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In this paper, we investigate the effectiveness of the method of coupling detection based on phase dynamics modeling in the analysis of the etalon systems whose phase dynamics properties are similar to the properties of the EEG signals from epilepsy patients who are in a coma state. On the example of the etalon model, a method of pre-filtering of signals is proposed, it provides a low level of errors while maintaining high sensitivity of the method. For the test systems, the optimal value of the method parameter and the length of the series are found.

We apply retrospective cost adaptive control (RCAC) to a linearized aircraft dynamics with an unknown transition to nonminimum-phase (NMP) dynamics. In prior work, RCAC was used for command-following with unknown NMP zeros. In this work we extend those results to command following for cases where the dynamics transition from minimum-phase to NMP. We use system identification techniques to identify the NMP zero, and use this information in RCAC. We consider both full-state feedback and output feedback, and in both cases we follow step commands with transitioning dynamics. We first consider the case where RCAC is unaware of the change and NMP zero identification is unavailable to RCAC. We then assume that NMP zero information is available to RCAC from system identification.

Plasma Focus devices are receiving attention in the field of plasma nanotechnology, particularly for the synthesis of nanostructured carbon and carbon thin films, since they are a good source of high energy ionic species. For attaining greater control over the deposition and processing of materials, the appropriate ion energies and ion flux and the control over plasma dynamics need to be achieved to make this process reliable and repeatable. One of the main parameter to achieve this control is the electrode dimensions, operating gas pressure, and gas mixture ratio in plasma focus device. We kept the operating voltages same. For example, to limit the amount of material deposited, it might be necessary to dilute the reactive gaseous environment with inert gases like He, N e or Ar. The dilution/mixture can affect the pinch dynamics inside the plasma focus device. In the present study, we report the use of different diagnostics, such as electrical probes and fast-gated imaging, to understand the pinch and post pinch plasma dynamics under methane gas operation mixed with neon and argon gases. In order to increase the pinch plasma volume for more material synthesis the experiments were also performed with modified plasma focus device with larger diameter anode. Elongated and larger volume pinch plasma column together with multiple pinches during later half-cycles of current discharge were obtained. These results will be discussed in detail during the conference.

We consider control of a dual rigid-body space-craft consisting of a bus and an appendage connected by a compliant joint. Thrust actuators are located on the spacecraft bus, and performance measurements are obtained from sensors on the appendage. This problem is challenging due to the flexibility of the joint and the noncolocation between the actuation and the performance variable. The goal is to motivate and investigate the challenges arising in control of nonminimum-phase (NMP) systems with rigid- and flexible-body dynamics. Exact equations of motion are derived for the spacecraft, and the invariant zeros of the linearized model are determined. This paper investigates the robustness of an adaptive control law to variations in the mass and inertia matrices of the bus and appendage as well as the geometry and joint stiffness. The adaptive controller uses no knowledge of the NMP dynamics.

In this paper we present experimental results of a multivariable linear predictive control strategy applied to a coupled, non-minimum phase dynamics system of six coupled water tanks with 3 controlled water levels (cm) and 3 manipulated pump outputs (V). The setup can be considered as three interacting sub-systems, with coupled dynamics due to the specific water flow directions. The experimental results indicate that the proposed strategy is robust to significant modelling errors, while maintaining good performance.

Adaptive control of a two-dimensional model of a flexible spacecraft with noncolocated sensors and actuators is achieved by output feedback using knowledge of only the system's impulse response. The model is composed of two planar rigid bodies linked by a torsional spring that emulates a multibody spacecraft with base body actuation and appendage pointing. Retrospective cost adaptive control is applied to a command-following problem. The controller uses a finite impulse response filter built from the Markov parameters of the nonminimum-phase (NMP) linearized model. Accordingly, this filter is constructed to contain an estimate of the location of the NMP zero; the filter's order is chosen to correspond to the number of time steps after which the plant's step response becomes positive.

This paper deals with output synchronization problem in nonlinear multi-agent systems. The main contribution of the paper is to guarantee output synchronization in the network while the dynamics of agents exhibit non-minimum phase behavior. To achieve this goal, a control signal is presented for each agent consisting of two terms. The first term is a linear function of each agent states employed in order to overcome the non-minimum phase dynamics of the multi-agent system, whereas the second term is a function of the output of neighboring agents which provides coupling among agents and guarantees output synchronization in the network. A numerical example is presented to verify the effectiveness of the proposed approach.

In this paper a new approach for studying slow transients, such as electromechanical transients, using three phase models of power systems is presented. Typically programs used for studying slow transients assume a positive sequence network model, limiting their application to the study of balanced power systems. While electromagnetic simulation software can be used for studying slow transients in unbalanced networks, their application to large systems can be resource and time intensive. The approach presented here overcomes the aforementioned limitations of existing software and provides a means for studying slow transients using complete three phase models of the electric network. Of the many potential applications of the approach presented, evaluating the impact of Distributed Generation (DG), such as rooftop solar photovoltaic (PV) based DG, on the stability of the electric grid is important particularly for utilities with high penetration of DG.

This paper investigates four control architectures that use adaptive control to follow step, ramp, and harmonic roll-angle commands for a linearized aircraft model with an unknown transition from minimum-phase to nonminimum-phase (NMP) dynamics. In particular, we consider retrospective cost adaptive control (RCAC) with 1) a command-feedforward control architecture; 2) an output-feedback control architecture; 3) a centralized control architecture that uses both command feedforward and output feedback; and 4) a decentralized control architecture that uses both command feedforward and output feedback. For baseline tests, we assume that the location of the NMP zero is known. The goal of this work is to improve the transient response and rate of convergence. Numerical testing shows that RCAC with the decentralized control architecture using command feedforward and output feedback gives the fastest convergence. Furthermore, resetting controller coefficients at the start of the transition improves the transient response.

Accounting for spectral hole burning (SHB), carrier heating (CH), carrier density modulation and longitudinal nonuniformity, ultrafast phase dynamics in bulk semiconductor optical amplifiers (SOAs) is numerically studied for different pump and probe wavelengths. We find that the contributions of SHB and CH to ultrafast phase dynamics are different in strength and change direction for different bands. Furthermore, we demonstrate that the phase dynamic range, phase recovery overshoot and phase partial recovery time depend on the probe and pump spectral positions.

Summary form only given. Nonlinear delay dynamical systems have found several fundamental and applied issues in Optics, since delays from time of flight of the light becomes easily important, even with a few cm of fibers, compared to fast or even ultra-fast photonic response times. Fiber pigtailed modern Telecom devices can thus provide easy system design strategies to build well-controlled high complexity nonlinear delay dynamics. Recently in that context, electro-optic phase modulation, combined with an imbalanced Mach-Zehnder DPSK demodulator providing a temporally nonlocal nonlinear phase-to-intensity conversion, together with a delayed optoelectronic feedback loop, was proposed as an efficient optical chaos generator for demonstrating 10 Gb/s optical chaos communications.

Ultrafast spectroscopy of quantum dot semiconductor optical amplifiers (SOAs) provides valuable information about the potential of these devices for emerging applications such as multi-wavelength regeneration while giving insight on their unique carrier dynamics. Pump-probe spectroscopy was used to analyse the carrier dynamics in InAs/GaAs quantum dot amplifiers. We have developed a ldquotwo-colourrdquo experimental configuration that allows us to pump and probe different parts of the amplified spontaneous emission spectrum and develop a detailed picture of the relevant carrier processes in both absorption and gain regimes of QD-SOAs. The study has revealed that hole recovery and intradot electron relaxation occur on a picosecond timescale, while the electron capture time is on the order of 10 ps. The relaxation of the wetting layer carrier density was shown to have a strong effect on the phase dynamics of both ground and excited state transients, while having a much weaker effect on the gain dynamics. Such behaviour is strongly encouraging for reduced pattern effect operation in high speed optical networks.

Towards hardware implementation of real-time visual image processing, we propose a piecewise linear (PWL) approximation of a coupled region-based Markov Random Field (MRF) model with hidden phase variables for coarse image region segmentation. We introduce PWL functions into update equations of the region-based model, in order to make it easy to control parameters that determine the balance between image segmentation and smoothing, as well as to make it efficient for hardware implementation. We can tune filtering properties of our model by controlling the parameters of the PWL functions in applications to a task of coarse image region segmentation. Finally, we demonstrate that closed regions in input images can be represented by phase variables in multi-scale.

We discuss CNNs in which the states are defined by the electrical phase of a dynamic physical process, such as electron tunneling in ultra-small junctions or integrate-and-fire processes in nanoscale structures or molecules. Such processes produce impulsive "neuron-like" waveforms which can be coupled to nearest neighbors in a 1D, 2D, or 3D array. Input data can be represented by the distribution of dc bias level, initial charge, or coupling strength within the array. Information processing can be realized through the nonlinear dynamics produced by interactions between elements, which give rise to an evolution of complex patterns in the phase-state. In this paper, we discuss information processing for a model physical system based on Coulomb blockade in a 2D array of ultra-small tunnel junctions.

Using sonograms and phase retrieval we experimentally investigate the pattern dependence of the amplitude and phase dynamics, the linewidth enhancement factor, and the chirp of a data-modulated 1.55 /spl mu/m vertical-cavity surface-emitting laser (VCSEL).

Optical chaos communications met intensive research efforts during the last 10 years [1,2], resulting in 2004 in a field experiment in the metropolitan optical network of Athens [3]. Current efforts are now concentrating on device oriented architectures, in order to improve reliability, efficiency, and security. Among the few competitive approaches developed in the literature, the electro-optic one showed first its strong potential in terms of bit rate and decoding quality [4]. However, it was suffering from a few drawbacks in terms of technological complexity, due to the intensity superposition condition required by the mixing between the binary intensity message and the chaotic optical intensity carrier.

Summary form only given. Experimental and theoretical studies of intensity and phase dynamics of spatially coupled lasers have produced interesting results. The investigation of these particular nonlinear oscillators in various well-controlled spatial arrangements gives closer insight into the relations between symmetry and dynamics. The experimental systems we consider consist of two or three coupled lasers in one semi-monolithic Nd:YVO/sub 4/ microchip resonator, generated by pump beams delivered through a 2D arrangement of single-mode optical fibers.

This paper measures sub-10 ps dynamics and magnitudes of gain and phase changes in InAs/GaAs quantum dots semiconductor optical amplifiers (SOA), Also this paper investigates the devices' suitability for different signal processing schemes. It is found that the pump-induced gain saturation dominates over nonlinear phase shifts, and is is inferred that QD SOAs are especially useful in signal processing schemes that exploit gain effects only.

We use femtosecond electron diffraction to capture the disordering of the solid and the emergence of liquid structure during strongly-driven laser melting. We discuss the impact of femtosecond pulse propagation on bright electron source design.

Already several years ago [3], it was suggested that a laser with optical injection can respond to external perturbations by emitting spikes if the perturbation overcomes a certain threshold, all the spikes being identical to each other, in complete analogy with the behaviour of the simple theta-model neuron [1]. The underlying explanation of this phenomenon lies in the isomorphism between a model of neuron [1] and that of an over-damped oscillator with periodic forcing (often called the Adler equation [2]). The control of these spikes was only achieved recently [5], while their observation goes back to [4]. Although there is an excellent agreement between these observations and the predictions of the reduction to pure phase dynamics of a laser model [3], it was soon noticed that whenever the pure phase dynamics reduction ceases to be valid, more complex dynamical phenomena can take place, leading to multipulse excitability [6]. This has led to the investigation of the behaviour of a semiconductor laser locked to an external forcing in response to external perturbations beyond the simple case of the Adler-like mode. We observe resonator features of the neuron-like system and multi-spike responses. Beyond improving the understanding of the neuron-like excitable dynamics of the laser with injected signal, our aim is to leverage the multipulse excitability and the resonator features of the optical neuron analogue for optical data processing and to provide possible insight about complex solitons interactions in forced oscillatory media [7, 8].

This paper introduces an extension of the Internal Model Control algorithm for efficient disturbance rejection. The approach is based on ideas from model based predictive control and diophantine equation derivation. As an illustration of the power of the extension, an example from the process industry is borrowed, namely a drum boiler. The process is challenging for control since it has an integrator and non-minimum phase dynamics. The performance of the proposed extension is compared against nominal IMC design and PID. The simulation results suggest that the proposed algorithm outperforms the other implementations in terms of effective disturbance rejections.

In this paper, we propose a framework for generating coordinated periodic movements of robotic systems with external inputs. We developed an adaptive pattern generator model that is composed of a two-factor observation model with a style parameter and phase dynamics with a phase variable. The style parameter controls the spatial patterns of the generated trajectories, and the phase variable controls its temporal profiles. To validate the effectiveness of our proposed method, we applied it to a simulated humanoid model to perform biped walking behaviors coordinated with observed walking patterns and the environment. The robot successfully performed stable biped walking behaviors even when the style of the observed walking pattern and the period were suddenly changed.

In this paper a control configuration for inverse-response processes is presented. It results in a Smith-type predictor scheme that aims to put the non-minimum phase dynamics out of the feedback loop. The design is carried out analytically by solving an H ∞ weighted optimization problem assuming a second order stable process with one positive zero. The performance of the proposed control configuration is compared by simulation with two different approaches to show its applicability.

This work concerns output trajectory tracking for the McDonnell Dougglas YAV68B Harrier VSTOL aircraft. This system can perform three distinct flight modes, and is modelled with a Lagrangian nonlinear hybrid non-minimum phase dynamics. Output tracking is solved using classical input/output linearization scheme associated to an internal dynamics stable inversion for each flight mode dynamics. The performance of the global switched control law is discussed and validated through simulation tests.

A phased-array two-dimensional CPLL array is introduced. The phase dynamics are analyzed and an approximate solution are obtained using the method of continuum phase. By detuning the free-running frequencies of edge elements, linear phase distribution can be achieved among the array. An experimental CPLL array circuit is also shown and tested, proceedings.

Large profile, high price, low efficiency in realization prevent phased array from being broadly used in automobile radar and communication systems, though phased array has high performance. The article puts forward a new kind of shifterless phased array based on coupled oscillators. The article studies the dynamics of nearest-neighbor coupled oscillators after reviewing the principles of electrical beam-scanning. According to the need of beam-scanning the desired solutions of phase dynamics are established. From that, we determine how the accessible parameters of coupled oscillators can be adjusted. The article also determines conditions under which those solutions are stable, i.e., physically realizable. Computer simulations are used to testify the usefulness of the method. Then in the last part of the article a complete transmit-receive scheme for vehicle radar and communication systems is given out.

New formulations of active vibration isolation problems for multiple degree-of-freedom (DOF) systems are presented. A position-tracking approach via partial emulation is proposed to take advantage of the natural dynamics of a particular type of actuator: the electrohydraulic actuator. A specific 2DOF system with nonminimum phase dynamics and a noncollocated sensor and actuator pair is chosen to implement this position-tracking approach. Experimental results demonstrate good vibration isolation performance.

Coding for the additive white Gaussian noise (AWGN) channel that also introduces an unknown carrier phase rotation is considered in this work. A simple model that captures the phase dynamics is one, where the unknown carrier phase is considered constant over a block of N symbols, and independent from block to block. In this work, LDPC codes in conjunction with pilot symbols are considered. In particular, a single pilot symbol of specified power is inserted in the beginning of each block of length N, in order to aid the joint estimation and decoding process. As expected, the presence of a pilot symbol implies an inevitable loss in the transmitted power, resulting in a trade-off between the power allocated between the pilots and the coded bits, and the quality of the joint estimation and decoding process.

Gain and phase dynamics induced by ultra-short pulse in semiconductor optical amplifiers operating in counter-propagating scheme are numerically investigated by employing a field propagation model. The numerical model accounts for the carrier depletion, carrier heating, spectral hole burning and gain dispersion. Propagating schemes have significant influences on gain and phase dynamics, especially for the ultrafast dynamics. Compared to the co-propagating, the counter-propagating causes reduced ultrafast dynamics in gain and phase dynamics. Relatively slow saturation processes in gain dynamics are observed. Analysis results show the drive currents and active lengths of semiconductor optical amplifiers are the main factors influencing the slow saturation processes.

The physics of quantum dot based optical devices has been studied intensively due to their interesting blend of atomic and solid state properties. Recently, attention has been focused on their absorption properties and has led to QD materials finding favour in such applications as monolithic mode-locked lasers, electro-absorption modulators and saturable absorber mirrors. In this study we perform a detailed experimental investigation of the ultrafast absorption and phase dynamics of a QD InAs/GaAs structure under reverse bias conditions using single colour pump-probe measurements. Experimental results reveal the fundamental timescales and underlying dynamical processes occurring in such absorbers. We will also consider the impact of the observed absorption and phase dynamics on some current applications of QD absorbers.

Graph coloring is a NP-hard problem, and computing the solution on a digital computer entails an exponential increase in the computing resources (time, memory) with increasing problem size. This has motivated the search for alternate and more efficient non-Boolean approaches. Here, we experimentally demonstrate the solution to this problem using the phase dynamics of coupled oscillators. Using a 30-oscillator IC platform with reconfigurable all-to-all coupling and minimal post-processing, our approach achieves 98% accuracy in detecting (near-) optimal solutions within 1 color of the optimal solution in comparison to the 77% accuracy achieved with the heuristic Johnson algorithm. Additionally, we propose a new local search-based post-processing scheme to improve the quality of the coloring solution. Finally, using circuit simulations, we demonstrate the scalability and speed up (~ 100×) achievable with the above approach in larger graphs.

Contact detection is an important topic in contemporary humanoid robotic research. Up to date control and state estimation schemes readily assume that feet contact status is known in advance. In this work, we elaborate on a broader question: in which gait phase is the robot currently in? We introduce an unsupervised learning framework for gait phase estimation based solely on proprioceptive sensing, namely joint encoder, inertial measurement unit and force/torque data. Initially, a meaningful physical explanation on data acquisition is presented. Subsequently, dimensionality reduction is performed to obtain a compact low-dimensional feature representation followed by clustering into three groups, one for each gait phase. The proposed framework is qualitatively and quantitatively assessed in simulation with ground-truth data of uneven/rough terrain walking gaits and insights about the latent gait phase dynamics are drawn. Additionally, its efficacy and robustness is demonstrated when incorporated in leg odometry computation. Since our implementation is based on sensing that is commonly available on humanoids today, we release an open-source ROS/Python package to reinforce further research endeavors.

The introduction of the unencrypted global positioning system (GPS) L2 civil (L2C) signal has the potential to improve measurements made with the L2 frequency, an important observable in GPS-based ionospheric research and monitoring. Recent work has shown significant differences between the legacy L2P(Y) and L2C-derived total electron content rate of change index (ROTI). This difference is observed between L2P(Y) and L2C-derived ROTI with certain receiver models and between zero-baseline receiver pairs. We discuss the likely cause for these differences: L1-aided tracking used to track both the L2P(Y) and L2C signals. We also present L2C data that are confirmed to be from tracking independent of L1. Using the ionospheric-free linear combination, we show that the independently tracked carrier phase dynamics are significantly more accurate than the L1-aided observables. This result is confirmed by comparing the behavior of the L2C and L2P(Y) carrier phase observables upon a sudden antenna rotation.

In this work, experimental study of chaotic synchronization of a semiconductor lasers is presented. An external optical feedback (OF) is used to reach the anti-phase chaotic synchronization among the orthogonal polarization modes of vertical cavity surface emitting laser (VCSEL). The high levels of (OF) achieve good anti-phase synchronization dynamic of the chaotic signal with zero time delay between the polarization dynamic of the VCSEL. For the (OF) levels of 101 μW and 150 μW we have observed good matching signal of the anti-phase dynamics among VCSEL's polarization modes. While low (OF) levels play less important role in this phenomenon. No synchronization among the orthogonal polarization signals obtained for the range of 1 μW to 53μW of (OF). Such property makes VCSELs attractive for applications; such as chaos based secure optical communications and random number generation.

Wide deployment of sensing and actuation capabilities in the electric power grid, along with changing dynamical characteristics, are necessitating analysis of power-system swing dynamics from an input-output perspective. In this article, the input-output properties of the swing dynamics, including the finite and infinite zeros, are characterized from a dynamical-networks perspective. Specifically, an explicit algebraic characterization is given for a matrix whose eigenvalues are the zeros, and in turn structural and graph-theoretic conditions for the absence and presence of nonminimum phase dynamics are developed. Based on these structural results and also an illustrative example, it is demonstrated that the zeros of the swing dynamics are important for analyzing transients and oscillations in the power transmission network, using reduced-order models, and designing controls.

This paper proposes an optimized continuous non-singular terminal sliding mode (NTSM) control scheme for a class of two-link flexible manipulators with uncertain model parameters. Firstly the original system is transformed into the controllable minimum phase system using output redefinition with purpose to change its non-minimum phase dynamics and the corresponding input-output subsystem and zero dynamic subsystem can be obtained. Then a novel continuous NTSM controller by combining NTSM and high order sliding mode (HOSM) on the basis of relative degree and a genetic algorithm is designed to obtain its optimal control performances, respectively. Simulation results illustrate the correctness of the proposed scheme.

In this paper we examine the amplitude and phase dynamics of power-electronic inverters in islanded microgrids that are controlled to emulate the dynamics of a class of weakly nonlinear Lienard-type oscillators. The general strategy of controlling inverters to emulate the behavior of Lienard-type oscillators is termed Virtual Oscillator Control (VOC), and it presents a compelling time-domain alternative to ubiquitous droop control methods which linearly trade off voltage frequencies and magnitudes with active and reactive power injections. In comparison to droop control, which assumes a priori that the network operates in a quasi-stationary sinusoidal steady state, VOC is a time-domain control strategy that globally stabilizes a desired sinusoidal steady state. The main, and somewhat surprising, result of this paper is that—when reduced to the sinusoidal steady state—the VOC dynamics correspond to those of droop control. Hence, VOC is a globally stabilizing control strategy that can deal with higher-order harmonics and includes droop control in the harmonic steady state. The results are intriguing, in that they suggest that droop control laws can be recovered from averaging the complex dynamics of a class of weakly nonlinear limit-cycle oscillators.

This paper presents a control approach for a single switch inverter. The inverter exhibits non-minimum phase behavior in some of the operating modes. A dual feedforward controller was employed with an adaptive PI controller to obtain perfect tracking performance. The controller successfully isolates the non-minimum phase part of the system from the minimum phase. Both separated minimum phase and non-minimum phase sub-systems were used in the dual feedforward scheme to generate desired references. The non-minimum phase dynamics are transformed to minimum phase by using an inverse system transfer function as parallel compensator. The adaptive PI controller was used to track the voltage references.

The nonlinear dynamics of semiconductor optical amplifiers (SOAs) are investigated. We focus on the nonlinear gain, phase and chirp dynamics that can be used for high speed all-optical switching. Ultrafast component in the phase dynamics is observed. We explain this phenomenon by using a numerical model that includes the impact of sub-picosecond intra-band effects in the SOA. In addition, we also investigate the chirp properties, and analyze the influences of chirp dynamics upon the detuned-filtering-based optical switches that can realize more than 160 Gbit/s operating speed. The results are useful for SOA-based high speed all-optical switching in photonic networks.

A systematic geometric design methodology to generate a stable controller for simultaneous local and remote attenuation that was previously proposed is experimentally validated on a structure. The local control path transfer function for this experimental system is non-minimum phase due to which the original broadband controller design would yield an unstable controller. Here a modified procedure for systems with local non-minimum phase dynamics is used to generate a stable controller. According to this method, reduction in vibration at local and remote points on a structure can be parameterised in terms of the available design freedom and a controller is realised in terms of the optimal selection of this using the minimum phase counterpart of the local control path transfer function. The modified method results in a controller that is both stable and stabilizing and which achieves the desired vibration attenuation at the local and remote points on the structure. An experimental facility that replicates the vibration transmission through the shaft of a propeller blade rig system is used to demonstrate the method. Vibration for excitation near the first bending mode frequency of the resonating part of this structure is attenuated at the non-resonating part of the system without deteriorating vibration at the resonating end.

This paper examines the issues involved in controlling an air-breathing hypersonic vehicle (characterized by their unstable, non-minimum phase dynamics) in the presence of significant modeling uncertainty and nonlinearities (control saturations). Modeling of the vehicle exhaust (plume) is complicated, often requiring computational fluid dynamic (CFD) simulations to capture all relevant effects. The focus of this paper is on obtaining a control law that maintains the vehicle trajectory within an acceptable tube while enforcing control constraints in the presence of modeling uncertainty. A robust domain of attraction based approach is used to generate/validate a feasible tube. The computational aspects of such an approach is examined, and the benefits of a decentralized control technique is considered. This approach is compared with other techniques such as linear matrix inequalities based controller design. These approaches are applied to a command following scenario in order to illustrate the performance of the proposed approach.

In a probability learning task, participants estimate the probabilistic reward contingencies, and this task has been used extensively to study instrumental conditioning with partial reinforcement. In the probabilistic reversal learning task, the probabilistic reward contingencies are reversed between options in the middle of the experiment to measure how well people adapt to new contingency situations. In this work, we used the attention-gated reinforcement learning (AGREL) model (Roelfsema & Van Ooyen, 2005) to simulate how people learn the probabilistic relationship between stimulus-reward pairs in probability and reversal learning tasks. AGREL algorithm put forward two important aspects of a learning phenomenon together in a neural network scheme: (1) the effect of unexpected outcomes on learning and (2) the effect of top-down (selective) attention on updating weights. Contrary to its importance in the learning literature, AGREL has not yet been tested with these well known learning tasks. The results of the first simulation showed that in a binary choice probability learning experiment an AGREL model can simulate different learning strategies, such as probability matching and maximizing. Secondly, we simulated a probabilistic reversal learning experiment with the same AGREL model, and the results showed that the AGREL model dynamically adapted to new contingency situations. Furthermore, we also evaluated effects of learning rate on the model's adaption to reversal contingency by plotting the inter-phase dynamics. These results showed that AGREL model simulates the traditional findings observed in probability and reversal learning experiments, and it can be further developed to understand the role of dopamine in learning and it can be used in model-based fMRI research.

This paper examines the use of output feedback to stabilize a planar vertical take-off and landing (PVTOL) aircraft in a finite time. The control of such PVTOL aircraft is already challenging due to the nonlinear cross-coupling between the aircraft axes and the issue of non-minimum phase dynamics. The results from this paper explore the control of the PVTOL aircraft model when there is the added design challenge of limited state information about the dynamics of the aircraft. A state feedback controller is designed by employing the use of a finite-time convergent control law. We then derive a finite-time observer such that the unknown states can be recovered in finite time and thus reducing the output feedback stabilization problem to the state feedback one. The finite-time observer proposed in this paper is unique due to the fact that the observer has two convergence modes to guarantee faster convergence rate for both small or large state errors.

The paper studies the phase coding in the neural networks composed of neural oscillator populations through the theory of the stochastic phase dynamics under the presence of inhibitory neurons, builds a stochastic nonlinear phase dynamic model subject to coupling action of inhibitory neurons, and numerically analyses the process of dynamic evolution and spontaneous behavior under the condition of simulation according to the model. The results prove that inhibitory neurons can reduce the amplitude of the average number density in excitatory neural oscillator population, and trend of the synchronization motion of excitatory neural oscillator population can be controlled through increasing coupling coefficient of inhibitory neurons. Firing density of population of neural oscillator and evolution of average number density is studied through variety of the stimulation intensity.

In this paper, we examine the control of a scramjet-powered hypersonic vehicle with significant aero-elastic-propulsion interactions. Such vehicles are characterized by open loop unstable non-minimum phase dynamics, low frequency aero-elastic modes, significant coupling, and hard constraints (e.g. control surface deflection limits, thrust margin). Within this paper, attention is placed on maintaining acceptable closed loop performance (i.e. tracking of speed and flight path angle commands) while satisfying hard control surface deflection constraints as well as stoichiometrically normalized fuel-equivalency-ratio (FER) margin constraints. Control surface constraints are a consequence of maximum permissible aerodynamic loading. FER margin constraints are a consequence of thermal choking (i.e. unity combustor exit Mach number) and the fact that thrust loss may not be captured for FER greater than unity. Such limits are particularly important since the vehicle is open loop unstable and “saturation” can result in instability. To address these issues, one can design conservative (i.e. less aggressive or lower bandwidth) controllers that maintain operation below saturation levels for anticipated reference commands (and disturbances). Doing so, however, unnecessarily sacrifices performance - particularly when small reference commands are issued. Within this paper, the above issues are addressed using generalized predictive control (GPC). A 3DOF longitudinal model for a generic hypersonic vehicle, which includes aero-elastic-propulsion interactions, is used to illustrate the ideas.

Wind turbulence causes abrupt variation in the power generation and delivery to the grid in the wind energy conversion systems. Most of the system parameters like tip-speed ratio, shaft dampness and dc-link voltage vary during the operation of the variable speed wind turbine drive system at different values of wind velocity. The wind speed turbulence excites the low frequency spectrum of the system. This paper presents analysis on the plant dynamics aspects at low frequencies and control of a wind turbine system operating in variable speed mode using back-to-back converter. The non-minimum phase dynamics of the system is discussed. The dc-link voltage tracking is analyzed.

Currently existing brain-computer interfaces (BCIs) extract feature vectors derived from amplitude information. However, they were not use the rich phase dynamics in the EEG. Phase synchronization was opposed to use for classification of motor imagery. In suitable time window, the electrodes of C3, C4 and central regions to match were selected and then Hilbert transform signal processing method was used for extracting the degree of phase synchronization between two electroencephalogram (EEC) signals by calculating the so-called phase locking value (PLV). The support vector machine (SVM) was used for classification of the motor imagery by a feature selection algorithm. It shows that the satisfactory results are obtained with single-trial accuracies of 92.5% and that synchronization differences between motor imagery depends upon frequency selection , length of data and electrode selection .

A new method of beam scanning via coupled phase locked loops (PLLs) is presented. The steady-state of phase dynamics equation and phase noise of coupled PLLs are analyzed. By detuning the free-running frequency of the edge oscillators, linear phase distributions across the one-dimensional PLLs array can be achieved. This coupled PLLs phase array can be used for phase-shifterless beam scanning. A S-band one- dimensional experimental array is presented, giving a measured phase progression among the array.