik, Raymond G.; Piatak, David J.; Nixon, Mark W.; Langston, Chester W.; Singleton, Jeffrey D.; Bennett, Richard L.; Brown, Ross K.
2001-01-01
The results of a joint NASA/Army/Bell Helicopter Textron wind-tunnel test to assess the potential of Generalized Predictive Control (GPC) for actively controlling the swashplate of tiltrotor aircraft to enhance aeroelastic stability in the airplane mode of flight are presented. GPC is an adaptive time-domain predictive control method that uses a linear difference equation to describe the input-output relationship of the system and to design the controller. The test was conducted in the Langley Transonic Dynamics Tunnel using an unpowered 1/5-scale semispan aeroelastic model of the V-22 that was modified to incorporate a GPC-based multi-input multi-output control algorithm to individually control each of the three swashplate actuators. Wing responses were used for feedback. The GPC-based control system was highly effective in increasing the stability of the critical wing mode for all of the conditions tested, without measurable degradation of the damping in the other modes. The algorithm was also robust with respect to its performance in adjusting to rapid changes in both the rotor speed and the tunnel airspeed.
Method and system for providing precise multi-function modulation
NASA Technical Reports Server (NTRS)
Davarian, Faramaz (Inventor); Sumida, Joe T. (Inventor)
1989-01-01
A method and system is disclosed which provides precise multi-function digitally implementable modulation for a communication system. The invention provides a modulation signal for a communication system in response to an input signal from a data source. A digitized time response is generated from samples of a time domain representation of a spectrum profile of a selected modulation scheme. The invention generates and stores coefficients for each input symbol in accordance with the selected modulation scheme. The output signal is provided by a plurality of samples, each sample being generated by summing the products of a predetermined number of the coefficients and a predetermined number of the samples of the digitized time response. In a specific illustrative implementation, the samples of the output signals are converted to analog signals, filtered and used to modulate a carrier in a conventional manner. The invention is versatile in that it allows for the storage of the digitized time responses and corresponding coefficient lookup table of a number of modulation schemes, any of which may then be selected for use in accordance with the teachings of the invention.
Bagherpoor, H M; Salmasi, Farzad R
2015-07-01
In this paper, robust model reference adaptive tracking controllers are considered for Single-Input Single-Output (SISO) and Multi-Input Multi-Output (MIMO) linear systems containing modeling uncertainties, unknown additive disturbances and actuator fault. Two new lemmas are proposed for both SISO and MIMO, under which dead-zone modification rule is improved such that the tracking error for any reference signal tends to zero in such systems. In the conventional approach, adaption of the controller parameters is ceased inside the dead-zone region which results tracking error, while preserving the system stability. In the proposed scheme, control signal is reinforced with an additive term based on tracking error inside the dead-zone which results in full reference tracking. In addition, no Fault Detection and Diagnosis (FDD) unit is needed in the proposed approach. Closed loop system stability and zero tracking error are proved by considering a suitable Lyapunov functions candidate. It is shown that the proposed control approach can assure that all the signals of the close loop system are bounded in faulty conditions. Finally, validity and performance of the new schemes have been illustrated through numerical simulations of SISO and MIMO systems in the presence of actuator faults, modeling uncertainty and output disturbance. Copyright © 2015 ISA. Published by Elsevier Ltd. All rights reserved.
Development of model reference adaptive control theory for electric power plant control applications
DOE Office of Scientific and Technical Information (OSTI.GOV)
Mabius, L.E.
1982-09-15
The scope of this effort includes the theoretical development of a multi-input, multi-output (MIMO) Model Reference Control (MRC) algorithm, (i.e., model following control law), Model Reference Adaptive Control (MRAC) algorithm and the formulation of a nonlinear model of a typical electric power plant. Previous single-input, single-output MRAC algorithm designs have been generalized to MIMO MRAC designs using the MIMO MRC algorithm. This MRC algorithm, which has been developed using Command Generator Tracker methodologies, represents the steady state behavior (in the adaptive sense) of the MRAC algorithm. The MRC algorithm is a fundamental component in the MRAC design and stability analysis.more » An enhanced MRC algorithm, which has been developed for systems with more controls than regulated outputs, alleviates the MRC stability constraint of stable plant transmission zeroes. The nonlinear power plant model is based on the Cromby model with the addition of a governor valve management algorithm, turbine dynamics and turbine interactions with extraction flows. An application of the MRC algorithm to a linearization of this model demonstrates its applicability to power plant systems. In particular, the generated power changes at 7% per minute while throttle pressure and temperature, reheat temperature and drum level are held constant with a reasonable level of control. The enhanced algorithm reduces significantly control fluctuations without modifying the output response.« less
Measuring efficiency of university-industry Ph.D. projects using best worst method.
Salimi, Negin; Rezaei, Jafar
A collaborative Ph.D. project, carried out by a doctoral candidate, is a type of collaboration between university and industry. Due to the importance of such projects, researchers have considered different ways to evaluate the success, with a focus on the outputs of these projects. However, what has been neglected is the other side of the coin-the inputs. The main aim of this study is to incorporate both the inputs and outputs of these projects into a more meaningful measure called efficiency. A ratio of the weighted sum of outputs over the weighted sum of inputs identifies the efficiency of a Ph.D. The weights of the inputs and outputs can be identified using a multi-criteria decision-making (MCDM) method. Data on inputs and outputs are collected from 51 Ph.D. candidates who graduated from Eindhoven University of Technology. The weights are identified using a new MCDM method called Best Worst Method (BWM). Because there may be differences in the opinion of Ph.D. candidates and supervisors on weighing the inputs and outputs, data for BWM are collected from both groups. It is interesting to see that there are differences in the level of efficiency from the two perspectives, because of the weight differences. Moreover, a comparison between the efficiency scores of these projects and their success scores reveals differences that may have significant implications. A sensitivity analysis divulges the most contributing inputs and outputs.
Using machine learning to replicate chaotic attractors and calculate Lyapunov exponents from data
NASA Astrophysics Data System (ADS)
Pathak, Jaideep; Lu, Zhixin; Hunt, Brian R.; Girvan, Michelle; Ott, Edward
2017-12-01
We use recent advances in the machine learning area known as "reservoir computing" to formulate a method for model-free estimation from data of the Lyapunov exponents of a chaotic process. The technique uses a limited time series of measurements as input to a high-dimensional dynamical system called a "reservoir." After the reservoir's response to the data is recorded, linear regression is used to learn a large set of parameters, called the "output weights." The learned output weights are then used to form a modified autonomous reservoir designed to be capable of producing an arbitrarily long time series whose ergodic properties approximate those of the input signal. When successful, we say that the autonomous reservoir reproduces the attractor's "climate." Since the reservoir equations and output weights are known, we can compute the derivatives needed to determine the Lyapunov exponents of the autonomous reservoir, which we then use as estimates of the Lyapunov exponents for the original input generating system. We illustrate the effectiveness of our technique with two examples, the Lorenz system and the Kuramoto-Sivashinsky (KS) equation. In the case of the KS equation, we note that the high dimensional nature of the system and the large number of Lyapunov exponents yield a challenging test of our method, which we find the method successfully passes.
NASA Astrophysics Data System (ADS)
Chen, Zhan-Ming; Chen, G. Q.
2013-07-01
This study presents a network simulation of the global embodied energy flows in 2007 based on a multi-region input-output model. The world economy is portrayed as a 6384-node network and the energy interactions between any two nodes are calculated and analyzed. According to the results, about 70% of the world's direct energy input is invested in resource, heavy manufacture, and transportation sectors which provide only 30% of the embodied energy to satisfy final demand. By contrast, non-transportation services sectors contribute to 24% of the world's demand-driven energy requirement with only 6% of the direct energy input. Commodity trade is shown to be an important alternative to fuel trade in redistributing energy, as international commodity flows embody 1.74E + 20 J of energy in magnitude up to 89% of the traded fuels. China is the largest embodied energy exporter with a net export of 3.26E + 19 J, in contrast to the United States as the largest importer with a net import of 2.50E + 19 J. The recent economic fluctuations following the financial crisis accelerate the relative expansions of energy requirement by developing countries, as a consequence China will take over the place of the United States as the world's top demand-driven energy consumer in 2022 and India will become the third largest in 2015.
Uenohara, Seiji; Mitsui, Takahito; Hirata, Yoshito; Morie, Takashi; Horio, Yoshihiko; Aihara, Kazuyuki
2013-06-01
We experimentally study strange nonchaotic attractors (SNAs) and chaotic attractors by using a nonlinear integrated circuit driven by a quasiperiodic input signal. An SNA is a geometrically strange attractor for which typical orbits have nonpositive Lyapunov exponents. It is a difficult problem to distinguish between SNAs and chaotic attractors experimentally. If a system has an SNA as a unique attractor, the system produces an identical response to a repeated quasiperiodic signal, regardless of the initial conditions, after a certain transient time. Such reproducibility of response outputs is called consistency. On the other hand, if the attractor is chaotic, the consistency is low owing to the sensitive dependence on initial conditions. In this paper, we analyze the experimental data for distinguishing between SNAs and chaotic attractors on the basis of the consistency.
Quantum channel for the transmission of information
Dress, William B.; Kisner, Roger A.; Richards, Roger K.
2004-01-13
Systems and methods are described for a quantum channel for the transmission of information. A method includes: down converting a beam of coherent energy to provide a beam of multi-color entangled photons; converging two spatially resolved portions of the beam of multi-color entangled photons into a converged multi-color entangled photon beam; changing a phase of at least a portion of the converged multi-color entangled photon beam to generate a first interferometric multi-color entangled photon beam; combining the first interferometric multi-color entangled photon beam with a second interferometric multi-color entangled photon beam within a single beam splitter; wherein combining includes erasing energy and momentum characteristics from both the first interferometric multi-color entangled photon beam and the second interferometric multi-color entangled photon beam; splitting the first interferometric multi-color entangled photon beam and the second interferometric multi-color entangled photon beam within the single beam splitter, wherein splitting yields a first output beam of multi-color entangled photons and a second output beam of multi-color entangled photons; and modulating the first output beam of multi-color entangled photons.
Liu, Bo; Zhang, Lijia; Xin, Xiangjun
2018-03-19
This paper proposes and demonstrates an enhanced secure 4-D modulation optical generalized filter bank multi-carrier (GFBMC) system based on joint constellation and Stokes vector scrambling. The constellation and Stokes vectors are scrambled by using different scrambling parameters. A multi-scroll Chua's circuit map is adopted as the chaotic model. Large secure key space can be obtained due to the multi-scroll attractors and independent operability of subcarriers. A 40.32Gb/s encrypted optical GFBMC signal with 128 parallel subcarriers is successfully demonstrated in the experiment. The results show good resistance against the illegal receiver and indicate a potential way for the future optical multi-carrier system.
Multivariable control of vapor compression systems
DOE Office of Scientific and Technical Information (OSTI.GOV)
He, X.D.; Liu, S.; Asada, H.H.
1999-07-01
This paper presents the results of a study of multi-input multi-output (MIMO) control of vapor compression cycles that have multiple actuators and sensors for regulating multiple outputs, e.g., superheat and evaporating temperature. The conventional single-input single-output (SISO) control was shown to have very limited performance. A low order lumped-parameter model was developed to describe the significant dynamics of vapor compression cycles. Dynamic modes were analyzed based on the low order model to provide physical insight of system dynamic behavior. To synthesize a MIMO control system, the Linear-Quadratic Gaussian (LQG) technique was applied to coordinate compressor speed and expansion valve openingmore » with guaranteed stability robustness in the design. Furthermore, to control a vapor compression cycle over a wide range of operating conditions where system nonlinearities become evident, a gain scheduling scheme was used so that the MIMO controller could adapt to changing operating conditions. Both analytical studies and experimental tests showed that the MIMO control could significantly improve the transient behavior of vapor compression cycles compared to the conventional SISO control scheme. The MIMO control proposed in this paper could be extended to the control of vapor compression cycles in a variety of HVAC and refrigeration applications to improve system performance and energy efficiency.« less
Liu, Yan-Jun; Tong, Shaocheng
2016-11-01
In this paper, we propose an optimal control scheme-based adaptive neural network design for a class of unknown nonlinear discrete-time systems. The controlled systems are in a block-triangular multi-input-multi-output pure-feedback structure, i.e., there are both state and input couplings and nonaffine functions to be included in every equation of each subsystem. The design objective is to provide a control scheme, which not only guarantees the stability of the systems, but also achieves optimal control performance. The main contribution of this paper is that it is for the first time to achieve the optimal performance for such a class of systems. Owing to the interactions among subsystems, making an optimal control signal is a difficult task. The design ideas are that: 1) the systems are transformed into an output predictor form; 2) for the output predictor, the ideal control signal and the strategic utility function can be approximated by using an action network and a critic network, respectively; and 3) an optimal control signal is constructed with the weight update rules to be designed based on a gradient descent method. The stability of the systems can be proved based on the difference Lyapunov method. Finally, a numerical simulation is given to illustrate the performance of the proposed scheme.
Johnstone, C.W.
1958-01-21
An anticoincidence device is described for a pair of adjacent channels of a multi-channel pulse height analyzer for preventing the lower channel from generating a count pulse in response to an input pulse when the input pulse has sufficient magnitude to reach the upper level channel. The anticoincidence circuit comprises a window amplifier, upper and lower level discriminators, and a biased-off amplifier. The output of the window amplifier is coupled to the inputs of the discriminators, the output of the upper level discriminator is connected to the resistance end of a series R-C network, the output of the lower level discriminator is coupled to the capacitance end of the R-C network, and the grid of the biased-off amplifier is coupled to the junction of the R-C network. In operation each discriminator produces a negative pulse output when the input pulse traverses its voltage setting. As a result of the connections to the R-C network, a trigger pulse will be sent to the biased-off amplifier when the incoming pulse level is sufficient to trigger only the lower level discriminator.
A multi-threshold sampling method for TOF-PET signal processing
NASA Astrophysics Data System (ADS)
Kim, H.; Kao, C. M.; Xie, Q.; Chen, C. T.; Zhou, L.; Tang, F.; Frisch, H.; Moses, W. W.; Choong, W. S.
2009-04-01
As an approach to realizing all-digital data acquisition for positron emission tomography (PET), we have previously proposed and studied a multi-threshold sampling method to generate samples of a PET event waveform with respect to a few user-defined amplitudes. In this sampling scheme, one can extract both the energy and timing information for an event. In this paper, we report our prototype implementation of this sampling method and the performance results obtained with this prototype. The prototype consists of two multi-threshold discriminator boards and a time-to-digital converter (TDC) board. Each of the multi-threshold discriminator boards takes one input and provides up to eight threshold levels, which can be defined by users, for sampling the input signal. The TDC board employs the CERN HPTDC chip that determines the digitized times of the leading and falling edges of the discriminator output pulses. We connect our prototype electronics to the outputs of two Hamamatsu R9800 photomultiplier tubes (PMTs) that are individually coupled to a 6.25×6.25×25 mm3 LSO crystal. By analyzing waveform samples generated by using four thresholds, we obtain a coincidence timing resolution of about 340 ps and an ˜18% energy resolution at 511 keV. We are also able to estimate the decay-time constant from the resulting samples and obtain a mean value of 44 ns with an ˜9 ns FWHM. In comparison, using digitized waveforms obtained at a 20 GSps sampling rate for the same LSO/PMT modules we obtain ˜300 ps coincidence timing resolution, ˜14% energy resolution at 511 keV, and ˜5 ns FWHM for the estimated decay-time constant. Details of the results on the timing and energy resolutions by using the multi-threshold method indicate that it is a promising approach for implementing digital PET data acquisition.
NASA Technical Reports Server (NTRS)
Lu, Yun-Chi; Chang, Hyo Duck; Krupp, Brian; Kumar, Ravindra; Swaroop, Anand
1992-01-01
On 18 Jan. 1991, NASA confirmed 29 Inter-Disciplinary Science (IDS) teams, each involving a group of investigators, to conduct interdisciplinary research using data products from Earth Observing System (EOS) instruments. These studies are multi-disciplinary and require output data products from multiple EOS instruments, including both FI and PI instruments. The purpose of this volume is to provide information on output products expected from IDS investigators, required input data, and retrieval algorithms. Also included in this volume is the revised analysis of the 'best' and 'alternative' match data products for IDS input requirements. The original analysis presented in the August 1991 release of the SPSO Report was revised to incorporate the restructuring of the EOS platform. As a result of the reduced EOS payload, some of EOS instruments were deselected and their data products would not be available for IDS research. Information on these data products is also presented.
Robust stability of second-order systems
NASA Technical Reports Server (NTRS)
Chuang, C.-H.
1995-01-01
It has been shown recently how virtual passive controllers can be designed for second-order dynamic systems to achieve robust stability. The virtual controllers were visualized as systems made up of spring, mass and damping elements. In this paper, a new approach emphasizing on the notion of positive realness to the same second-order dynamic systems is used. Necessary and sufficient conditions for positive realness are presented for scalar spring-mass-dashpot systems. For multi-input multi-output systems, we show how a mass-spring-dashpot system can be made positive real by properly choosing its output variables. In particular, sufficient conditions are shown for the system without output velocity. Furthermore, if velocity cannot be measured then the system parameters must be precise to keep the system positive real. In practice, system parameters are not always constant and cannot be measured precisely. Therefore, in order to be useful positive real systems must be robust to some degrees. This can be achieved with the design presented in this paper.
Associative memory model with spontaneous neural activity
NASA Astrophysics Data System (ADS)
Kurikawa, Tomoki; Kaneko, Kunihiko
2012-05-01
We propose a novel associative memory model wherein the neural activity without an input (i.e., spontaneous activity) is modified by an input to generate a target response that is memorized for recall upon the same input. Suitable design of synaptic connections enables the model to memorize input/output (I/O) mappings equaling 70% of the total number of neurons, where the evoked activity distinguishes a target pattern from others. Spontaneous neural activity without an input shows chaotic dynamics but keeps some similarity with evoked activities, as reported in recent experimental studies.
Alsmadi, Othman M K; Abo-Hammour, Zaer S
2015-01-01
A robust computational technique for model order reduction (MOR) of multi-time-scale discrete systems (single input single output (SISO) and multi-input multioutput (MIMO)) is presented in this paper. This work is motivated by the singular perturbation of multi-time-scale systems where some specific dynamics may not have significant influence on the overall system behavior. The new approach is proposed using genetic algorithms (GA) with the advantage of obtaining a reduced order model, maintaining the exact dominant dynamics in the reduced order, and minimizing the steady state error. The reduction process is performed by obtaining an upper triangular transformed matrix of the system state matrix defined in state space representation along with the elements of B, C, and D matrices. The GA computational procedure is based on maximizing the fitness function corresponding to the response deviation between the full and reduced order models. The proposed computational intelligence MOR method is compared to recently published work on MOR techniques where simulation results show the potential and advantages of the new approach.
Uncertainty Quantification in Multi-Scale Coronary Simulations Using Multi-resolution Expansion
NASA Astrophysics Data System (ADS)
Tran, Justin; Schiavazzi, Daniele; Ramachandra, Abhay; Kahn, Andrew; Marsden, Alison
2016-11-01
Computational simulations of coronary flow can provide non-invasive information on hemodynamics that can aid in surgical planning and research on disease propagation. In this study, patient-specific geometries of the aorta and coronary arteries are constructed from CT imaging data and finite element flow simulations are carried out using the open source software SimVascular. Lumped parameter networks (LPN), consisting of circuit representations of vascular hemodynamics and coronary physiology, are used as coupled boundary conditions for the solver. The outputs of these simulations depend on a set of clinically-derived input parameters that define the geometry and boundary conditions, however their values are subjected to uncertainty. We quantify the effects of uncertainty from two sources: uncertainty in the material properties of the vessel wall and uncertainty in the lumped parameter models whose values are estimated by assimilating patient-specific clinical and literature data. We use a generalized multi-resolution chaos approach to propagate the uncertainty. The advantages of this approach lies in its ability to support inputs sampled from arbitrary distributions and its built-in adaptivity that efficiently approximates stochastic responses characterized by steep gradients.
Wu, Jie; Zhou, Zhu-Jun; Zhan, Xi-Sheng; Yan, Huai-Cheng; Ge, Ming-Feng
2017-05-01
This paper investigates the optimal modified tracking performance of multi-input multi-output (MIMO) networked control systems (NCSs) with packet dropouts and bandwidth constraints. Some explicit expressions are obtained by using co-prime factorization and the spectral decomposition technique. The obtained results show that the optimal modified tracking performance is related to the intrinsic properties of a given plant such as non-minimum phase (NMP) zeros, unstable poles, and their directions. Furthermore, the modified factor, packet dropouts probability and bandwidth also impact the optimal modified tracking performance of the NCSs. The optimal modified tracking performance with channel input power constraint is obtained by searching through all stabilizing two-parameter compensator. Finally, some typical examples are given to illustrate the effectiveness of the theoretical results. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.
Adaptive control of a jet turboshaft engine driving a variable pitch propeller using multiple models
NASA Astrophysics Data System (ADS)
Ahmadian, Narjes; Khosravi, Alireza; Sarhadi, Pouria
2017-08-01
In this paper, a multiple model adaptive control (MMAC) method is proposed for a gas turbine engine. The model of a twin spool turbo-shaft engine driving a variable pitch propeller includes various operating points. Variations in fuel flow and propeller pitch inputs produce different operating conditions which force the controller to be adopted rapidly. Important operating points are three idle, cruise and full thrust cases for the entire flight envelope. A multi-input multi-output (MIMO) version of second level adaptation using multiple models is developed. Also, stability analysis using Lyapunov method is presented. The proposed method is compared with two conventional first level adaptation and model reference adaptive control techniques. Simulation results for JetCat SPT5 turbo-shaft engine demonstrate the performance and fidelity of the proposed method.
NASA Astrophysics Data System (ADS)
Liu, Jianxing; Laghrouche, Salah; Wack, Maxime
2014-06-01
In this paper, a full-bridge boost power converter topology is studied for power factor control, using output higher order sliding mode control. The AC/DC converters are used for charging the battery and super-capacitor in hybrid electric vehicles from the utility. The proposed control forces the input currents to track the desired values, which can control the output voltage while keeping the power factor close to one. Super-twisting sliding mode observer is employed to estimate the input currents and load resistance only from the measurement of output voltage. Lyapunov analysis shows the asymptotic convergence of the closed-loop system to zero. Multi-rate simulation illustrates the effectiveness and robustness of the proposed controller in the presence of measurement noise.
The Neurophysiology of Autonomic Dysfunction in SCI: Plasticity in the Input and Output Neurons
2014-04-01
multi-segmental spinal pain reflex Location: Halls B-H Presentation Time: Tuesday , Nov 16, 2010, 8:00 AM - 9:00 AM Authors: *K. E. TANSEY1, M...neurological scoring methods. Cognitive functions were tested using Fear Conditioning tests at 8–10 days post- injury and Morris Water Maze tests 11–15
ERIC Educational Resources Information Center
Aikman, Sheila; Rao, Nitya
2012-01-01
The article draws on qualitative educational research across a diversity of low-income countries to examine the gendered inequalities in education as complex, multi-faceted and situated rather than a series of barriers to be overcome through linear input-output processes focused on isolated dimensions of quality. It argues that frameworks for…
Robust predictive control with optimal load tracking for critical applications. Final report
DOE Office of Scientific and Technical Information (OSTI.GOV)
Tse, J.; Bentsman, J.; Miller, N.
1994-09-01
This report derives a multi-input multi-output (MIMO) version of a two-degree-of-freedom receding-horizon control law based on mixed H{sub 2}/H{infinity} minimization. First, the integrand in the frequency domain representation of the MIMO performance criterion is decomposed into disturbance and reference spectra. Then the controller is derived which minimizes the peak of the disturbance spectrum and the integral of the reference spectrum on the unit circle. The resulting two-degree-of-freedom MIMO control strategy, referred to as the minimax predictive multivariable control (MPC), is shown to have worst-case-disturbance-rejection and robust-stability properties superior to those of purely H{sub 2}-optimal controllers, such as Generalized Predictive Controlmore » (GPC), for identical horizons. An attractive feature of the receding horizon structure of MPC is that it can, in ways similar to GPC, directly incorporate input constraints and pre-programmed reference inputs, which are nontrivial tasks in the standard H{infinity} design.« less
Recursive Deadbeat Controller Design
NASA Technical Reports Server (NTRS)
Juang, Jer-Nan; Phan, Minh Q.
1997-01-01
This paper presents a recursive algorithm for a deadbeat predictive controller design. The method combines together the concepts of system identification and deadbeat controller designs. It starts with the multi-step output prediction equation and derives the control force in terms of past input and output time histories. The formulation thus derived satisfies simultaneously system identification and deadbeat controller design requirements. As soon as the coefficient matrices are identified satisfying the output prediction equation, no further work is required to compute the deadbeat control gain matrices. The method can be implemented recursively just as any typical recursive system identification techniques.
NASA Astrophysics Data System (ADS)
Mansor, Zakwan; Zakaria, Mohd Zakimi; Nor, Azuwir Mohd; Saad, Mohd Sazli; Ahmad, Robiah; Jamaluddin, Hishamuddin
2017-09-01
This paper presents the black-box modelling of palm oil biodiesel engine (POB) using multi-objective optimization differential evolution (MOODE) algorithm. Two objective functions are considered in the algorithm for optimization; minimizing the number of term of a model structure and minimizing the mean square error between actual and predicted outputs. The mathematical model used in this study to represent the POB system is nonlinear auto-regressive moving average with exogenous input (NARMAX) model. Finally, model validity tests are applied in order to validate the possible models that was obtained from MOODE algorithm and lead to select an optimal model.
Multivariable PID controller design tuning using bat algorithm for activated sludge process
NASA Astrophysics Data System (ADS)
Atikah Nor’Azlan, Nur; Asmiza Selamat, Nur; Mat Yahya, Nafrizuan
2018-04-01
The designing of a multivariable PID control for multi input multi output is being concerned with this project by applying four multivariable PID control tuning which is Davison, Penttinen-Koivo, Maciejowski and Proposed Combined method. The determination of this study is to investigate the performance of selected optimization technique to tune the parameter of MPID controller. The selected optimization technique is Bat Algorithm (BA). All the MPID-BA tuning result will be compared and analyzed. Later, the best MPID-BA will be chosen in order to determine which techniques are better based on the system performances in terms of transient response.
Boiler-turbine control system design using a genetic algorithm
DOE Office of Scientific and Technical Information (OSTI.GOV)
Dimeo, R.; Lee, K.Y.
1995-12-01
This paper discusses the application of a genetic algorithm to control system design for a boiler-turbine plant. In particular the authors study the ability of the genetic algorithm to develop a proportional-integral (PI) controller and a state feedback controller for a non-linear multi-input/multi-output (MIMO) plant model. The plant model is presented along with a discussion of the inherent difficulties in such controller development. A sketch of the genetic algorithm (GA) is presented and its strategy as a method of control system design is discussed. Results are presented for two different control systems that have been designed with the genetic algorithm.
Neural dynamic optimization for control systems. I. Background.
Seong, C Y; Widrow, B
2001-01-01
The paper presents neural dynamic optimization (NDO) as a method of optimal feedback control for nonlinear multi-input-multi-output (MIMO) systems. The main feature of NDO is that it enables neural networks to approximate the optimal feedback solution whose existence dynamic programming (DP) justifies, thereby reducing the complexities of computation and storage problems of the classical methods such as DP. This paper mainly describes the background and motivations for the development of NDO, while the two other subsequent papers of this topic present the theory of NDO and demonstrate the method with several applications including control of autonomous vehicles and of a robot arm, respectively.
Neural dynamic optimization for control systems.III. Applications.
Seong, C Y; Widrow, B
2001-01-01
For pt.II. see ibid., p. 490-501. The paper presents neural dynamic optimization (NDO) as a method of optimal feedback control for nonlinear multi-input-multi-output (MIMO) systems. The main feature of NDO is that it enables neural networks to approximate the optimal feedback solution whose existence dynamic programming (DP) justifies, thereby reducing the complexities of computation and storage problems of the classical methods such as DP. This paper demonstrates NDO with several applications including control of autonomous vehicles and of a robot-arm, while the two other companion papers of this topic describes the background for the development of NDO and present the theory of the method, respectively.
Neural dynamic optimization for control systems.II. Theory.
Seong, C Y; Widrow, B
2001-01-01
The paper presents neural dynamic optimization (NDO) as a method of optimal feedback control for nonlinear multi-input-multi-output (MIMO) systems. The main feature of NDO is that it enables neural networks to approximate the optimal feedback solution whose existence dynamic programming (DP) justifies, thereby reducing the complexities of computation and storage problems of the classical methods such as DP. This paper mainly describes the theory of NDO, while the two other companion papers of this topic explain the background for the development of NDO and demonstrate the method with several applications including control of autonomous vehicles and of a robot arm, respectively.
An optimal control model approach to the design of compensators for simulator delay
NASA Technical Reports Server (NTRS)
Baron, S.; Lancraft, R.; Caglayan, A.
1982-01-01
The effects of display delay on pilot performance and workload and of the design of the filters to ameliorate these effects were investigated. The optimal control model for pilot/vehicle analysis was used both to determine the potential delay effects and to design the compensators. The model was applied to a simple roll tracking task and to a complex hover task. The results confirm that even small delays can degrade performance and impose a workload penalty. A time-domain compensator designed by using the optimal control model directly appears capable of providing extensive compensation for these effects even in multi-input, multi-output problems.
Horton, J.A.
1994-05-03
Apparatus for increasing the length of a laser pulse to reduce its peak power without substantial loss in the average power of the pulse is disclosed. The apparatus uses a White cell having a plurality of optical delay paths of successively increasing number of passes between the field mirror and the objective mirrors. A pulse from a laser travels through a multi-leg reflective path between a beam splitter and a totally reflective mirror to the laser output. The laser pulse is also simultaneously injected through the beam splitter to the input mirrors of the optical delay paths. The pulses from the output mirrors of the optical delay paths go simultaneously to the laser output and to the input mirrors of the longer optical delay paths. The beam splitter is 50% reflective and 50% transmissive to provide equal attenuation of all of the pulses at the laser output. 6 figures.
Yang, Xiaoyan; Cui, Jianwei; Lao, Dazhong; Li, Donghai; Chen, Junhui
2016-05-01
In this paper, a composite control based on Active Disturbance Rejection Control (ADRC) and Input Shaping is presented for TRMS with two degrees of freedom (DOF). The control tasks consist of accurately tracking desired trajectories and obtaining disturbance rejection in both horizontal and vertical planes. Due to un-measurable states as well as uncertainties stemming from modeling uncertainty and unknown disturbance torques, ADRC is employed, and feed-forward Input Shaping is used to improve the dynamical response. In the proposed approach, because the coupling effects are maintained in controller derivation, there is no requirement to decouple the TRMS into horizontal and vertical subsystems, which is usually performed in the literature. Finally, the proposed method is implemented on the TRMS platform, and the results are compared with those of PID and ADRC in a similar structure. The experimental results demonstrate the effectiveness of the proposed method. The operation of the controller allows for an excellent set-point tracking behavior and disturbance rejection with system nonlinearity and complex coupling conditions. Copyright © 2016 ISA. Published by Elsevier Ltd. All rights reserved.
Robust set-point regulation for ecological models with multiple management goals.
Guiver, Chris; Mueller, Markus; Hodgson, Dave; Townley, Stuart
2016-05-01
Population managers will often have to deal with problems of meeting multiple goals, for example, keeping at specific levels both the total population and population abundances in given stage-classes of a stratified population. In control engineering, such set-point regulation problems are commonly tackled using multi-input, multi-output proportional and integral (PI) feedback controllers. Building on our recent results for population management with single goals, we develop a PI control approach in a context of multi-objective population management. We show that robust set-point regulation is achieved by using a modified PI controller with saturation and anti-windup elements, both described in the paper, and illustrate the theory with examples. Our results apply more generally to linear control systems with positive state variables, including a class of infinite-dimensional systems, and thus have broader appeal.
NASA Astrophysics Data System (ADS)
Zeb Gul, Jahan; Yang, Bong-Su; Yang, Young Jin; Chang, Dong Eui; Choi, Kyung Hyun
2016-11-01
Soft bots have the expedient ability of adopting intricate postures and fitting in complex shapes compared to mechanical robots. This paper presents a unique in situ UV curing three-dimensional (3D) printed multi-material tri-legged soft bot with spider mimicked multi-step dynamic forward gait using commercial bio metal filament (BMF) as an actuator. The printed soft bot can produce controllable forward motion in response to external signals. The fundamental properties of BMF, including output force, contractions at different frequencies, initial loading rate, and displacement-rate are verified. The tri-pedal soft bot CAD model is designed inspired by spider’s legged structure and its locomotion is assessed by simulating strain and displacement using finite element analysis. A customized rotational multi-head 3D printing system assisted with multiple wavelength’s curing lasers is used for in situ fabrication of tri-pedal soft-bot using two flexible materials (epoxy and polyurethane) in three layered steps. The size of tri-pedal soft-bot is 80 mm in diameter and each pedal’s width and depth is 5 mm × 5 mm respectively. The maximum forward speed achieved is 2.7 mm s-1 @ 5 Hz with input voltage of 3 V and 250 mA on a smooth surface. The fabricated tri-pedal soft bot proved its power efficiency and controllable locomotion at three input signal frequencies (1, 2, 5 Hz).
High-Speed Isolation Board for Flight Hardware Testing
NASA Technical Reports Server (NTRS)
Yamamoto, Clifford K.; Goodpasture, Richard L.
2011-01-01
There is a need to provide a portable and cost-effective galvanic isolation between ground support equipment and flight hardware such that any unforeseen voltage differential between ground and power supplies is eliminated. An interface board was designed for use between the ground support equipment and the flight hardware that electrically isolates all input and output signals and faithfully reproduces them on each side of the interface. It utilizes highly integrated multi-channel isolating devices to minimize size and reduce assembly time. This single-board solution provides appropriate connector hardware and breakout of required flight signals to individual connectors as needed for various ground support equipment. The board utilizes multi-channel integrated circuits that contain transformer coupling, thereby allowing input and output signals to be isolated from one another while still providing high-fidelity reproduction of the signal up to 90 MHz. The board also takes in a single-voltage power supply input from the ground support equipment and in turn provides a transformer-derived isolated voltage supply to power the portion of the circuitry that is electrically connected to the flight hardware. Prior designs used expensive opto-isolated couplers that were required for each signal to isolate and were time-consuming to assemble. In addition, these earlier designs were bulky and required a 2U rack-mount enclosure. The new design is smaller than a piece of 8.5 11-in. (.22 28-mm) paper and can be easily hand-carried where needed. The flight hardware in question is based on a lineage of existing software-defined radios (SDRs) that utilize a common interface connector with many similar input-output signals present. There are currently four to five variations of this SDR, and more upcoming versions are planned based on the more recent design.
Chaos in Kepler's Multiple Planet Systems and K2s Observations of the Atmospheres of Uranus Neptune
NASA Technical Reports Server (NTRS)
Lissauer, Jack J.
2016-01-01
More than one-third of the 4700 planet candidates found by NASA's Kepler spacecraft during its prime mission are associated with target stars that have more than one planet candidate, and such "multis" account for the vast majority of candidates that have been verified as true planets. The large number of multis tells us that flat multiplanet systems like our Solar System are common. Virtually all of the candidate planetary systems are stable, as tested by numerical integrations that assume a physically motivated mass-radius relationship, but some of the systems lie in chaotic regions close to instability. The characteristics of some of the most interesting confirmed Kepler multi-planet systems will be discussed. The Kepler spacecraft's 'second life' in theK2 mission has allowed it to obtain long time-series observations of Solar System targets, including the giant planets Uranus & Neptune. These observations show variability caused by the chaotic weather patterns on Uranus & Neptune.
A Blueprint for Demonstrating Quantum Supremacy with Superconducting Qubits
NASA Technical Reports Server (NTRS)
Kechedzhi, Kostyantyn
2018-01-01
Long coherence times and high fidelity control recently achieved in scalable superconducting circuits paved the way for the growing number of experimental studies of many-qubit quantum coherent phenomena in these devices. Albeit full implementation of quantum error correction and fault tolerant quantum computation remains a challenge the near term pre-error correction devices could allow new fundamental experiments despite inevitable accumulation of errors. One such open question foundational for quantum computing is achieving the so called quantum supremacy, an experimental demonstration of a computational task that takes polynomial time on the quantum computer whereas the best classical algorithm would require exponential time and/or resources. It is possible to formulate such a task for a quantum computer consisting of less than a 100 qubits. The computational task we consider is to provide approximate samples from a non-trivial quantum distribution. This is a generalization for the case of superconducting circuits of ideas behind boson sampling protocol for quantum optics introduced by Arkhipov and Aaronson. In this presentation we discuss a proof-of-principle demonstration of such a sampling task on a 9-qubit chain of superconducting gmon qubits developed by Google. We discuss theoretical analysis of the driven evolution of the device resulting in output approximating samples from a uniform distribution in the Hilbert space, a quantum chaotic state. We analyze quantum chaotic characteristics of the output of the circuit and the time required to generate a sufficiently complex quantum distribution. We demonstrate that the classical simulation of the sampling output requires exponential resources by connecting the task of calculating the output amplitudes to the sign problem of the Quantum Monte Carlo method. We also discuss the detailed theoretical modeling required to achieve high fidelity control and calibration of the multi-qubit unitary evolution in the device. We use a novel cross-entropy statistical metric as a figure of merit to verify the output and calibrate the device controls. Finally, we demonstrate the statistics of the wave function amplitudes generated on the 9-gmon chain and verify the quantum chaotic nature of the generated quantum distribution. This verifies the implementation of the quantum supremacy protocol.
Blaettler, M; Bruegger, A; Forster, I C; Lehareinger, Y
1988-03-01
The design of an analog interface to a digital audio signal processor (DASP)-video cassette recorder (VCR) system is described. The complete system represents a low-cost alternative to both FM instrumentation tape recorders and multi-channel chart recorders. The interface or DASP input-output unit described in this paper enables the recording and playback of up to 12 analog channels with a maximum of 12 bit resolution and a bandwidth of 2 kHz per channel. Internal control and timing in the recording component of the interface is performed using ROMs which can be reprogrammed to suit different analog-to-digital converter hardware. Improvement in the bandwidth specifications is possible by connecting channels in parallel. A parallel 16 bit data output port is provided for direct transfer of the digitized data to a computer.
NASA Technical Reports Server (NTRS)
Davis, Brynmor; Kim, Edward; Piepmeier, Jeffrey; Hildebrand, Peter H. (Technical Monitor)
2001-01-01
Many new Earth remote-sensing instruments are embracing both the advantages and added complexity that result from interferometric or fully polarimetric operation. To increase instrument understanding and functionality a model of the signals these instruments measure is presented. A stochastic model is used as it recognizes the non-deterministic nature of any real-world measurements while also providing a tractable mathematical framework. A stationary, Gaussian-distributed model structure is proposed. Temporal and spectral correlation measures provide a statistical description of the physical properties of coherence and polarization-state. From this relationship the model is mathematically defined. The model is shown to be unique for any set of physical parameters. A method of realizing the model (necessary for applications such as synthetic calibration-signal generation) is given and computer simulation results are presented. The signals are constructed using the output of a multi-input multi-output linear filter system, driven with white noise.
Fabrication of Multi-point Side-Firing Optical Fiber by Laser Micro-ablation
Nguyen, Hoang; Arnob, Md Masud Parvez; Becker, Aaron T; Wolfe, John C; Hogan, Matthew K; Horner, Philip J; Shih, Wei-Chuan
2018-01-01
A multi-point, side-firing design enables an optical fiber to output light at multiple desired locations along the fiber body. This provides advantages over traditional end-to-end fibers, especially in applications requiring fiber bundles such as brain stimulation or remote sensing. This paper demonstrates that continuous wave (CW) laser micro-ablation can controllably create conical-shaped cavities, or side windows, for outputting light. The dimensions of these cavities determine the amount of firing light and their firing angle. Experimental data show that a single side window on a 730 μm fiber can deliver more than 8 % of the input light. This was increased to more than 19 % on a 65 μm fiber with side windows created using femtosecond (fs) laser ablation and chemical etching. Fine control of light distribution along an optical fiber is critical for various biomedical applications such as light activated drug-release and optogenetics studies. PMID:28454166
NASA Technical Reports Server (NTRS)
Sliwa, S. M.
1984-01-01
A prime obstacle to the widespread use of adaptive control is the degradation of performance and possible instability resulting from the presence of unmodeled dynamics. The approach taken is to explicitly include the unstructured model uncertainty in the output error identification algorithm. The order of the compensator is successively increased by including identified modes. During this model building stage, heuristic rules are used to test for convergence prior to designing compensators. Additionally, the recursive identification algorithm as extended to multi-input, multi-output systems. Enhancements were also made to reduce the computational burden of an algorithm for obtaining minimal state space realizations from the inexact, multivariate transfer functions which result from the identification process. A number of potential adaptive control applications for this approach are illustrated using computer simulations. Results indicated that when speed of adaptation and plant stability are not critical, the proposed schemes converge to enhance system performance.
An adaptive tracking observer for failure-detection systems
NASA Technical Reports Server (NTRS)
Sidar, M.
1982-01-01
The design problem of adaptive observers applied to linear, constant and variable parameters, multi-input, multi-output systems, is considered. It is shown that, in order to keep the observer's (or Kalman filter) false-alarm rate (FAR) under a certain specified value, it is necessary to have an acceptable proper matching between the observer (or KF) model and the system parameters. An adaptive observer algorithm is introduced in order to maintain desired system-observer model matching, despite initial mismatching and/or system parameter variations. Only a properly designed adaptive observer is able to detect abrupt changes in the system (actuator, sensor failures, etc.) with adequate reliability and FAR. Conditions for convergence for the adaptive process were obtained, leading to a simple adaptive law (algorithm) with the possibility of an a priori choice of fixed adaptive gains. Simulation results show good tracking performance with small observer output errors and accurate and fast parameter identification, in both deterministic and stochastic cases.
Joint FACET: the Canada-Netherlands initiative to study multisensor data fusion systems
NASA Astrophysics Data System (ADS)
Bosse, Eloi; Theil, Arne; Roy, Jean; Huizing, Albert G.; van Aartsen, Simon
1998-09-01
This paper presents the progress of a collaborative effort between Canada and The Netherlands in analyzing multi-sensor data fusion systems, e.g. for potential application to their respective frigates. In view of the overlapping interest in studying and comparing applicability and performance and advanced state-of-the-art Multi-Sensor Data FUsion (MSDF) techniques, the two research establishments involved have decided to join their efforts in the development of MSDF testbeds. This resulted in the so-called Joint-FACET, a highly modular and flexible series of applications that is capable of processing both real and synthetic input data. Joint-FACET allows the user to create and edit test scenarios with multiple ships, sensor and targets, generate realistic sensor outputs, and to process these outputs with a variety of MSDF algorithms. These MSDF algorithms can also be tested using typical experimental data collected during live military exercises.
NASA Astrophysics Data System (ADS)
Hahn, S. J.; Fawley, W. M.; Kim, K.-J.; Edighoffer, J. A.
1995-04-01
We examine the performance of the so-called electron output scheme recently proposed by the Novosibirsk group [G.I. Erg et al., 15th Int. Free Electron Laser Conf., The Hague, The Netherlands, 1993, Book of Abstracts p. 50; Preprint Budker INP 93-75]. In this scheme, the key role of the FEL oscillator is to induce bunching, while an external undulator, called the radiator, then outcouples the bunched electron beam to optical energy via coherent emission. The level of the intracavity power in the oscillator is kept low by employing a transverse optical klystron (TOK) configuration, thus avoiding excessive thermal loading on the cavity mirrors. Time-dependent effects are important in the operation of the electron output scheme because high gain in the TOK oscillator leads to sideband instabilities and chaotic behavior. We have carried out an extensive simulation study by using 1D and 2D time-dependent codes and find that proper control of the oscillator cavity detuning and cavity loss results in high output bunching with a narrow spectral bandwidth. Large cavity detuning in the oscillator and tapering of the radiator undulator is necessary for the optimum output power.
The drivers of facility-based immunization performance and costs. An application to Moldova.
Maceira, Daniel; Goguadze, Ketevan; Gotsadze, George
2015-05-07
This paper identifies factors that affect the cost and performance of the routine immunization program in Moldova through an analysis of facility-based data collected as part of a multi-country costing and financing study of routine immunization (EPIC). A nationally representative sample of health care facilities (50) was selected through multi-stage, stratified random sampling. Data on inputs, unit prices and facility outputs were collected during October 3rd 2012-January 14th 2013 using a pre-tested structured questionnaire. Ordinary least square (OLS) regression analysis was performed to determine factors affecting facility outputs (number of doses administered and fully immunized children) and explaining variation in total facility costs. The study found that the number of working hours, vaccine wastage rates, and whether or not a doctor worked at a facility (among other factors) were positively and significantly associated with output levels. In addition, the level of output, price of inputs and share of the population with university education were significantly associated with higher facility costs. A 1% increase in fully immunized child would increase total cost by 0.7%. Few costing studies of primary health care services in developing countries evaluate the drivers of performance and cost. This exercise attempted to fill this knowledge gap and helped to identify organizational and managerial factors at a primary care district and national level that could be addressed by improved program management aimed at improved performance. Copyright © 2015 Elsevier Ltd. All rights reserved.
Blank, Jos L T; van Hulst, Bart L
2017-02-17
Well-trained, well-distributed and productive health workers are crucial for access to high-quality, cost-effective healthcare. Because neither a shortage nor a surplus of health workers is wanted, policymakers use workforce planning models to get information on future labour markets and adjust policies accordingly. A neglected topic of workforce planning models is productivity growth, which has an effect on future demand for labour. However, calculating productivity growth for specific types of input is not as straightforward as it seems. This study shows how to calculate factor technical change (FTC) for specific types of input. The paper first theoretically derives FTCs from technical change in a consistent manner. FTC differs from a ratio of output and input, in that it deals with the multi-input, multi-output character of the production process in the health sector. Furthermore, it takes into account substitution effects between different inputs. An application of the calculation of FTCs is given for the Dutch hospital industry for the period 2003-2011. A translog cost function is estimated and used to calculate technical change and FTC for individual inputs, especially specific labour inputs. The results show that technical change increased by 2.8% per year in Dutch hospitals during 2003-2011. FTC differs amongst the various inputs. The FTC of nursing personnel increased by 3.2% per year, implying that fewer nurses were needed to let demand meet supply on the labour market. Sensitivity analyses show consistent results for the FTC of nurses. Productivity growth, especially of individual outputs, is a neglected topic in workforce planning models. FTC is a productivity measure that is consistent with technical change and accounts for substitution effects. An application to the Dutch hospital industry shows that the FTC of nursing personnel outpaced technical change during 2003-2011. The optimal input mix changed, resulting in fewer nurses being needed to let demand meet supply on the labour market. Policymakers should consider using more detailed and specific data on the nature of technical change when forecasting the future demand for health workers.
Digital multi-channel stabilization of four-mode phase-sensitive parametric multicasting.
Liu, Lan; Tong, Zhi; Wiberg, Andreas O J; Kuo, Bill P P; Myslivets, Evgeny; Alic, Nikola; Radic, Stojan
2014-07-28
Stable four-mode phase-sensitive (4MPS) process was investigated as a means to enhance two-pump driven parametric multicasting conversion efficiency (CE) and signal to noise ratio (SNR). Instability of multi-beam, phase sensitive (PS) device that inherently behaves as an interferometer, with output subject to ambient induced fluctuations, was addressed theoretically and experimentally. A new stabilization technique that controls phases of three input waves of the 4MPS multicaster and maximizes CE was developed and described. Stabilization relies on digital phase-locked loop (DPLL) specifically was developed to control pump phases to guarantee stable 4MPS operation that is independent of environmental fluctuations. The technique also controls a single (signal) input phase to optimize the PS-induced improvement of the CE and SNR. The new, continuous-operation DPLL has allowed for fully stabilized PS parametric broadband multicasting, demonstrating CE improvement over 20 signal copies in excess of 10 dB.
Feng, Kai-Ming; Wu, Chung-Yu; Wen, Yu-Hsiang
2012-01-16
By utilizing the cyclic filtering function of an NxN arrayed waveguide grating (AWG), we propose and experimentally demonstrate a novel multi-function all optical packet switching (OPS) architecture by applying a periodical wavelength arrangement between the AWG in the optical routing/buffering unit and a set of wideband optical filters in the switched output ports to achieve the desired routing and buffering functions. The proposed OPS employs only one tunable wavelength converter at the input port to convert the input wavelength to a designated wavelength which reduces the number of active optical components and thus the complexity of the traffic control is simplified in the OPS. With the proposed OPS architecture, multiple optical packet switching functions, including arbitrary packet switching and buffering, first-in-first-out (FIFO) packet multiplexing, packet demultiplexing and packet add/drop multiplexing, have been successfully demonstrated.
2015-11-01
28 2.3.4 Input/Output Automata ...various other modeling frameworks such as I/O Automata , Kahn Process Networks, Petri-nets, Multi-dimensional SDF, etc. are also used for designing...Formal Ideally suited to model DSP applications 3 Petri Nets Graphical Formal Used for modeling distributed systems 4 I/O Automata Both Formal
NASA Astrophysics Data System (ADS)
Gottwald, Georg; Melbourne, Ian
2013-04-01
Whereas diffusion limits of stochastic multi-scale systems have a long and successful history, the case of constructing stochastic parametrizations of chaotic deterministic systems has been much less studied. We present rigorous results of convergence of a chaotic slow-fast system to a stochastic differential equation with multiplicative noise. Furthermore we present rigorous results for chaotic slow-fast maps, occurring as numerical discretizations of continuous time systems. This raises the issue of how to interpret certain stochastic integrals; surprisingly the resulting integrals of the stochastic limit system are generically neither of Stratonovich nor of Ito type in the case of maps. It is shown that the limit system of a numerical discretisation is different to the associated continuous time system. This has important consequences when interpreting the statistics of long time simulations of multi-scale systems - they may be very different to the one of the original continuous time system which we set out to study.
A novel auto-tuning PID control mechanism for nonlinear systems.
Cetin, Meric; Iplikci, Serdar
2015-09-01
In this paper, a novel Runge-Kutta (RK) discretization-based model-predictive auto-tuning proportional-integral-derivative controller (RK-PID) is introduced for the control of continuous-time nonlinear systems. The parameters of the PID controller are tuned using RK model of the system through prediction error-square minimization where the predicted information of tracking error provides an enhanced tuning of the parameters. Based on the model-predictive control (MPC) approach, the proposed mechanism provides necessary PID parameter adaptations while generating additive correction terms to assist the initially inadequate PID controller. Efficiency of the proposed mechanism has been tested on two experimental real-time systems: an unstable single-input single-output (SISO) nonlinear magnetic-levitation system and a nonlinear multi-input multi-output (MIMO) liquid-level system. RK-PID has been compared to standard PID, standard nonlinear MPC (NMPC), RK-MPC and conventional sliding-mode control (SMC) methods in terms of control performance, robustness, computational complexity and design issue. The proposed mechanism exhibits acceptable tuning and control performance with very small steady-state tracking errors, and provides very short settling time for parameter convergence. Copyright © 2015 ISA. Published by Elsevier Ltd. All rights reserved.
Predictive Feedback and Feedforward Control for Systems with Unknown Disturbances
NASA Technical Reports Server (NTRS)
Juang, Jer-Nan; Eure, Kenneth W.
1998-01-01
Predictive feedback control has been successfully used in the regulation of plate vibrations when no reference signal is available for feedforward control. However, if a reference signal is available it may be used to enhance regulation by incorporating a feedforward path in the feedback controller. Such a controller is known as a hybrid controller. This paper presents the theory and implementation of the hybrid controller for general linear systems, in particular for structural vibration induced by acoustic noise. The generalized predictive control is extended to include a feedforward path in the multi-input multi-output case and implemented on a single-input single-output test plant to achieve plate vibration regulation. There are cases in acoustic-induce vibration where the disturbance signal is not available to be used by the hybrid controller, but a disturbance model is available. In this case the disturbance model may be used in the feedback controller to enhance performance. In practice, however, neither the disturbance signal nor the disturbance model is available. This paper presents the theory of identifying and incorporating the noise model into the feedback controller. Implementations are performed on a test plant and regulation improvements over the case where no noise model is used are demonstrated.
Cho, Sunghyun; Choi, Ji-Woong; You, Cheolwoo
2013-10-02
Mobile wireless multimedia sensor networks (WMSNs), which consist of mobile sink or sensor nodes and use rich sensing information, require much faster and more reliable wireless links than static wireless sensor networks (WSNs). This paper proposes an adaptive multi-node (MN) multiple input and multiple output (MIMO) transmission to improve the transmission reliability and capacity of mobile sink nodes when they experience spatial correlation. Unlike conventional single-node (SN) MIMO transmission, the proposed scheme considers the use of transmission antennas from more than two sensor nodes. To find an optimal antenna set and a MIMO transmission scheme, a MN MIMO channel model is introduced first, followed by derivation of closed-form ergodic capacity expressions with different MIMO transmission schemes, such as space-time transmit diversity coding and spatial multiplexing. The capacity varies according to the antenna correlation and the path gain from multiple sensor nodes. Based on these statistical results, we propose an adaptive MIMO mode and antenna set switching algorithm that maximizes the ergodic capacity of mobile sink nodes. The ergodic capacity of the proposed scheme is compared with conventional SN MIMO schemes, where the gain increases as the antenna correlation and path gain ratio increase.
Cho, Sunghyun; Choi, Ji-Woong; You, Cheolwoo
2013-01-01
Mobile wireless multimedia sensor networks (WMSNs), which consist of mobile sink or sensor nodes and use rich sensing information, require much faster and more reliable wireless links than static wireless sensor networks (WSNs). This paper proposes an adaptive multi-node (MN) multiple input and multiple output (MIMO) transmission to improve the transmission reliability and capacity of mobile sink nodes when they experience spatial correlation. Unlike conventional single-node (SN) MIMO transmission, the proposed scheme considers the use of transmission antennas from more than two sensor nodes. To find an optimal antenna set and a MIMO transmission scheme, a MN MIMO channel model is introduced first, followed by derivation of closed-form ergodic capacity expressions with different MIMO transmission schemes, such as space-time transmit diversity coding and spatial multiplexing. The capacity varies according to the antenna correlation and the path gain from multiple sensor nodes. Based on these statistical results, we propose an adaptive MIMO mode and antenna set switching algorithm that maximizes the ergodic capacity of mobile sink nodes. The ergodic capacity of the proposed scheme is compared with conventional SN MIMO schemes, where the gain increases as the antenna correlation and path gain ratio increase. PMID:24152920
NASA Technical Reports Server (NTRS)
Kapasouris, Petros
1988-01-01
A systematic control design methodology is introduced for multi-input/multi-output systems with multiple saturations. The methodology can be applied to stable and unstable open loop plants with magnitude and/or rate control saturations and to systems in which state limitations are desired. This new methodology is a substantial improvement over previous heuristic single-input/single-output approaches. The idea is to introduce a supervisor loop so that when the references and/or disturbances are sufficiently small, the control system operates linearly as designed. For signals large enough to cause saturations, the control law is modified in such a way to ensure stability and to preserve, to the extent possible, the behavior of the linear control design. Key benefits of this methodology are: the modified compensator never produces saturating control signals, integrators and/or slow dynamics in the compensator never windup, the directional properties of the controls are maintained, and the closed loop system has certain guaranteed stability properties. The advantages of the new design methodology are illustrated by numerous simulations, including the multivariable longitudinal control of modified models of the F-8 (stable) and F-16 (unstable) aircraft.
A multi-purpose readout electronics for CdTe and CZT detectors for x-ray imaging applications
NASA Astrophysics Data System (ADS)
Yue, X. B.; Deng, Z.; Xing, Y. X.; Liu, Y. N.
2017-09-01
A multi-purpose readout electronics based on the DPLMS digital filter has been developed for CdTe and CZT detectors for X-ray imaging applications. Different filter coefficients can be synthesized optimized either for high energy resolution at relatively low counting rate or for high rate photon-counting with reduced energy resolution. The effects of signal width constraints, sampling rate and length were numerical studied by Mento Carlo simulation with simple CRRC shaper input signals. The signal width constraint had minor effect and the ENC was only increased by 6.5% when the signal width was shortened down to 2 τc. The sampling rate and length depended on the characteristic time constants of both input and output signals. For simple CR-RC input signals, the minimum number of the filter coefficients was 12 with 10% increase in ENC when the output time constant was close to the input shaping time. A prototype readout electronics was developed for demonstration, using a previously designed analog front ASIC and a commercial ADC card. Two different DPLMS filters were successfully synthesized and applied for high resolution and high counting rate applications respectively. The readout electronics was also tested with a linear array CdTe detector. The energy resolutions of Am-241 59.5 keV peak were measured to be 6.41% in FWHM for the high resolution filter and to be 13.58% in FWHM for the high counting rate filter with 160 ns signal width constraint.
MULTI-CHANNEL ELECTRIC PULSE HEIGHT ANALYZER
Gallagher, J.D. et al.
1960-11-22
An apparatus is given for converting binary information into coded decimal form comprising means, in combination with a binary adder, a live memory and a source of bigit pulses, for synchronizing the bigit pulses and the adder output pulses; a source of digit pulses synchronized with every fourth bigit pulse; means for generating a conversion pulse in response to the time coincidence of the adder output pulse and a digit pulse: means having a delay equal to two bigit pulse periods coupling the adder output with the memory; means for promptly impressing said conversion pulse on the input of said memory: and means having a delay equal to one bigit pulse period for again impressing the conversion pulse on the input of the memory whereby a fourth bigit adder pulse results in the insertion into the memory of second, third and fourth bigits.
Life cycle assessment modelling of waste-to-energy incineration in Spain and Portugal.
Margallo, M; Aldaco, R; Irabien, A; Carrillo, V; Fischer, M; Bala, A; Fullana, P
2014-06-01
In recent years, waste management systems have been evaluated using a life cycle assessment (LCA) approach. A main shortcoming of prior studies was the focus on a mixture of waste with different characteristics. The estimation of emissions and consumptions associated with each waste fraction in these studies presented allocation problems. Waste-to-energy (WTE) incineration is a clear example in which municipal solid waste (MSW), comprising many types of materials, is processed to produce several outputs. This paper investigates an approach to better understand incineration processes in Spain and Portugal by applying a multi-input/output allocation model. The application of this model enabled predictions of WTE inputs and outputs, including the consumption of ancillary materials and combustibles, air emissions, solid wastes, and the energy produced during the combustion of each waste fraction. © The Author(s) 2014.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Finsterle, Stefan A.
2010-11-01
iTOUGH2 (inverse TOUGH2) provides inverse modeling capabilities for TOUGH2, a simulator for multi-dimensional , multi-phase, multi-component, non-isothermal flow and transport in fractured porous media. It performs sensitivity analysis, parameter estimation, and uncertainty propagation, analysis in geosciences and reservoir engineering and other application areas. It supports a number of different combination of fluids and components [equation-of-state (EOS) modules]. In addition, the optimization routines implemented in iTOUGH2 can also be used or sensitivity analysis, automatic model calibration, and uncertainty quantification of any external code that uses text-based input and output files. This link is achieved by means of the PEST application programmingmore » interface. iTOUGH2 solves the inverse problem by minimizing a non-linear objective function of the weighted differences between model output and the corresponding observations. Multiple minimization algorithms (derivative fee, gradient-based and second-order; local and global) are available. iTOUGH2 also performs Latin Hypercube Monte Carlos simulation for uncertainty propagation analysis. A detailed residual and error analysis is provided. This upgrade includes new EOS modules (specifically EOS7c, ECO2N and TMVOC), hysteretic relative permeability and capillary pressure functions and the PEST API. More details can be found at http://esd.lbl.gov/iTOUGH2 and the publications cited there. Hardware Req.: Multi-platform; Related/auxiliary software PVM (if running in parallel).« less
Liu, Yan-Jun; Tong, Shaocheng; Chen, C L Philip; Li, Dong-Juan
2017-11-01
A neural network (NN) adaptive control design problem is addressed for a class of uncertain multi-input-multi-output (MIMO) nonlinear systems in block-triangular form. The considered systems contain uncertainty dynamics and their states are enforced to subject to bounded constraints as well as the couplings among various inputs and outputs are inserted in each subsystem. To stabilize this class of systems, a novel adaptive control strategy is constructively framed by using the backstepping design technique and NNs. The novel integral barrier Lyapunov functionals (BLFs) are employed to overcome the violation of the full state constraints. The proposed strategy can not only guarantee the boundedness of the closed-loop system and the outputs are driven to follow the reference signals, but also can ensure all the states to remain in the predefined compact sets. Moreover, the transformed constraints on the errors are used in the previous BLF, and accordingly it is required to determine clearly the bounds of the virtual controllers. Thus, it can relax the conservative limitations in the traditional BLF-based controls for the full state constraints. This conservatism can be solved in this paper and it is for the first time to control this class of MIMO systems with the full state constraints. The performance of the proposed control strategy can be verified through a simulation example.
Using Systems Thinking to train future leaders in global health.
Paxton, Anne; Frost, Laura J
2017-07-09
Systems Thinking provides a useful set of concepts and tools that can be used to train students to be effective and innovative global health leaders in an ever-changing and often chaotic world. This paper describes an experiential, multi-disciplinary curriculum that uses Systems Thinking to frame and analyse global health policies and practices. The curriculum uses case studies and hands-on activities to deepen students' understanding of the following concepts: complex adaptive systems, dynamic complexity, inter-relationships, feedback loops, policy resistance, mental models, boundary critique, leverage points, and multi-disciplinary, multi-sectoral, and multi-stakeholder thinking and action. A sample of Systems Thinking tools for analysing global health policies and practices are also introduced.
NASA Astrophysics Data System (ADS)
Koliopoulos, T. C.; Koliopoulou, G.
2007-10-01
We present an input-output solution for simulating the associated behavior and optimized physical needs of an environmental system. The simulations and numerical analysis determined the accurate boundary loads and areas that were required to interact for the proper physical operation of a complicated environmental system. A case study was conducted to simulate the optimum balance of an environmental system based on an artificial intelligent multi-interacting input-output numerical scheme. The numerical results were focused on probable further environmental management techniques, with the objective of minimizing any risks and associated environmental impact to protect the quality of public health and the environment. Our conclusions allowed us to minimize the associated risks, focusing on probable cases in an emergency to protect the surrounded anthropogenic or natural environment. Therefore, the lining magnitude could be determined for any useful associated technical works to support the environmental system under examination, taking into account its particular boundary necessities and constraints.
Method and apparatus for stabilizing pulsed microwave amplifiers
Hopkins, Donald B.
1993-01-01
Phase and amplitude variations at the output of a high power pulsed microwave amplifier arising from instabilities of the driving electron beam are suppressed with a feed-forward system that can stabilize pulses which are too brief for regulation by conventional feedback techniques. Such variations tend to be similar during successive pulses. The variations are detected during each pulse by comparing the amplifier output with the low power input signal to obtain phase and amplitude error signals. This enables storage of phase and amplitude correction signals which are used to make compensating changes in the low power input signal during the following amplifier output pulse which suppress the variations. In the preferred form of the invention, successive increments of the correction signals for each pulse are stored in separate channels of a multi-channel storage. Sequential readout of the increments during the next pulse provides variable control voltages to a voltage controlled phase shifter and voltage controlled amplitude modulator in the amplifier input signal path.
Method and apparatus for stabilizing pulsed microwave amplifiers
Hopkins, D.B.
1993-01-26
Phase and amplitude variations at the output of a high power pulsed microwave amplifier arising from instabilities of the driving electron beam are suppressed with a feed-forward system that can stabilize pulses which are too brief for regulation by conventional feedback techniques. Such variations tend to be similar during successive pulses. The variations are detected during each pulse by comparing the amplifier output with the low power input signal to obtain phase and amplitude error signals. This enables storage of phase and amplitude correction signals which are used to make compensating changes in the low power input signal during the following amplifier output pulse which suppress the variations. In the preferred form of the invention, successive increments of the correction signals for each pulse are stored in separate channels of a multi-channel storage. Sequential readout of the increments during the next pulse provides variable control voltages to a voltage controlled phase shifter and voltage controlled amplitude modulator in the amplifier input signal path.
NASA Astrophysics Data System (ADS)
Lumentut, M. F.; Howard, I. M.
2013-03-01
Power harvesters that extract energy from vibrating systems via piezoelectric transduction show strong potential for powering smart wireless sensor devices in applications of health condition monitoring of rotating machinery and structures. This paper presents an analytical method for modelling an electromechanical piezoelectric bimorph beam with tip mass under two input base transverse and longitudinal excitations. The Euler-Bernoulli beam equations were used to model the piezoelectric bimorph beam. The polarity-electric field of the piezoelectric element is excited by the strain field caused by base input excitation, resulting in electrical charge. The governing electromechanical dynamic equations were derived analytically using the weak form of the Hamiltonian principle to obtain the constitutive equations. Three constitutive electromechanical dynamic equations based on independent coefficients of virtual displacement vectors were formulated and then further modelled using the normalised Ritz eigenfunction series. The electromechanical formulations include both the series and parallel connections of the piezoelectric bimorph. The multi-mode frequency response functions (FRFs) under varying electrical load resistance were formulated using Laplace transformation for the multi-input mechanical vibrations to provide the multi-output dynamic displacement, velocity, voltage, current and power. The experimental and theoretical validations reduced for the single mode system were shown to provide reasonable predictions. The model results from polar base excitation for off-axis input motions were validated with experimental results showing the change to the electrical power frequency response amplitude as a function of excitation angle, with relevance for practical implementation.
Multi-modality image fusion based on enhanced fuzzy radial basis function neural networks.
Chao, Zhen; Kim, Dohyeon; Kim, Hee-Joung
2018-04-01
In clinical applications, single modality images do not provide sufficient diagnostic information. Therefore, it is necessary to combine the advantages or complementarities of different modalities of images. Recently, neural network technique was applied to medical image fusion by many researchers, but there are still many deficiencies. In this study, we propose a novel fusion method to combine multi-modality medical images based on the enhanced fuzzy radial basis function neural network (Fuzzy-RBFNN), which includes five layers: input, fuzzy partition, front combination, inference, and output. Moreover, we propose a hybrid of the gravitational search algorithm (GSA) and error back propagation algorithm (EBPA) to train the network to update the parameters of the network. Two different patterns of images are used as inputs of the neural network, and the output is the fused image. A comparison with the conventional fusion methods and another neural network method through subjective observation and objective evaluation indexes reveals that the proposed method effectively synthesized the information of input images and achieved better results. Meanwhile, we also trained the network by using the EBPA and GSA, individually. The results reveal that the EBPGSA not only outperformed both EBPA and GSA, but also trained the neural network more accurately by analyzing the same evaluation indexes. Copyright © 2018 Associazione Italiana di Fisica Medica. Published by Elsevier Ltd. All rights reserved.
Skinner, Owen S; Schachner, Luis F; Kelleher, Neil L
2016-12-08
Recent advances in top-down mass spectrometry using native electrospray now enable the analysis of intact protein complexes with relatively small sample amounts in an untargeted mode. Here, we describe how to characterize both homo- and heteropolymeric complexes with high molecular specificity using input data produced by tandem mass spectrometry of whole protein assemblies. The tool described is a "search engine for multi-proteoform complexes," (SEMPC) and is available for free online. The output is a list of candidate multi-proteoform complexes and scoring metrics, which are used to define a distinct set of one or more unique protein subunits, their overall stoichiometry in the intact complex, and their pre- and post-translational modifications. Thus, we present an approach for the identification and characterization of intact protein complexes from native mass spectrometry data. © 2016 by John Wiley & Sons, Inc. Copyright © 2016 John Wiley & Sons, Inc.
NASA Astrophysics Data System (ADS)
Navarrete, Álvaro; Wang, Wenyuan; Xu, Feihu; Curty, Marcos
2018-04-01
The experimental characterization of multi-photon quantum interference effects in optical networks is essential in many applications of photonic quantum technologies, which include quantum computing and quantum communication as two prominent examples. However, such characterization often requires technologies which are beyond our current experimental capabilities, and today's methods suffer from errors due to the use of imperfect sources and photodetectors. In this paper, we introduce a simple experimental technique to characterize multi-photon quantum interference by means of practical laser sources and threshold single-photon detectors. Our technique is based on well-known methods in quantum cryptography which use decoy settings to tightly estimate the statistics provided by perfect devices. As an illustration of its practicality, we use this technique to obtain a tight estimation of both the generalized Hong‑Ou‑Mandel dip in a beamsplitter with six input photons and the three-photon coincidence probability at the output of a tritter.
Study on Data Clustering and Intelligent Decision Algorithm of Indoor Localization
NASA Astrophysics Data System (ADS)
Liu, Zexi
2018-01-01
Indoor positioning technology enables the human beings to have the ability of positional perception in architectural space, and there is a shortage of single network coverage and the problem of location data redundancy. So this article puts forward the indoor positioning data clustering algorithm and intelligent decision-making research, design the basic ideas of multi-source indoor positioning technology, analyzes the fingerprint localization algorithm based on distance measurement, position and orientation of inertial device integration. By optimizing the clustering processing of massive indoor location data, the data normalization pretreatment, multi-dimensional controllable clustering center and multi-factor clustering are realized, and the redundancy of locating data is reduced. In addition, the path is proposed based on neural network inference and decision, design the sparse data input layer, the dynamic feedback hidden layer and output layer, low dimensional results improve the intelligent navigation path planning.
A cryptographic hash function based on chaotic network automata
NASA Astrophysics Data System (ADS)
Machicao, Jeaneth; Bruno, Odemir M.
2017-12-01
Chaos theory has been used to develop several cryptographic methods relying on the pseudo-random properties extracted from simple nonlinear systems such as cellular automata (CA). Cryptographic hash functions (CHF) are commonly used to check data integrity. CHF “compress” arbitrary long messages (input) into much smaller representations called hash values or message digest (output), designed to prevent the ability to reverse the hash values into the original message. This paper proposes a chaos-based CHF inspired on an encryption method based on chaotic CA rule B1357-S2468. Here, we propose an hybrid model that combines CA and networks, called network automata (CNA), whose chaotic spatio-temporal outputs are used to compute a hash value. Following the Merkle and Damgård model of construction, a portion of the message is entered as the initial condition of the network automata, so that the rest parts of messages are iteratively entered to perturb the system. The chaotic network automata shuffles the message using flexible control parameters, so that the generated hash value is highly sensitive to the message. As demonstrated in our experiments, the proposed model has excellent pseudo-randomness and sensitivity properties with acceptable performance when compared to conventional hash functions.
UWB multi-burst transmit driver for averaging receivers
Dallum, Gregory E
2012-11-20
A multi-burst transmitter for ultra-wideband (UWB) communication systems generates a sequence of precisely spaced RF bursts from a single trigger event. There are two oscillators in the transmitter circuit, a gated burst rate oscillator and a gated RF burst or RF power output oscillator. The burst rate oscillator produces a relatively low frequency, i.e., MHz, square wave output for a selected transmit cycle, and drives the RF burst oscillator, which produces RF bursts of much higher frequency, i.e., GHz, during the transmit cycle. The frequency of the burst rate oscillator sets the spacing of the RF burst packets. The first oscillator output passes through a bias driver to the second oscillator. The bias driver conditions, e.g., level shifts, the signal from the first oscillator for input into the second oscillator, and also controls the length of each RF burst. A trigger pulse actuates a timing circuit, formed of a flip-flop and associated reset time delay circuit, that controls the operation of the first oscillator, i.e., how long it oscillates (which defines the transmit cycle).
NASA Astrophysics Data System (ADS)
Luy, N. T.
2018-04-01
The design of distributed cooperative H∞ optimal controllers for multi-agent systems is a major challenge when the agents' models are uncertain multi-input and multi-output nonlinear systems in strict-feedback form in the presence of external disturbances. In this paper, first, the distributed cooperative H∞ optimal tracking problem is transformed into controlling the cooperative tracking error dynamics in affine form. Second, control schemes and online algorithms are proposed via adaptive dynamic programming (ADP) and the theory of zero-sum differential graphical games. The schemes use only one neural network (NN) for each agent instead of three from ADP to reduce computational complexity as well as avoid choosing initial NN weights for stabilising controllers. It is shown that despite not using knowledge of cooperative internal dynamics, the proposed algorithms not only approximate values to Nash equilibrium but also guarantee all signals, such as the NN weight approximation errors and the cooperative tracking errors in the closed-loop system, to be uniformly ultimately bounded. Finally, the effectiveness of the proposed method is shown by simulation results of an application to wheeled mobile multi-robot systems.
Control law synthesis and optimization software for large order aeroservoelastic systems
NASA Technical Reports Server (NTRS)
Mukhopadhyay, V.; Pototzky, A.; Noll, Thomas
1989-01-01
A flexible aircraft or space structure with active control is typically modeled by a large-order state space system of equations in order to accurately represent the rigid and flexible body modes, unsteady aerodynamic forces, actuator dynamics and gust spectra. The control law of this multi-input/multi-output (MIMO) system is expected to satisfy multiple design requirements on the dynamic loads, responses, actuator deflection and rate limitations, as well as maintain certain stability margins, yet should be simple enough to be implemented on an onboard digital microprocessor. A software package for performing an analog or digital control law synthesis for such a system, using optimal control theory and constrained optimization techniques is described.
Robust, Decoupled, Flight Control Design with Rate Saturating Actuators
NASA Technical Reports Server (NTRS)
Snell, S. A.; Hess, R. A.
1997-01-01
Techniques for the design of control systems for manually controlled, high-performance aircraft must provide the following: (1) multi-input, multi-output (MIMO) solutions, (2) acceptable handling qualities including no tendencies for pilot-induced oscillations, (3) a tractable approach for compensator design, (4) performance and stability robustness in the presence of significant plant uncertainty, and (5) performance and stability robustness in the presence actuator saturation (particularly rate saturation). A design technique built upon Quantitative Feedback Theory is offered as a candidate methodology which can provide flight control systems meeting these requirements, and do so over a considerable part of the flight envelope. An example utilizing a simplified model of a supermaneuverable fighter aircraft demonstrates the proposed design methodology.
Advanced wireless mobile collaborative sensing network for tactical and strategic missions
NASA Astrophysics Data System (ADS)
Xu, Hao
2017-05-01
In this paper, an advanced wireless mobile collaborative sensing network will be developed. Through properly combining wireless sensor network, emerging mobile robots and multi-antenna sensing/communication techniques, we could demonstrate superiority of developed sensing network. To be concrete, heterogeneous mobile robots including unmanned aerial vehicle (UAV) and unmanned ground vehicle (UGV) are equipped with multi-model sensors and wireless transceiver antennas. Through real-time collaborative formation control, multiple mobile robots can team the best formation that can provide most accurate sensing results. Also, formatting multiple mobile robots can also construct a multiple-input multiple-output (MIMO) communication system that can provide a reliable and high performance communication network.
NASA Technical Reports Server (NTRS)
Noll, Thomas E.; Perry, Boyd, III; Tiffany, Sherwood H.; Cole, Stanley R.; Buttrill, Carey S.; Adams, William M., Jr.; Houck, Jacob A.; Srinathkumar, S.; Mukhopadhyay, Vivek; Pototzky, Anthony S.
1989-01-01
The status of the joint NASA/Rockwell Active Flexible Wing Wind-Tunnel Test Program is described. The objectives are to develop and validate the analysis, design, and test methodologies required to apply multifunction active control technology for improving aircraft performance and stability. Major tasks include designing digital multi-input/multi-output flutter-suppression and rolling-maneuver-load alleviation concepts for a flexible full-span wind-tunnel model, obtaining an experimental data base for the basic model and each control concept and providing comparisons between experimental and analytical results to validate the methodologies. The opportunity is provided to improve real-time simulation techniques and to gain practical experience with digital control law implementation procedures.
Computational tools for multi-linked flexible structures
NASA Technical Reports Server (NTRS)
Lee, Gordon K. F.; Brubaker, Thomas A.; Shults, James R.
1990-01-01
A software module which designs and tests controllers and filters in Kalman Estimator form, based on a polynomial state-space model is discussed. The user-friendly program employs an interactive graphics approach to simplify the design process. A variety of input methods are provided to test the effectiveness of the estimator. Utilities are provided which address important issues in filter design such as graphical analysis, statistical analysis, and calculation time. The program also provides the user with the ability to save filter parameters, inputs, and outputs for future use.
Huang, Jianhua; Chen, Yujin; Lin, Yanfu; Gong, Xinghong; Luo, Zundu; Huang, Yidong
2018-04-15
An Er:Yb:Lu 2 Si 2 O 7 microchip laser was constructed by placing a 1.2 mm thick, Y-cut Er:Yb:Lu 2 Si 2 O 7 microchip between two 1.2 mm thick sapphire crystals, in which input and output mirrors were directly deposited onto one face of each crystal. End-pumped by a continuous-wave 975.4 nm diode laser, a 1564 nm multi-longitudinal-mode laser with a maximum output power of 940 mW and slope efficiency of 20% was realized at an absorbed pump power of 5.5 W when the transmission of output mirror was 2.2%. When the transmission of the output mirror was increased to 6%, a 1537 nm single-longitudinal-mode laser with a maximum output power of 440 mW and slope efficiency of 12% was realized at an absorbed pump power of 4.3 W. The results indicate that the Er:Yb:Lu 2 Si 2 O 7 crystal is a promising microchip gain medium to realize a single-longitudinal-mode laser.
Emulating RRTMG Radiation with Deep Neural Networks for the Accelerated Model for Climate and Energy
NASA Astrophysics Data System (ADS)
Pal, A.; Norman, M. R.
2017-12-01
The RRTMG radiation scheme in the Accelerated Model for Climate and Energy Multi-scale Model Framework (ACME-MMF), is a bottleneck and consumes approximately 50% of the computational time. To simulate a case using RRTMG radiation scheme in ACME-MMF with high throughput and high resolution will therefore require a speed-up of this calculation while retaining physical fidelity. In this study, RRTMG radiation is emulated with Deep Neural Networks (DNNs). The first step towards this goal is to run a case with ACME-MMF and generate input data sets for the DNNs. A principal component analysis of these input data sets are carried out. Artificial data sets are created using the previous data sets to cover a wider space. These artificial data sets are used in a standalone RRTMG radiation scheme to generate outputs in a cost effective manner. These input-output pairs are used to train multiple architectures DNNs(1). Another DNN(2) is trained using the inputs to predict the error. A reverse emulation is trained to map the output to input. An error controlled code is developed with the two DNNs (1 and 2) and will determine when/if the original parameterization needs to be used.
Machine Learning Classification of Heterogeneous Fields to Estimate Physical Responses
NASA Astrophysics Data System (ADS)
McKenna, S. A.; Akhriev, A.; Alzate, C.; Zhuk, S.
2017-12-01
The promise of machine learning to enhance physics-based simulation is examined here using the transient pressure response to a pumping well in a heterogeneous aquifer. 10,000 random fields of log10 hydraulic conductivity (K) are created and conditioned on a single K measurement at the pumping well. Each K-field is used as input to a forward simulation of drawdown (pressure decline). The differential equations governing groundwater flow to the well serve as a non-linear transform of the input K-field to an output drawdown field. The results are stored and the data set is split into training and testing sets for classification. A Euclidean distance measure between any two fields is calculated and the resulting distances between all pairs of fields define a similarity matrix. Similarity matrices are calculated for both input K-fields and the resulting drawdown fields at the end of the simulation. The similarity matrices are then used as input to spectral clustering to determine groupings of similar input and output fields. Additionally, the similarity matrix is used as input to multi-dimensional scaling to visualize the clustering of fields in lower dimensional spaces. We examine the ability to cluster both input K-fields and output drawdown fields separately with the goal of identifying K-fields that create similar drawdowns and, conversely, given a set of simulated drawdown fields, identify meaningful clusters of input K-fields. Feature extraction based on statistical parametric mapping provides insight into what features of the fields drive the classification results. The final goal is to successfully classify input K-fields into the correct output class, and also, given an output drawdown field, be able to infer the correct class of input field that created it.
Chaotic behaviors of operational amplifiers.
Yim, Geo-Su; Ryu, Jung-Wan; Park, Young-Jai; Rim, Sunghwan; Lee, Soo-Young; Kye, Won-Ho; Kim, Chil-Min
2004-04-01
We investigate nonlinear dynamical behaviors of operational amplifiers. When the output terminal of an operational amplifier is connected to the inverting input terminal, the circuit exhibits period-doubling bifurcation, chaos, and periodic windows, depending on the voltages of the positive and the negative power supplies. We study these nonlinear dynamical characteristics of this electronic circuit experimentally.
Simulating multiprimary LCDs on standard tri-stimulus LC displays
NASA Astrophysics Data System (ADS)
Lebowsky, Fritz; Vonneilich, Katrin; Bonse, Thomas
2008-01-01
Large-scale, direct view TV screens, in particular those based on liquid crystal technology, are beginning to use subpixel structures with more than three subpixels to implement a multi-primary display with up to six primaries. Since their input color space is likely to remain tri-stimulus RGB we first focus on some fundamental constraints. Among them, we elaborate simplified gamut mapping architectures as well as color filter geometry, transparency, and chromaticity coordinates in color space. Based on a 'display centric' RGB color space tetrahedrization combined with linear interpolation we describe a simulation framework which enables optimization for up to 7 primaries. We evaluated the performance through mapping the multi-primary design back onto a RGB LC display gamut without building a prototype multi-primary display. As long as we kept the RGB equivalent output signal within the display gamut we could analyze all desirable multi-primary configurations with regard to colorimetric variance and visually perceived quality. Not only does our simulation tool enable us to verify a novel concept it also demonstrates how carefully one needs to design a multiprimary display for LCD TV applications.
NASA Astrophysics Data System (ADS)
Zhao, Yongli; Ji, Yuefeng; Zhang, Jie; Li, Hui; Xiong, Qianjin; Qiu, Shaofeng
2014-08-01
Ultrahigh throughout capacity requirement is challenging the current optical switching nodes with the fast development of data center networks. Pbit/s level all optical switching networks need to be deployed soon, which will cause the high complexity of node architecture. How to control the future network and node equipment together will become a new problem. An enhanced Software Defined Networking (eSDN) control architecture is proposed in the paper, which consists of Provider NOX (P-NOX) and Node NOX (N-NOX). With the cooperation of P-NOX and N-NOX, the flexible control of the entire network can be achieved. All optical switching network testbed has been experimentally demonstrated with efficient control of enhanced Software Defined Networking (eSDN). Pbit/s level all optical switching nodes in the testbed are implemented based on multi-dimensional switching architecture, i.e. multi-level and multi-planar. Due to the space and cost limitation, each optical switching node is only equipped with four input line boxes and four output line boxes respectively. Experimental results are given to verify the performance of our proposed control and switching architecture.
Software Defined Radio with Parallelized Software Architecture
NASA Technical Reports Server (NTRS)
Heckler, Greg
2013-01-01
This software implements software-defined radio procession over multi-core, multi-CPU systems in a way that maximizes the use of CPU resources in the system. The software treats each processing step in either a communications or navigation modulator or demodulator system as an independent, threaded block. Each threaded block is defined with a programmable number of input or output buffers; these buffers are implemented using POSIX pipes. In addition, each threaded block is assigned a unique thread upon block installation. A modulator or demodulator system is built by assembly of the threaded blocks into a flow graph, which assembles the processing blocks to accomplish the desired signal processing. This software architecture allows the software to scale effortlessly between single CPU/single-core computers or multi-CPU/multi-core computers without recompilation. NASA spaceflight and ground communications systems currently rely exclusively on ASICs or FPGAs. This software allows low- and medium-bandwidth (100 bps to .50 Mbps) software defined radios to be designed and implemented solely in C/C++ software, while lowering development costs and facilitating reuse and extensibility.
High temperature charge amplifier for geothermal applications
Lindblom, Scott C.; Maldonado, Frank J.; Henfling, Joseph A.
2015-12-08
An amplifier circuit in a multi-chip module includes a charge to voltage converter circuit, a voltage amplifier a low pass filter and a voltage to current converter. The charge to voltage converter receives a signal representing an electrical charge and generates a voltage signal proportional to the input signal. The voltage amplifier receives the voltage signal from the charge to voltage converter, then amplifies the voltage signal by the gain factor to output an amplified voltage signal. The lowpass filter passes low frequency components of the amplified voltage signal and attenuates frequency components greater than a cutoff frequency. The voltage to current converter receives the output signal of the lowpass filter and converts the output signal to a current output signal; wherein an amplifier circuit output is selectable between the output signal of the lowpass filter and the current output signal.
NASA Astrophysics Data System (ADS)
Badrzadeh, Honey; Sarukkalige, Ranjan; Jayawardena, A. W.
2013-12-01
Discrete wavelet transform was applied to decomposed ANN and ANFIS inputs.Novel approach of WNF with subtractive clustering applied for flow forecasting.Forecasting was performed in 1-5 step ahead, using multi-variate inputs.Forecasting accuracy of peak values and longer lead-time significantly improved.
NASA Astrophysics Data System (ADS)
Ling, Jun
Achieving reliable underwater acoustic communications (UAC) has long been recognized as a challenging problem owing to the scarce bandwidth available and the reverberant spread in both time and frequency domains. To pursue high data rates, we consider a multi-input multi-output (MIMO) UAC system, and our focus is placed on two main issues regarding a MIMO UAC system: (1) channel estimation, which involves the design of the training sequences and the development of a reliable channel estimation algorithm, and (2) symbol detection, which requires interference cancelation schemes due to simultaneous transmission from multiple transducers. To enhance channel estimation performance, we present a cyclic approach for designing training sequences with good auto- and cross-correlation properties, and a channel estimation algorithm called the iterative adaptive approach (IAA). Sparse channel estimates can be obtained by combining IAA with the Bayesian information criterion (BIC). Moreover, we present sparse learning via iterative minimization (SLIM) and demonstrate that SLIM gives similar performance to IAA but at a much lower computational cost. Furthermore, an extension of the SLIM algorithm is introduced to estimate the sparse and frequency modulated acoustic channels. The extended algorithm is referred to as generalization of SLIM (GoSLIM). Regarding symbol detection, a linear minimum mean-squared error based detection scheme, called RELAX-BLAST, which is a combination of vertical Bell Labs layered space-time (V-BLAST) algorithm and the cyclic principle of the RELAX algorithm, is presented and it is shown that RELAX-BLAST outperforms V-BLAST. We show that RELAX-BLAST can be implemented efficiently by making use of the conjugate gradient method and diagonalization properties of circulant matrices. This fast implementation approach requires only simple fast Fourier transform operations and facilitates parallel implementations. The effectiveness of the proposed MIMO schemes is verified by both computer simulations and experimental results obtained by analyzing the measurements acquired in multiple in-water experiments.
An enhanced multi-channel bacterial foraging optimization algorithm for MIMO communication system
NASA Astrophysics Data System (ADS)
Palanimuthu, Senthilkumar Jayalakshmi; Muthial, Chandrasekaran
2017-04-01
Channel estimation and optimisation are the main challenging tasks in Multi Input Multi Output (MIMO) wireless communication systems. In this work, a Multi-Channel Bacterial Foraging Optimization Algorithm approach is proposed for the selection of antenna in a transmission area. The main advantage of this method is, it reduces the loss of bandwidth during data transmission effectively. Here, we considered the channel estimation and optimisation for improving the transmission speed and reducing the unused bandwidth. Initially, the message is given to the input of the communication system. Then, the symbol mapping process is performed for converting the message into signals. It will be encoded based on the space-time encoding technique. Here, the single signal is divided into multiple signals and it will be given to the input of space-time precoder. Hence, the multiplexing is applied to transmission channel estimation. In this paper, the Rayleigh channel is selected based on the bandwidth range. This is the Gaussian distribution type channel. Then, the demultiplexing is applied on the obtained signal that is the reverse function of multiplexing, which splits the combined signal arriving from a medium into the original information signal. Furthermore, the long-term evolution technique is used for scheduling the time to channels during transmission. Here, the hidden Markov model technique is employed to predict the status information of the channel. Finally, the signals are decoded and the reconstructed signal is obtained after performing the scheduling process. The experimental results evaluate the performance of the proposed MIMO communication system in terms of bit error rate, mean squared error, average throughput, outage capacity and signal to interference noise ratio.
User Interface on the World Wide Web: How to Implement a Multi-Level Program Online
NASA Technical Reports Server (NTRS)
Cranford, Jonathan W.
1995-01-01
The objective of this Langley Aerospace Research Summer Scholars (LARSS) research project was to write a user interface that utilizes current World Wide Web (WWW) technologies for an existing computer program written in C, entitled LaRCRisk. The project entailed researching data presentation and script execution on the WWW and than writing input/output procedures for the database management portion of LaRCRisk.
Tsai, Jason Sheng-Hong; Du, Yan-Yi; Huang, Pei-Hsiang; Guo, Shu-Mei; Shieh, Leang-San; Chen, Yuhua
2011-07-01
In this paper, a digital redesign methodology of the iterative learning-based decentralized adaptive tracker is proposed to improve the dynamic performance of sampled-data linear large-scale control systems consisting of N interconnected multi-input multi-output subsystems, so that the system output will follow any trajectory which may not be presented by the analytic reference model initially. To overcome the interference of each sub-system and simplify the controller design, the proposed model reference decentralized adaptive control scheme constructs a decoupled well-designed reference model first. Then, according to the well-designed model, this paper develops a digital decentralized adaptive tracker based on the optimal analog control and prediction-based digital redesign technique for the sampled-data large-scale coupling system. In order to enhance the tracking performance of the digital tracker at specified sampling instants, we apply the iterative learning control (ILC) to train the control input via continual learning. As a result, the proposed iterative learning-based decentralized adaptive tracker not only has robust closed-loop decoupled property but also possesses good tracking performance at both transient and steady state. Besides, evolutionary programming is applied to search for a good learning gain to speed up the learning process of ILC. Copyright © 2011 ISA. Published by Elsevier Ltd. All rights reserved.
Martinez, Sara; Marchamalo, Miguel; Alvarez, Sergio
2018-03-15
Wood has been presented as a carbon-neutral material capable of significantly contribute to climate change mitigation and has become an appealing option for the building sector. This paper presents the quantification of the organization environmental footprint of a wood parquet company. The multi-regional input-output (MRIO) database EXIOBASE was used with a further structural path analysis decomposition. The application of the proposed method quantifies 14 environmental impacts. Highly influential sectors and regions responsible for these impacts are assessed to propose efficient measures. For the parquet company studied, the highest impact category once normalized was ozone depletion and the dominant sector responsible for this impact was the chemical industry from Spain and China. The structural path decomposition related to ozone loss revealed that the indirect impacts embedded in the supply chain are higher than the direct impacts. It can be concluded that the assessment of the organizational environmental footprint can be carried out applying this well-structured and robust method. Its implementation will enable tracking of the environmental burdens through a company's supply chain at a global scale and provide information for the adoption of environmental strategies. Copyright © 2017 Elsevier B.V. All rights reserved.
From water use to water scarcity footprinting in environmentally extended input-output analysis.
Ridoutt, Bradley George; Hadjikakou, Michalis; Nolan, Martin; Bryan, Brett A
2018-05-18
Environmentally extended input-output analysis (EEIOA) supports environmental policy by quantifying how demand for goods and services leads to resource use and emissions across the economy. However, some types of resource use and emissions require spatially-explicit impact assessment for meaningful interpretation, which is not possible in conventional EEIOA. For example, water use in locations of scarcity and abundance is not environmentally equivalent. Opportunities for spatially-explicit impact assessment in conventional EEIOA are limited because official input-output tables tend to be produced at the scale of political units which are not usually well aligned with environmentally relevant spatial units. In this study, spatially-explicit water scarcity factors and a spatially disaggregated Australian water use account were used to develop water scarcity extensions that were coupled with a multi-regional input-output model (MRIO). The results link demand for agricultural commodities to the problem of water scarcity in Australia and globally. Important differences were observed between the water use and water scarcity footprint results, as well as the relative importance of direct and indirect water use, with significant implications for sustainable production and consumption-related policies. The approach presented here is suggested as a feasible general approach for incorporating spatially-explicit impact assessment in EEIOA.
Li, Dong-Juan; Li, Da-Peng
2017-09-14
In this paper, an adaptive output feedback control is framed for uncertain nonlinear discrete-time systems. The considered systems are a class of multi-input multioutput nonaffine nonlinear systems, and they are in the nested lower triangular form. Furthermore, the unknown dead-zone inputs are nonlinearly embedded into the systems. These properties of the systems will make it very difficult and challenging to construct a stable controller. By introducing a new diffeomorphism coordinate transformation, the controlled system is first transformed into a state-output model. By introducing a group of new variables, an input-output model is finally obtained. Based on the transformed model, the implicit function theorem is used to determine the existence of the ideal controllers and the approximators are employed to approximate the ideal controllers. By using the mean value theorem, the nonaffine functions of systems can become an affine structure but nonaffine terms still exist. The adaptation auxiliary terms are skillfully designed to cancel the effect of the dead-zone input. Based on the Lyapunov difference theorem, the boundedness of all the signals in the closed-loop system can be ensured and the tracking errors are kept in a bounded compact set. The effectiveness of the proposed technique is checked by a simulation study.
NASA Astrophysics Data System (ADS)
Asgari, Somayyeh; Granpayeh, Nosrat
2017-06-01
Two parallel graphene sheet waveguides and a graphene cylindrical resonator between them is proposed, analyzed, and simulated numerically by using the finite-difference time-domain method. One end of each graphene waveguide is the input and output port. The resonance and the prominent mid-infrared band-pass filtering effect are achieved. The transmittance spectrum is tuned by varying the radius of the graphene cylindrical resonator, the dielectric inside it, and also the chemical potential of graphene utilizing gate voltage. Simulation results are in good agreement with theoretical calculations. As an application, a multi/demultiplexer is proposed and analyzed. Our studies demonstrate that graphene based ultra-compact, nano-scale devices can be designed for optical processing and photonic integrated devices.
NASA Technical Reports Server (NTRS)
Wells, S. R.; Hess, R. A.
2002-01-01
A frequency-domain procedure for the design of sliding mode controllers for multi-input, multi-output (MIMO) systems is presented. The methodology accommodates the effects of parasitic dynamics such as those introduced by unmodeled actuators through the introduction of multiple asymptotic observers and model reference hedging. The design procedure includes a frequency domain approach to specify the sliding manifold, the observer eigenvalues, and the hedge model. The procedure is applied to the development of a flight control system for a linear model of the Innovative Control Effector (ICE) fighter aircraft. The stability and performance robustness of the resulting design is demonstrated through the introduction of significant degradation in the control effector actuators and variation in vehicle dynamics.
Non-cross talk multi-channel photomultiplier using guided electron multipliers
Gomez, J.; Majewski, S.; Weisenberger, A.G.
1995-09-26
An improved multi-channel electron multiplier is provided that exhibits zero cross-talk and high rate operation. Resistive material input and output masks are employed to control divergence of electrons. Electron multiplication takes place in closed channels. Several embodiments are provided for these channels including a continuous resistive emissive multiplier and a discrete resistive multiplier with discrete dynode chains interspaced with resistive layers-masks. Both basic embodiments provide high gain multiplication of electrons without accumulating surface charges while containing electrons to their proper channels to eliminate cross-talk. The invention can be for example applied to improve the performance of ion mass spectrometers, positron emission tomography devices, in DNA sequencing and other beta radiography applications and in many applications in particle physics. 28 figs.
Non cross talk multi-channel photomultiplier using guided electron multipliers
Gomez, Javier; Majewski, Stanislaw; Weisenberger, Andrew G.
1995-01-01
An improved multi-channel electron multiplier is provided that exhibits zero cross-talk and high rate operation. Resistive material input and output masks are employed to control divergence of electrons. Electron multiplication takes place in closed channels. Several embodiments are provided for these channels including a continuous resistive emissive multiplier and a discrete resistive multiplier with discrete dynode chains interspaced with resistive layers-masks. Both basic embodiments provide high gain multiplication of electrons without accumulating surface charges while containing electrons to their proper channels to eliminate cross-talk. The invention can be for example applied to improve the performance of ion mass spectrometers, positron emission tomography devices, in DNA sequencing and other beta radiography applications and in many applications in particle physics.
The optimal location of piezoelectric actuators and sensors for vibration control of plates
NASA Astrophysics Data System (ADS)
Kumar, K. Ramesh; Narayanan, S.
2007-12-01
This paper considers the optimal placement of collocated piezoelectric actuator-sensor pairs on a thin plate using a model-based linear quadratic regulator (LQR) controller. LQR performance is taken as objective for finding the optimal location of sensor-actuator pairs. The problem is formulated using the finite element method (FEM) as multi-input-multi-output (MIMO) model control. The discrete optimal sensor and actuator location problem is formulated in the framework of a zero-one optimization problem. A genetic algorithm (GA) is used to solve the zero-one optimization problem. Different classical control strategies like direct proportional feedback, constant-gain negative velocity feedback and the LQR optimal control scheme are applied to study the control effectiveness.
Ghabraei, Soheil; Moradi, Hamed; Vossoughi, Gholamreza
2015-09-01
To guarantee the safety and efficient performance of the power plant, a robust controller for the boiler-turbine unit is needed. In this paper, a robust adaptive sliding mode controller (RASMC) is proposed to control a nonlinear multi-input multi-output (MIMO) model of industrial boiler-turbine unit, in the presence of unknown bounded uncertainties and external disturbances. To overcome the coupled nonlinearities and investigate the zero dynamics, input-output linearization is performed, and then the new decoupled inputs are derived. To tackle the uncertainties and external disturbances, appropriate adaption laws are introduced. For constructing the RASMC, suitable sliding surface is considered. To guarantee the sliding motion occurrence, appropriate control laws are constructed. Then the robustness and stability of the proposed RASMC is proved via Lyapunov stability theory. To compare the performance of the purposed RASMC with traditional control schemes, a type-I servo controller is designed. To evaluate the performance of the proposed control schemes, simulation studies on nonlinear MIMO dynamic system in the presence of high frequency bounded uncertainties and external disturbances are conducted and compared. Comparison of the results reveals the superiority of proposed RASMC over the traditional control schemes. RAMSC acts efficiently in disturbance rejection and keeping the system behavior in desirable tracking objectives, without the existence of unstable quasi-periodic solutions. Copyright © 2015 ISA. Published by Elsevier Ltd. All rights reserved.
Machine Learning Techniques for Global Sensitivity Analysis in Climate Models
NASA Astrophysics Data System (ADS)
Safta, C.; Sargsyan, K.; Ricciuto, D. M.
2017-12-01
Climate models studies are not only challenged by the compute intensive nature of these models but also by the high-dimensionality of the input parameter space. In our previous work with the land model components (Sargsyan et al., 2014) we identified subsets of 10 to 20 parameters relevant for each QoI via Bayesian compressive sensing and variance-based decomposition. Nevertheless the algorithms were challenged by the nonlinear input-output dependencies for some of the relevant QoIs. In this work we will explore a combination of techniques to extract relevant parameters for each QoI and subsequently construct surrogate models with quantified uncertainty necessary to future developments, e.g. model calibration and prediction studies. In the first step, we will compare the skill of machine-learning models (e.g. neural networks, support vector machine) to identify the optimal number of classes in selected QoIs and construct robust multi-class classifiers that will partition the parameter space in regions with smooth input-output dependencies. These classifiers will be coupled with techniques aimed at building sparse and/or low-rank surrogate models tailored to each class. Specifically we will explore and compare sparse learning techniques with low-rank tensor decompositions. These models will be used to identify parameters that are important for each QoI. Surrogate accuracy requirements are higher for subsequent model calibration studies and we will ascertain the performance of this workflow for multi-site ALM simulation ensembles.
Lower-Order Compensation Chain Threshold-Reduction Technique for Multi-Stage Voltage Multipliers.
Dell' Anna, Francesco; Dong, Tao; Li, Ping; Wen, Yumei; Azadmehr, Mehdi; Casu, Mario; Berg, Yngvar
2018-04-17
This paper presents a novel threshold-compensation technique for multi-stage voltage multipliers employed in low power applications such as passive and autonomous wireless sensing nodes (WSNs) powered by energy harvesters. The proposed threshold-reduction technique enables a topological design methodology which, through an optimum control of the trade-off among transistor conductivity and leakage losses, is aimed at maximizing the voltage conversion efficiency (VCE) for a given ac input signal and physical chip area occupation. The conducted simulations positively assert the validity of the proposed design methodology, emphasizing the exploitable design space yielded by the transistor connection scheme in the voltage multiplier chain. An experimental validation and comparison of threshold-compensation techniques was performed, adopting 2N5247 N-channel junction field effect transistors (JFETs) for the realization of the voltage multiplier prototypes. The attained measurements clearly support the effectiveness of the proposed threshold-reduction approach, which can significantly reduce the chip area occupation for a given target output performance and ac input signal.
Demonstration of a robust magnonic spin wave interferometer.
Kanazawa, Naoki; Goto, Taichi; Sekiguchi, Koji; Granovsky, Alexander B; Ross, Caroline A; Takagi, Hiroyuki; Nakamura, Yuichi; Inoue, Mitsuteru
2016-07-22
Magnonics is an emerging field dealing with ultralow power consumption logic circuits, in which the flow of spin waves, rather than electric charges, transmits and processes information. Waves, including spin waves, excel at encoding information via their phase using interference. This enables a number of inputs to be processed in one device, which offers the promise of multi-input multi-output logic gates. To realize such an integrated device, it is essential to demonstrate spin wave interferometers using spatially isotropic spin waves with high operational stability. However, spin wave reflection at the waveguide edge has previously limited the stability of interfering waves, precluding the use of isotropic spin waves, i.e., forward volume waves. Here, a spin wave absorber is demonstrated comprising a yttrium iron garnet waveguide partially covered by gold. This device is shown experimentally to be a robust spin wave interferometer using the forward volume mode, with a large ON/OFF isolation value of 13.7 dB even in magnetic fields over 30 Oe.
Demonstration of a robust magnonic spin wave interferometer
Kanazawa, Naoki; Goto, Taichi; Sekiguchi, Koji; Granovsky, Alexander B.; Ross, Caroline A.; Takagi, Hiroyuki; Nakamura, Yuichi; Inoue, Mitsuteru
2016-01-01
Magnonics is an emerging field dealing with ultralow power consumption logic circuits, in which the flow of spin waves, rather than electric charges, transmits and processes information. Waves, including spin waves, excel at encoding information via their phase using interference. This enables a number of inputs to be processed in one device, which offers the promise of multi-input multi-output logic gates. To realize such an integrated device, it is essential to demonstrate spin wave interferometers using spatially isotropic spin waves with high operational stability. However, spin wave reflection at the waveguide edge has previously limited the stability of interfering waves, precluding the use of isotropic spin waves, i.e., forward volume waves. Here, a spin wave absorber is demonstrated comprising a yttrium iron garnet waveguide partially covered by gold. This device is shown experimentally to be a robust spin wave interferometer using the forward volume mode, with a large ON/OFF isolation value of 13.7 dB even in magnetic fields over 30 Oe. PMID:27443989
LMI-Based Fuzzy Optimal Variance Control of Airfoil Model Subject to Input Constraints
NASA Technical Reports Server (NTRS)
Swei, Sean S.M.; Ayoubi, Mohammad A.
2017-01-01
This paper presents a study of fuzzy optimal variance control problem for dynamical systems subject to actuator amplitude and rate constraints. Using Takagi-Sugeno fuzzy modeling and dynamic Parallel Distributed Compensation technique, the stability and the constraints can be cast as a multi-objective optimization problem in the form of Linear Matrix Inequalities. By utilizing the formulations and solutions for the input and output variance constraint problems, we develop a fuzzy full-state feedback controller. The stability and performance of the proposed controller is demonstrated through its application to the airfoil flutter suppression.
Coexisting multiple attractors and riddled basins of a memristive system.
Wang, Guangyi; Yuan, Fang; Chen, Guanrong; Zhang, Yu
2018-01-01
In this paper, a new memristor-based chaotic system is designed, analyzed, and implemented. Multistability, multiple attractors, and complex riddled basins are observed from the system, which are investigated along with other dynamical behaviors such as equilibrium points and their stabilities, symmetrical bifurcation diagrams, and sustained chaotic states. With different sets of system parameters, the system can also generate various multi-scroll attractors. Finally, the system is realized by experimental circuits.
Diode-Pumped Narrow Linewidth Multi-kW Metalized Yb Fiber Amplifier
2016-10-01
multi-kW Yb fiber amplifier in a bi-directional pumping configuration. Each pump outputs 2 kW in a 200 µm, 0.2 NA multi-mode fiber. Gold -coated...multi-mode instability, with 90% O-O efficiency 12 GHz Linewidth and M2 < 1.15. OCIS codes: (140.3510) Lasers , fiber; (140.3615) Lasers , ytterbium...060.2430) Fibers, single-mode. 1. INTRODUCTION Yb-doped fiber laser has experienced exponential growth over the past decade. The output power
Robust Indoor Human Activity Recognition Using Wireless Signals.
Wang, Yi; Jiang, Xinli; Cao, Rongyu; Wang, Xiyang
2015-07-15
Wireless signals-based activity detection and recognition technology may be complementary to the existing vision-based methods, especially under the circumstance of occlusions, viewpoint change, complex background, lighting condition change, and so on. This paper explores the properties of the channel state information (CSI) of Wi-Fi signals, and presents a robust indoor daily human activity recognition framework with only one pair of transmission points (TP) and access points (AP). First of all, some indoor human actions are selected as primitive actions forming a training set. Then, an online filtering method is designed to make actions' CSI curves smooth and allow them to contain enough pattern information. Each primitive action pattern can be segmented from the outliers of its multi-input multi-output (MIMO) signals by a proposed segmentation method. Lastly, in online activities recognition, by selecting proper features and Support Vector Machine (SVM) based multi-classification, activities constituted by primitive actions can be recognized insensitive to the locations, orientations, and speeds.
NASA Astrophysics Data System (ADS)
Konishi, Toshifumi; Yamane, Daisuke; Matsushima, Takaaki; Masu, Kazuya; Machida, Katsuyuki; Toshiyoshi, Hiroshi
2014-01-01
This paper reports the design and evaluation results of a capacitive CMOS-MEMS sensor that consists of the proposed sensor circuit and a capacitive MEMS device implemented on the circuit. To design a capacitive CMOS-MEMS sensor, a multi-physics simulation of the electromechanical behavior of both the MEMS structure and the sensing LSI was carried out simultaneously. In order to verify the validity of the design, we applied the capacitive CMOS-MEMS sensor to a MEMS accelerometer implemented by the post-CMOS process onto a 0.35-µm CMOS circuit. The experimental results of the CMOS-MEMS accelerometer exhibited good agreement with the simulation results within the input acceleration range between 0.5 and 6 G (1 G = 9.8 m/s2), corresponding to the output voltages between 908.6 and 915.4 mV, respectively. Therefore, we have confirmed that our capacitive CMOS-MEMS sensor and the multi-physics simulation will be beneficial method to realize integrated CMOS-MEMS technology.
NASA Astrophysics Data System (ADS)
Li, Changping; Yi, Ying; Lee, Kyujin; Lee, Kyesan
2014-08-01
Visible light communication (VLC) applied in an intelligent transportation system (ITS) has attracted growing attentions, but it also faces challenges, for example deep path loss and optical multi-path dispersion. In this work, we modelled an actual outdoor optical channel as a Rician channel and further proposed space-time block coding (STBC) orthogonal frequency-division multiplexing (OFDM) technology to reduce the influence of severe optical multi-path dispersion associated with such a mock channel for achieving the effective BER of 10-6 even at a low signal-to-noise ratio (SNR). In this case, the optical signals transmission distance can be extended as long as possible. Through the simulation results of STBC-OFDM and single-input-single-output (SISO) counterparts in bit error rate (BER) performance comparison, we can distinctly observe that the VLC-ITS system using STBC-OFDM technique can obtain a strongly improved BER performance due to multi-path dispersion alleviation.
Real-time digital signal recovery for a multi-pole low-pass transfer function system.
Lee, Jhinhwan
2017-08-01
In order to solve the problems of waveform distortion and signal delay by many physical and electrical systems with multi-pole linear low-pass transfer characteristics, a simple digital-signal-processing (DSP)-based method of real-time recovery of the original source waveform from the distorted output waveform is proposed. A mathematical analysis on the convolution kernel representation of the single-pole low-pass transfer function shows that the original source waveform can be accurately recovered in real time using a particular moving average algorithm applied on the input stream of the distorted waveform, which can also significantly reduce the overall delay time constant. This method is generalized for multi-pole low-pass systems and has noise characteristics of the inverse of the low-pass filter characteristics. This method can be applied to most sensors and amplifiers operating close to their frequency response limits to improve the overall performance of data acquisition systems and digital feedback control systems.
Dual adaptive control: Design principles and applications
NASA Technical Reports Server (NTRS)
Mookerjee, Purusottam
1988-01-01
The design of an actively adaptive dual controller based on an approximation of the stochastic dynamic programming equation for a multi-step horizon is presented. A dual controller that can enhance identification of the system while controlling it at the same time is derived for multi-dimensional problems. This dual controller uses sensitivity functions of the expected future cost with respect to the parameter uncertainties. A passively adaptive cautious controller and the actively adaptive dual controller are examined. In many instances, the cautious controller is seen to turn off while the latter avoids the turn-off of the control and the slow convergence of the parameter estimates, characteristic of the cautious controller. The algorithms have been applied to a multi-variable static model which represents a simplified linear version of the relationship between the vibration output and the higher harmonic control input for a helicopter. Monte Carlo comparisons based on parametric and nonparametric statistical analysis indicate the superiority of the dual controller over the baseline controller.
NASA Astrophysics Data System (ADS)
Dumon, M.; Van Ranst, E.
2016-01-01
This paper presents a free and open-source program called PyXRD (short for Python X-ray diffraction) to improve the quantification of complex, poly-phasic mixed-layer phyllosilicate assemblages. The validity of the program was checked by comparing its output with Sybilla v2.2.2, which shares the same mathematical formalism. The novelty of this program is the ab initio incorporation of the multi-specimen method, making it possible to share phases and (a selection of) their parameters across multiple specimens. PyXRD thus allows for modelling multiple specimens side by side, and this approach speeds up the manual refinement process significantly. To check the hypothesis that this multi-specimen set-up - as it effectively reduces the number of parameters and increases the number of observations - can also improve automatic parameter refinements, we calculated X-ray diffraction patterns for four theoretical mineral assemblages. These patterns were then used as input for one refinement employing the multi-specimen set-up and one employing the single-pattern set-ups. For all of the assemblages, PyXRD was able to reproduce or approximate the input parameters with the multi-specimen approach. Diverging solutions only occurred in single-pattern set-ups, which do not contain enough information to discern all minerals present (e.g. patterns of heated samples). Assuming a correct qualitative interpretation was made and a single pattern exists in which all phases are sufficiently discernible, the obtained results indicate a good quantification can often be obtained with just that pattern. However, these results from theoretical experiments cannot automatically be extrapolated to all real-life experiments. In any case, PyXRD has proven to be useful when X-ray diffraction patterns are modelled for complex mineral assemblages containing mixed-layer phyllosilicates with a multi-specimen approach.
Chaotic Experiences and Low-Income Children’s Social-Emotional Development
Bobbitt, Kaeley C.; Gershoff, Elizabeth T.
2016-01-01
Development in early childhood is increasingly likely to take place in multiple contexts. Continuity and discontinuity in children’s experiences across multiple contexts have important implications for their development. This study examines the extent to which children experience chaos in their homes and in their preschool settings is linked with their social-emotional development over the course of the preschool year. Data from a large, representative sample of low-income preschool children attending Head Start was used to test a series of multi-level models. Children whose experiences of their homes were highly chaotic, regardless of the how chaotic their experiences of their classroom were, decreased in their social-emotional skills over the preschool year. Chaotic experiences in the home environment thus appear to have more influence on children’s development than do chaotic preschool experiences. PMID:28435178
NASA Astrophysics Data System (ADS)
Li, Shifeng; Duan, Zhaoyun; Huang, Hua; Liu, Zhenbang; He, Hu; Wang, Fei; Wang, Zhanliang; Gong, Yubin
2018-04-01
In this paper, an extended interaction oversized coaxial relativistic klystron amplifier (EIOC-RKA) with Gigawatt-level output at Ka band is proposed. We introduce the oversized coaxial and multi-gap resonant cavities to increase the power capacity and investigate a non-uniform extended interaction output cavity to improve the electronic efficiency of the EIOC-RKA. We develop a high order mode gap in the input and output cavities to easily design and fabricate the input and output couplers. Meanwhile, we design the EIOC-RKA by using the particle-in-cell simulation. In the simulations, we use an electron beam with a current of 6 kA and a voltage of 525 kV, which is focused by a low focusing magnetic flux intensity of 0.5 T. The simulation results demonstrate that the saturated output power is 1.17 GW, the electronic efficiency is 37.1%, and the saturated gain is 57 dB at 30 GHz. The self-oscillation is suppressed by adopting the absorbing materials. The proposed EIOC-RKA has plenty of advantages such as large power capacity, high electronic efficiency, low focusing magnetic, high gain, and simple structure.
A multi-purpose open-source triggering platform for magnetic resonance
NASA Astrophysics Data System (ADS)
Ruytenberg, T.; Webb, A. G.; Beenakker, J. W. M.
2014-10-01
Many MR scans need to be synchronised with external events such as the cardiac or respiratory cycles. For common physiological functions commercial trigger equipment exists, but for more experimental inputs these are not available. This paper describes the design of a multi-purpose open-source trigger platform for MR systems. The heart of the system is an open-source Arduino Due microcontroller. This microcontroller samples an analogue input and digitally processes these data to determine the trigger. The output of the microcontroller is programmed to mimic a physiological signal which is fed into the electrocardiogram (ECG) or pulse oximeter port of MR scanner. The microcontroller is connected to a Bluetooth dongle that allows wireless monitoring and control outside the scanner room. This device can be programmed to generate a trigger based on various types of input. As one example, this paper describes how it can be used as an acoustic cardiac triggering unit. For this, a plastic stethoscope is connected to a microphone which is used as an input for the system. This test setup was used to acquire retrospectively-triggered cardiac scans in ten volunteers. Analysis showed that this platform produces a reliable trigger (>99% triggers are correct) with a small average 8 ms variation between the exact trigger points.
A multi-purpose open-source triggering platform for magnetic resonance.
Ruytenberg, T; Webb, A G; Beenakker, J W M
2014-10-01
Many MR scans need to be synchronised with external events such as the cardiac or respiratory cycles. For common physiological functions commercial trigger equipment exists, but for more experimental inputs these are not available. This paper describes the design of a multi-purpose open-source trigger platform for MR systems. The heart of the system is an open-source Arduino Due microcontroller. This microcontroller samples an analogue input and digitally processes these data to determine the trigger. The output of the microcontroller is programmed to mimic a physiological signal which is fed into the electrocardiogram (ECG) or pulse oximeter port of MR scanner. The microcontroller is connected to a Bluetooth dongle that allows wireless monitoring and control outside the scanner room. This device can be programmed to generate a trigger based on various types of input. As one example, this paper describes how it can be used as an acoustic cardiac triggering unit. For this, a plastic stethoscope is connected to a microphone which is used as an input for the system. This test setup was used to acquire retrospectively-triggered cardiac scans in ten volunteers. Analysis showed that this platform produces a reliable trigger (>99% triggers are correct) with a small average 8 ms variation between the exact trigger points. Copyright © 2014 Elsevier Inc. All rights reserved.
1991-08-01
day oscillation in the extratropical atmosphere as identified by multi-channel singular spectrum analysis 10:25 Coffee Break 10:50 Read Chaotic...day oscillation in the extratropical atmosphere as identified by multi-channel singular spectrum analysis M. Kimoto, M. Ghil and K.-C. Mo ABSTRACT...The three-dimensional spatial structure of an oscillatory mode in the Northern Hemisphere (NH) extratropics will be describe.d The oscillation is
The equal combination synchronization of a class of chaotic systems with discontinuous output
DOE Office of Scientific and Technical Information (OSTI.GOV)
Luo, Runzi; Zeng, Yanhui
This paper investigates the equal combination synchronization of a class of chaotic systems. The chaotic systems are assumed that only the output state variable is available and the output may be discontinuous state variable. By constructing proper observers, some novel criteria for the equal combination synchronization are proposed. The Lorenz chaotic system is taken as an example to demonstrate the efficiency of the proposed approach.
Squeezed light from conventionally pumped multi-level lasers
NASA Technical Reports Server (NTRS)
Ralph, T. C.; Savage, C. M.
1992-01-01
We have calculated the amplitude squeezing in the output of several conventionally pumped multi-level lasers. We present results which show that standard laser models can produce significantly squeezed outputs in certain parameter ranges.
Distributed MIMO chaotic radar based on wavelength-division multiplexing technology.
Yao, Tingfeng; Zhu, Dan; Ben, De; Pan, Shilong
2015-04-15
A distributed multiple-input multiple-output chaotic radar based on wavelength-division multiplexing technology (WDM) is proposed and demonstrated. The wideband quasi-orthogonal chaotic signals generated by different optoelectronic oscillators (OEOs) are emitted by separated antennas to gain spatial diversity against the fluctuation of a target's radar cross section and enhance the detection capability. The received signals collected by the receive antennas and the reference signals from the OEOs are delivered to the central station for joint processing by exploiting WDM technology. The centralized signal processing avoids precise time synchronization of the distributed system and greatly simplifies the remote units, which improves the localization accuracy of the entire system. A proof-of-concept experiment for two-dimensional localization of a metal target is demonstrated. The maximum position error is less than 6.5 cm.
Xarray: multi-dimensional data analysis in Python
NASA Astrophysics Data System (ADS)
Hoyer, Stephan; Hamman, Joe; Maussion, Fabien
2017-04-01
xarray (http://xarray.pydata.org) is an open source project and Python package that provides a toolkit and data structures for N-dimensional labeled arrays, which are the bread and butter of modern geoscientific data analysis. Key features of the package include label-based indexing and arithmetic, interoperability with the core scientific Python packages (e.g., pandas, NumPy, Matplotlib, Cartopy), out-of-core computation on datasets that don't fit into memory, a wide range of input/output options, and advanced multi-dimensional data manipulation tools such as group-by and resampling. In this contribution we will present the key features of the library and demonstrate its great potential for a wide range of applications, from (big-)data processing on super computers to data exploration in front of a classroom.
NASA Astrophysics Data System (ADS)
Zhu, Yixiao; Jiang, Mingxuan; Ruan, Xiaoke; Chen, Zeyu; Li, Chenjia; Zhang, Fan
2018-05-01
We experimentally demonstrate 6.4 Tb/s wavelength division multiplexed (WDM) direct-detection transmission based on Nyquist twin-SSB modulation over 25 km SSMF with bit error rates (BERs) below the 20% hard-decision forward error correction (HD-FEC) threshold of 1.5 × 10-2. The two sidebands of each channel are separately detected using Kramers-Kronig receiver without MIMO equalization. We also carry out numerical simulations to evaluate the system robustness against I/Q amplitude imbalance, I/Q phase deviation and the extinction ratio of modulator, respectively. Furthermore, we show in simulation that the requirement of steep edge optical filter can be relaxed if multi-input-multi-output (MIMO) equalization between the two sidebands is used.
Controllers, observers, and applications thereof
NASA Technical Reports Server (NTRS)
Gao, Zhiqiang (Inventor); Zhou, Wankun (Inventor); Miklosovic, Robert (Inventor); Radke, Aaron (Inventor); Zheng, Qing (Inventor)
2011-01-01
Controller scaling and parameterization are described. Techniques that can be improved by employing the scaling and parameterization include, but are not limited to, controller design, tuning and optimization. The scaling and parameterization methods described here apply to transfer function based controllers, including PID controllers. The parameterization methods also apply to state feedback and state observer based controllers, as well as linear active disturbance rejection (ADRC) controllers. Parameterization simplifies the use of ADRC. A discrete extended state observer (DESO) and a generalized extended state observer (GESO) are described. They improve the performance of the ESO and therefore ADRC. A tracking control algorithm is also described that improves the performance of the ADRC controller. A general algorithm is described for applying ADRC to multi-input multi-output systems. Several specific applications of the control systems and processes are disclosed.
Method and system to perform energy-extraction based active noise control
NASA Technical Reports Server (NTRS)
Kelkar, Atul (Inventor); Joshi, Suresh M. (Inventor)
2009-01-01
A method to provide active noise control to reduce noise and vibration in reverberant acoustic enclosures such as aircraft, vehicles, appliances, instruments, industrial equipment and the like is presented. A continuous-time multi-input multi-output (MIMO) state space mathematical model of the plant is obtained via analytical modeling and system identification. Compensation is designed to render the mathematical model passive in the sense of mathematical system theory. The compensated system is checked to ensure robustness of the passive property of the plant. The check ensures that the passivity is preserved if the mathematical model parameters are perturbed from nominal values. A passivity-based controller is designed and verified using numerical simulations and then tested. The controller is designed so that the resulting closed-loop response shows the desired noise reduction.
Modelling chaotic vibrations using NASTRAN
NASA Technical Reports Server (NTRS)
Sheerer, T. J.
1993-01-01
Due to the unavailability and, later, prohibitive cost of the computational power required, many phenomena in nonlinear dynamic systems have in the past been addressed in terms of linear systems. Linear systems respond to periodic inputs with periodic outputs, and may be characterized in the time domain or in the frequency domain as convenient. Reduction to the frequency domain is frequently desireable to reduce the amount of computation required for solution. Nonlinear systems are only soluble in the time domain, and may exhibit a time history which is extremely sensitive to initial conditions. Such systems are termed chaotic. Dynamic buckling, aeroelasticity, fatigue analysis, control systems and electromechanical actuators are among the areas where chaotic vibrations have been observed. Direct transient analysis over a long time period presents a ready means of simulating the behavior of self-excited or externally excited nonlinear systems for a range of experimental parameters, either to characterize chaotic behavior for development of load spectra, or to define its envelope and preclude its occurrence.
NASA Astrophysics Data System (ADS)
Jeřábek, Jan; Šotner, Roman; Vrba, Kamil
2011-11-01
A universal filter with dual-output current follower (DO-CF), two transconductance amplifiers (OTAs) and two passive elements is presented in this paper. The filter is tunable, of the single-input multiple-output (SIMO) type, and operates in the current mode. Our solution utilizes a low-impedance input node and high-impedance outputs. All types of the active elements used can be realized using our UCC-N1B 0520 integrated circuit and therefore the paper contains not only simulation results that were obtained with the help of behavioral model of the UCC-N1B 0520 element, but also the characteristics that were gained by measurement with the mentioned circuit. The presented simulation and measurement results prove the quality of designed filter. Similar multi-loop structures are very-well known, but there are some drawbacks that are not discussed in similar papers. This paper also contains detailed study of parasitic influences on the filter performance.
Horton, James A.
1994-01-01
Apparatus (20) for increasing the length of a laser pulse to reduce its peak power without substantial loss in the average power of the pulse. The apparatus (20) uses a White cell (10) having a plurality of optical delay paths (18a-18d) of successively increasing number of passes between the field mirror (13) and the objective mirrors (11 and 12). A pulse (26) from a laser (27) travels through a multi-leg reflective path (28) between a beam splitter (21) and a totally reflective mirror (24) to the laser output (37). The laser pulse (26) is also simultaneously injected through the beam splitter (21) to the input mirrors (14a-14d) of the optical delay paths (18a-18d). The pulses from the output mirrors (16a-16d) of the optical delay paths (18a-18d) go simultaneously to the laser output (37) and to the input mirrors ( 14b-14d) of the longer optical delay paths. The beam splitter (21) is 50% reflective and 50% transmissive to provide equal attenuation of all of the pulses at the laser output (37).
Micro-fabrication of a novel linear actuator
NASA Astrophysics Data System (ADS)
Jiang, Shuidong; Liu, Lei; Hou, Yangqing; Fang, Houfei
2017-04-01
The novel linear actuator is researched with light weight, small volume, low power consumption, fast response and relatively large displacement output. It can be used for the net surface control of large deployable mesh antennas, the tension precise adjustment of the controlled cable in the tension and tensile truss structure and many other applications. The structure and the geometry parameters are designed and analysed by finite element method in multi-physics coupling. Meantime, the relationship between input voltage and displacement output is computed, and the strength check is completed according to the stress distribution. Carbon fiber reinforced composite (CFRC), glass fiber reinforced composited (GFRC), and Lead Zirconium Titanate (PZT) materials are used to fabricate the actuator by using laser etching and others MEMS process. The displacement output is measured by the laser displacement sensor device at the input voltage range of DC0-180V. The response time is obtained by oscilloscope at the arbitrarily voltage in the above range. The nominal force output is measured by the PTR-1101 mechanics setup. Finally, the computed and test results are compared and analysed.
Borchani, Hanen; Bielza, Concha; Toro, Carlos; Larrañaga, Pedro
2013-03-01
Our aim is to use multi-dimensional Bayesian network classifiers in order to predict the human immunodeficiency virus type 1 (HIV-1) reverse transcriptase and protease inhibitors given an input set of respective resistance mutations that an HIV patient carries. Multi-dimensional Bayesian network classifiers (MBCs) are probabilistic graphical models especially designed to solve multi-dimensional classification problems, where each input instance in the data set has to be assigned simultaneously to multiple output class variables that are not necessarily binary. In this paper, we introduce a new method, named MB-MBC, for learning MBCs from data by determining the Markov blanket around each class variable using the HITON algorithm. Our method is applied to both reverse transcriptase and protease data sets obtained from the Stanford HIV-1 database. Regarding the prediction of antiretroviral combination therapies, the experimental study shows promising results in terms of classification accuracy compared with state-of-the-art MBC learning algorithms. For reverse transcriptase inhibitors, we get 71% and 11% in mean and global accuracy, respectively; while for protease inhibitors, we get more than 84% and 31% in mean and global accuracy, respectively. In addition, the analysis of MBC graphical structures lets us gain insight into both known and novel interactions between reverse transcriptase and protease inhibitors and their respective resistance mutations. MB-MBC algorithm is a valuable tool to analyze the HIV-1 reverse transcriptase and protease inhibitors prediction problem and to discover interactions within and between these two classes of inhibitors. Copyright © 2012 Elsevier B.V. All rights reserved.
NASA Astrophysics Data System (ADS)
Lu, C.
2017-12-01
This study utilized field outcrops, thin sections, geochemical data, and GR logging curves to investigate the development model of paleokarst within the Longwangmiao Formation in the Lower Cambrian, western Central Yangtze Block, SW China. The Longwangmiao Formation, which belongs to a third-order sequence, consists of four forth-order sequences and is located in the uppermost part of the Lower Cambrian. The vertical variations of the δ13C and δ18O values indicate the existence of multi-stage eogenetic karst events. The eogenetic karst event in the uppermost part of the Longwangmiao Formation is recognized by the dripstones developed within paleocaves, vertical paleoweathering crust with four zones (bedrock, a weak weathering zone, an intense weathering zone and a solution collapsed zone), two generations of calcsparite cement showing bright luminescence and a zonation from nonluminescent to bright to nonluminescent, two types breccias (matrix-rich clast-supported chaotic breccia and matrix-supported chaotic breccia) and rundkarren. The episodic variations of stratiform dissolution vugs and breccias in vertical, and facies-controlled dissolution and filling features indicated the development of multi-stages eogenetic karst. The development of the paleokarst model is controlled by multi-level sea-level changes. The long eccentricity cycle dictates the fluctuations of the forth-order sea-level, generating multi-stage eogenetic karst events. The paleokarst model is an important step towards better understanding the link between the probably orbitally forced sea-level oscillations and eogenetic karst in the Lower Cambrian. According to this paleokarst model, hydrocarbon exploration should focus on both the karst highlands and the karst transitional zone.
3D Visualization of Hydrological Model Outputs For a Better Understanding of Multi-Scale Phenomena
NASA Astrophysics Data System (ADS)
Richard, J.; Schertzer, D. J. M.; Tchiguirinskaia, I.
2014-12-01
During the last decades, many hydrological models has been created to simulate extreme events or scenarios on catchments. The classical outputs of these models are 2D maps, time series or graphs, which are easily understood by scientists, but not so much by many stakeholders, e.g. mayors or local authorities, and the general public. One goal of the Blue Green Dream project is to create outputs that are adequate for them. To reach this goal, we decided to convert most of the model outputs into a unique 3D visualization interface that combines all of them. This conversion has to be performed with an hydrological thinking to keep the information consistent with the context and the raw outputs.We focus our work on the conversion of the outputs of the Multi-Hydro (MH) model, which is physically based, fully distributed and with a GIS data interface. MH splits the urban water cycle into 4 components: the rainfall, the surface runoff, the infiltration and the drainage. To each of them, corresponds a modeling module with specific inputs and outputs. The superimposition of all this information will highlight the model outputs and help to verify the quality of the raw input data. For example, the spatial and the time variability of the rain generated by the rainfall module will be directly visible in 4D (3D + time) before running a full simulation. It is the same with the runoff module: because the result quality depends of the resolution of the rasterized land use, it will confirm or not the choice of the cell size.As most of the inputs and outputs are GIS files, two main conversions will be applied to display the results into 3D. First, a conversion from vector files to 3D objects. For example, buildings are defined in 2D inside a GIS vector file. Each polygon can be extruded with an height to create volumes. The principle is the same for the roads but an intrusion, instead of an extrusion, is done inside the topography file. The second main conversion is the raster conversion. Several files, such as the topography, the land use, the water depth, etc., are defined by geo-referenced grids. The corresponding grids are converted into a list of triangles to be displayed inside the 3D window. For the water depth, the display in pixels will not longer be the only solution. Creation of water contours will be done to more easily delineate the flood inside the catchment.
Semantic classification of business images
NASA Astrophysics Data System (ADS)
Erol, Berna; Hull, Jonathan J.
2006-01-01
Digital cameras are becoming increasingly common for capturing information in business settings. In this paper, we describe a novel method for classifying images into the following semantic classes: document, whiteboard, business card, slide, and regular images. Our method is based on combining low-level image features, such as text color, layout, and handwriting features with high-level OCR output analysis. Several Support Vector Machine Classifiers are combined for multi-class classification of input images. The system yields 95% accuracy in classification.
NASA Astrophysics Data System (ADS)
Bashiri, Mahdi; Farshbaf-Geranmayeh, Amir; Mogouie, Hamed
2013-11-01
In this paper, a new method is proposed to optimize a multi-response optimization problem based on the Taguchi method for the processes where controllable factors are the smaller-the-better (STB)-type variables and the analyzer desires to find an optimal solution with smaller amount of controllable factors. In such processes, the overall output quality of the product should be maximized while the usage of the process inputs, the controllable factors, should be minimized. Since all possible combinations of factors' levels, are not considered in the Taguchi method, the response values of the possible unpracticed treatments are estimated using the artificial neural network (ANN). The neural network is tuned by the central composite design (CCD) and the genetic algorithm (GA). Then data envelopment analysis (DEA) is applied for determining the efficiency of each treatment. Although the important issue for implementation of DEA is its philosophy, which is maximization of outputs versus minimization of inputs, this important issue has been neglected in previous similar studies in multi-response problems. Finally, the most efficient treatment is determined using the maximin weight model approach. The performance of the proposed method is verified in a plastic molding process. Moreover a sensitivity analysis has been done by an efficiency estimator neural network. The results show efficiency of the proposed approach.
All-optical regenerator of multi-channel signals.
Li, Lu; Patki, Pallavi G; Kwon, Young B; Stelmakh, Veronika; Campbell, Brandon D; Annamalai, Muthiah; Lakoba, Taras I; Vasilyev, Michael
2017-10-12
One of the main reasons why nonlinear-optical signal processing (regeneration, logic, etc.) has not yet become a practical alternative to electronic processing is that the all-optical elements with nonlinear input-output relationship have remained inherently single-channel devices (just like their electronic counterparts) and, hence, cannot fully utilise the parallel processing potential of optical fibres and amplifiers. The nonlinear input-output transfer function requires strong optical nonlinearity, e.g. self-phase modulation, which, for fundamental reasons, is always accompanied by cross-phase modulation and four-wave mixing. In processing multiple wavelength-division-multiplexing channels, large cross-phase modulation and four-wave mixing crosstalks among the channels destroy signal quality. Here we describe a solution to this problem: an optical signal processor employing a group-delay-managed nonlinear medium where strong self-phase modulation is achieved without such nonlinear crosstalk. We demonstrate, for the first time to our knowledge, simultaneous all-optical regeneration of up to 16 wavelength-division-multiplexing channels by one device. This multi-channel concept can be extended to other nonlinear-optical processing schemes.Nonlinear optical processing devices are not yet fully practical as they are single channel. Here the authors demonstrate all-optical regeneration of up to 16 channels by one device, employing a group-delay-managed nonlinear medium where strong self-phase modulation is achieved without nonlinear inter-channel crosstalk.
Enhanced Passive RF-DC Converter Circuit Efficiency for Low RF Energy Harvesting
Chaour, Issam; Fakhfakh, Ahmed; Kanoun, Olfa
2017-01-01
For radio frequency energy transmission, the conversion efficiency of the receiver is decisive not only for reducing sending power, but also for enabling energy transmission over long and variable distances. In this contribution, we present a passive RF-DC converter for energy harvesting at ultra-low input power at 868 MHz. The novel converter consists of a reactive matching circuit and a combined voltage multiplier and rectifier. The stored energy in the input inductor and capacitance, during the negative wave, is conveyed to the output capacitance during the positive one. Although Dickson and Villard topologies have principally comparable efficiency for multi-stage voltage multipliers, the Dickson topology reaches a better efficiency within the novel ultra-low input power converter concept. At the output stage, a low-pass filter is introduced to reduce ripple at high frequencies in order to realize a stable DC signal. The proposed rectifier enables harvesting energy at even a low input power from −40 dBm for a resistive load of 50 kΩ. It realizes a significant improvement in comparison with state of the art solutions. PMID:28282910
Enhanced Passive RF-DC Converter Circuit Efficiency for Low RF Energy Harvesting.
Chaour, Issam; Fakhfakh, Ahmed; Kanoun, Olfa
2017-03-09
For radio frequency energy transmission, the conversion efficiency of the receiver is decisive not only for reducing sending power, but also for enabling energy transmission over long and variable distances. In this contribution, we present a passive RF-DC converter for energy harvesting at ultra-low input power at 868 MHz. The novel converter consists of a reactive matching circuit and a combined voltage multiplier and rectifier. The stored energy in the input inductor and capacitance, during the negative wave, is conveyed to the output capacitance during the positive one. Although Dickson and Villard topologies have principally comparable efficiency for multi-stage voltage multipliers, the Dickson topology reaches a better efficiency within the novel ultra-low input power converter concept. At the output stage, a low-pass filter is introduced to reduce ripple at high frequencies in order to realize a stable DC signal. The proposed rectifier enables harvesting energy at even a low input power from -40 dBm for a resistive load of 50 kΩ. It realizes a significant improvement in comparison with state of the art solutions.
Dynamics of a neuron model in different two-dimensional parameter-spaces
NASA Astrophysics Data System (ADS)
Rech, Paulo C.
2011-03-01
We report some two-dimensional parameter-space diagrams numerically obtained for the multi-parameter Hindmarsh-Rose neuron model. Several different parameter planes are considered, and we show that regardless of the combination of parameters, a typical scenario is preserved: for all choice of two parameters, the parameter-space presents a comb-shaped chaotic region immersed in a large periodic region. We also show that exist regions close these chaotic region, separated by the comb teeth, organized themselves in period-adding bifurcation cascades.
Phase Modulator with Terahertz Optical Bandwidth Formed by Multi-Layered Dielectric Stack
NASA Technical Reports Server (NTRS)
Keys, Andrew S. (Inventor); Fork, Richard L. (Inventor)
2005-01-01
An optical phase modulator includes a bandpass multilayer stack, formed by a plurality of dielectric layers, preferably of GaAs and AlAs, and having a transmission function related to the refractive index of the layers of the stack, for receiving an optical input signal to be phase modulated. A phase modulator device produces a nonmechanical change in the refractive index of each layer of the stack by, e.g., the injection of free carrier, to provide shifting of the transmission function so as to produce phase modulation of the optical input signal and to thereby produce a phase modulated output signal.
A radial map of multi-whisker correlation selectivity in the rat barrel cortex
Estebanez, Luc; Bertherat, Julien; Shulz, Daniel E.; Bourdieu, Laurent; Léger, Jean- François
2016-01-01
In the barrel cortex, several features of single-whisker stimuli are organized in functional maps. The barrel cortex also encodes spatio-temporal correlation patterns of multi-whisker inputs, but so far the cortical mapping of neurons tuned to such input statistics is unknown. Here we report that layer 2/3 of the rat barrel cortex contains an additional functional map based on neuronal tuning to correlated versus uncorrelated multi-whisker stimuli: neuron responses to uncorrelated multi-whisker stimulation are strongest above barrel centres, whereas neuron responses to correlated and anti-correlated multi-whisker stimulation peak above the barrel–septal borders, forming rings of multi-whisker synchrony-preferring cells. PMID:27869114
A radial map of multi-whisker correlation selectivity in the rat barrel cortex.
Estebanez, Luc; Bertherat, Julien; Shulz, Daniel E; Bourdieu, Laurent; Léger, Jean-François
2016-11-21
In the barrel cortex, several features of single-whisker stimuli are organized in functional maps. The barrel cortex also encodes spatio-temporal correlation patterns of multi-whisker inputs, but so far the cortical mapping of neurons tuned to such input statistics is unknown. Here we report that layer 2/3 of the rat barrel cortex contains an additional functional map based on neuronal tuning to correlated versus uncorrelated multi-whisker stimuli: neuron responses to uncorrelated multi-whisker stimulation are strongest above barrel centres, whereas neuron responses to correlated and anti-correlated multi-whisker stimulation peak above the barrel-septal borders, forming rings of multi-whisker synchrony-preferring cells.
Tyson, S F; Burton, L; McGovern, A
2014-12-01
To explore how multi-disciplinary team meetings operate in stroke rehabilitation. Non-participant observation of multi-disciplinary team meetings and semi-structured interviews with attending staff. Twelve meetings were observed (at least one at each site) and 18 staff (one psychologist, one social worker; four nurses; four physiotherapists four occupational therapists, two speech and language therapists, one stroke co-ordinator and one stroke ward manager) were interviewed in eight in-patient stroke rehabilitation units. Multi-disciplinary team meetings in stroke rehabilitation were complex, demanding and highly varied. A model emerged which identified the main inputs to influence conduct of the meetings were personal contributions of the members and structure and format of the meetings. These were mediated by the team climate and leadership skills of the chair. The desired outputs; clinical decisions and the attributes of apparently effective meetings were identified by the staff. A notable difference between the meetings that staff considered effective and those that were not, was their structure and format. Successful meetings tended to feature a set agenda, structured documentation; formal use of measurement tools; pre-meeting preparation and skilled chairing. These features were often absent in meetings perceived to be ineffective. The main features of operation of multi-disciplinary team meetings have been identified which will enable assessment tools and interventions to improve effectiveness to be developed. © The Author(s) 2014.
NASA Astrophysics Data System (ADS)
Wan, Shunping; Tian, Qian; Sun, Liqun; Yao, Minyan; Mao, Xianhui; Qiu, Hongyun
2004-05-01
This paper reports an experimental research on the stability of bidirectional outputs and multi-longitudinal mode interference of laser diode end-pumped Nd:YVO4 solid-state ring laser (DPSSL). The bidirectional, multi-longitudinal and TEM00 mode continuous wave outputs are obtained and the output powers are measured and their stabilities are analyzed respectively. The spectral characteristic of the outputs is measured. The interfering pattern of the bidirectional longitudinal mode outputs is obtained and analyzed in the condition of the ring cavity with rotation velocity. The movement of the interfering fringe of the multi-longitudinal modes is very sensitive to the deformation of the setup base and the fluctuation of the intracavity air, but is stationary or randomly dithers when the stage is rotating.
NASA Astrophysics Data System (ADS)
Vishwakarma, Siddharth; Kumar, Ajit; Pandey, Abha; Upadhyay, K. K.
2017-01-01
A chromogenic fluoride probe bearing bis imine groups having dual -NH functionality (BSB) has been designed, synthesised and structurally characterized by its single crystal X-ray diffraction studies. The BSB could visually and spectroscopically recognise F- with high selectivity over other anions by exhibiting intense chromogenic response (from colourless to red) for F- in acetonitrile solution. The UV-visible titration and 1H NMR titration experiments indicated that the observed changes occur via a combined process including hydrogen bonding and deprotonation between the BSB and F-. Moreover theoretical calculations at the Density Functional Theory (DFT) level shed further light upon probe design strategy and the nature of interactions between BSB and F-. The limit of detection and binding constant of BSB towards F- were found to be 6.9 × 10- 7 M and 1.42 ± 0.069 × 108 M- 2 respectively. Finally, by using F- and H+ as chemical inputs and the absorbance as output, a INHIBIT logic gate was constructed, which exhibits "Multi-write" ability without obvious degradation in its optical output.
NASA Technical Reports Server (NTRS)
Patten, W. N.; Robertshaw, H. H.; Pierpont, D.; Wynn, R. H.
1989-01-01
A new, near-optimal feedback control technique is introduced that is shown to provide excellent vibration attenuation for those distributed parameter systems that are often encountered in the areas of aeroservoelasticity and large space systems. The technique relies on a novel solution methodology for the classical optimal control problem. Specifically, the quadratic regulator control problem for a flexible vibrating structure is first cast in a weak functional form that admits an approximate solution. The necessary conditions (first-order) are then solved via a time finite-element method. The procedure produces a low dimensional, algebraic parameterization of the optimal control problem that provides a rigorous basis for a discrete controller with a first-order like hold output. Simulation has shown that the algorithm can successfully control a wide variety of plant forms including multi-input/multi-output systems and systems exhibiting significant nonlinearities. In order to firmly establish the efficacy of the algorithm, a laboratory control experiment was implemented to provide planar (bending) vibration attenuation of a highly flexible beam (with a first clamped-free mode of approximately 0.5 Hz).
Control oriented concentrating solar power (CSP) plant model and its applications
NASA Astrophysics Data System (ADS)
Luo, Qi
Solar receivers in concentrating solar thermal power plants (CSP) undergo over 10,000 start-ups and shutdowns, and over 25,000 rapid rate of change in temperature on receivers due to cloud transients resulting in performance degradation and material fatigue in their expected lifetime of over 30 years. The research proposes to develop a three-level controller that uses multi-input-multi-output (MIMO) control technology to minimize the effect of these disturbances, improve plant performance, and extend plant life. The controller can be readily installed on any vendor supplied state-of-the-art control hardware. We propose a three-level controller architecture using multi-input-multi-output (MIMO) control for CSP plants that can be implemented on existing plants to improve performance, reliability, and extend the life of the plant. This architecture optimizes the performance on multiple time scalesreactive level (regulation to temperature set points), tactical level (adaptation of temperature set points), and strategic level (trading off fatigue life due to thermal cycling and current production). This controller unique to CSP plants operating at temperatures greater than 550 °C, will make CSPs competitive with conventional power plants and contribute significantly towards the Sunshot goal of 0.06/kWh(e), while responding with agility to both market dynamics and changes in solar irradiance such as due to passing clouds. Moreover, our development of control software with performance guarantees will avoid early stage failures and permit smooth grid integration of the CSP power plants. The proposed controller can be implemented with existing control hardware infrastructure with little or no additional equipment. In the thesis, we demonstrate a dynamics model of CSP, of which different components are modelled with different time scales. We also show a real time control strategy of CSP control oriented model in steady state. Furthermore, we shown different controllers design for disturbance rejection and reference tracking to handle complex receiver dynamics under system disturbance and measurement noise. At last, we show different applications of this control oriented CSP model including life cycle enhancement and electricity load forecasting using both neural network and regression tree.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Behrang, M.A.; Assareh, E.; Ghanbarzadeh, A.
2010-08-15
The main objective of present study is to predict daily global solar radiation (GSR) on a horizontal surface, based on meteorological variables, using different artificial neural network (ANN) techniques. Daily mean air temperature, relative humidity, sunshine hours, evaporation, and wind speed values between 2002 and 2006 for Dezful city in Iran (32 16'N, 48 25'E), are used in this study. In order to consider the effect of each meteorological variable on daily GSR prediction, six following combinations of input variables are considered: (I)Day of the year, daily mean air temperature and relative humidity as inputs and daily GSR as output.more » (II)Day of the year, daily mean air temperature and sunshine hours as inputs and daily GSR as output. (III)Day of the year, daily mean air temperature, relative humidity and sunshine hours as inputs and daily GSR as output. (IV)Day of the year, daily mean air temperature, relative humidity, sunshine hours and evaporation as inputs and daily GSR as output. (V)Day of the year, daily mean air temperature, relative humidity, sunshine hours and wind speed as inputs and daily GSR as output. (VI)Day of the year, daily mean air temperature, relative humidity, sunshine hours, evaporation and wind speed as inputs and daily GSR as output. Multi-layer perceptron (MLP) and radial basis function (RBF) neural networks are applied for daily GSR modeling based on six proposed combinations. The measured data between 2002 and 2005 are used to train the neural networks while the data for 214 days from 2006 are used as testing data. The comparison of obtained results from ANNs and different conventional GSR prediction (CGSRP) models shows very good improvements (i.e. the predicted values of best ANN model (MLP-V) has a mean absolute percentage error (MAPE) about 5.21% versus 10.02% for best CGSRP model (CGSRP 5)). (author)« less
Cooperative path planning for multi-USV based on improved artificial bee colony algorithm
NASA Astrophysics Data System (ADS)
Cao, Lu; Chen, Qiwei
2018-03-01
Due to the complex constraints, more uncertain factors and critical real-time demand of path planning for multiple unmanned surface vehicle (multi-USV), an improved artificial bee colony (I-ABC) algorithm were proposed to solve the model of cooperative path planning for multi-USV. First the Voronoi diagram of battle field space is conceived to generate the optimal area of USVs paths. Then the chaotic searching algorithm is used to initialize the collection of paths, which is regard as foods of the ABC algorithm. With the limited data, the initial collection can search the optimal area of paths perfectly. Finally simulations of the multi-USV path planning under various threats have been carried out. Simulation results verify that the I-ABC algorithm can improve the diversity of nectar source and the convergence rate of algorithm. It can increase the adaptability of dynamic battlefield and unexpected threats for USV.
A parameter estimation subroutine package
NASA Technical Reports Server (NTRS)
Bierman, G. J.; Nead, M. W.
1978-01-01
Linear least squares estimation and regression analyses continue to play a major role in orbit determination and related areas. In this report we document a library of FORTRAN subroutines that have been developed to facilitate analyses of a variety of estimation problems. Our purpose is to present an easy to use, multi-purpose set of algorithms that are reasonably efficient and which use a minimal amount of computer storage. Subroutine inputs, outputs, usage and listings are given along with examples of how these routines can be used. The following outline indicates the scope of this report: Section (1) introduction with reference to background material; Section (2) examples and applications; Section (3) subroutine directory summary; Section (4) the subroutine directory user description with input, output, and usage explained; and Section (5) subroutine FORTRAN listings. The routines are compact and efficient and are far superior to the normal equation and Kalman filter data processing algorithms that are often used for least squares analyses.
Torque ripple reduction of brushless DC motor based on adaptive input-output feedback linearization.
Shirvani Boroujeni, M; Markadeh, G R Arab; Soltani, J
2017-09-01
Torque ripple reduction of Brushless DC Motors (BLDCs) is an interesting subject in variable speed AC drives. In this paper at first, a mathematical expression for torque ripple harmonics is obtained. Then for a non-ideal BLDC motor with known harmonic contents of back-EMF, calculation of desired reference current amplitudes, which are required to eliminate some selected harmonics of torque ripple, are reviewed. In order to inject the reference harmonic currents to the motor windings, an Adaptive Input-Output Feedback Linearization (AIOFBL) control is proposed, which generates the reference voltages for three phases voltage source inverter in stationary reference frame. Experimental results are presented to show the capability and validity of the proposed control method and are compared with the vector control in Multi-Reference Frame (MRF) and Pseudo-Vector Control (P-VC) method results. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.
NASA Astrophysics Data System (ADS)
Çakır, Süleyman
2017-10-01
In this study, a two-phase methodology for resource allocation problems under a fuzzy environment is proposed. In the first phase, the imprecise Shannon's entropy method and the acceptability index are suggested, for the first time in the literature, to select input and output variables to be used in the data envelopment analysis (DEA) application. In the second step, an interval inverse DEA model is executed for resource allocation in a short run. In an effort to exemplify the practicality of the proposed fuzzy model, a real case application has been conducted involving 16 cement firms listed in Borsa Istanbul. The results of the case application indicated that the proposed hybrid model is a viable procedure to handle input-output selection and resource allocation problems under fuzzy conditions. The presented methodology can also lend itself to different applications such as multi-criteria decision-making problems.
Modified Levenberg-Marquardt Method for RÖSSLER Chaotic System Fuzzy Modeling Training
NASA Astrophysics Data System (ADS)
Wang, Yu-Hui; Wu, Qing-Xian; Jiang, Chang-Sheng; Xue, Ya-Li; Fang, Wei
Generally, fuzzy approximation models require some human knowledge and experience. Operator's experience is involved in the mathematics of fuzzy theory as a collection of heuristic rules. The main goal of this paper is to present a new method for identifying unknown nonlinear dynamics such as Rössler system without any human knowledge. Instead of heuristic rules, the presented method uses the input-output data pairs to identify the Rössler chaotic system. The training algorithm is a modified Levenberg-Marquardt (L-M) method, which can adjust the parameters of each linear polynomial and fuzzy membership functions on line, and do not rely on experts' experience excessively. Finally, it is applied to training Rössler chaotic system fuzzy identification. Comparing this method with the standard L-M method, the convergence speed is accelerated. The simulation results demonstrate the effectiveness of the proposed method.
CLARO: an ASIC for high rate single photon counting with multi-anode photomultipliers
NASA Astrophysics Data System (ADS)
Baszczyk, M.; Carniti, P.; Cassina, L.; Cotta Ramusino, A.; Dorosz, P.; Fiorini, M.; Gotti, C.; Kucewicz, W.; Malaguti, R.; Pessina, G.
2017-08-01
The CLARO is a radiation-hard 8-channel ASIC designed for single photon counting with multi-anode photomultiplier tubes. Each channel outputs a digital pulse when the input signal from the photomultiplier crosses a configurable threshold. The fast return to baseline, typically within 25 ns, and below 50 ns in all conditions, allows to count up to 107 hits/s on each channel, with a power consumption of about 1 mW per channel. The ASIC presented here is a much improved version of the first 4-channel prototype. The threshold can be precisely set in a wide range, between 30 ke- (5 fC) and 16 Me- (2.6 pC). The noise of the amplifier with a 10 pF input capacitance is 3.5 ke- (0.6 fC) RMS. All settings are stored in a 128-bit configuration and status register, protected against soft errors with triple modular redundancy. The paper describes the design of the ASIC at transistor-level, and demonstrates its performance on the test bench.
NASA Astrophysics Data System (ADS)
Ye, Tian-Yu
2016-09-01
Recently, Liu et al. proposed a two-party quantum private comparison (QPC) protocol using entanglement swapping of Bell entangled state (Commun. Theor. Phys. 57 (2012) 583). Subsequently Liu et al. pointed out that in Liu et al.'s protocol, the TP can extract the two users' secret inputs without being detected by launching the Bell-basis measurement attack, and suggested the corresponding improvement to mend this loophole (Commun. Theor. Phys. 62 (2014) 210). In this paper, we first point out the information leakage problem toward TP existing in both of the above two protocols, and then suggest the corresponding improvement by using the one-way hash function to encrypt the two users' secret inputs. We further put forward the three-party QPC protocol also based on entanglement swapping of Bell entangled state, and then validate its output correctness and its security in detail. Finally, we generalize the three-party QPC protocol into the multi-party case, which can accomplish arbitrary pair's comparison of equality among K users within one execution. Supported by the National Natural Science Foundation of China under Grant No. 61402407
CQPSO scheduling algorithm for heterogeneous multi-core DAG task model
NASA Astrophysics Data System (ADS)
Zhai, Wenzheng; Hu, Yue-Li; Ran, Feng
2017-07-01
Efficient task scheduling is critical to achieve high performance in a heterogeneous multi-core computing environment. The paper focuses on the heterogeneous multi-core directed acyclic graph (DAG) task model and proposes a novel task scheduling method based on an improved chaotic quantum-behaved particle swarm optimization (CQPSO) algorithm. A task priority scheduling list was built. A processor with minimum cumulative earliest finish time (EFT) was acted as the object of the first task assignment. The task precedence relationships were satisfied and the total execution time of all tasks was minimized. The experimental results show that the proposed algorithm has the advantage of optimization abilities, simple and feasible, fast convergence, and can be applied to the task scheduling optimization for other heterogeneous and distributed environment.
Scenario driven data modelling: a method for integrating diverse sources of data and data streams
Brettin, Thomas S.; Cottingham, Robert W.; Griffith, Shelton D.; Quest, Daniel J.
2015-09-08
A system and method of integrating diverse sources of data and data streams is presented. The method can include selecting a scenario based on a topic, creating a multi-relational directed graph based on the scenario, identifying and converting resources in accordance with the scenario and updating the multi-directed graph based on the resources, identifying data feeds in accordance with the scenario and updating the multi-directed graph based on the data feeds, identifying analytical routines in accordance with the scenario and updating the multi-directed graph using the analytical routines and identifying data outputs in accordance with the scenario and defining queries to produce the data outputs from the multi-directed graph.
Flatness-based control in successive loops for stabilization of heart's electrical activity
NASA Astrophysics Data System (ADS)
Rigatos, Gerasimos; Melkikh, Alexey
2016-12-01
The article proposes a new flatness-based control method implemented in successive loops which allows for stabilization of the heart's electrical activity. Heart's pacemaking function is modeled as a set of coupled oscillators which potentially can exhibit chaotic behavior. It is shown that this model satisfies differential flatness properties. Next, the control and stabilization of this model is performed with the use of flatness-based control implemented in cascading loops. By applying a per-row decomposition of the state-space model of the coupled oscillators a set of nonlinear differential equations is obtained. Differential flatness properties are shown to hold for the subsystems associated with the each one of the aforementioned differential equations and next a local flatness-based controller is designed for each subsystem. For the i-th subsystem, state variable xi is chosen to be the flat output and state variable xi+1 is taken to be a virtual control input. Then the value of the virtual control input which eliminates the output tracking error for the i-th subsystem becomes reference setpoint for the i + 1-th subsystem. In this manner the control of the entire state-space model is performed by successive flatness-based control loops. By arriving at the n-th row of the state-space model one computes the control input that can be actually exerted on the aforementioned biosystem. This real control input of the coupled oscillators' system, contains recursively all virtual control inputs associated with the previous n - 1 rows of the state-space model. This control approach achieves asymptotically the elimination of the chaotic oscillation effects and the stabilization of the heart's pulsation rhythm. The stability of the proposed control scheme is proven with the use of Lyapunov analysis.
A Computational Methodology for Simulating Thermal Loss Testing of the Advanced Stirling Convertor
NASA Technical Reports Server (NTRS)
Reid, Terry V.; Wilson, Scott D.; Schifer, Nicholas A.; Briggs, Maxwell H.
2012-01-01
The U.S. Department of Energy (DOE) and Lockheed Martin Space Systems Company (LMSSC) have been developing the Advanced Stirling Radioisotope Generator (ASRG) for use as a power system for space science missions. This generator would use two highefficiency Advanced Stirling Convertors (ASCs), developed by Sunpower Inc. and NASA Glenn Research Center (GRC). The ASCs convert thermal energy from a radioisotope heat source into electricity. As part of ground testing of these ASCs, different operating conditions are used to simulate expected mission conditions. These conditions require achieving a particular operating frequency, hot end and cold end temperatures, and specified electrical power output for a given net heat input. In an effort to improve net heat input predictions, numerous tasks have been performed which provided a more accurate value for net heat input into the ASCs, including the use of multidimensional numerical models. Validation test hardware has also been used to provide a direct comparison of numerical results and validate the multi-dimensional numerical models used to predict convertor net heat input and efficiency. These validation tests were designed to simulate the temperature profile of an operating Stirling convertor and resulted in a measured net heat input of 244.4 W. The methodology was applied to the multi-dimensional numerical model which resulted in a net heat input of 240.3 W. The computational methodology resulted in a value of net heat input that was 1.7 percent less than that measured during laboratory testing. The resulting computational methodology and results are discussed.
NASA Technical Reports Server (NTRS)
Jones, R. L.
1984-01-01
An interactive digital computer program for modal analysis and gain estimation for eigensystem synthesis was written. Both mathematical and operation considerations are described; however, the mathematical presentation is limited to those concepts essential to the operational capability of the program. The program is capable of both modal and spectral synthesis of multi-input control systems. It is user friendly, has scratchpad capability and dynamic memory, and can be used to design either state or output feedback systems.
The Pandora multi-algorithm approach to automated pattern recognition in LAr TPC detectors
NASA Astrophysics Data System (ADS)
Marshall, J. S.; Blake, A. S. T.; Thomson, M. A.; Escudero, L.; de Vries, J.; Weston, J.;
2017-09-01
The development and operation of Liquid Argon Time Projection Chambers (LAr TPCs) for neutrino physics has created a need for new approaches to pattern recognition, in order to fully exploit the superb imaging capabilities offered by this technology. The Pandora Software Development Kit provides functionality to aid the process of designing, implementing and running pattern recognition algorithms. It promotes the use of a multi-algorithm approach to pattern recognition: individual algorithms each address a specific task in a particular topology; a series of many tens of algorithms then carefully builds-up a picture of the event. The input to the Pandora pattern recognition is a list of 2D Hits. The output from the chain of over 70 algorithms is a hierarchy of reconstructed 3D Particles, each with an identified particle type, vertex and direction.
Rotorcraft control system design for uncertain vehicle dynamics using quantitative feedback theory
NASA Technical Reports Server (NTRS)
Hess, R. A.
1994-01-01
Quantitative Feedback Theory describes a frequency-domain technique for the design of multi-input, multi-output control systems which must meet time or frequency domain performance criteria when specified uncertainty exists in the linear description of the vehicle dynamics. This theory is applied to the design of the longitudinal flight control system for a linear model of the BO-105C rotorcraft. Uncertainty in the vehicle model is due to the variation in the vehicle dynamics over a range of airspeeds from 0-100 kts. For purposes of exposition, the vehicle description contains no rotor or actuator dynamics. The design example indicates the manner in which significant uncertainty exists in the vehicle model. The advantage of using a sequential loop closure technique to reduce the cost of feedback is demonstrated by example.
Global identifiability of linear compartmental models--a computer algebra algorithm.
Audoly, S; D'Angiò, L; Saccomani, M P; Cobelli, C
1998-01-01
A priori global identifiability deals with the uniqueness of the solution for the unknown parameters of a model and is, thus, a prerequisite for parameter estimation of biological dynamic models. Global identifiability is however difficult to test, since it requires solving a system of algebraic nonlinear equations which increases both in nonlinearity degree and number of terms and unknowns with increasing model order. In this paper, a computer algebra tool, GLOBI (GLOBal Identifiability) is presented, which combines the topological transfer function method with the Buchberger algorithm, to test global identifiability of linear compartmental models. GLOBI allows for the automatic testing of a priori global identifiability of general structure compartmental models from general multi input-multi output experiments. Examples of usage of GLOBI to analyze a priori global identifiability of some complex biological compartmental models are provided.
NASA Technical Reports Server (NTRS)
Murphy, Patrick C.; Davidson, John B.
1998-01-01
A multi-input, multi-output control law design methodology, named "CRAFT", is presented. CRAFT stands for the design objectives addressed, namely, Control power, Robustness, Agility, and Flying Qualities Tradeoffs. The methodology makes use of control law design metrics from each of the four design objective areas. It combines eigenspace assignment, which allows for direct specification of eigenvalues and eigenvectors, with a graphical approach for representing the metrics that captures numerous design goals in one composite illustration. Sensitivity of the metrics to eigenspace choice is clearly displayed, enabling the designer to assess the cost of design tradeoffs. This approach enhances the designer's ability to make informed design tradeoffs and to reach effective final designs. An example of the CRAFT methodology applied to an advanced experimental fighter and discussion of associated design issues are provided.
Enhanced Imaging of Building Interior for Portable MIMO Through-the-wall Radar
NASA Astrophysics Data System (ADS)
Song, Yongping; Zhu, Jiahua; Hu, Jun; Jin, Tian; Zhou, Zhimin
2018-01-01
Portable multi-input multi-output (MIMO) radar system is able to imaging the building interior through aperture synthesis. However, significant grating lobes are invoked in the directly imaging results, which may deteriorate the imaging quality of other targets and influence the detail information extraction of imaging scene. In this paper, a two-stage coherence factor (CF) weighting method is proposed to enhance the imaging quality. After obtaining the sub-imaging results of each spatial sampling position using conventional CF approach, a window function is employed to calculate the proposed “enhanced CF” adaptive to the spatial variety effect behind the wall for the combination of these sub-images. The real data experiment illustrates the better performance of proposed method on grating lobes suppression and imaging quality enhancement compare to the traditional radar imaging approach.
Zhou, Xian; Zhong, Kangping; Gao, Yuliang; Sui, Qi; Dong, Zhenghua; Yuan, Jinhui; Wang, Liang; Long, Keping; Lau, Alan Pak Tao; Lu, Chao
2015-04-06
Discrete multi-tone (DMT) modulation is an attractive modulation format for short-reach applications to achieve the best use of available channel bandwidth and signal noise ratio (SNR). In order to realize polarization-multiplexed DMT modulation with direct detection, we derive an analytical transmission model for dual polarizations with intensity modulation and direct diction (IM-DD) in this paper. Based on the model, we propose a novel polarization-interleave-multiplexed DMT modulation with direct diction (PIM-DMT-DD) transmission system, where the polarization de-multiplexing can be achieved by using a simple multiple-input-multiple-output (MIMO) equalizer and the transmission performance is optimized over two distinct received polarization states to eliminate the singularity issue of MIMO demultiplexing algorithms. The feasibility and effectiveness of the proposed PIM-DMT-DD system are investigated via theoretical analyses and simulation studies.
MIMO-OFDM System's Performance Using LDPC Codes for a Mobile Robot
NASA Astrophysics Data System (ADS)
Daoud, Omar; Alani, Omar
This work deals with the performance of a Sniffer Mobile Robot (SNFRbot)-based spatial multiplexed wireless Orthogonal Frequency Division Multiplexing (OFDM) transmission technology. The use of Multi-Input Multi-Output (MIMO)-OFDM technology increases the wireless transmission rate without increasing transmission power or bandwidth. A generic multilayer architecture of the SNFRbot is proposed with low power and low cost. Some experimental results are presented and show the efficiency of sniffing deadly gazes, sensing high temperatures and sending live videos of the monitored situation. Moreover, simulation results show the achieved performance by tackling the Peak-to-Average Power Ratio (PAPR) problem of the used technology using Low Density Parity Check (LDPC) codes; and the effect of combating the PAPR on the bit error rate (BER) and the signal to noise ratio (SNR) over a Doppler spread channel.
NASA Astrophysics Data System (ADS)
Wang, Fei; Chen, Hong; Guo, Konghui; Cao, Dongpu
2017-09-01
The path following and directional stability are two crucial problems when a road vehicle experiences a tire blow-out or sudden tire failure. Considering the requirement of rapid road vehicle motion control during a tire blow-out, this article proposes a novel linearized decoupling control procedure with three design steps for a class of second order multi-input-multi-output non-affine system. The evaluating indicators for controller performance are presented and a performance related control parameter distribution map is obtained based on the stochastic algorithm which is an innovation for non-blind parameter adjustment in engineering implementation. The analysis on the robustness of the proposed integrated controller is also performed. The simulation studies for a range of driving conditions are conducted, to demonstrate the effectiveness of the proposed controller.
Toward a More Robust Pruning Procedure for MLP Networks
NASA Technical Reports Server (NTRS)
Stepniewski, Slawomir W.; Jorgensen, Charles C.
1998-01-01
Choosing a proper neural network architecture is a problem of great practical importance. Smaller models mean not only simpler designs but also lower variance for parameter estimation and network prediction. The widespread utilization of neural networks in modeling highlights an issue in human factors. The procedure of building neural models should find an appropriate level of model complexity in a more or less automatic fashion to make it less prone to human subjectivity. In this paper we present a Singular Value Decomposition based node elimination technique and enhanced implementation of the Optimal Brain Surgeon algorithm. Combining both methods creates a powerful pruning engine that can be used for tuning feedforward connectionist models. The performance of the proposed method is demonstrated by adjusting the structure of a multi-input multi-output model used to calibrate a six-component wind tunnel strain gage.
Chen, Dong; Eisley, Noel A.; Steinmacher-Burow, Burkhard; Heidelberger, Philip
2013-01-29
A computer implemented method and a system for routing data packets in a multi-dimensional computer network. The method comprises routing a data packet among nodes along one dimension towards a root node, each node having input and output communication links, said root node not having any outgoing uplinks, and determining at each node if the data packet has reached a predefined coordinate for the dimension or an edge of the subrectangle for the dimension, and if the data packet has reached the predefined coordinate for the dimension or the edge of the subrectangle for the dimension, determining if the data packet has reached the root node, and if the data packet has not reached the root node, routing the data packet among nodes along another dimension towards the root node.
Optogenetic Modulation and Multi-Electrode Analysis of Cerebellar Networks In Vivo
Kruse, Wolfgang; Krause, Martin; Aarse, Janna; Mark, Melanie D.; Manahan-Vaughan, Denise; Herlitze, Stefan
2014-01-01
The firing patterns of cerebellar Purkinje cells (PCs), as the sole output of the cerebellar cortex, determine and tune motor behavior. PC firing is modulated by various inputs from different brain regions and by cell-types including granule cells (GCs), climbing fibers and inhibitory interneurons. To understand how signal integration in PCs occurs and how subtle changes in the modulation of PC firing lead to adjustment of motor behaviors, it is important to precisely record PC firing in vivo and to control modulatory pathways in a spatio-temporal manner. Combining optogenetic and multi-electrode approaches, we established a new method to integrate light-guides into a multi-electrode system. With this method we are able to variably position the light-guide in defined regions relative to the recording electrode with micrometer precision. We show that PC firing can be precisely monitored and modulated by light-activation of channelrhodopsin-2 (ChR2) expressed in PCs, GCs and interneurons. Thus, this method is ideally suited to investigate the spatio/temporal modulation of PCs in anesthetized and in behaving mice. PMID:25144735
Performance analysis of cooperative virtual MIMO systems for wireless sensor networks.
Rafique, Zimran; Seet, Boon-Chong; Al-Anbuky, Adnan
2013-05-28
Multi-Input Multi-Output (MIMO) techniques can be used to increase the data rate for a given bit error rate (BER) and transmission power. Due to the small form factor, energy and processing constraints of wireless sensor nodes, a cooperative Virtual MIMO as opposed to True MIMO system architecture is considered more feasible for wireless sensor network (WSN) applications. Virtual MIMO with Vertical-Bell Labs Layered Space-Time (V-BLAST) multiplexing architecture has been recently established to enhance WSN performance. In this paper, we further investigate the impact of different modulation techniques, and analyze for the first time, the performance of a cooperative Virtual MIMO system based on V-BLAST architecture with multi-carrier modulation techniques. Through analytical models and simulations using real hardware and environment settings, both communication and processing energy consumptions, BER, spectral efficiency, and total time delay of multiple cooperative nodes each with single antenna are evaluated. The results show that cooperative Virtual-MIMO with Binary Phase Shift Keying-Wavelet based Orthogonal Frequency Division Multiplexing (BPSK-WOFDM) modulation is a promising solution for future high data-rate and energy-efficient WSNs.
Performance Analysis of Cooperative Virtual MIMO Systems for Wireless Sensor Networks
Rafique, Zimran; Seet, Boon-Chong; Al-Anbuky, Adnan
2013-01-01
Multi-Input Multi-Output (MIMO) techniques can be used to increase the data rate for a given bit error rate (BER) and transmission power. Due to the small form factor, energy and processing constraints of wireless sensor nodes, a cooperative Virtual MIMO as opposed to True MIMO system architecture is considered more feasible for wireless sensor network (WSN) applications. Virtual MIMO with Vertical-Bell Labs Layered Space-Time (V-BLAST) multiplexing architecture has been recently established to enhance WSN performance. In this paper, we further investigate the impact of different modulation techniques, and analyze for the first time, the performance of a cooperative Virtual MIMO system based on V-BLAST architecture with multi-carrier modulation techniques. Through analytical models and simulations using real hardware and environment settings, both communication and processing energy consumptions, BER, spectral efficiency, and total time delay of multiple cooperative nodes each with single antenna are evaluated. The results show that cooperative Virtual-MIMO with Binary Phase Shift Keying-Wavelet based Orthogonal Frequency Division Multiplexing (BPSK-WOFDM) modulation is a promising solution for future high data-rate and energy-efficient WSNs. PMID:23760087
Software Defined Radio with Parallelized Software Architecture
NASA Technical Reports Server (NTRS)
Heckler, Greg
2013-01-01
This software implements software-defined radio procession over multicore, multi-CPU systems in a way that maximizes the use of CPU resources in the system. The software treats each processing step in either a communications or navigation modulator or demodulator system as an independent, threaded block. Each threaded block is defined with a programmable number of input or output buffers; these buffers are implemented using POSIX pipes. In addition, each threaded block is assigned a unique thread upon block installation. A modulator or demodulator system is built by assembly of the threaded blocks into a flow graph, which assembles the processing blocks to accomplish the desired signal processing. This software architecture allows the software to scale effortlessly between single CPU/single-core computers or multi-CPU/multi-core computers without recompilation. NASA spaceflight and ground communications systems currently rely exclusively on ASICs or FPGAs. This software allows low- and medium-bandwidth (100 bps to approx.50 Mbps) software defined radios to be designed and implemented solely in C/C++ software, while lowering development costs and facilitating reuse and extensibility.
Xiao, WenBo; Nazario, Gina; Wu, HuaMing; Zhang, HuaMing; Cheng, Feng
2017-01-01
In this article, we introduced an artificial neural network (ANN) based computational model to predict the output power of three types of photovoltaic cells, mono-crystalline (mono-), multi-crystalline (multi-), and amorphous (amor-) crystalline. The prediction results are very close to the experimental data, and were also influenced by numbers of hidden neurons. The order of the solar generation power output influenced by the external conditions from smallest to biggest is: multi-, mono-, and amor- crystalline silicon cells. In addition, the dependences of power prediction on the number of hidden neurons were studied. For multi- and amorphous crystalline cell, three or four hidden layer units resulted in the high correlation coefficient and low MSEs. For mono-crystalline cell, the best results were achieved at the hidden layer unit of 8.
van der Lee, J H; Svrcek, W Y; Young, B R
2008-01-01
Model Predictive Control is a valuable tool for the process control engineer in a wide variety of applications. Because of this the structure of an MPC can vary dramatically from application to application. There have been a number of works dedicated to MPC tuning for specific cases. Since MPCs can differ significantly, this means that these tuning methods become inapplicable and a trial and error tuning approach must be used. This can be quite time consuming and can result in non-optimum tuning. In an attempt to resolve this, a generalized automated tuning algorithm for MPCs was developed. This approach is numerically based and combines a genetic algorithm with multi-objective fuzzy decision-making. The key advantages to this approach are that genetic algorithms are not problem specific and only need to be adapted to account for the number and ranges of tuning parameters for a given MPC. As well, multi-objective fuzzy decision-making can handle qualitative statements of what optimum control is, in addition to being able to use multiple inputs to determine tuning parameters that best match the desired results. This is particularly useful for multi-input, multi-output (MIMO) cases where the definition of "optimum" control is subject to the opinion of the control engineer tuning the system. A case study will be presented in order to illustrate the use of the tuning algorithm. This will include how different definitions of "optimum" control can arise, and how they are accounted for in the multi-objective decision making algorithm. The resulting tuning parameters from each of the definition sets will be compared, and in doing so show that the tuning parameters vary in order to meet each definition of optimum control, thus showing the generalized automated tuning algorithm approach for tuning MPCs is feasible.
Latin Hypercube Sampling (LHS) UNIX Library/Standalone
DOE Office of Scientific and Technical Information (OSTI.GOV)
2004-05-13
The LHS UNIX Library/Standalone software provides the capability to draw random samples from over 30 distribution types. It performs the sampling by a stratified sampling method called Latin Hypercube Sampling (LHS). Multiple distributions can be sampled simultaneously, with user-specified correlations amongst the input distributions, LHS UNIX Library/ Standalone provides a way to generate multi-variate samples. The LHS samples can be generated either as a callable library (e.g., from within the DAKOTA software framework) or as a standalone capability. LHS UNIX Library/Standalone uses the Latin Hypercube Sampling method (LHS) to generate samples. LHS is a constrained Monte Carlo sampling scheme. Inmore » LHS, the range of each variable is divided into non-overlapping intervals on the basis of equal probability. A sample is selected at random with respect to the probability density in each interval, If multiple variables are sampled simultaneously, then values obtained for each are paired in a random manner with the n values of the other variables. In some cases, the pairing is restricted to obtain specified correlations amongst the input variables. Many simulation codes have input parameters that are uncertain and can be specified by a distribution, To perform uncertainty analysis and sensitivity analysis, random values are drawn from the input parameter distributions, and the simulation is run with these values to obtain output values. If this is done repeatedly, with many input samples drawn, one can build up a distribution of the output as well as examine correlations between input and output variables.« less
A mixed analog/digital chaotic neuro-computer system for quadratic assignment problems.
Horio, Yoshihiko; Ikeguchi, Tohru; Aihara, Kazuyuki
2005-01-01
We construct a mixed analog/digital chaotic neuro-computer prototype system for quadratic assignment problems (QAPs). The QAP is one of the difficult NP-hard problems, and includes several real-world applications. Chaotic neural networks have been used to solve combinatorial optimization problems through chaotic search dynamics, which efficiently searches optimal or near optimal solutions. However, preliminary experiments have shown that, although it obtained good feasible solutions, the Hopfield-type chaotic neuro-computer hardware system could not obtain the optimal solution of the QAP. Therefore, in the present study, we improve the system performance by adopting a solution construction method, which constructs a feasible solution using the analog internal state values of the chaotic neurons at each iteration. In order to include the construction method into our hardware, we install a multi-channel analog-to-digital conversion system to observe the internal states of the chaotic neurons. We show experimentally that a great improvement in the system performance over the original Hopfield-type chaotic neuro-computer is obtained. That is, we obtain the optimal solution for the size-10 QAP in less than 1000 iterations. In addition, we propose a guideline for parameter tuning of the chaotic neuro-computer system according to the observation of the internal states of several chaotic neurons in the network.
Dual-threshold segmentation using Arimoto entropy based on chaotic bee colony optimization
NASA Astrophysics Data System (ADS)
Li, Li
2018-03-01
In order to extract target from complex background more quickly and accurately, and to further improve the detection effect of defects, a method of dual-threshold segmentation using Arimoto entropy based on chaotic bee colony optimization was proposed. Firstly, the method of single-threshold selection based on Arimoto entropy was extended to dual-threshold selection in order to separate the target from the background more accurately. Then intermediate variables in formulae of Arimoto entropy dual-threshold selection was calculated by recursion to eliminate redundant computation effectively and to reduce the amount of calculation. Finally, the local search phase of artificial bee colony algorithm was improved by chaotic sequence based on tent mapping. The fast search for two optimal thresholds was achieved using the improved bee colony optimization algorithm, thus the search could be accelerated obviously. A large number of experimental results show that, compared with the existing segmentation methods such as multi-threshold segmentation method using maximum Shannon entropy, two-dimensional Shannon entropy segmentation method, two-dimensional Tsallis gray entropy segmentation method and multi-threshold segmentation method using reciprocal gray entropy, the proposed method can segment target more quickly and accurately with superior segmentation effect. It proves to be an instant and effective method for image segmentation.
Synchronization transition in neuronal networks composed of chaotic or non-chaotic oscillators.
Xu, Kesheng; Maidana, Jean Paul; Castro, Samy; Orio, Patricio
2018-05-30
Chaotic dynamics has been shown in the dynamics of neurons and neural networks, in experimental data and numerical simulations. Theoretical studies have proposed an underlying role of chaos in neural systems. Nevertheless, whether chaotic neural oscillators make a significant contribution to network behaviour and whether the dynamical richness of neural networks is sensitive to the dynamics of isolated neurons, still remain open questions. We investigated synchronization transitions in heterogeneous neural networks of neurons connected by electrical coupling in a small world topology. The nodes in our model are oscillatory neurons that - when isolated - can exhibit either chaotic or non-chaotic behaviour, depending on conductance parameters. We found that the heterogeneity of firing rates and firing patterns make a greater contribution than chaos to the steepness of the synchronization transition curve. We also show that chaotic dynamics of the isolated neurons do not always make a visible difference in the transition to full synchrony. Moreover, macroscopic chaos is observed regardless of the dynamics nature of the neurons. However, performing a Functional Connectivity Dynamics analysis, we show that chaotic nodes can promote what is known as multi-stable behaviour, where the network dynamically switches between a number of different semi-synchronized, metastable states.
An inductorless multi-mode RF front end for GNSS receiver in 55 nm CMOS
NASA Astrophysics Data System (ADS)
Yanbin, Luo; Chengyan, Ma; Yebing, Gan; Min, Qian; Tianchun, Ye
2015-10-01
An inductorless multi-mode RF front end for a global navigation satellite system (GNSS) receiver is presented. Unlike the traditional topology of a low noise amplifier (LNA), the inductorless current-mode noise-canceling LNA is applied in this design. The high-impedance-input radio frequency amplifier (RFA) further amplifies the GNSS signals and changes the single-end signal path into fully differential. The passive mixer down-converts the signals to the intermediate frequency (IF) band and conveys the signals to the analogue blocks. The local oscillator (LO) buffer divides the output frequency of the voltage controlled oscillator (VCO) and generates 25%-duty-cycle quadrature square waves to drive the mixer. Our measurement results display that the implemented RF front end achieves good overall performance while consuming only 6.7 mA from 1.2 V supply. The input return loss is better than -26 dB and the ultra low noise figure of 1.43 dB leads to high sensitivity of the GNSS receiver. The input 1 dB compression point is -43 dBm at the high gain of 48 dB. The designed circuit is fabricated in 55 nm CMOS technology and the die area, which is much smaller than traditional circuit, is around 220 × 280 μm2.
Kumar, Anupam; Kumar, Vijay
2017-05-01
In this paper, a novel concept of an interval type-2 fractional order fuzzy PID (IT2FO-FPID) controller, which requires fractional order integrator and fractional order differentiator, is proposed. The incorporation of Takagi-Sugeno-Kang (TSK) type interval type-2 fuzzy logic controller (IT2FLC) with fractional controller of PID-type is investigated for time response measure due to both unit step response and unit load disturbance. The resulting IT2FO-FPID controller is examined on different delayed linear and nonlinear benchmark plants followed by robustness analysis. In order to design this controller, fractional order integrator-differentiator operators are considered as design variables including input-output scaling factors. A new hybridized algorithm named as artificial bee colony-genetic algorithm (ABC-GA) is used to optimize the parameters of the controller while minimizing weighted sum of integral of time absolute error (ITAE) and integral of square of control output (ISCO). To assess the comparative performance of the IT2FO-FPID, authors compared it against existing controllers, i.e., interval type-2 fuzzy PID (IT2-FPID), type-1 fractional order fuzzy PID (T1FO-FPID), type-1 fuzzy PID (T1-FPID), and conventional PID controllers. Furthermore, to show the effectiveness of the proposed controller, the perturbed processes along with the larger dead time are tested. Moreover, the proposed controllers are also implemented on multi input multi output (MIMO), coupled, and highly complex nonlinear two-link robot manipulator system in presence of un-modeled dynamics. Finally, the simulation results explicitly indicate that the performance of the proposed IT2FO-FPID controller is superior to its conventional counterparts in most of the cases. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.
Akbaş, Halil; Bilgen, Bilge; Turhan, Aykut Melih
2015-11-01
This study proposes an integrated prediction and optimization model by using multi-layer perceptron neural network and particle swarm optimization techniques. Three different objective functions are formulated. The first one is the maximization of methane percentage with single output. The second one is the maximization of biogas production with single output. The last one is the maximization of biogas quality and biogas production with two outputs. Methane percentage, carbon dioxide percentage, and other contents' percentage are used as the biogas quality criteria. Based on the formulated models and data from a wastewater treatment facility, optimal values of input variables and their corresponding maximum output values are found out for each model. It is expected that the application of the integrated prediction and optimization models increases the biogas production and biogas quality, and contributes to the quantity of electricity production at the wastewater treatment facility. Copyright © 2015 Elsevier Ltd. All rights reserved.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Hessell, Steven M.; Morris, Robert L.; McGrogan, Sean W.
A powertrain including an engine and torque machines is configured to transfer torque through a multi-mode transmission to an output member. A method for controlling the powertrain includes employing a closed-loop speed control system to control torque commands for the torque machines in response to a desired input speed. Upon approaching a power limit of a power storage device transferring power to the torque machines, power limited torque commands are determined for the torque machines in response to the power limit and the closed-loop speed control system is employed to determine an engine torque command in response to the desiredmore » input speed and the power limited torque commands for the torque machines.« less
Multi-channel spatialization systems for audio signals
NASA Technical Reports Server (NTRS)
Begault, Durand R. (Inventor)
1993-01-01
Synthetic head related transfer functions (HRTF's) for imposing reprogrammable spatial cues to a plurality of audio input signals included, for example, in multiple narrow-band audio communications signals received simultaneously are generated and stored in interchangeable programmable read only memories (PROM's) which store both head related transfer function impulse response data and source positional information for a plurality of desired virtual source locations. The analog inputs of the audio signals are filtered and converted to digital signals from which synthetic head related transfer functions are generated in the form of linear phase finite impulse response filters. The outputs of the impulse response filters are subsequently reconverted to analog signals, filtered, mixed, and fed to a pair of headphones.
Multi-channel spatialization system for audio signals
NASA Technical Reports Server (NTRS)
Begault, Durand R. (Inventor)
1995-01-01
Synthetic head related transfer functions (HRTF's) for imposing reprogramable spatial cues to a plurality of audio input signals included, for example, in multiple narrow-band audio communications signals received simultaneously are generated and stored in interchangeable programmable read only memories (PROM's) which store both head related transfer function impulse response data and source positional information for a plurality of desired virtual source locations. The analog inputs of the audio signals are filtered and converted to digital signals from which synthetic head related transfer functions are generated in the form of linear phase finite impulse response filters. The outputs of the impulse response filters are subsequently reconverted to analog signals, filtered, mixed and fed to a pair of headphones.
Multi-input and binary reproducible, high bandwidth floating point adder in a collective network
Chen, Dong; Eisley, Noel A.; Heidelberger, Philip; Steinmacher-Burow, Burkhard
2016-11-15
To add floating point numbers in a parallel computing system, a collective logic device receives the floating point numbers from computing nodes. The collective logic devices converts the floating point numbers to integer numbers. The collective logic device adds the integer numbers and generating a summation of the integer numbers. The collective logic device converts the summation to a floating point number. The collective logic device performs the receiving, the converting the floating point numbers, the adding, the generating and the converting the summation in one pass. One pass indicates that the computing nodes send inputs only once to the collective logic device and receive outputs only once from the collective logic device.
Method and system for compact, multi-pass pulsed laser amplifier
Erlandson, Alvin Charles
2014-11-25
A laser amplifier includes an input aperture operable to receive laser radiation having a first polarization, an output aperture coupled to the input aperture by an optical path, and a polarizer disposed along an optical path. A transmission axis of the polarizer is aligned with the first polarization. The laser amplifier also includes n optical switch disposed along the optical path. The optical switch is operable to pass the laser radiation when operated in a first state and to reflect the laser radiation when operated in a second state. The laser amplifier further includes an optical gain element disposed along the optical path and a polarization rotation device disposed along the optical path.
Divide and control: split design of multi-input DNA logic gates.
Gerasimova, Yulia V; Kolpashchikov, Dmitry M
2015-01-18
Logic gates made of DNA have received significant attention as biocompatible building blocks for molecular circuits. The majority of DNA logic gates, however, are controlled by the minimum number of inputs: one, two or three. Here we report a strategy to design a multi-input logic gate by splitting a DNA construct.
Ultra-fast consensus of discrete-time multi-agent systems with multi-step predictive output feedback
NASA Astrophysics Data System (ADS)
Zhang, Wenle; Liu, Jianchang
2016-04-01
This article addresses the ultra-fast consensus problem of high-order discrete-time multi-agent systems based on a unified consensus framework. A novel multi-step predictive output mechanism is proposed under a directed communication topology containing a spanning tree. By predicting the outputs of a network several steps ahead and adding this information into the consensus protocol, it is shown that the asymptotic convergence factor is improved by a power of q + 1 compared to the routine consensus. The difficult problem of selecting the optimal control gain is solved well by introducing a variable called convergence step. In addition, the ultra-fast formation achievement is studied on the basis of this new consensus protocol. Finally, the ultra-fast consensus with respect to a reference model and robust consensus is discussed. Some simulations are performed to illustrate the effectiveness of the theoretical results.
NASA Astrophysics Data System (ADS)
Bauer, Johannes; Dávila-Chacón, Jorge; Wermter, Stefan
2015-10-01
Humans and other animals have been shown to perform near-optimally in multi-sensory integration tasks. Probabilistic population codes (PPCs) have been proposed as a mechanism by which optimal integration can be accomplished. Previous approaches have focussed on how neural networks might produce PPCs from sensory input or perform calculations using them, like combining multiple PPCs. Less attention has been given to the question of how the necessary organisation of neurons can arise and how the required knowledge about the input statistics can be learned. In this paper, we propose a model of learning multi-sensory integration based on an unsupervised learning algorithm in which an artificial neural network learns the noise characteristics of each of its sources of input. Our algorithm borrows from the self-organising map the ability to learn latent-variable models of the input and extends it to learning to produce a PPC approximating a probability density function over the latent variable behind its (noisy) input. The neurons in our network are only required to perform simple calculations and we make few assumptions about input noise properties and tuning functions. We report on a neurorobotic experiment in which we apply our algorithm to multi-sensory integration in a humanoid robot to demonstrate its effectiveness and compare it to human multi-sensory integration on the behavioural level. We also show in simulations that our algorithm performs near-optimally under certain plausible conditions, and that it reproduces important aspects of natural multi-sensory integration on the neural level.
Estimation of effective connectivity using multi-layer perceptron artificial neural network.
Talebi, Nasibeh; Nasrabadi, Ali Motie; Mohammad-Rezazadeh, Iman
2018-02-01
Studies on interactions between brain regions estimate effective connectivity, (usually) based on the causality inferences made on the basis of temporal precedence. In this study, the causal relationship is modeled by a multi-layer perceptron feed-forward artificial neural network, because of the ANN's ability to generate appropriate input-output mapping and to learn from training examples without the need of detailed knowledge of the underlying system. At any time instant, the past samples of data are placed in the network input, and the subsequent values are predicted at its output. To estimate the strength of interactions, the measure of " Causality coefficient " is defined based on the network structure, the connecting weights and the parameters of hidden layer activation function. Simulation analysis demonstrates that the method, called "CREANN" (Causal Relationship Estimation by Artificial Neural Network), can estimate time-invariant and time-varying effective connectivity in terms of MVAR coefficients. The method shows robustness with respect to noise level of data. Furthermore, the estimations are not significantly influenced by the model order (considered time-lag), and the different initial conditions (initial random weights and parameters of the network). CREANN is also applied to EEG data collected during a memory recognition task. The results implicate that it can show changes in the information flow between brain regions, involving in the episodic memory retrieval process. These convincing results emphasize that CREANN can be used as an appropriate method to estimate the causal relationship among brain signals.
High dimensional model representation method for fuzzy structural dynamics
NASA Astrophysics Data System (ADS)
Adhikari, S.; Chowdhury, R.; Friswell, M. I.
2011-03-01
Uncertainty propagation in multi-parameter complex structures possess significant computational challenges. This paper investigates the possibility of using the High Dimensional Model Representation (HDMR) approach when uncertain system parameters are modeled using fuzzy variables. In particular, the application of HDMR is proposed for fuzzy finite element analysis of linear dynamical systems. The HDMR expansion is an efficient formulation for high-dimensional mapping in complex systems if the higher order variable correlations are weak, thereby permitting the input-output relationship behavior to be captured by the terms of low-order. The computational effort to determine the expansion functions using the α-cut method scales polynomically with the number of variables rather than exponentially. This logic is based on the fundamental assumption underlying the HDMR representation that only low-order correlations among the input variables are likely to have significant impacts upon the outputs for most high-dimensional complex systems. The proposed method is first illustrated for multi-parameter nonlinear mathematical test functions with fuzzy variables. The method is then integrated with a commercial finite element software (ADINA). Modal analysis of a simplified aircraft wing with fuzzy parameters has been used to illustrate the generality of the proposed approach. In the numerical examples, triangular membership functions have been used and the results have been validated against direct Monte Carlo simulations. It is shown that using the proposed HDMR approach, the number of finite element function calls can be reduced without significantly compromising the accuracy.
Day 1 for the Integrated Multi-Satellite Retrievals for GPM (IMERG) Data Sets
NASA Astrophysics Data System (ADS)
Huffman, G. J.; Bolvin, D. T.; Braithwaite, D.; Hsu, K. L.; Joyce, R.; Kidd, C.; Sorooshian, S.; Xie, P.
2014-12-01
The Integrated Multi-satellitE Retrievals for GPM (IMERG) is designed to compute the best time series of (nearly) global precipitation from "all" precipitation-relevant satellites and global surface precipitation gauge analyses. IMERG was developed to use GPM Core Observatory data as a reference for the international constellation of satellites of opportunity that constitute the GPM virtual constellation. Computationally, IMERG is a unified U.S. algorithm drawing on strengths in the three contributing groups, whose previous work includes: 1) the TRMM Multi-satellite Precipitation Analysis (TMPA); 2) the CPC Morphing algorithm with Kalman Filtering (K-CMORPH); and 3) the Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks using a Cloud Classification System (PERSIANN-CCS). We review the IMERG design, development, testing, and current status. IMERG provides 0.1°x0.1° half-hourly data, and will be run at multiple times, providing successively more accurate estimates: 4 hours, 8 hours, and 2 months after observation time. In Day 1 the spatial extent is 60°N-S, for the period March 2014 to the present. In subsequent reprocessing the data will extend to fully global, covering the period 1998 to the present. Both the set of input data set retrievals and the IMERG system are substantially different than those used in previous U.S. products. The input passive microwave data are all being produced with GPROF2014, which is substantially upgraded compared to previous versions. For the first time, this includes microwave sounders. Accordingly, there is a strong need to carefully check the initial test data sets for performance. IMERG output will be illustrated using pre-operational test data, including the variety of supporting fields, such as the merged-microwave and infrared estimates, and the precipitation type. Finally, we will summarize the expected release of various output products, and the subsequent reprocessing sequence.
Application of a neural network as a potential aid in predicting NTF pump failure
NASA Technical Reports Server (NTRS)
Rogers, James L.; Hill, Jeffrey S.; Lamarsh, William J., II; Bradley, David E.
1993-01-01
The National Transonic Facility has three centrifugal multi-stage pumps to supply liquid nitrogen to the wind tunnel. Pump reliability is critical to facility operation and test capability. A highly desirable goal is to be able to detect a pump rotating component problem as early as possible during normal operation and avoid serious damage to other pump components. If a problem is detected before serious damage occurs, the repair cost and downtime could be reduced significantly. A neural network-based tool was developed for monitoring pump performance and aiding in predicting pump failure. Once trained, neural networks can rapidly process many combinations of input values other than those used for training to approximate previously unknown output values. This neural network was applied to establish relationships among the critical frequencies and aid in predicting failures. Training pairs were developed from frequency scans from typical tunnel operations. After training, various combinations of critical pump frequencies were propagated through the neural network. The approximated output was used to create a contour plot depicting the relationships of the input frequencies to the output pump frequency.
NASA Astrophysics Data System (ADS)
Coronel-Escamilla, A.; Gómez-Aguilar, J. F.; Torres, L.; Escobar-Jiménez, R. F.; Valtierra-Rodríguez, M.
2017-12-01
In this paper, we propose a state-observer-based approach to synchronize variable-order fractional (VOF) chaotic systems. In particular, this work is focused on complete synchronization with a so-called unidirectional master-slave topology. The master is described by a dynamical system in state-space representation whereas the slave is described by a state observer. The slave is composed of a master copy and a correction term which in turn is constituted of an estimation error and an appropriate gain that assures the synchronization. The differential equations of the VOF chaotic system are described by the Liouville-Caputo and Atangana-Baleanu-Caputo derivatives. Numerical simulations involving the synchronization of Rössler oscillators, Chua's systems and multi-scrolls are studied. The simulations show that different chaotic behaviors can be obtained if different smooths functions defined in the interval (0 , 1 ] are used as the variable order of the fractional derivatives. Furthermore, simulations show that the VOF chaotic systems can be synchronized.
Chaotic map clustering algorithm for EEG analysis
NASA Astrophysics Data System (ADS)
Bellotti, R.; De Carlo, F.; Stramaglia, S.
2004-03-01
The non-parametric chaotic map clustering algorithm has been applied to the analysis of electroencephalographic signals, in order to recognize the Huntington's disease, one of the most dangerous pathologies of the central nervous system. The performance of the method has been compared with those obtained through parametric algorithms, as K-means and deterministic annealing, and supervised multi-layer perceptron. While supervised neural networks need a training phase, performed by means of data tagged by the genetic test, and the parametric methods require a prior choice of the number of classes to find, the chaotic map clustering gives a natural evidence of the pathological class, without any training or supervision, thus providing a new efficient methodology for the recognition of patterns affected by the Huntington's disease.
Diode-end-pumped solid-state lasers with dual gain media for multi-wavelength emission
NASA Astrophysics Data System (ADS)
Cho, C. Y.; Chang, C. C.; Chen, Y. F.
2015-01-01
We develop a theoretical model for designing a compact efficient multi-wavelength laser with dual gain media in a shared resonator. The developed model can be used to analyze the optimal output reflectivity for each wavelength to achieve maximum output power for multi-wavelength emission. We further demonstrate a dual-wavelength laser at 946 nm and 1064 nm with Nd:YAG and Nd:YVO4 crystals to confirm the numerical analysis. Under optimum conditions and at incident pump power of 17 W, output power at 946 nm and 1064 nm was up to 2.51 W and 2.81 W, respectively.
Chaotic interactions of self-replicating RNA.
Forst, C V
1996-03-01
A general system of high-order differential equations describing complex dynamics of replicating biomolecules is given. Symmetry relations and coordinate transformations of general replication systems leading to topologically equivalent systems are derived. Three chaotic attractors observed in Lotka-Volterra equations of dimension n = 3 are shown to represent three cross-sections of one and the same chaotic regime. Also a fractal torus in a generalized three-dimensional Lotka-Volterra Model has been linked to one of the chaotic attractors. The strange attractors are studied in the equivalent four-dimensional catalytic replicator network. The fractal torus has been examined in adapted Lotka-Volterra equations. Analytic expressions are derived for the Lyapunov exponents of the flow in the replicator system. Lyapunov spectra for different pathways into chaos has been calculated. In the generalized Lotka-Volterra system a second inner rest point--coexisting with (quasi)-periodic orbits--can be observed; with an abundance of different bifurcations. Pathways from chaotic tori, via quasi-periodic tori, via limit cycles, via multi-periodic orbits--emerging out of periodic doubling bifurcations--to "simple" chaotic attractors can be found.
Splice loss requirements in multi-mode fiber mode-division-multiplex transmission links.
Warm, Stefan; Petermann, Klaus
2013-01-14
We investigate numerically the influence of fiber splices and fiber connectors to the statistics of mode dependent loss (MDL) and multiple-input multiple-output (MIMO) outage capacity in mode multiplexed multi-mode fiber links. Our results indicate required splice losses much lower than currently feasible to achieve a reasonable outage capacity in long-haul transmission systems. Splice losses as low as 0.03dB may effectively lead to an outage of MIMO channels after only a few hundred kilometers transmission length. In a first approximation, the relative capacity solely depends on the accumulated splice loss and should be less than ≈ 2dB to ensure a relative capacity of 90%. We also show that discrete mode permutation (mixing) within the transmission line may effectively increase the maximum transmission distance by a factor of 5 for conventional splice losses.
Enhanced Attitude Control Experiment for SSTI Lewis Spacecraft
NASA Technical Reports Server (NTRS)
Maghami, Peoman G.
1997-01-01
The enhanced attitude control system experiment is a technology demonstration experiment on the NASA's small spacecraft technology initiative program's Lewis spacecraft to evaluate advanced attitude control strategies. The purpose of the enhanced attitude control system experiment is to evaluate the feasibility of designing and implementing robust multi-input/multi-output attitude control strategies for enhanced pointing performance of spacecraft to improve the quality of the measurements of the science instruments. Different control design strategies based on modern and robust control theories are being considered for the enhanced attitude control system experiment. This paper describes the experiment as well as the design and synthesis of a mixed H(sub 2)/H(sub infinity) controller for attitude control. The control synthesis uses a nonlinear programming technique to tune the controller parameters and impose robustness and performance constraints. Simulations are carried out to demonstrate the feasibility of the proposed attitude control design strategy. Introduction
Generic functional requirements for a NASA general-purpose data base management system
NASA Technical Reports Server (NTRS)
Lohman, G. M.
1981-01-01
Generic functional requirements for a general-purpose, multi-mission data base management system (DBMS) for application to remotely sensed scientific data bases are detailed. The motivation for utilizing DBMS technology in this environment is explained. The major requirements include: (1) a DBMS for scientific observational data; (2) a multi-mission capability; (3) user-friendly; (4) extensive and integrated information about data; (5) robust languages for defining data structures and formats; (6) scientific data types and structures; (7) flexible physical access mechanisms; (8) ways of representing spatial relationships; (9) a high level nonprocedural interactive query and data manipulation language; (10) data base maintenance utilities; (11) high rate input/output and large data volume storage; and adaptability to a distributed data base and/or data base machine configuration. Detailed functions are specified in a top-down hierarchic fashion. Implementation, performance, and support requirements are also given.
Multi-functional Electric Module for a Vehicle
NASA Technical Reports Server (NTRS)
Waligora, Thomas M. (Inventor); Fraser-Chanpong, Nathan (Inventor); Figuered, Joshua M. (Inventor); Reed, Ryan (Inventor); Akinyode, Akinjide Akinniyi (Inventor); Spain, Ivan (Inventor); Dawson, Andrew D. (Inventor); Herrera, Eduardo (Inventor); Markee, Mason M. (Inventor); Bluethmann, William J. (Inventor)
2015-01-01
A multi-functional electric module (eModule) is provided for a vehicle having a chassis, a master controller, and a drive wheel having a propulsion-braking module. The eModule includes a steering control assembly, mounting bracket, propulsion control assembly, brake controller, housing, and control arm. The steering control assembly includes a steering motor controlled by steering controllers in response to control signals from the master controller. A mounting feature of the bracket connects to the chassis. The propulsion control assembly and brake controller are in communication with the propulsion-braking module. The control arm connects to the lower portion and contains elements of a suspension system, with the control arm being connectable to the drive wheel via a wheel input/output block. The controllers are responsive to the master controller to control a respective steering, propulsion, and braking function. The steering motor may have a dual-wound stator with windings controlled via the respective steering controllers.
NASA Technical Reports Server (NTRS)
Mill, F. W.; Krebs, G. N.; Strauss, E. S.
1976-01-01
The Multi-Purpose System Simulator (MPSS) model was used to investigate the current and projected performance of the Monitor and Control Display System (MACDS) at the Goddard Space Flight Center in processing and displaying launch data adequately. MACDS consists of two interconnected mini-computers with associated terminal input and display output equipment and a disk-stored data base. Three configurations of MACDS were evaluated via MPSS and their performances ascertained. First, the current version of MACDS was found inadequate to handle projected launch data loads because of unacceptable data backlogging. Second, the current MACDS hardware with enhanced software was capable of handling two times the anticipated data loads. Third, an up-graded hardware ensemble combined with the enhanced software was capable of handling four times the anticipated data loads.
Multi-sectorial convergence in greenhouse gas emissions.
Oliveira, Guilherme de; Bourscheidt, Deise Maria
2017-07-01
This paper uses the World Input-Output Database (WIOD) to test the hypothesis of per capita convergence in greenhouse gas (GHG) emissions for a multi-sectorial panel of countries. The empirical strategy applies conventional estimators of random and fixed effects and Arellano and Bond's (1991) GMM to the main pollutants related to the greenhouse effect. For reasonable empirical specifications, the model revealed robust evidence of per capita convergence in CH 4 emissions in the agriculture, food, and services sectors. The evidence of convergence in CO 2 emissions was moderate in the following sectors: agriculture, food, non-durable goods manufacturing, and services. In all cases, the time for convergence was less than 15 years. Regarding emissions by energy use, the largest source of global warming, there was only moderate evidence in the extractive industry sector-all other pollutants presented little or no evidence. Copyright © 2017 Elsevier Ltd. All rights reserved.
Bounemeur, Abdelhamid; Chemachema, Mohamed; Essounbouli, Najib
2018-05-10
In this paper, an active fuzzy fault tolerant tracking control (AFFTTC) scheme is developed for a class of multi-input multi-output (MIMO) unknown nonlinear systems in the presence of unknown actuator faults, sensor failures and external disturbance. The developed control scheme deals with four kinds of faults for both sensors and actuators. The bias, drift, and loss of accuracy additive faults are considered along with the loss of effectiveness multiplicative fault. A fuzzy adaptive controller based on back-stepping design is developed to deal with actuator failures and unknown system dynamics. However, an additional robust control term is added to deal with sensor faults, approximation errors, and external disturbances. Lyapunov theory is used to prove the stability of the closed loop system. Numerical simulations on a quadrotor are presented to show the effectiveness of the proposed approach. Copyright © 2018 ISA. Published by Elsevier Ltd. All rights reserved.
Pandey, Vinay Kumar; Kar, Indrani; Mahanta, Chitralekha
2017-07-01
In this paper, an adaptive control method using multiple models with second level adaptation is proposed for a class of nonlinear multi-input multi-output (MIMO) coupled systems. Multiple estimation models are used to tune the unknown parameters at the first level. The second level adaptation provides a single parameter vector for the controller. A feedback linearization technique is used to design a state feedback control. The efficacy of the designed controller is validated by conducting real time experiment on a laboratory setup of twin rotor MIMO system (TRMS). The TRMS setup is discussed in detail and the experiments were performed for regulation and tracking problem for pitch and yaw control using different reference signals. An Extended Kalman Filter (EKF) has been used to observe the unavailable states of the TRMS. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.
Application of fuzzy adaptive control to a MIMO nonlinear time-delay pump-valve system.
Lai, Zhounian; Wu, Peng; Wu, Dazhuan
2015-07-01
In this paper, a control strategy to balance the reliability against efficiency is introduced to overcome the common off-design operation problem in pump-valve systems. The pump-valve system is a nonlinear multi-input-multi-output (MIMO) system with time delays which cannot be accurately measured but can be approximately modeled using Bernoulli Principle. A fuzzy adaptive controller is applied to approximate system parameters and achieve the control of delay-free model since the system model is inaccurate and the direct feedback linearization method cannot be applied. An extended Smith predictor is introduced to compensate time delays of the system using the inaccurate system model. The experiment is carried out to verify the effectiveness of the control strategy whose results show that the control performance is well achieved. Copyright © 2015 ISA. Published by Elsevier Ltd. All rights reserved.
Storm-based Cloud-to-Ground Lightning Probabilities and Warnings
NASA Astrophysics Data System (ADS)
Calhoun, K. M.; Meyer, T.; Kingfield, D.
2017-12-01
A new cloud-to-ground (CG) lightning probability algorithm has been developed using machine-learning methods. With storm-based inputs of Earth Networks' in-cloud lightning, Vaisala's CG lightning, multi-radar/multi-sensor (MRMS) radar derived products including the Maximum Expected Size of Hail (MESH) and Vertically Integrated Liquid (VIL), and near storm environmental data including lapse rate and CAPE, a random forest algorithm was trained to produce probabilities of CG lightning up to one-hour in advance. As part of the Prototype Probabilistic Hazard Information experiment in the Hazardous Weather Testbed in 2016 and 2017, National Weather Service forecasters were asked to use this CG lightning probability guidance to create rapidly updating probability grids and warnings for the threat of CG lightning for 0-60 minutes. The output from forecasters was shared with end-users, including emergency managers and broadcast meteorologists, as part of an integrated warning team.
Visualization techniques to aid in the analysis of multi-spectral astrophysical data sets
NASA Technical Reports Server (NTRS)
Domik, Gitta; Alam, Salim; Pinkney, Paul
1992-01-01
This report describes our project activities for the period Sep. 1991 - Oct. 1992. Our activities included stabilizing the software system STAR, porting STAR to IDL/widgets (improved user interface), targeting new visualization techniques for multi-dimensional data visualization (emphasizing 3D visualization), and exploring leading-edge 3D interface devices. During the past project year we emphasized high-end visualization techniques, by exploring new tools offered by state-of-the-art visualization software (such as AVS3 and IDL4/widgets), by experimenting with tools still under research at the Department of Computer Science (e.g., use of glyphs for multidimensional data visualization), and by researching current 3D input/output devices as they could be used to explore 3D astrophysical data. As always, any project activity is driven by the need to interpret astrophysical data more effectively.
Umeki, Takeshi; Takara, Hidehiko; Miyamoto, Yutaka; Asobe, Masaki
2012-10-22
We demonstrated the simultaneous amplification of a coherent multi-carrier signal using a χ(2)-based non-degenerate phase sensitive amplifier (PSA). The signal-to-noise ratio (SNR), which is degraded by the additional amplified spontaneous emission (ASE) noise, can be recovered due to the gain difference between a phase-correlated signal-idler pair and uncorrelated excess noise. Utilizing the second harmonic pumping of a χ(2)-based PSA enables us to observe the SNR recovery directly by comparing the SNR for the input with that for the PSA output. A 3-dB optical-SNR (OSNR) improvement was obtained as a result of the gain difference. We also achieved a 3-dB SNR improvement in the electric domain by reducing the signal-ASE beat noise. The receiver sensitivity for a 10 Gbit/s phase shift keying signal was clearly improved with the PSA.
Deep-subwavelength Decoupling for MIMO Antennas in Mobile Handsets with Singular Medium.
Xu, Su; Zhang, Ming; Wen, Huailin; Wang, Jun
2017-09-22
Decreasing the mutual coupling between Multi-input Multi-output (MIMO) antenna elements in a mobile handset and achieving a high data rate is a challenging topic as the 5 th -generation (5G) communication age is coming. Conventional decoupling components for MIMO antennas have to be re-designed when the geometries or frequencies of antennas have any adjustment. In this paper, we report a novel metamaterial-based decoupling strategy for MIMO antennas in mobile handsets with wide applicability. The decoupling component is made of subwavelength metal/air layers, which can be treated as singular medium over a broad frequency band. The flexible applicable property of the decoupling strategy is verified with different antennas over different frequency bands with the same metamaterial decoupling element. Finally, 1/100-wavelength 10-dB isolation is demonstrated for a 24-element MIMO antenna in mobile handsets over the frequency band from 4.55 to 4.75 GHz.
Zero-forcing pre-coding for MIMO WiMAX transceivers: Performance analysis and implementation issues
NASA Astrophysics Data System (ADS)
Cattoni, A. F.; Le Moullec, Y.; Sacchi, C.
Next generation wireless communication networks are expected to achieve ever increasing data rates. Multi-User Multiple-Input-Multiple-Output (MU-MIMO) is a key technique to obtain the expected performance, because such a technique combines the high capacity achievable using MIMO channel with the benefits of space division multiple access. In MU-MIMO systems, the base stations transmit signals to two or more users over the same channel, for this reason every user can experience inter-user interference. This paper provides a capacity analysis of an online, interference-based pre-coding algorithm able to mitigate the multi-user interference of the MU-MIMO systems in the context of a realistic WiMAX application scenario. Simulation results show that pre-coding can significantly increase the channel capacity. Furthermore, the paper presents several feasibility considerations for implementation of the analyzed technique in a possible FPGA-based software defined radio.
A novel multi-scroll chaotic generator: Analysis, simulation, and implementation
NASA Astrophysics Data System (ADS)
Zhang, Gui-Tao; Wang, Fa-Qiang
2018-01-01
Not Available Project supported by the National Natural Science Foundation of China (Grant Nos. 51377124 and 51521065), the Foundation for the Author of National Excellent Doctoral Dissertation, China (Grant No. 201337), and the New Star of Youth Science and Technology of Shaanxi Province, China (Grant No. 2016KJXX-40).
Multicoordination Control Strategy Performance in Hybrid Power Systems
DOE Office of Scientific and Technical Information (OSTI.GOV)
Pezzini, Paolo; Bryden, Kenneth M.; Tucker, David
This paper evaluates a state-space methodology of a multi-input multi-output (MIMO) control strategy using a 2 × 2 tightly coupled scenario applied to a physical gas turbine fuel cell hybrid power system. A centralized MIMO controller was preferred compared to a decentralized control approach because previous simulation studies showed that the coupling effect identified during the simultaneous control of the turbine speed and cathode airflow was better minimized. The MIMO controller was developed using a state-space dynamic model of the system that was derived using first-order transfer functions empirically obtained through experimental tests. The controller performance was evaluated in termsmore » of disturbance rejection through perturbations in the gas turbine operation, and setpoint tracking maneuver through turbine speed and cathode airflow steps. The experimental results illustrate that a multicoordination control strategy was able to mitigate the coupling of each actuator to each output during the simultaneous control of the system, and improved the overall system performance during transient conditions. On the other hand, the controller showed different performance during validation in simulation environment compared to validation in the physical facility, which will require a better dynamic modeling of the system for the implementation of future multivariable control strategies.« less
Multicoordination Control Strategy Performance in Hybrid Power Systems
Pezzini, Paolo; Bryden, Kenneth M.; Tucker, David
2018-04-11
This paper evaluates a state-space methodology of a multi-input multi-output (MIMO) control strategy using a 2 × 2 tightly coupled scenario applied to a physical gas turbine fuel cell hybrid power system. A centralized MIMO controller was preferred compared to a decentralized control approach because previous simulation studies showed that the coupling effect identified during the simultaneous control of the turbine speed and cathode airflow was better minimized. The MIMO controller was developed using a state-space dynamic model of the system that was derived using first-order transfer functions empirically obtained through experimental tests. The controller performance was evaluated in termsmore » of disturbance rejection through perturbations in the gas turbine operation, and setpoint tracking maneuver through turbine speed and cathode airflow steps. The experimental results illustrate that a multicoordination control strategy was able to mitigate the coupling of each actuator to each output during the simultaneous control of the system, and improved the overall system performance during transient conditions. On the other hand, the controller showed different performance during validation in simulation environment compared to validation in the physical facility, which will require a better dynamic modeling of the system for the implementation of future multivariable control strategies.« less
Vishwakarma, Siddharth; Kumar, Ajit; Pandey, Abha; Upadhyay, K K
2017-01-05
A chromogenic fluoride probe bearing bis imine groups having dual -NH functionality (BSB) has been designed, synthesised and structurally characterized by its single crystal X-ray diffraction studies. The BSB could visually and spectroscopically recognise F(-) with high selectivity over other anions by exhibiting intense chromogenic response (from colourless to red) for F(-) in acetonitrile solution. The UV-visible titration and (1)H NMR titration experiments indicated that the observed changes occur via a combined process including hydrogen bonding and deprotonation between the BSB and F(-). Moreover theoretical calculations at the Density Functional Theory (DFT) level shed further light upon probe design strategy and the nature of interactions between BSB and F(-). The limit of detection and binding constant of BSB towards F(-) were found to be 6.9×10(-7)M and 1.42±0.069×10(8)M(-2) respectively. Finally, by using F(-)and H(+) as chemical inputs and the absorbance as output, a INHIBIT logic gate was constructed, which exhibits "Multi-write" ability without obvious degradation in its optical output. Copyright © 2016 Elsevier B.V. All rights reserved.
NASA Astrophysics Data System (ADS)
Hu, Guansheng; Zhang, Tao; Zhang, Xuan; Shi, Gentai; Bai, Haojie
2018-03-01
In order to achieve multi-color temperature and multi-magnitude output, magnitude and temperature can real-time adjust, a new type of calibration single star simulator was designed with adjustable magnitude and optical spectrum output in this article. xenon lamp and halogen tungsten lamp were used as light source. The control of spectrum band and temperature of star was realized with different multi-beam narrow band spectrum with light of varying intensity. When light source with different spectral characteristics and color temperature go into the magnitude regulator, the light energy attenuation were under control by adjusting the light luminosity. This method can completely satisfy the requirements of calibration single star simulator with adjustable magnitude and optical spectrum output in order to achieve the adjustable purpose of magnitude and spectrum.
Presentation planning using an integrated knowledge base
NASA Technical Reports Server (NTRS)
Arens, Yigal; Miller, Lawrence; Sondheimer, Norman
1988-01-01
A description is given of user interface research aimed at bringing together multiple input and output modes in a way that handles mixed mode input (commands, menus, forms, natural language), interacts with a diverse collection of underlying software utilities in a uniform way, and presents the results through a combination of output modes including natural language text, maps, charts and graphs. The system, Integrated Interfaces, derives much of its ability to interact uniformly with the user and the underlying services and to build its presentations, from the information present in a central knowledge base. This knowledge base integrates models of the application domain (Navy ships in the Pacific region, in the current demonstration version); the structure of visual displays and their graphical features; the underlying services (data bases and expert systems); and interface functions. The emphasis is on a presentation planner that uses the knowledge base to produce multi-modal output. There has been a flurry of recent work in user interface management systems. (Several recent examples are listed in the references). Existing work is characterized by an attempt to relieve the software designer of the burden of handcrafting an interface for each application. The work has generally focused on intelligently handling input. This paper deals with the other end of the pipeline - presentations.
NASA Astrophysics Data System (ADS)
Wang, Xianxun; Mei, Yadong
2017-04-01
Coordinative operation of hydro-wind-photovoltaic is the solution of mitigating the conflict of power generation and output fluctuation of new energy and conquering the bottleneck of new energy development. Due to the deficiencies of characterizing output fluctuation, depicting grid construction and disposal of power abandon, the research of coordinative mechanism is influenced. In this paper, the multi-object and multi-hierarchy model of coordinative operation of hydro-wind-photovoltaic is built with the aim of maximizing power generation and minimizing output fluctuation and the constraints of topotaxy of power grid and balanced disposal of power abandon. In the case study, the comparison of uncoordinative and coordinative operation is carried out with the perspectives of power generation, power abandon and output fluctuation. By comparison from power generation, power abandon and output fluctuation between separate operation and coordinative operation of multi-power, the coordinative mechanism is studied. Compared with running solely, coordinative operation of hydro-wind-photovoltaic can gain the compensation benefits. Peak-alternation operation reduces the power abandon significantly and maximizes resource utilization effectively by compensating regulation of hydropower. The Pareto frontier of power generation and output fluctuation is obtained through multiple-objective optimization. It clarifies the relationship of mutual influence between these two objects. When coordinative operation is taken, output fluctuation can be markedly reduced at the cost of a slight decline of power generation. The power abandon also drops sharply compared with operating separately. Applying multi-objective optimization method to optimize the coordinate operation, Pareto optimal solution set of power generation and output fluctuation is achieved.
High Frequency Single-Stage Multi-Bypass Pulse Tube Cryocooler for 23.8K
NASA Astrophysics Data System (ADS)
Yang, Junling; Hou, Xiaofeng; Yang, Luwei; Zhou, Yuan; Zhang, Liang
2008-03-01
A below 30K single-stage high-frequency multi-bypass pulse tube cryocooler(PTC) is introduced in this paper. At present, the lowest temperature of 27.46K has been achieved with input power of 100W and 23.8K with input power of 200W. Experiments show that if the area of multi-bypass and the length of inertance tube matching well, a better performance of PTC will be obtained.
Engines-only flight control system
NASA Technical Reports Server (NTRS)
Burcham, Frank W. (Inventor); Gilyard, Glenn B (Inventor); Conley, Joseph L. (Inventor); Stewart, James F. (Inventor); Fullerton, Charles G. (Inventor)
1994-01-01
A backup flight control system for controlling the flightpath of a multi-engine airplane using the main drive engines is introduced. The backup flight control system comprises an input device for generating a control command indicative of a desired flightpath, a feedback sensor for generating a feedback signal indicative of at least one of pitch rate, pitch attitude, roll rate and roll attitude, and a control device for changing the output power of at least one of the main drive engines on each side of the airplane in response to the control command and the feedback signal.
NASA Astrophysics Data System (ADS)
Abing, Stephen Lloyd N.; Barton, Mercie Grace L.; Dumdum, Michael Gerard M.; Bongo, Miriam F.; Ocampo, Lanndon A.
2018-02-01
This paper adopts a modified approach of data envelopment analysis (DEA) to measure the academic efficiency of university departments. In real-world case studies, conventional DEA models often identify too many decision-making units (DMUs) as efficient. This occurs when the number of DMUs under evaluation is not large enough compared to the total number of decision variables. To overcome this limitation and reduce the number of decision variables, multi-objective data envelopment analysis (MODEA) approach previously presented in the literature is applied. The MODEA approach applies Shapley value as a cooperative game to determine the appropriate weights and efficiency score of each category of inputs. To illustrate the performance of the adopted approach, a case study is conducted in a university in the Philippines. The input variables are academic staff, non-academic staff, classrooms, laboratories, research grants, and department expenditures, while the output variables are the number of graduates and publications. The results of the case study revealed that all DMUs are inefficient. DMUs with efficiency scores close to the ideal efficiency score may be emulated by other DMUs with least efficiency scores.
Self-balanced modulation and magnetic rebalancing method for parallel multilevel inverters
DOE Office of Scientific and Technical Information (OSTI.GOV)
Li, Hui; Shi, Yanjun
A self-balanced modulation method and a closed-loop magnetic flux rebalancing control method for parallel multilevel inverters. The combination of the two methods provides for balancing of the magnetic flux of the inter-cell transformers (ICTs) of the parallel multilevel inverters without deteriorating the quality of the output voltage. In various embodiments a parallel multi-level inverter modulator is provide including a multi-channel comparator to generate a multiplexed digitized ideal waveform for a parallel multi-level inverter and a finite state machine (FSM) module coupled to the parallel multi-channel comparator, the FSM module to receive the multiplexed digitized ideal waveform and to generate amore » pulse width modulated gate-drive signal for each switching device of the parallel multi-level inverter. The system and method provides for optimization of the output voltage spectrum without influence the magnetic balancing.« less
Using multi-criteria analysis of simulation models to understand complex biological systems
Maureen C. Kennedy; E. David Ford
2011-01-01
Scientists frequently use computer-simulation models to help solve complex biological problems. Typically, such models are highly integrated, they produce multiple outputs, and standard methods of model analysis are ill suited for evaluating them. We show how multi-criteria optimization with Pareto optimality allows for model outputs to be compared to multiple system...
Zhang, Shu; Taft, Cyrus W; Bentsman, Joseph; Hussey, Aaron; Petrus, Bryan
2012-09-01
Tuning a complex multi-loop PID based control system requires considerable experience. In today's power industry the number of available qualified tuners is dwindling and there is a great need for better tuning tools to maintain and improve the performance of complex multivariable processes. Multi-loop PID tuning is the procedure for the online tuning of a cluster of PID controllers operating in a closed loop with a multivariable process. This paper presents the first application of the simultaneous tuning technique to the multi-input-multi-output (MIMO) PID based nonlinear controller in the power plant control context, with the closed-loop system consisting of a MIMO nonlinear boiler/turbine model and a nonlinear cluster of six PID-type controllers. Although simplified, the dynamics and cross-coupling of the process and the PID cluster are similar to those used in a real power plant. The particular technique selected, iterative feedback tuning (IFT), utilizes the linearized version of the PID cluster for signal conditioning, but the data collection and tuning is carried out on the full nonlinear closed-loop system. Based on the figure of merit for the control system performance, the IFT is shown to deliver performance favorably comparable to that attained through the empirical tuning carried out by an experienced control engineer. Copyright © 2012 ISA. Published by Elsevier Ltd. All rights reserved.
Efficiency measurement of health care organizations: What models are used?
Jaafaripooyan, Ebrahim; Emamgholipour, Sara; Raei, Behzad
2017-01-01
Background: Literature abounds with various techniques for efficiency measurement of health care organizations (HCOs), which should be used cautiously and appropriately. The present study aimed at discovering the rules regulating the interplay among the number of inputs, outputs, and decision- making units (DMUs) and identifying all methods used for the measurement of Iranian HCOs and critically appraising all DEA studies on Iranian HCOs in their application of such rules. Methods: The present study employed a systematic search of all studies related to efficiency measurement of Iranian HCOs. A search was conducted in different databases such as PubMed and Scopus between 2001 and 2015 to identify the studies related to the measurement in health care. The retrieved studies passed through a multi-stage (title, abstract, body) filtering process. Data extraction table for each study was completed and included method, number of inputs and outputs, DMUs, and their efficiency score. Results: Various methods were found for efficiency measurement. Overall, 122 studies were retrieved, of which 73 had exclusively employed DEA technique for measuring the efficiency of HCOs in Iran, and 23 with hybrid models (including DEA). Only 6 studies had explicitly used the rules of thumb. Conclusion: The number of inputs, outputs, and DMUs should be cautiously selected in DEA like techniques, as their proportionality can directly affect the discriminatory power of the technique. The given literature seemed to be, to a large extent, unsuccessful in attending to such proportionality. This study collected a list of key rules (of thumb) on the interplay of inputs, outputs, and DMUs, which could be considered by most researchers keen to apply DEA technique.
Zhang, Zhengyan; Zhang, Jianyun; Zhou, Qingsong; Li, Xiaobo
2018-03-07
In this paper, we consider the problem of tracking the direction of arrivals (DOA) and the direction of departure (DOD) of multiple targets for bistatic multiple-input multiple-output (MIMO) radar. A high-precision tracking algorithm for target angle is proposed. First, the linear relationship between the covariance matrix difference and the angle difference of the adjacent moment was obtained through three approximate relations. Then, the proposed algorithm obtained the relationship between the elements in the covariance matrix difference. On this basis, the performance of the algorithm was improved by averaging the covariance matrix element. Finally, the least square method was used to estimate the DOD and DOA. The algorithm realized the automatic correlation of the angle and provided better performance when compared with the adaptive asymmetric joint diagonalization (AAJD) algorithm. The simulation results demonstrated the effectiveness of the proposed algorithm. The algorithm provides the technical support for the practical application of MIMO radar.
Optimal Frequency-Domain System Realization with Weighting
NASA Technical Reports Server (NTRS)
Juang, Jer-Nan; Maghami, Peiman G.
1999-01-01
Several approaches are presented to identify an experimental system model directly from frequency response data. The formulation uses a matrix-fraction description as the model structure. Frequency weighting such as exponential weighting is introduced to solve a weighted least-squares problem to obtain the coefficient matrices for the matrix-fraction description. A multi-variable state-space model can then be formed using the coefficient matrices of the matrix-fraction description. Three different approaches are introduced to fine-tune the model using nonlinear programming methods to minimize the desired cost function. The first method uses an eigenvalue assignment technique to reassign a subset of system poles to improve the identified model. The second method deals with the model in the real Schur or modal form, reassigns a subset of system poles, and adjusts the columns (rows) of the input (output) influence matrix using a nonlinear optimizer. The third method also optimizes a subset of poles, but the input and output influence matrices are refined at every optimization step through least-squares procedures.
Development of metamodels for predicting aerosol dispersion in ventilated spaces
NASA Astrophysics Data System (ADS)
Hoque, Shamia; Farouk, Bakhtier; Haas, Charles N.
2011-04-01
Artificial neural network (ANN) based metamodels were developed to describe the relationship between the design variables and their effects on the dispersion of aerosols in a ventilated space. A Hammersley sequence sampling (HSS) technique was employed to efficiently explore the multi-parameter design space and to build numerical simulation scenarios. A detailed computational fluid dynamics (CFD) model was applied to simulate these scenarios. The results derived from the CFD simulations were used to train and test the metamodels. Feed forward ANN's were developed to map the relationship between the inputs and the outputs. The predictive ability of the neural network based metamodels was compared to linear and quadratic metamodels also derived from the same CFD simulation results. The ANN based metamodel performed well in predicting the independent data sets including data generated at the boundaries. Sensitivity analysis showed that particle tracking time to residence time and the location of input and output with relation to the height of the room had more impact than the other dimensionless groups on particle behavior.
Efficient RF energy harvesting by using a fractal structured rectenna system
NASA Astrophysics Data System (ADS)
Oh, Sechang; Ramasamy, Mouli; Varadan, Vijay K.
2014-04-01
A rectenna system delivers, collects, and converts RF energy into direct current to power the electronic devices or recharge batteries. It consists of an antenna for receiving RF power, an input filter for processing energy and impedance matching, a rectifier, an output filter, and a load resistor. However, the conventional rectenna systems have drawback in terms of power generation, as the single resonant frequency of an antenna can generate only low power compared to multiple resonant frequencies. A multi band rectenna system is an optimal solution to generate more power. This paper proposes the design of a novel rectenna system, which involves developing a multi band rectenna with a fractal structured antenna to facilitate an increase in energy harvesting from various sources like Wi-Fi, TV signals, mobile networks and other ambient sources, eliminating the limitation of a single band technique. The usage of fractal antennas effects certain prominent advantages in terms of size and multiple resonances. Even though, a fractal antenna incorporates multiple resonances, controlling the resonant frequencies is an important aspect to generate power from the various desired RF sources. Hence, this paper also describes the design parameters of the fractal antenna and the methods to control the multi band frequency.
Deep Visual Attention Prediction
NASA Astrophysics Data System (ADS)
Wang, Wenguan; Shen, Jianbing
2018-05-01
In this work, we aim to predict human eye fixation with view-free scenes based on an end-to-end deep learning architecture. Although Convolutional Neural Networks (CNNs) have made substantial improvement on human attention prediction, it is still needed to improve CNN based attention models by efficiently leveraging multi-scale features. Our visual attention network is proposed to capture hierarchical saliency information from deep, coarse layers with global saliency information to shallow, fine layers with local saliency response. Our model is based on a skip-layer network structure, which predicts human attention from multiple convolutional layers with various reception fields. Final saliency prediction is achieved via the cooperation of those global and local predictions. Our model is learned in a deep supervision manner, where supervision is directly fed into multi-level layers, instead of previous approaches of providing supervision only at the output layer and propagating this supervision back to earlier layers. Our model thus incorporates multi-level saliency predictions within a single network, which significantly decreases the redundancy of previous approaches of learning multiple network streams with different input scales. Extensive experimental analysis on various challenging benchmark datasets demonstrate our method yields state-of-the-art performance with competitive inference time.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Seyedhosseini, Mojtaba; Kumar, Ritwik; Jurrus, Elizabeth R.
2011-10-01
Automated neural circuit reconstruction through electron microscopy (EM) images is a challenging problem. In this paper, we present a novel method that exploits multi-scale contextual information together with Radon-like features (RLF) to learn a series of discriminative models. The main idea is to build a framework which is capable of extracting information about cell membranes from a large contextual area of an EM image in a computationally efficient way. Toward this goal, we extract RLF that can be computed efficiently from the input image and generate a scale-space representation of the context images that are obtained at the output ofmore » each discriminative model in the series. Compared to a single-scale model, the use of a multi-scale representation of the context image gives the subsequent classifiers access to a larger contextual area in an effective way. Our strategy is general and independent of the classifier and has the potential to be used in any context based framework. We demonstrate that our method outperforms the state-of-the-art algorithms in detection of neuron membranes in EM images.« less
Multi Objective Optimization of Yarn Quality and Fibre Quality Using Evolutionary Algorithm
NASA Astrophysics Data System (ADS)
Ghosh, Anindya; Das, Subhasis; Banerjee, Debamalya
2013-03-01
The quality and cost of resulting yarn play a significant role to determine its end application. The challenging task of any spinner lies in producing a good quality yarn with added cost benefit. The present work does a multi-objective optimization on two objectives, viz. maximization of cotton yarn strength and minimization of raw material quality. The first objective function has been formulated based on the artificial neural network input-output relation between cotton fibre properties and yarn strength. The second objective function is formulated with the well known regression equation of spinning consistency index. It is obvious that these two objectives are conflicting in nature i.e. not a single combination of cotton fibre parameters does exist which produce maximum yarn strength and minimum cotton fibre quality simultaneously. Therefore, it has several optimal solutions from which a trade-off is needed depending upon the requirement of user. In this work, the optimal solutions are obtained with an elitist multi-objective evolutionary algorithm based on Non-dominated Sorting Genetic Algorithm II (NSGA-II). These optimum solutions may lead to the efficient exploitation of raw materials to produce better quality yarns at low costs.
Plowright, Alleyn T; Johnstone, Craig; Kihlberg, Jan; Pettersson, Jonas; Robb, Graeme; Thompson, Richard A
2012-01-01
In drug discovery, the central process of constructing and testing hypotheses, carefully conducting experiments and analysing the associated data for new findings and information is known as the design-make-test-analyse cycle. Each step relies heavily on the inputs and outputs of the other three components. In this article we report our efforts to improve and integrate all parts to enable smooth and rapid flow of high quality ideas. Key improvements include enhancing multi-disciplinary input into 'Design', increasing the use of knowledge and reducing cycle times in 'Make', providing parallel sets of relevant data within ten working days in 'Test' and maximising the learning in 'Analyse'. Copyright © 2011 Elsevier Ltd. All rights reserved.
Multi-input and binary reproducible, high bandwidth floating point adder in a collective network
DOE Office of Scientific and Technical Information (OSTI.GOV)
Chen, Dong; Eisley, Noel A; Heidelberger, Philip
To add floating point numbers in a parallel computing system, a collective logic device receives the floating point numbers from computing nodes. The collective logic devices converts the floating point numbers to integer numbers. The collective logic device adds the integer numbers and generating a summation of the integer numbers. The collective logic device converts the summation to a floating point number. The collective logic device performs the receiving, the converting the floating point numbers, the adding, the generating and the converting the summation in one pass. One pass indicates that the computing nodes send inputs only once to themore » collective logic device and receive outputs only once from the collective logic device.« less
Memcapacitor model and its application in chaotic oscillator with memristor.
Wang, Guangyi; Zang, Shouchi; Wang, Xiaoyuan; Yuan, Fang; Iu, Herbert Ho-Ching
2017-01-01
Memristors and memcapacitors are two new nonlinear elements with memory. In this paper, we present a Hewlett-Packard memristor model and a charge-controlled memcapacitor model and design a new chaotic oscillator based on the two models for exploring the characteristics of memristors and memcapacitors in nonlinear circuits. Furthermore, many basic dynamical behaviors of the oscillator, including equilibrium sets, Lyapunov exponent spectrums, and bifurcations with various circuit parameters, are investigated theoretically and numerically. Our analysis results show that the proposed oscillator possesses complex dynamics such as an infinite number of equilibria, coexistence oscillation, and multi-stability. Finally, a discrete model of the chaotic oscillator is given and the main statistical properties of this oscillator are verified via Digital Signal Processing chip experiments and National Institute of Standards and Technology tests.
Printed Multi-Turn Loop Antenna for RF Bio-Telemetry
NASA Technical Reports Server (NTRS)
Simons, Rainee N.; Hall, David G.; Miranda, Felix A.
2004-01-01
In this paper, a novel printed multi-turn loop antenna for contact-less powering and RF telemetry from implantable bio- MEMS sensors at a design frequency of 300 MHz is demonstrated. In addition, computed values of input reactance, radiation resistance, skin effect resistance, and radiation efficiency for the printed multi-turn loop antenna are presented. The computed input reactance is compared with the measured values and shown to be in fair agreement. The computed radiation efficiency at the design frequency is about 24 percent.
Advances in integrated photonic circuits for packet-switched interconnection
NASA Astrophysics Data System (ADS)
Williams, Kevin A.; Stabile, Ripalta
2014-03-01
Sustained increases in capacity and connectivity are needed to overcome congestion in a range of broadband communication network nodes. Packet routing and switching in the electronic domain are leading to unsustainable energy- and bandwidth-densities, motivating research into hybrid solutions: optical switching engines are introduced for massive-bandwidth data transport while the electronic domain is clocked at more modest GHz rates to manage routing. Commercially-deployed optical switching engines using MEMS technologies are unwieldy and too slow to reconfigure for future packet-based networking. Optoelectronic packet-compliant switch technologies have been demonstrated as laboratory prototypes, but they have so far mostly used discretely pigtailed components, which are impractical for control plane development and product assembly. Integrated photonics has long held the promise of reduced hardware complexity and may be the critical step towards packet-compliant optical switching engines. Recently a number of laboratories world-wide have prototyped optical switching circuits using monolithic integration technology with up to several hundreds of integrated optical components per chip. Our own work has focused on multi-input to multi-output switching matrices. Recently we have demonstrated 8×8×8λ space and wavelength selective switches using gated cyclic routers and 16×16 broadband switching chips using monolithic multi-stage networks. We now operate these advanced circuits with custom control planes implemented with FPGAs to explore real time packet routing in multi-wavelength, multi-port test-beds. We review our contributions in the context of state of the art photonic integrated circuit technology and packet optical switching hardware demonstrations.
Merging of multi-string BWTs with applications
Holt, James; McMillan, Leonard
2014-01-01
Motivation: The throughput of genomic sequencing has increased to the point that is overrunning the rate of downstream analysis. This, along with the desire to revisit old data, has led to a situation where large quantities of raw, and nearly impenetrable, sequence data are rapidly filling the hard drives of modern biology labs. These datasets can be compressed via a multi-string variant of the Burrows–Wheeler Transform (BWT), which provides the side benefit of searches for arbitrary k-mers within the raw data as well as the ability to reconstitute arbitrary reads as needed. We propose a method for merging such datasets for both increased compression and downstream analysis. Results: We present a novel algorithm that merges multi-string BWTs in O(LCS×N) time where LCS is the length of their longest common substring between any of the inputs, and N is the total length of all inputs combined (number of symbols) using O(N×log2(F)) bits where F is the number of multi-string BWTs merged. This merged multi-string BWT is also shown to have a higher compressibility compared with the input multi-string BWTs separately. Additionally, we explore some uses of a merged multi-string BWT for bioinformatics applications. Availability and implementation: The MSBWT package is available through PyPI with source code located at https://code.google.com/p/msbwt/. Contact: holtjma@cs.unc.edu PMID:25172922
Solar Wind Interaction with the Martian Upper Atmosphere at Early Mars/Extreme Solar Conditions
NASA Astrophysics Data System (ADS)
Dong, C.; Bougher, S. W.; Ma, Y.; Toth, G.; Lee, Y.; Nagy, A. F.; Tenishev, V.; Pawlowski, D. J.; Combi, M. R.
2014-12-01
The investigation of ion escape fluxes from Mars, resulting from the solar wind interaction with its upper atmosphere/ionosphere, is important due to its potential impact on the long-term evolution of Mars atmosphere (e.g., loss of water) over its history. In the present work, we adopt the 3-D Mars cold neutral atmosphere profiles (0 ~ 300 km) from the newly developed and validated Mars Global Ionosphere Thermosphere Model (M-GITM) and the 3-D hot oxygen profiles (100 km ~ 5 RM) from the exosphere Monte Carlo model Adaptive Mesh Particle Simulator (AMPS). We apply these 3-D model output fields into the 3-D BATS-R-US Mars multi-fluid MHD (MF-MHD) model (100 km ~ 20 RM) that can simulate the interplay between Mars upper atmosphere and solar wind by considering the dynamics of individual ion species. The multi-fluid MHD model solves separate continuity, momentum and energy equations for each ion species (H+, O+, O2+, CO2+). The M-GITM model together with the AMPS exosphere model take into account the effects of solar cycle and seasonal variations on both cold and hot neutral atmospheres. This feature allows us to investigate the corresponding effects on the Mars upper atmosphere ion escape by using a one-way coupling approach, i.e., both the M-GITM and AMPS model output fields are used as the input for the multi-fluid MHD model and the M-GITM is used as input into the AMPS exosphere model. In this study, we present M-GITM, AMPS, and MF-MHD calculations (1-way coupled) for 2.5 GYA conditions and/or extreme solar conditions for present day Mars (high solar wind velocities, high solar wind dynamic pressure, and high solar irradiance conditions, etc.). Present day extreme conditions may result in MF-MHD outputs that are similar to 2.5 GYA cases. The crustal field orientations are also considered in this study. By comparing estimates of past ion escape rates with the current ion loss rates to be returned by the MAVEN spacecraft (2013-2016), we can better constrain the total ion loss to space over Mars history, and thus enhance the science returned from the MAVEN mission.
Transition to Chaos in Random Neuronal Networks
NASA Astrophysics Data System (ADS)
Kadmon, Jonathan; Sompolinsky, Haim
2015-10-01
Firing patterns in the central nervous system often exhibit strong temporal irregularity and considerable heterogeneity in time-averaged response properties. Previous studies suggested that these properties are the outcome of the intrinsic chaotic dynamics of the neural circuits. Indeed, simplified rate-based neuronal networks with synaptic connections drawn from Gaussian distribution and sigmoidal nonlinearity are known to exhibit chaotic dynamics when the synaptic gain (i.e., connection variance) is sufficiently large. In the limit of an infinitely large network, there is a sharp transition from a fixed point to chaos, as the synaptic gain reaches a critical value. Near the onset, chaotic fluctuations are slow, analogous to the ubiquitous, slow irregular fluctuations observed in the firing rates of many cortical circuits. However, the existence of a transition from a fixed point to chaos in neuronal circuit models with more realistic architectures and firing dynamics has not been established. In this work, we investigate rate-based dynamics of neuronal circuits composed of several subpopulations with randomly diluted connections. Nonzero connections are either positive for excitatory neurons or negative for inhibitory ones, while single neuron output is strictly positive with output rates rising as a power law above threshold, in line with known constraints in many biological systems. Using dynamic mean field theory, we find the phase diagram depicting the regimes of stable fixed-point, unstable-dynamic, and chaotic-rate fluctuations. We focus on the latter and characterize the properties of systems near this transition. We show that dilute excitatory-inhibitory architectures exhibit the same onset to chaos as the single population with Gaussian connectivity. In these architectures, the large mean excitatory and inhibitory inputs dynamically balance each other, amplifying the effect of the residual fluctuations. Importantly, the existence of a transition to chaos and its critical properties depend on the shape of the single-neuron nonlinear input-output transfer function, near firing threshold. In particular, for nonlinear transfer functions with a sharp rise near threshold, the transition to chaos disappears in the limit of a large network; instead, the system exhibits chaotic fluctuations even for small synaptic gain. Finally, we investigate transition to chaos in network models with spiking dynamics. We show that when synaptic time constants are slow relative to the mean inverse firing rates, the network undergoes a transition from fast spiking fluctuations with constant rates to a state where the firing rates exhibit chaotic fluctuations, similar to the transition predicted by rate-based dynamics. Systems with finite synaptic time constants and firing rates exhibit a smooth transition from a regime dominated by stationary firing rates to a regime of slow rate fluctuations. This smooth crossover obeys scaling properties, similar to crossover phenomena in statistical mechanics. The theoretical results are supported by computer simulations of several neuronal architectures and dynamics. Consequences for cortical circuit dynamics are discussed. These results advance our understanding of the properties of intrinsic dynamics in realistic neuronal networks and their functional consequences.
Multi-Baker Map as a Model of Digital PD Control
NASA Astrophysics Data System (ADS)
Csernák, Gábor; Gyebrószki, Gergely; Stépán, Gábor
Digital stabilization of unstable equilibria of linear systems may lead to small amplitude stochastic-like oscillations. We show that these vibrations can be related to a deterministic chaotic dynamics induced by sampling and quantization. A detailed analytical proof of chaos is presented for the case of a PD controlled oscillator: it is shown that there exists a finite attracting domain in the phase-space, the largest Lyapunov exponent is positive and the existence of a Smale horseshoe is also pointed out. The corresponding two-dimensional micro-chaos map is a multi-baker map, i.e. it consists of a finite series of baker’s maps.
Multi-MW K-Band Harmonic Multiplier: RF Source For High-Gradient Accelerator R & D
NASA Astrophysics Data System (ADS)
Solyak, N. A.; Yakovlev, V. P.; Kazakov, S. Yu.; Hirshfield, J. L.
2009-01-01
A preliminary design is presented for a two-cavity harmonic multiplier, intended as a high-power RF source for use in experiments aimed at developing high-gradient structures for a future collider. The harmonic multiplier is to produce power at selected frequencies in K-band (18-26.5 GHz) using as an RF driver an XK-5 S-band klystron (2.856 GHz). The device is to be built with a TE111 rotating mode input cavity and interchangeable output cavities running in the TEn11 rotating mode, with n = 7,8,9 at 19.992, 22.848, and 25.704 GHz. An example for a 7th harmonic multiplier is described, using a 250 kV, 20 A injected laminar electron beam; with 10 MW of S-band drive power, 4.7 MW of 20-GHz output power is predicted. Details are described of the magnetic circuit, cavities, and output coupler.
Consumption-based Total Suspended Particulate Matter Emissions in Jing-Jin-Ji Area of China
NASA Astrophysics Data System (ADS)
Yang, S.; Chen, S.; Chen, B.
2014-12-01
The highly-industrialized regions in China have been facing a serious problem of haze mainly consisted of total suspended particulate matter (TSPM), which has attracted great attention from the public since it directly impairs human health and clinically increases the risks of various respiratory and pulmonary diseases. In this paper, we set up a multi-regional input-output (MRIO) model to analyze the transferring routes of TSPM emissions between regions through trades. TSPM emission from particulate source regions and sectors are identified by analyzing the embodied TSPM flows through monetary flow and carbon footprint. The track of TSPM from origin to end via consumption activities are also revealed by tracing the product supply chain associated with the TSPM emissions. Beijing-Tianjin-Hebei (Jing-Jin-Ji) as the most industrialized area of China is selected for a case study. The result shows that over 70% of TSPM emissions associated with goods consumed in Beijing and Tianjin occurred outside of their own administrative boundaries, implying that Beijing and Tianjin are net embodied TSPM importers. Meanwhile, 63% of the total TSPM emissions in Hebei Province are resulted from the outside demand, indicating Hebei is a net exporter. In addition, nearly half of TSPM emissions are the by-products related to electricity and heating supply and non-metal mineral products in Jing-Jin-Ji Area. Based on the model results, we provided new insights into establishing systemic strategies and identifying mitigation priorities to stem TSPM emissions in China. Keywords: total suspended particulate matter (TSPM); urban ecosystem modeling; multi-regional input-output (MRIO); China
Schoer, Karl; Wood, Richard; Arto, Iñaki; Weinzettel, Jan
2013-12-17
The mass of material consumed by a population has become a useful proxy for measuring environmental pressure. The "raw material equivalents" (RME) metric of material consumption addresses the issue of including the full supply chain (including imports) when calculating national or product level material impacts. The RME calculation suffers from data availability, however, as quantitative data on production practices along the full supply chain (in different regions) is required. Hence, the RME is currently being estimated by three main approaches: (1) assuming domestic technology in foreign economies, (2) utilizing region-specific life-cycle inventories (in a hybrid framework), and (3) utilizing multi-regional input-output (MRIO) analysis to explicitly cover all regions of the supply chain. While the first approach has been shown to give inaccurate results, this paper focuses on the benefits and costs of the latter two approaches. We analyze results from two key (MRIO and hybrid) projects modeling raw material equivalents, adjusting the models in a stepwise manner in order to quantify the effects of individual conceptual elements. We attempt to isolate the MRIO gap, which denotes the quantitative impact of calculating the RME of imports by an MRIO approach instead of the hybrid model, focusing on the RME of EU external trade imports. While, the models give quantitatively similar results, differences become more pronounced when tracking more detailed material flows. We assess the advantages and disadvantages of the two approaches and look forward to ways to further harmonize data and approaches.
Demand-driven water withdrawals by Chinese industry: a multi-regional input-output analysis
NASA Astrophysics Data System (ADS)
Zhang, Bo; Chen, Z. M.; Zeng, L.; Qiao, H.; Chen, B.
2016-03-01
With ever increasing water demands and the continuous intensification of water scarcity arising from China's industrialization, the country is struggling to harmonize its industrial development and water supply. This paper presents a systems analysis of water withdrawals by Chinese industry and investigates demand-driven industrial water uses embodied in final demand and interregional trade based on a multi-regional input-output model. In 2007, the Electric Power, Steam, and Hot Water Production and Supply sector ranks first in direct industrial water withdrawal (DWW), and Construction has the largest embodied industrial water use (EWU). Investment, consumption, and exports contribute to 34.6%, 33.3%, and 30.6% of the national total EWU, respectively. Specifically, 58.0%, 51.1%, 48.6%, 43.3%, and 37.5% of the regional EWUs respectively in Guangdong, Shanghai, Zhejiang, Jiangsu, and Fujian are attributed to international exports. The total interregional import/export of embodied water is equivalent to about 40% of the national total DWW, of which 55.5% is associated with the DWWs of Electric Power, Steam, and Hot Water Production and Supply. Jiangsu is the biggest interregional exporter and deficit receiver of embodied water, in contrast to Guangdong as the biggest interregional importer and surplus receiver. Without implementing effective water-saving measures and adjusting industrial structures, the regional imbalance between water availability and water demand tends to intensify considering the water impact of domestic trade of industrial products. Steps taken to improve water use efficiency in production, and to enhance embodied water saving in consumption are both of great significance for supporting China's water policies.
High energy, high average power solid state green or UV laser
Hackel, Lloyd A.; Norton, Mary; Dane, C. Brent
2004-03-02
A system for producing a green or UV output beam for illuminating a large area with relatively high beam fluence. A Nd:glass laser produces a near-infrared output by means of an oscillator that generates a high quality but low power output and then multi-pass through and amplification in a zig-zag slab amplifier and wavefront correction in a phase conjugator at the midway point of the multi-pass amplification. The green or UV output is generated by means of conversion crystals that follow final propagation through the zig-zag slab amplifier.
High-Throughput, Adaptive FFT Architecture for FPGA-Based Spaceborne Data Processors
NASA Technical Reports Server (NTRS)
NguyenKobayashi, Kayla; Zheng, Jason X.; He, Yutao; Shah, Biren N.
2011-01-01
Exponential growth in microelectronics technology such as field-programmable gate arrays (FPGAs) has enabled high-performance spaceborne instruments with increasing onboard data processing capabilities. As a commonly used digital signal processing (DSP) building block, fast Fourier transform (FFT) has been of great interest in onboard data processing applications, which needs to strike a reasonable balance between high-performance (throughput, block size, etc.) and low resource usage (power, silicon footprint, etc.). It is also desirable to be designed so that a single design can be reused and adapted into instruments with different requirements. The Multi-Pass Wide Kernel FFT (MPWK-FFT) architecture was developed, in which the high-throughput benefits of the parallel FFT structure and the low resource usage of Singleton s single butterfly method is exploited. The result is a wide-kernel, multipass, adaptive FFT architecture. The 32K-point MPWK-FFT architecture includes 32 radix-2 butterflies, 64 FIFOs to store the real inputs, 64 FIFOs to store the imaginary inputs, complex twiddle factor storage, and FIFO logic to route the outputs to the correct FIFO. The inputs are stored in sequential fashion into the FIFOs, and the outputs of each butterfly are sequentially written first into the even FIFO, then the odd FIFO. Because of the order of the outputs written into the FIFOs, the depth of the even FIFOs, which are 768 each, are 1.5 times larger than the odd FIFOs, which are 512 each. The total memory needed for data storage, assuming that each sample is 36 bits, is 2.95 Mbits. The twiddle factors are stored in internal ROM inside the FPGA for fast access time. The total memory size to store the twiddle factors is 589.9Kbits. This FFT structure combines the benefits of high throughput from the parallel FFT kernels and low resource usage from the multi-pass FFT kernels with desired adaptability. Space instrument missions that need onboard FFT capabilities such as the proposed DESDynl, SWOT (Surface Water Ocean Topography), and Europa sounding radar missions would greatly benefit from this technology with significant reductions in non-recurring cost and risk.
Prediction Study on Anti-Slide Control of Railway Vehicle Based on RBF Neural Networks
NASA Astrophysics Data System (ADS)
Yang, Lijun; Zhang, Jimin
While railway vehicle braking, Anti-slide control system will detect operating status of each wheel-sets e.g. speed difference and deceleration etc. Once the detected value on some wheel-set is over pre-defined threshold, brake effort on such wheel-set will be adjusted automatically to avoid blocking. Such method takes effect on guarantee safety operation of vehicle and avoid wheel-set flatness, however it cannot adapt itself to the rail adhesion variation. While wheel-sets slide, the operating status is chaotic time series with certain law, and can be predicted with the law and experiment data in certain time. The predicted values can be used as the input reference signals of vehicle anti-slide control system, to judge and control the slide status of wheel-sets. In this article, the RBF neural networks is taken to predict wheel-set slide status in multi-step with weight vector adjusted based on online self-adaptive algorithm, and the center & normalizing parameters of active function of the hidden unit of RBF neural networks' hidden layer computed with K-means clustering algorithm. With multi-step prediction simulation, the predicted signal with appropriate precision can be used by anti-slide system to trace actively and adjust wheel-set slide tendency, so as to adapt to wheel-rail adhesion variation and reduce the risk of wheel-set blocking.
NASA Astrophysics Data System (ADS)
Roshani, Amir; Erfanian, Abbas
2016-08-01
Objective. An important issue in restoring motor function through intraspinal microstimulation (ISMS) is the motor control. To provide a physiologically plausible motor control using ISMS, it should be able to control the individual motor unit which is the lowest functional unit of motor control. By focal stimulation only a small group of motor neurons (MNs) within a motor pool can be activated. Different groups of MNs within a motor pool can potentially be activated without involving adjacent motor pools by local stimulation of different parts of a motor pool via microelectrode array implanted into a motor pool. However, since the system has multiple inputs with single output during multi-electrode ISMS, it poses a challenge to movement control. In this paper, we proposed a modular robust control strategy for movement control, whereas multi-electrode array is implanted into each motor activation pool of a muscle. Approach. The controller was based on the combination of proportional-integral-derivative and adaptive fuzzy sliding mode control. The global stability of the controller was guaranteed. Main results. The results of the experiments on rat models showed that the multi-electrode control can provide a more robust control and accurate tracking performance than a single-electrode control. The control output can be pulse amplitude (pulse amplitude modulation, PAM) or pulse width (pulse width modulation, PWM) of the stimulation signal. The results demonstrated that the controller with PAM provided faster convergence rate and better tracking performance than the controller with PWM. Significance. This work represents a promising control approach to the restoring motor functions using ISMS. The proposed controller requires no prior knowledge about the dynamics of the system to be controlled and no offline learning phase. The proposed control design is modular in the sense that each motor pool has an independent controller and each controller is able to control ISMS through an array of microelectrodes.
Detection of faults and software reliability analysis
NASA Technical Reports Server (NTRS)
Knight, John C.
1987-01-01
Multi-version or N-version programming is proposed as a method of providing fault tolerance in software. The approach requires the separate, independent preparation of multiple versions of a piece of software for some application. These versions are executed in parallel in the application environment; each receives identical inputs and each produces its version of the required outputs. The outputs are collected by a voter and, in principle, they should all be the same. In practice there may be some disagreement. If this occurs, the results of the majority are taken to be the correct output, and that is the output used by the system. A total of 27 programs were produced. Each of these programs was then subjected to one million randomly-generated test cases. The experiment yielded a number of programs containing faults that are useful for general studies of software reliability as well as studies of N-version programming. Fault tolerance through data diversity and analytic models of comparison testing are discussed.
Anabtawi, Nijad; Ferzli, Rony; Harmanani, Haidar M.
2017-01-01
This paper presents a step down, switched mode power converter for use in multi-standard envelope tracking radio frequency power amplifiers (RFPA). The converter is based on a programmable order sigma delta modulator that can be configured to operate with either 1st, 2nd, 3rd or 4th order loop filters, eliminating the need for a bulky passive output filter. Output ripple, sideband noise and spectral emission requirements of different wireless standards can be met by configuring the modulator’s filter order and converter’s sampling frequency. The proposed converter is entirely digital and is implemented in 14nm bulk CMOS process for post layout verification. For an input voltage of 3.3V, the converter’s output can be regulated to any voltage level from 0.5V to 2.5V, at a nominal switching frequency of 150MHz. It achieves a maximum efficiency of 94% at 1.5 W output power. PMID:28919657
All-fiber 7x1 signal combiner for incoherent laser beam combining
NASA Astrophysics Data System (ADS)
Noordegraaf, D.; Maack, M. D.; Skovgaard, P. M. W.; Johansen, J.; Becker, F.; Belke, S.; Blomqvist, M.; Laegsgaard, J.
2011-02-01
We demonstrate an all-fiber 7x1 signal combiner for incoherent laser beam combining. This is a potential key component for reaching several kW of stabile laser output power. The combiner couples the output from 7 single-mode (SM) fiber lasers into a single multi-mode (MM) fiber. The input signal fibers have a core diameter of 17 μm and the output MM fiber has a core diameter of 100 μm. In a tapered section light gradually leaks out of the SM fibers and is captured by a surrounding fluorine-doped cladding. The combiner is tested up to 2.5 kW of combined output power and only a minor increase in device temperature is observed. At an intermediate power level of 600 W a beam parameter product (BPP) of 2.22 mm x mrad is measured, corresponding to an M2 value of 6.5. These values are approaching the theoretical limit dictated by brightness conservation.
Detailed finite element method modeling of evaporating multi-component droplets
DOE Office of Scientific and Technical Information (OSTI.GOV)
Diddens, Christian, E-mail: C.Diddens@tue.nl
The evaporation of sessile multi-component droplets is modeled with an axisymmetic finite element method. The model comprises the coupled processes of mixture evaporation, multi-component flow with composition-dependent fluid properties and thermal effects. Based on representative examples of water–glycerol and water–ethanol droplets, regular and chaotic examples of solutal Marangoni flows are discussed. Furthermore, the relevance of the substrate thickness for the evaporative cooling of volatile binary mixture droplets is pointed out. It is shown how the evaporation of the more volatile component can drastically decrease the interface temperature, so that ambient vapor of the less volatile component condenses on the droplet.more » Finally, results of this model are compared with corresponding results of a lubrication theory model, showing that the application of lubrication theory can cause considerable errors even for moderate contact angles of 40°. - Graphical abstract:.« less
Using Enrollment Data to Predict Retention Rate
ERIC Educational Resources Information Center
Bingham, Melissa A.; Solverson, Natalie Walleser
2016-01-01
First- to second-year retention rates are one metric reported by colleges and universities to convey institutional success to a variety of external constituents. But how much of a retention rate is institutional inputs, and how much can be understood by examining student inputs? The authors utilize multi-year, multi-institutional data to examine…
NASA Astrophysics Data System (ADS)
Suhartono, Lee, Muhammad Hisyam; Rezeki, Sri
2017-05-01
Intervention analysis is a statistical model in the group of time series analysis which is widely used to describe the effect of an intervention caused by external or internal factors. An example of external factors that often occurs in Indonesia is a disaster, both natural or man-made disaster. The main purpose of this paper is to provide the results of theoretical studies on identification step for determining the order of multi inputs intervention analysis for evaluating the magnitude and duration of the impact of interventions on time series data. The theoretical result showed that the standardized residuals could be used properly as response function for determining the order of multi inputs intervention model. Then, these results are applied for evaluating the impact of a disaster on a real case in Indonesia, i.e. the magnitude and duration of the impact of the Lapindo mud on the volume of vehicles on the highway. Moreover, the empirical results showed that the multi inputs intervention model can describe and explain accurately the magnitude and duration of the impact of disasters on a time series data.
Oden, Jérémy; Lavrov, Roman; Chembo, Yanne K; Larger, Laurent
2017-11-01
We propose a chaos communication scheme based on a chaotic optical phase carrier generated with an optoelectronic oscillator with nonlinear time-delay feedback. The system includes a dedicated non-local nonlinearity, which is a customized three-wave imbalanced interferometer. This particular feature increases the complexity of the chaotic waveform and thus the security of the transmitted information, as these interferometers are characterized by four independent parameters which are part of the secret key for the chaos encryption scheme. We first analyze the route to chaos in the system, and evidence a sequence of period doubling bifurcations from the steady-state to fully developed chaos. Then, in the chaotic regime, we study the synchronization between the emitter and the receiver, and achieve chaotic carrier cancellation with a signal-to-noise ratio up to 20 dB. We finally demonstrate error-free chaos communications at a data rate of 3 Gbit/s.
NASA Astrophysics Data System (ADS)
Oden, Jérémy; Lavrov, Roman; Chembo, Yanne K.; Larger, Laurent
2017-11-01
We propose a chaos communication scheme based on a chaotic optical phase carrier generated with an optoelectronic oscillator with nonlinear time-delay feedback. The system includes a dedicated non-local nonlinearity, which is a customized three-wave imbalanced interferometer. This particular feature increases the complexity of the chaotic waveform and thus the security of the transmitted information, as these interferometers are characterized by four independent parameters which are part of the secret key for the chaos encryption scheme. We first analyze the route to chaos in the system, and evidence a sequence of period doubling bifurcations from the steady-state to fully developed chaos. Then, in the chaotic regime, we study the synchronization between the emitter and the receiver, and achieve chaotic carrier cancellation with a signal-to-noise ratio up to 20 dB. We finally demonstrate error-free chaos communications at a data rate of 3 Gbit/s.
NASA Astrophysics Data System (ADS)
Ferreira, Maria Teodora; Follmann, Rosangela; Domingues, Margarete O.; Macau, Elbert E. N.; Kiss, István Z.
2017-08-01
Phase synchronization may emerge from mutually interacting non-linear oscillators, even under weak coupling, when phase differences are bounded, while amplitudes remain uncorrelated. However, the detection of this phenomenon can be a challenging problem to tackle. In this work, we apply the Discrete Complex Wavelet Approach (DCWA) for phase assignment, considering signals from coupled chaotic systems and experimental data. The DCWA is based on the Dual-Tree Complex Wavelet Transform (DT-CWT), which is a discrete transformation. Due to its multi-scale properties in the context of phase characterization, it is possible to obtain very good results from scalar time series, even with non-phase-coherent chaotic systems without state space reconstruction or pre-processing. The method correctly predicts the phase synchronization for a chemical experiment with three locally coupled, non-phase-coherent chaotic processes. The impact of different time-scales is demonstrated on the synchronization process that outlines the advantages of DCWA for analysis of experimental data.
NASA Astrophysics Data System (ADS)
Behera, Kishore Kumar; Pal, Snehanshu
2018-03-01
This paper describes a new approach towards optimum utilisation of ferrochrome added during stainless steel making in AOD converter. The objective of optimisation is to enhance end blow chromium content of steel and reduce the ferrochrome addition during refining. By developing a thermodynamic based mathematical model, a study has been conducted to compute the optimum trade-off between ferrochrome addition and end blow chromium content of stainless steel using a predator prey genetic algorithm through training of 100 dataset considering different input and output variables such as oxygen, argon, nitrogen blowing rate, duration of blowing, initial bath temperature, chromium and carbon content, weight of ferrochrome added during refining. Optimisation is performed within constrained imposed on the input parameters whose values fall within certain ranges. The analysis of pareto fronts is observed to generate a set of feasible optimal solution between the two conflicting objectives that provides an effective guideline for better ferrochrome utilisation. It is found out that after a certain critical range, further addition of ferrochrome does not affect the chromium percentage of steel. Single variable response analysis is performed to study the variation and interaction of all individual input parameters on output variables.
Parameterized data-driven fuzzy model based optimal control of a semi-batch reactor.
Kamesh, Reddi; Rani, K Yamuna
2016-09-01
A parameterized data-driven fuzzy (PDDF) model structure is proposed for semi-batch processes, and its application for optimal control is illustrated. The orthonormally parameterized input trajectories, initial states and process parameters are the inputs to the model, which predicts the output trajectories in terms of Fourier coefficients. Fuzzy rules are formulated based on the signs of a linear data-driven model, while the defuzzification step incorporates a linear regression model to shift the domain from input to output domain. The fuzzy model is employed to formulate an optimal control problem for single rate as well as multi-rate systems. Simulation study on a multivariable semi-batch reactor system reveals that the proposed PDDF modeling approach is capable of capturing the nonlinear and time-varying behavior inherent in the semi-batch system fairly accurately, and the results of operating trajectory optimization using the proposed model are found to be comparable to the results obtained using the exact first principles model, and are also found to be comparable to or better than parameterized data-driven artificial neural network model based optimization results. Copyright © 2016 ISA. Published by Elsevier Ltd. All rights reserved.
[Emergy analysis on different planting patterns of typical watersheds in Loess Plateau.
Deng, Jian; Zhao, Fa Zhu; Han, Xin Hui; Feng, Yong Zhong; Yang, Gai He
2016-05-01
To objectively evaluate and compare the stability and sustainability of different planting patterns of typical watersheds in Loess Plateau of China after the Grain for Green Project, this paper used the emergy analysis method to quantify the emergy inputs and outputs of three watersheds with different planting patterns, i.e., both grains and fruit trees (Gaoxigou watershed), mainly grains (Wuliwan watershed) and mainly fruit trees (Miaozuigou watershed). In addition, an emergy analysis system was established to evaluate the suitability of the three patterns from the perspectives of natural resources pressure as well as social and economic development levels. More than 75% of the total emergy inputs of all the three watersheds were purchased, and nonrenewable emergy inputs had a much larger contribution than renewable emergy inputs, indicating the characteristic of low emergy self-sufficient ratio and considerable high environmental loading ratio. The pattern of planting grains had high emergy inputs but low emergy outputs, while the patterns of planting fruit trees and planting both had high emergy inputs and outputs. The energy densities of all three patterns reached two times of the average of agricultural systems in China. Especially, the net emergy of planting grains pattern was the lowest while that of planting both grains and fruit trees was the highest. The environmental sustainability index (ESI) of planting grains pattern was less than 1 and both emergy and ESI were much lower than national averages. The ESI of planting both grains and fruit trees pattern was the highest. In summary, comparison of the three patterns showed that planting both grains and fruit trees had better sustainability and high stability and the emergy production efficiency was high. Thus, it was suggested to change the agricultural development from watershed based units to multi-industry integrated mode.
Imitative and best response behaviors in a nonlinear Cournotian setting
NASA Astrophysics Data System (ADS)
Cerboni Baiardi, Lorenzo; Naimzada, Ahmad K.
2018-05-01
We consider the competition among quantity setting players in a deterministic nonlinear oligopoly framework characterized by an isoelastic demand curve. Players are characterized by having heterogeneous decisional mechanisms to set their outputs: some players are imitators, while the remaining others adopt a rational-like rule according to which their past decisions are adjusted towards their static expectation best response. The Cournot-Nash production level is a stationary state of our model together with a further production level that can be interpreted as the competitive outcome in case only imitators are present. We found that both the number of players and the relative fraction of imitators influence stability of the Cournot-Nash equilibrium with an ambiguous role, and double instability thresholds may be observed. Global analysis shows that a wide variety of complex dynamic scenarios emerge. Chaotic trajectories as well as multi-stabilities, where different attractors coexist, are robust phenomena that can be observed for a wide spectrum of parameter sets.
A fiber optic multi-stress monitoring system for power transformer
NASA Astrophysics Data System (ADS)
Kim, Dae-gil; Sampath, Umesh; Kim, Hyunjin; Song, Minho
2017-04-01
A fiber-optic multi-stress monitoring system which uses 4 FBG sensors and a fiber-optic mandrel acoustic emission sensor is proposed. FBG sensors and a mandrel sensor measure different types of stresses occurring in electrical power transformer, such as temperature and acoustic signals. The sensor system uses single broadband light source to address the outputs of both sensors using single fiber-optic circuitry. An athermal-packaged FBG is used to supply quasi-coherent light for the Sagnac interferometer demodulation which processes the mandrel sensor output. The proposed sensor system could simplify the optical circuit for the multi-stress measurements and enhance the cost-effectiveness of the sensor system.
Liang, Hongjing; Zhang, Huaguang; Wang, Zhanshan
2015-11-01
This paper considers output synchronization of discrete-time multi-agent systems with directed communication topologies. The directed communication graph contains a spanning tree and the exosystem as its root. Distributed observer-based consensus protocols are proposed, based on the relative outputs of neighboring agents. A multi-step algorithm is presented to construct the observer-based protocols. In light of the discrete-time algebraic Riccati equation and internal model principle, synchronization problem is completed. At last, numerical simulation is provided to verify the effectiveness of the theoretical results. Copyright © 2015 ISA. Published by Elsevier Ltd. All rights reserved.
NASA Astrophysics Data System (ADS)
Massoud, E. C.; Huisman, J.; Benincà, E.; Bouten, W.; Vrugt, J. A.
2017-12-01
Species abundances in ecological communities can display chaotic non-equilibrium dynamics. A characteristic feature of chaotic systems is that long-term prediction of the system's trajectory is fundamentally impossible. How then should we make predictions for complex multi-species communities? We explore data assimilation (DA) with the Ensemble Kalman Filter (EnKF) to fuse a two-predator-two-prey model with abundance data from a long term experiment of a plankton community which displays chaotic dynamics. The results show that DA improves substantially the predictability and ecological forecast horizon of complex community dynamics. In addition, we show that DA helps provide guidance on measurement design, for instance on defining the frequency of observations. The study presented here is highly innovative, because DA methods at the current stage are almost unknown in ecology.
Rafieerad, A R; Bushroa, A R; Nasiri-Tabrizi, B; Kaboli, S H A; Khanahmadi, S; Amiri, Ahmad; Vadivelu, J; Yusof, F; Basirun, W J; Wasa, K
2017-05-01
Recently, the robust optimization and prediction models have been highly noticed in district of surface engineering and coating techniques to obtain the highest possible output values through least trial and error experiments. Besides, due to necessity of finding the optimum value of dependent variables, the multi-objective metaheuristic models have been proposed to optimize various processes. Herein, oriented mixed oxide nanotubular arrays were grown on Ti-6Al-7Nb (Ti67) implant using physical vapor deposition magnetron sputtering (PVDMS) designed by Taguchi and following electrochemical anodization. The obtained adhesion strength and hardness of Ti67/Nb were modeled by particle swarm optimization (PSO) to predict the outputs performance. According to developed models, multi-objective PSO (MOPSO) run aimed at finding PVDMS inputs to maximize current outputs simultaneously. The provided sputtering parameters were applied as validation experiment and resulted in higher adhesion strength and hardness of interfaced layer with Ti67. The as-deposited Nb layer before and after optimization were anodized in fluoride-base electrolyte for 300min. To crystallize the coatings, the anodically grown mixed oxide TiO 2 -Nb 2 O 5 -Al 2 O 3 nanotubes were annealed at 440°C for 30min. From the FESEM observations, the optimized adhesive Nb interlayer led to further homogeneity of mixed nanotube arrays. As a result of this surface modification, the anodized sample after annealing showed the highest mechanical, tribological, corrosion resistant and in-vitro bioactivity properties, where a thick bone-like apatite layer was formed on the mixed oxide nanotubes surface within 10 days immersion in simulated body fluid (SBF) after applied MOPSO. The novel results of this study can be effective in optimizing a variety of the surface properties of the nanostructured implants. Copyright © 2016 Elsevier Ltd. All rights reserved.
Exploring plenoptic properties of correlation imaging with chaotic light
NASA Astrophysics Data System (ADS)
Pepe, Francesco V.; Vaccarelli, Ornella; Garuccio, Augusto; Scarcelli, Giuliano; D'Angelo, Milena
2017-11-01
In a setup illuminated by chaotic light, we consider different schemes that enable us to perform imaging by measuring second-order intensity correlations. The most relevant feature of the proposed protocols is the ability to perform plenoptic imaging, namely to reconstruct the geometrical path of light propagating in the system, by imaging both the object and the focusing element. This property allows us to encode, in a single data acquisition, both multi-perspective images of the scene and light distribution in different planes between the scene and the focusing element. We unveil the plenoptic property of three different setups, explore their refocusing potentialities and discuss their practical applications.
Proper orthogonal decomposition-based spectral higher-order stochastic estimation
DOE Office of Scientific and Technical Information (OSTI.GOV)
Baars, Woutijn J., E-mail: wbaars@unimelb.edu.au; Tinney, Charles E.
A unique routine, capable of identifying both linear and higher-order coherence in multiple-input/output systems, is presented. The technique combines two well-established methods: Proper Orthogonal Decomposition (POD) and Higher-Order Spectra Analysis. The latter of these is based on known methods for characterizing nonlinear systems by way of Volterra series. In that, both linear and higher-order kernels are formed to quantify the spectral (nonlinear) transfer of energy between the system's input and output. This reduces essentially to spectral Linear Stochastic Estimation when only first-order terms are considered, and is therefore presented in the context of stochastic estimation as spectral Higher-Order Stochastic Estimationmore » (HOSE). The trade-off to seeking higher-order transfer kernels is that the increased complexity restricts the analysis to single-input/output systems. Low-dimensional (POD-based) analysis techniques are inserted to alleviate this void as POD coefficients represent the dynamics of the spatial structures (modes) of a multi-degree-of-freedom system. The mathematical framework behind this POD-based HOSE method is first described. The method is then tested in the context of jet aeroacoustics by modeling acoustically efficient large-scale instabilities as combinations of wave packets. The growth, saturation, and decay of these spatially convecting wave packets are shown to couple both linearly and nonlinearly in the near-field to produce waveforms that propagate acoustically to the far-field for different frequency combinations.« less
MMX-I: data-processing software for multimodal X-ray imaging and tomography.
Bergamaschi, Antoine; Medjoubi, Kadda; Messaoudi, Cédric; Marco, Sergio; Somogyi, Andrea
2016-05-01
A new multi-platform freeware has been developed for the processing and reconstruction of scanning multi-technique X-ray imaging and tomography datasets. The software platform aims to treat different scanning imaging techniques: X-ray fluorescence, phase, absorption and dark field and any of their combinations, thus providing an easy-to-use data processing tool for the X-ray imaging user community. A dedicated data input stream copes with the input and management of large datasets (several hundred GB) collected during a typical multi-technique fast scan at the Nanoscopium beamline and even on a standard PC. To the authors' knowledge, this is the first software tool that aims at treating all of the modalities of scanning multi-technique imaging and tomography experiments.
Coyle, Scott M; Lim, Wendell A
2016-01-14
The Ras-superfamily GTPases are central controllers of cell proliferation and morphology. Ras signaling is mediated by a system of interacting molecules: upstream enzymes (GEF/GAP) regulate Ras's ability to recruit multiple competing downstream effectors. We developed a multiplexed, multi-turnover assay for measuring the dynamic signaling behavior of in vitro reconstituted H-Ras signaling systems. By including both upstream regulators and downstream effectors, we can systematically map how different network configurations shape the dynamic system response. The concentration and identity of both upstream and downstream signaling components strongly impacted the timing, duration, shape, and amplitude of effector outputs. The distorted output of oncogenic alleles of Ras was highly dependent on the balance of positive (GAP) and negative (GEF) regulators in the system. We found that different effectors interpreted the same inputs with distinct output dynamics, enabling a Ras system to encode multiple unique temporal outputs in response to a single input. We also found that different Ras-to-GEF positive feedback mechanisms could reshape output dynamics in distinct ways, such as signal amplification or overshoot minimization. Mapping of the space of output behaviors accessible to Ras provides a design manual for programming Ras circuits, and reveals how these systems are readily adapted to produce an array of dynamic signaling behaviors. Nonetheless, this versatility comes with a trade-off of fragility, as there exist numerous paths to altered signaling behaviors that could cause disease.
A parameter estimation subroutine package
NASA Technical Reports Server (NTRS)
Bierman, G. J.; Nead, M. W.
1978-01-01
Linear least squares estimation and regression analyses continue to play a major role in orbit determination and related areas. A library of FORTRAN subroutines were developed to facilitate analyses of a variety of estimation problems. An easy to use, multi-purpose set of algorithms that are reasonably efficient and which use a minimal amount of computer storage are presented. Subroutine inputs, outputs, usage and listings are given, along with examples of how these routines can be used. The routines are compact and efficient and are far superior to the normal equation and Kalman filter data processing algorithms that are often used for least squares analyses.
High power density dc/dc converter: Component selection and design
NASA Technical Reports Server (NTRS)
Divan, Deepakraj M.
1989-01-01
Further work pertaining to design considerations for the new high power, high frequency dc/dc converters is discussed. The goal of the project is the development of high power, high power density dc/dc converters at power levels in the multi-kilowatt to megawatt range for aerospace applications. The prototype converter is rated for 50 kW at a switching frequency of 50 kHz, with an input voltage of 200 Vdc and an output of 2000 Vdc. The overall power density must be in the vicinity of 0.2 to 0.3 kg/kW.
Multi-frequency klystron designed for high efficiency
DOE Office of Scientific and Technical Information (OSTI.GOV)
Jensen, Aaron
A multi-frequency klystron has an electron gun which generates a beam, a circuit of bunch-align-collect (BAC) tuned cavities that bunch the beam and amplify an RF signal, a collector where the beam is collected and dumped, and a standard output cavity and waveguide coupled to a window to output RF power at a fundamental mode to an external load. In addition, the klystron has additional bunch-align-collect (BAC) cavities tuned to a higher harmonic frequency, and a harmonic output cavity and waveguide coupled via a window to an additional external load.
Time-multiplexed, optically-addressed, gigabit optical crossbar switch
NASA Technical Reports Server (NTRS)
Lang, Robert J. (Inventor); Cheng, Li-Jen (Inventor); Maserjian, Joseph (Inventor)
1994-01-01
A time-multiplexed, optically-addressed, crossbar switch (38) is provided using a two-dimensional, optically-addressed, reflective spatial light modulator (O-SLM) (20). Since the optical addressing is time-multiplexed, only N addressing lines are required for an N.times.N crossbar, rather than the N.sup.2 lines needed in the prior art. This reduction in addressing lines makes possible the development of enormous crossbar switches, such as 100.times.100, for the first time. In addition, since data paths remain entirely in the optics domain, data speeds can reach the multi-gigabit level. In the switch, a row (40) of N inputs (42) at the read wavelength is spread over one axis of the O-SLM. The light is refocused along the other axis to an output array (48) of detectors (50), so that each input has the potential to talk to any one output. The O-SLM is normally off, i.e., non-reflective, so that the output is, in the absence of an input signal, zero. A one-dimensional array (52) of lasers (54) at the write wavelength is imaged onto the O-SLM. Each laser scans across an entire row of the O-SLM; where the laser is on, it turns on a portion of the O-SLM and establishes a connection between a particular input and a particular output. A full row is scanned in a time much shorter than the response time of the O-SLM, so that state of the O-SLM is capacitively stored and dynamically refreshed. The scanning is accomplished by tuning the wavelength of the laser and passing it through a grating, which sweeps the beam in space.
NASA Technical Reports Server (NTRS)
Hein, C.; Meystel, A.
1994-01-01
There are many multi-stage optimization problems that are not easily solved through any known direct method when the stages are coupled. For instance, we have investigated the problem of planning a vehicle's control sequence to negotiate obstacles and reach a goal in minimum time. The vehicle has a known mass, and the controlling forces have finite limits. We have developed a technique that finds admissible control trajectories which tend to minimize the vehicle's transit time through the obstacle field. The immediate applications is that of a space robot which must rapidly traverse around 2-or-3 dimensional structures via application of a rotating thruster or non-rotating on-off for such vehicles is located at the Marshall Space Flight Center in Huntsville Alabama. However, it appears that the development method is applicable to a general set of optimization problems in which the cost function and the multi-dimensional multi-state system can be any nonlinear functions, which are continuous in the operating regions. Other applications included the planning of optimal navigation pathways through a transversability graph; the planning of control input for under-water maneuvering vehicles which have complex control state-space relationships; the planning of control sequences for milling and manufacturing robots; the planning of control and trajectories for automated delivery vehicles; and the optimization and athletic training in slalom sports.
USDA-ARS?s Scientific Manuscript database
Water-saturated column experiments were conducted to investigate the effect of input concentration (Co) and sand grain size on the transport and retention of low concentrations (1, 0.01, and 0.005 mg L/1) of functionalized 14C-labeled multi-walled carbon nanotubes (MWCNT) under repulsive electrostat...
NASA Astrophysics Data System (ADS)
Al-Mansoori, M. H.; Al-Sheriyani, A.; Al-Nassri, S.; Hasoon, F. N.
2017-06-01
In this paper, we demonstrate a multi-wavelength Brillouin-erbium fiber laser (BEFL) with ~33 GHz frequency spacing using cascaded stimulated Brillouin scattering effects in optical fiber. The proposed laser structure exhibits a stable output channel with a tuning range of 19 nm, from 1549 nm to 1568 nm. The number of stable output channels produced is six channels with a triple-Brillouin frequency spacing. The output channels exhibit high output power and high optical signal-to-noise ratios (OSNRs). The laser structure has the potential to be used as a multi-wavelength source for optical communication systems.
NASA Astrophysics Data System (ADS)
Mayvan, Ali D.; Aghaeinia, Hassan; Kazemi, Mohammad
2017-12-01
This paper focuses on robust transceiver design for throughput enhancement on the interference channel (IC), under imperfect channel state information (CSI). In this paper, two algorithms are proposed to improve the throughput of the multi-input multi-output (MIMO) IC. Each transmitter and receiver has, respectively, M and N antennas and IC operates in a time division duplex mode. In the first proposed algorithm, each transceiver adjusts its filter to maximize the expected value of signal-to-interference-plus-noise ratio (SINR). On the other hand, the second algorithm tries to minimize the variances of the SINRs to hedge against the variability due to CSI error. Taylor expansion is exploited to approximate the effect of CSI imperfection on mean and variance. The proposed robust algorithms utilize the reciprocity of wireless networks to optimize the estimated statistical properties in two different working modes. Monte Carlo simulations are employed to investigate sum rate performance of the proposed algorithms and the advantage of incorporating variation minimization into the transceiver design.
The multi-disciplinary design study: A life cycle cost algorithm
NASA Technical Reports Server (NTRS)
Harding, R. R.; Pichi, F. J.
1988-01-01
The approach and results of a Life Cycle Cost (LCC) analysis of the Space Station Solar Dynamic Power Subsystem (SDPS) including gimbal pointing and power output performance are documented. The Multi-Discipline Design Tool (MDDT) computer program developed during the 1986 study has been modified to include the design, performance, and cost algorithms for the SDPS as described. As with the Space Station structural and control subsystems, the LCC of the SDPS can be computed within the MDDT program as a function of the engineering design variables. Two simple examples of MDDT's capability to evaluate cost sensitivity and design based on LCC are included. MDDT was designed to accept NASA's IMAT computer program data as input so that IMAT's detailed structural and controls design capability can be assessed with expected system LCC as computed by MDDT. No changes to IMAT were required. Detailed knowledge of IMAT is not required to perform the LCC analyses as the interface with IMAT is noninteractive.
Multi-sensory integration in a small brain
NASA Astrophysics Data System (ADS)
Gepner, Ruben; Wolk, Jason; Gershow, Marc
Understanding how fluctuating multi-sensory stimuli are integrated and transformed in neural circuits has proved a difficult task. To address this question, we study the sensori-motor transformations happening in the brain of the Drosophila larva, a tractable model system with about 10,000 neurons. Using genetic tools that allow us to manipulate the activity of individual brain cells through their transparent body, we observe the stochastic decisions made by freely-behaving animals as their visual and olfactory environments fluctuate independently. We then use simple linear-nonlinear models to correlate outputs with relevant features in the inputs, and adaptive filtering processes to track changes in these relevant parameters used by the larva's brain to make decisions. We show how these techniques allow us to probe how statistics of stimuli from different sensory modalities combine to affect behavior, and can potentially guide our understanding of how neural circuits are anatomically and functionally integrated. Supported by NIH Grant 1DP2EB022359 and NSF Grant PHY-1455015.
Analysis of airframe/engine interactions in integrated flight and propulsion control
NASA Technical Reports Server (NTRS)
Schierman, John D.; Schmidt, David K.
1991-01-01
An analysis framework for the assessment of dynamic cross-coupling between airframe and engine systems from the perspective of integrated flight/propulsion control is presented. This analysis involves to determining the significance of the interactions with respect to deterioration in stability robustness and performance, as well as critical frequency ranges where problems may occur due to these interactions. The analysis illustrated here investigates both the airframe's effects on the engine control loops and the engine's effects on the airframe control loops in two case studies. The second case study involves a multi-input/multi-output analysis of the airframe. Sensitivity studies are performed on critical interactions to examine the degradations in the system's stability robustness and performance. Magnitudes of the interactions required to cause instabilities, as well as the frequencies at which the instabilities occur are recorded. Finally, the analysis framework is expanded to include control laws which contain cross-feeds between the airframe and engine systems.
MIMO H∞ control of three-axis ship-mounted mobile antenna systems
NASA Astrophysics Data System (ADS)
Kuseyri, İ. Sina
2018-02-01
The need for on-line information in any environment has led to the development of mobile satellite communication terminals. These high data-rate terminals require inertial antenna pointing error tolerance within fractions of a degree. However, the base motion of the antenna platform in mobile applications complicates this pointing problem and must be accounted for. Gimbaled motorised pedestals are used to eliminate the effect of disturbance and maintain uninterrupted communication. In this paper, a three-axis ship-mounted antenna on a pedestal gimbal system is studied. Based on the derived dynamic model of the antenna pedestal multi input-multi output PID and H∞ linear controllers are designed to stabilise the antenna to keep its orientation unaltered towards the satellite while the sea waves disturb the antenna. Simulation results are presented to show the stabilisation performance of the system with the synthesised controllers. It is shown through performance comparison and analysis that the proposed H∞ control structure is preferable over PID controlled system in terms of system stability and the disturbance rejection.
A power-efficient ZF precoding scheme for multi-user indoor visible light communication systems
NASA Astrophysics Data System (ADS)
Zhao, Qiong; Fan, Yangyu; Deng, Lijun; Kang, Bochao
2017-02-01
In this study, we propose a power-efficient ZF precoding scheme for visible light communication (VLC) downlink multi-user multiple-input-single-output (MU-MISO) systems, which incorporates the zero-forcing (ZF) and the characteristics of VLC systems. The main idea of this scheme is that the channel matrix used to perform pseudoinverse comes from the set of optical Access Points (APs) shared by more than one user, instead of the set of all involved serving APs as the existing ZF precoding schemes often used. By doing this, the waste of power, which is caused by the transmission of one user's data in the un-serving APs, can be avoided. In addition, the size of the channel matrix needs to perform pseudoinverse becomes smaller, which helps to reduce the computation complexity. Simulation results in two scenarios show that the proposed ZF precoding scheme has higher power efficiency, better bit error rate (BER) performance and lower computation complexity compared with traditional ZF precoding schemes.
Novel transformation-based response prediction of shear building using interval neural network
NASA Astrophysics Data System (ADS)
Chakraverty, S.; Sahoo, Deepti Moyi
2017-04-01
Present paper uses powerful technique of interval neural network (INN) to simulate and estimate structural response of multi-storey shear buildings subject to earthquake motion. The INN is first trained for a real earthquake data, viz., the ground acceleration as input and the numerically generated responses of different floors of multi-storey buildings as output. Till date, no model exists to handle positive and negative data in the INN. As such here, the bipolar data in [ -1, 1] are converted first to unipolar form, i.e., to [0, 1] by means of a novel transformation for the first time to handle the above training patterns in normalized form. Once the training is done, again the unipolar data are converted back to its bipolar form by using the inverse transformation. The trained INN architecture is then used to simulate and test the structural response of different floors for various intensity earthquake data and it is found that the predicted responses given by INN model are good for practical purposes.
Stereo Sound Field Controller Design Using Partial Model Matching on the Frequency Domain
NASA Astrophysics Data System (ADS)
Kumon, Makoto; Miike, Katsuhiro; Eguchi, Kazuki; Mizumoto, Ikuro; Iwai, Zenta
The objective of sound field control is to make the acoustic characteristics of a listening room close to those of the desired system. Conventional methods apply feedforward controllers, such as digital filters, to achieve this objective. However, feedback controllers are also necessary in order to attenuate noise or to compensate the uncertainty of the acoustic characteristics of the listening room. Since acoustic characteristics are well modeled on the frequency domain, it is efficient to design controllers with respect to frequency responses, but it is difficult to design a multi input multi output (MIMO) control system on a wide frequency domain. In the present study, a partial model matching method on the frequency domain was adopted because this method requires only sampled data, rather than complex mathematical models of the plant, in order to design controllers for MIMO systems. The partial model matching method was applied to design two-degree-of-freedom controllers for acoustic equalization and noise reduction. Experiments demonstrated effectiveness of the proposed method.
Rotorcraft flight control design using quantitative feedback theory and dynamic crossfeeds
NASA Technical Reports Server (NTRS)
Cheng, Rendy P.
1995-01-01
A multi-input, multi-output controls design with robust crossfeeds is presented for a rotorcraft in near-hovering flight using quantitative feedback theory (QFT). Decoupling criteria are developed for dynamic crossfeed design and implementation. Frequency dependent performance metrics focusing on piloted flight are developed and tested on 23 flight configurations. The metrics show that the resulting design is superior to alternative control system designs using conventional fixed-gain crossfeeds and to feedback-only designs which rely on high gains to suppress undesired off-axis responses. The use of dynamic, robust crossfeeds prior to the QFT design reduces the magnitude of required feedback gain and results in performance that meets current handling qualities specifications relative to the decoupling of off-axis responses. The combined effect of the QFT feedback design following the implementation of low-order, dynamic crossfeed compensator successfully decouples ten of twelve off-axis channels. For the other two channels it was not possible to find a single, low-order crossfeed that was effective.
Low-order black-box models for control system design in large power systems
DOE Office of Scientific and Technical Information (OSTI.GOV)
Kamwa, I.; Trudel, G.; Gerin-Lajoie, L.
1996-02-01
The paper studies two multi-input multi-output (MIMO) procedures for the identification of low-order state-space models of power systems, by probing the network in open loop with low-energy pulses or random signals. Although such data may result from actual measurements, the development assumes simulated responses from a transient stability program, hence benefiting from the existing large base of stability models. While pulse data is processed using the eigensystem realization algorithm, the analysis of random responses is done by means of subspace identification methods. On a prototype Hydro-Quebec power system, including SVCs, DC lines, series compensation, and more than 1,100 buses, itmore » is verified that the two approaches are equivalent only when strict requirements are imposed on the pulse length and magnitude. The 10th-order equivalent models derived by random-signal probing allow for effective tuning of decentralized power system stabilizers (PSSs) able to damp both local and very slow inter-area modes.« less
Low-order black-box models for control system design in large power systems
DOE Office of Scientific and Technical Information (OSTI.GOV)
Kamwa, I.; Trudel, G.; Gerin-Lajoie, L.
1995-12-31
The paper studies two multi-input multi-output (MIMO) procedures for the identification of low-order state-space models of power systems, by probing the network in open loop with low-energy pulses or random signals. Although such data may result from actual measurements, the development assumes simulated responses from a transient stability program, hence benefiting form the existing large base of stability models. While pulse data is processed using the eigensystem realization algorithm, the analysis of random responses is done by means of subspace identification methods. On a prototype Hydro-Quebec power system, including SVCs, DC lines, series compensation, and more than 1,100 buses, itmore » is verified that the two approaches are equivalent only when strict requirements are imposed on the pulse length and magnitude. The 10th-order equivalent models derived by random-signal probing allow for effective tuning of decentralized power system stabilizers (PSSs) able to damp both local and very slow inter-area modes.« less
A 12 GHz wavelength spacing multi-wavelength laser source for wireless communication systems
NASA Astrophysics Data System (ADS)
Peng, P. C.; Shiu, R. K.; Bitew, M. A.; Chang, T. L.; Lai, C. H.; Junior, J. I.
2017-08-01
This paper presents a multi-wavelength laser source with 12 GHz wavelength spacing based on a single distributed feedback laser. A light wave generated from the distributed feedback laser is fed into a frequency shifter loop consisting of 50:50 coupler, dual-parallel Mach-Zehnder modulator, optical amplifier, optical filter, and polarization controller. The frequency of the input wavelength is shifted and then re-injected into the frequency shifter loop. By re-injecting the shifted wavelengths multiple times, we have generated 84 optical carriers with 12 GHz wavelength spacing and stable output power. For each channel, two wavelengths are modulated by a wireless data using the phase modulator and transmitted through a 25 km single mode fiber. In contrast to previously developed schemes, the proposed laser source does not incur DC bias drift problem. Moreover, it is a good candidate for radio-over-fiber systems to support multiple users using a single distributed feedback laser.
Generalized Predictive Control of Dynamic Systems with Rigid-Body Modes
NASA Technical Reports Server (NTRS)
Kvaternik, Raymond G.
2013-01-01
Numerical simulations to assess the effectiveness of Generalized Predictive Control (GPC) for active control of dynamic systems having rigid-body modes are presented. GPC is a linear, time-invariant, multi-input/multi-output predictive control method that uses an ARX model to characterize the system and to design the controller. Although the method can accommodate both embedded (implicit) and explicit feedforward paths for incorporation of disturbance effects, only the case of embedded feedforward in which the disturbances are assumed to be unknown is considered here. Results from numerical simulations using mathematical models of both a free-free three-degree-of-freedom mass-spring-dashpot system and the XV-15 tiltrotor research aircraft are presented. In regulation mode operation, which calls for zero system response in the presence of disturbances, the simulations showed reductions of nearly 100%. In tracking mode operations, where the system is commanded to follow a specified path, the GPC controllers produced the desired responses, even in the presence of disturbances.
Band-edge engineering for controlled multi-modal nanolasing in plasmonic superlattices
Wang, Danqing; Yang, Ankun; Wang, Weijia; ...
2017-07-10
Single band-edge states can trap light and function as high-quality optical feedback for microscale lasers and nanolasers. However, access to more than a single band-edge mode for nanolasing has not been possible because of limited cavity designs. Here, we describe how plasmonic superlattices-finite-arrays of nanoparticles (patches) grouped into microscale arrays-can support multiple band-edge modes capable of multi-modal nanolasing at programmed emission wavelengths and with large mode spacings. Different lasing modes show distinct input-output light behaviour and decay dynamics that can be tailored by nanoparticle size. By modelling the superlattice nanolasers with a four-level gain system and a time-domain approach, wemore » reveal that the accumulation of population inversion at plasmonic hot spots can be spatially modulated by the diffractive coupling order of the patches. Furthermore, we show that symmetry-broken superlattices can sustain switchable nanolasing between a single mode and multiple modes.« less
Control advances for achieving the ITER baseline scenario on KSTAR
NASA Astrophysics Data System (ADS)
Eidietis, N. W.; Barr, J.; Hahn, S. H.; Humphreys, D. A.; in, Y. K.; Jeon, Y. M.; Lanctot, M. J.; Mueller, D.; Walker, M. L.
2017-10-01
Control methodologies developed to enable successful production of ITER baseline scenario (IBS) plasmas on the superconducting KSTAR tokamak are presented: decoupled vertical control (DVC), real-time feedforward (rtFF) calculation, and multi-input multi-output (MIMO) X-point control. DVC provides fast vertical control with the in-vessel control coils (IVCC) while sharing slow vertical control with the poloidal field (PF) coils to avoid IVCC saturation. rtFF compensates for inaccuracies in offline PF current feedforward programming, allowing reduction or removal of integral gain (and its detrimental phase lag) from the shape controller. Finally, MIMO X-point control provides accurate positioning of the X-point despite low controllability due to the large distance between coils and plasma. Combined, these techniques enabled achievement of IBS parameters (q95 = 3.2, βN = 2) with a scaled ITER shape on KSTAR. n =2 RMP response displays a strong dependence upon this shaping. Work supported by the US DOE under Award DE-SC0010685 and the KSTAR project.
An alternate protocol to achieve stochastic and deterministic resonances
NASA Astrophysics Data System (ADS)
Tiwari, Ishant; Dave, Darshil; Phogat, Richa; Khera, Neev; Parmananda, P.
2017-10-01
Periodic and Aperiodic Stochastic Resonance (SR) and Deterministic Resonance (DR) are studied in this paper. To check for the ubiquitousness of the phenomena, two unrelated systems, namely, FitzHugh-Nagumo and a particle in a bistable potential well, are studied. Instead of the conventional scenario of noise amplitude (in the case of SR) or chaotic signal amplitude (in the case of DR) variation, a tunable system parameter ("a" in the case of FitzHugh-Nagumo model and the damping coefficient "j" in the bistable model) is regulated. The operating values of these parameters are defined as the "setpoint" of the system throughout the present work. Our results indicate that there exists an optimal value of the setpoint for which maximum information transfer between the input and the output signals takes place. This information transfer from the input sub-threshold signal to the output dynamics is quantified by the normalised cross-correlation coefficient ( | CCC | ). | CCC | as a function of the setpoint exhibits a unimodal variation which is characteristic of SR (or DR). Furthermore, | CCC | is computed for a grid of noise (or chaotic signal) amplitude and setpoint values. The heat map of | CCC | over this grid yields the presence of a resonance region in the noise-setpoint plane for which the maximum enhancement of the input sub-threshold signal is observed. This resonance region could be possibly used to explain how organisms maintain their signal detection efficacy with fluctuating amounts of noise present in their environment. Interestingly, the method of regulating the setpoint without changing the noise amplitude was not able to induce Coherence Resonance (CR). A possible, qualitative reasoning for this is provided.
Taghanaki, Saeid Asgari; Kawahara, Jeremy; Miles, Brandon; Hamarneh, Ghassan
2017-07-01
Feature reduction is an essential stage in computer aided breast cancer diagnosis systems. Multilayer neural networks can be trained to extract relevant features by encoding high-dimensional data into low-dimensional codes. Optimizing traditional auto-encoders works well only if the initial weights are close to a proper solution. They are also trained to only reduce the mean squared reconstruction error (MRE) between the encoder inputs and the decoder outputs, but do not address the classification error. The goal of the current work is to test the hypothesis that extending traditional auto-encoders (which only minimize reconstruction error) to multi-objective optimization for finding Pareto-optimal solutions provides more discriminative features that will improve classification performance when compared to single-objective and other multi-objective approaches (i.e. scalarized and sequential). In this paper, we introduce a novel multi-objective optimization of deep auto-encoder networks, in which the auto-encoder optimizes two objectives: MRE and mean classification error (MCE) for Pareto-optimal solutions, rather than just MRE. These two objectives are optimized simultaneously by a non-dominated sorting genetic algorithm. We tested our method on 949 X-ray mammograms categorized into 12 classes. The results show that the features identified by the proposed algorithm allow a classification accuracy of up to 98.45%, demonstrating favourable accuracy over the results of state-of-the-art methods reported in the literature. We conclude that adding the classification objective to the traditional auto-encoder objective and optimizing for finding Pareto-optimal solutions, using evolutionary multi-objective optimization, results in producing more discriminative features. Copyright © 2017 Elsevier B.V. All rights reserved.
NASA Astrophysics Data System (ADS)
Stefan, V. Alexander
2016-10-01
The ultraviolet photons may control the imbalance of sodium and potassium ions in the brain bioplasma and, consequently, may prove to be efficient in the prevention of epileptic seizures. A novel method is based on the multi-ultraviolet-photon beam interaction with the epilepsy-topion-bioplasma, (nonlinear coupling of an ultra high frequency mode to the brain beta phonons). It is hypothesized that epilepsy is a chaotic-dynamics phenomenon: small electrical changes in the epilepsy-topion-bioplasma lead, (within the 10s of milliseconds), to the onset of chaos, (seizure-excessive electrical discharge), and subsequent cascading into adjacent areas.
Database-driven web interface automating gyrokinetic simulations for validation
NASA Astrophysics Data System (ADS)
Ernst, D. R.
2010-11-01
We are developing a web interface to connect plasma microturbulence simulation codes with experimental data. The website automates the preparation of gyrokinetic simulations utilizing plasma profile and magnetic equilibrium data from TRANSP analysis of experiments, read from MDSPLUS over the internet. This database-driven tool saves user sessions, allowing searches of previous simulations, which can be restored to repeat the same analysis for a new discharge. The website includes a multi-tab, multi-frame, publication quality java plotter Webgraph, developed as part of this project. Input files can be uploaded as templates and edited with context-sensitive help. The website creates inputs for GS2 and GYRO using a well-tested and verified back-end, in use for several years for the GS2 code [D. R. Ernst et al., Phys. Plasmas 11(5) 2637 (2004)]. A centralized web site has the advantage that users receive bug fixes instantaneously, while avoiding the duplicated effort of local compilations. Possible extensions to the database to manage run outputs, toward prototyping for the Fusion Simulation Project, are envisioned. Much of the web development utilized support from the DoE National Undergraduate Fellowship program [e.g., A. Suarez and D. R. Ernst, http://meetings.aps.org/link/BAPS.2005.DPP.GP1.57.
NASA Astrophysics Data System (ADS)
Fang, X. C.; Hu-Guo, Ch.; Ollivier-Henry, N.; Brasse, D.; Hu, Y.
2010-06-01
This paper represents the design of a low-noise, wide band multi-channel readout integrated circuit (IC) used as front end readout electronics of avalanche photo diodes (APD) dedicated to a small animal positron emission tomography (PET) system. The first ten-channel prototype chip (APD-Chip) of the analog parts has been designed and fabricated in a 0.35 μm CMOS process. Every channel of the APD_Chip includes a charge-sensitive preamplifier (CSA), a CR-(RC)2 shaper, and an analog buffer. In a channel, the CSA reads charge signals (10 bits dynamic range) from an APD array having 10 pF of capacitance per pixel. A linearized degenerated differential pair which ensures high linearity in all dynamical range is used as the high feedback resistor for preventing pile up of signals. The designed CSA has the capability of compensating automatically up to 200 nA leakage current from the detector. The CR-(RC)2 shaper filters and shapes the output signal of the CSA. An equivalent input noise charge obtained from test is 275 e -+ 10 e-/pF. In this paper the prototype is presented for both its theoretical analysis and its test results.
Tahmasbi, Vahid; Ghoreishi, Majid; Zolfaghari, Mojtaba
2017-11-01
The bone drilling process is very prominent in orthopedic surgeries and in the repair of bone fractures. It is also very common in dentistry and bone sampling operations. Due to the complexity of bone and the sensitivity of the process, bone drilling is one of the most important and sensitive processes in biomedical engineering. Orthopedic surgeries can be improved using robotic systems and mechatronic tools. The most crucial problem during drilling is an unwanted increase in process temperature (higher than 47 °C), which causes thermal osteonecrosis or cell death and local burning of the bone tissue. Moreover, imposing higher forces to the bone may lead to breaking or cracking and consequently cause serious damage. In this study, a mathematical second-order linear regression model as a function of tool drilling speed, feed rate, tool diameter, and their effective interactions is introduced to predict temperature and force during the bone drilling process. This model can determine the maximum speed of surgery that remains within an acceptable temperature range. Moreover, for the first time, using designed experiments, the bone drilling process was modeled, and the drilling speed, feed rate, and tool diameter were optimized. Then, using response surface methodology and applying a multi-objective optimization, drilling force was minimized to sustain an acceptable temperature range without damaging the bone or the surrounding tissue. In addition, for the first time, Sobol statistical sensitivity analysis is used to ascertain the effect of process input parameters on process temperature and force. The results show that among all effective input parameters, tool rotational speed, feed rate, and tool diameter have the highest influence on process temperature and force, respectively. The behavior of each output parameters with variation in each input parameter is further investigated. Finally, a multi-objective optimization has been performed considering all the aforementioned parameters. This optimization yielded a set of data that can considerably improve orthopedic osteosynthesis outcomes.
NASA Astrophysics Data System (ADS)
Downey, Austin; D'Alessandro, Antonella; Ubertini, Filippo; Laflamme, Simon; Geiger, Randall
2017-06-01
Investigation of multi-functional carbon-based self-sensing structural materials for structural health monitoring applications is a topic of growing interest. These materials are self-sensing in the sense that they can provide measurable electrical outputs corresponding to physical changes such as strain or induced damage. Nevertheless, the development of an appropriate measurement technique for such materials is yet to be achieved, as many results in the literature suggest that these materials exhibit a drift in their output when measured with direct current (DC) methods. In most of the cases, the electrical output is a resistance and the reported drift is an increase in resistance from the time the measurement starts due to material polarization. Alternating current methods seem more appropriate at eliminating the time drift. However, published results show they are not immune to drift. Moreover, the use of multiple impedance measurement devices (LCR meters) does not allow for the simultaneous multi-channel sampling of multi-sectioned self-sensing materials due to signal crosstalk. The capability to simultaneously monitor multiple sections of self-sensing structural materials is needed to deploy these multi-functional materials for structural health monitoring. Here, a biphasic DC measurement approach with a periodic measure/discharge cycle in the form of a square wave sensing current is used to provide consistent, stable resistance measurements for self-sensing structural materials. DC measurements are made during the measurement region of the square wave while material depolarization is obtained during the discharge region of the periodic signal. The proposed technique is experimentally shown to remove the signal drift in a carbon-based self-sensing cementitious material while providing simultaneous multi-channel measurements of a multi-sectioned self-sensing material. The application of the proposed electrical measurement technique appears promising for real-time utilization of self-sensing materials in structural health monitoring.
Zhang, Zhen; Ma, Cheng; Zhu, Rong
2017-08-23
Artificial Neural Networks (ANNs), including Deep Neural Networks (DNNs), have become the state-of-the-art methods in machine learning and achieved amazing success in speech recognition, visual object recognition, and many other domains. There are several hardware platforms for developing accelerated implementation of ANN models. Since Field Programmable Gate Array (FPGA) architectures are flexible and can provide high performance per watt of power consumption, they have drawn a number of applications from scientists. In this paper, we propose a FPGA-based, granularity-variable neuromorphic processor (FBGVNP). The traits of FBGVNP can be summarized as granularity variability, scalability, integrated computing, and addressing ability: first, the number of neurons is variable rather than constant in one core; second, the multi-core network scale can be extended in various forms; third, the neuron addressing and computing processes are executed simultaneously. These make the processor more flexible and better suited for different applications. Moreover, a neural network-based controller is mapped to FBGVNP and applied in a multi-input, multi-output, (MIMO) real-time, temperature-sensing and control system. Experiments validate the effectiveness of the neuromorphic processor. The FBGVNP provides a new scheme for building ANNs, which is flexible, highly energy-efficient, and can be applied in many areas.
Zhang, Zhen; Zhu, Rong
2017-01-01
Artificial Neural Networks (ANNs), including Deep Neural Networks (DNNs), have become the state-of-the-art methods in machine learning and achieved amazing success in speech recognition, visual object recognition, and many other domains. There are several hardware platforms for developing accelerated implementation of ANN models. Since Field Programmable Gate Array (FPGA) architectures are flexible and can provide high performance per watt of power consumption, they have drawn a number of applications from scientists. In this paper, we propose a FPGA-based, granularity-variable neuromorphic processor (FBGVNP). The traits of FBGVNP can be summarized as granularity variability, scalability, integrated computing, and addressing ability: first, the number of neurons is variable rather than constant in one core; second, the multi-core network scale can be extended in various forms; third, the neuron addressing and computing processes are executed simultaneously. These make the processor more flexible and better suited for different applications. Moreover, a neural network-based controller is mapped to FBGVNP and applied in a multi-input, multi-output, (MIMO) real-time, temperature-sensing and control system. Experiments validate the effectiveness of the neuromorphic processor. The FBGVNP provides a new scheme for building ANNs, which is flexible, highly energy-efficient, and can be applied in many areas. PMID:28832522
Billings, Jay Jay; Deyton, Jordan H.; Forest Hull, S.; ...
2015-07-17
Building new fission reactors in the United States presents many technical and regulatory challenges. Chief among the technical challenges is the need to share and present results from new high- fidelity, high- performance simulations in an easily consumable way. In light of the modern multi-scale, multi-physics simulations can generate petabytes of data, this will require the development of new techniques and methods to reduce the data to familiar quantities of interest with a more reasonable resolution and size. Furthermore, some of the results from these simulations may be new quantities for which visualization and analysis techniques are not immediately availablemore » in the community and need to be developed. Our paper describes a new system for managing high-performance simulation results in a domain-specific way that naturally exposes quantities of interest for light water and sodium-cooled fast reactors. It enables easy qualitative and quantitative comparisons between simulation results with a graphical user interface and cross-platform, multi-language input- output libraries for use by developers to work with the data. One example comparing results from two different simulation suites for a single assembly in a light-water reactor is presented along with a detailed discussion of the system s requirements and design.« less
DOE Office of Scientific and Technical Information (OSTI.GOV)
Khawli, Toufik Al; Eppelt, Urs; Hermanns, Torsten
2016-06-08
In production industries, parameter identification, sensitivity analysis and multi-dimensional visualization are vital steps in the planning process for achieving optimal designs and gaining valuable information. Sensitivity analysis and visualization can help in identifying the most-influential parameters and quantify their contribution to the model output, reduce the model complexity, and enhance the understanding of the model behavior. Typically, this requires a large number of simulations, which can be both very expensive and time consuming when the simulation models are numerically complex and the number of parameter inputs increases. There are three main constituent parts in this work. The first part ismore » to substitute the numerical, physical model by an accurate surrogate model, the so-called metamodel. The second part includes a multi-dimensional visualization approach for the visual exploration of metamodels. In the third part, the metamodel is used to provide the two global sensitivity measures: i) the Elementary Effect for screening the parameters, and ii) the variance decomposition method for calculating the Sobol indices that quantify both the main and interaction effects. The application of the proposed approach is illustrated with an industrial application with the goal of optimizing a drilling process using a Gaussian laser beam.« less