A New Gradient Descent Approach for Local Learning of Fuzzy Neural Models

The majority of reported learning methods for Takagi-Sugeno-Kang fuzzy neural models to date mainly focus on the improvement of their accuracy. However, one of the key design requirements in building an interpretable fuzzy model is that each obtained rule consequent must match well with the system local behaviour when all the rules are aggregated to produce the overall system output. This is one of the distinctive characteristics from black-box models such as neural networks. Therefore, how to find a desirable set of fuzzy partitions and, hence, to identify the corresponding consequent models which can be directly explained in terms of system behaviour presents a critical step in fuzzy neural modelling. In this paper, a new learning approach considering both nonlinear parameters in the rule premises and linear parameters in the rule consequents is proposed. Unlike the conventional two-stage optimization procedure widely practised in the field where the two sets of parameters are optimized separately, the consequent parameters are transformed into a dependent set on the premise parameters, thereby enabling the introduction of a new integrated gradient descent learning approach. A new Jacobian matrix is thus proposed and efficiently computed to achieve a more accurate approximation of the cost function by using the second-order Levenberg-Marquardt optimization method. Several other interpretability issues about the fuzzy neural model are also discussed and integrated into this new learning approach. Numerical examples are presented to illustrate the resultant structure of the fuzzy neural models and the effectiveness of the proposed new algorithm, and compared with the results from some well-known methods.

Strong-field photodetachment of H- by few-cycle laser pulses

The recent adiabatic saddle-point method of Shearer et al. [ Phys. Rev. A 84 033409 (2011)] is applied to study strong-field photodetachment of H- by few-cycle linearly polarized laser pulses of frequencies near the two-photon detachment threshold. The behavior of the saddle points in the complex-time plane for a range of laser parameters is explored. A detailed analysis of the influence of laser intensities [(2×1011)–(6.5 × 1011) W/cm2], midinfrared laser wavelengths (1800–2700 nm), and various values of the carrier envelope phase (CEP) on (i) three-dimensional probability detachment distributions, (ii) photoangular distributions (PADs), (iii) energy spectra, and (iv) momentum distributions are presented. Examination of the probability distributions and PADs reveal main lobes and jetlike structures. Bifurcation phenomena in the probability distributions and PADs are also observed as the wavelength and intensity increase. Our simulations show that the (i) probability distributions, (ii) PADs, and (iii) energy spectra are extremely sensitive to the CEP and thus measuring such distributions provides a useful tool for determining this phase. The symmetrical properties of the electron momentum distributions are also found to be strongly correlated with the CEP and this provides an additional robust method for measuring the CEP of a laser pulse. Our calculations further show that for a three-cycle pulse inclusion of all eight saddle points is required in the evaluation of the transition amplitude to yield an accurate description of the photodetachment process. This is in contrast to recent results for a five-cycle pulse.

Feedforward Control of Shape Memory Alloy Actuators Using Fuzzy-Based Inverse Preisach Model

This brief investigates a possible application of the inverse Preisach model in combination with the feedforward and feedback control strategies to control shape memory alloy actuators. In the feedforward control design, a fuzzy-based inverse Preisach model is used to compensate for the hysteresis nonlinearity effect. An extrema input history and a fuzzy inference is utilized to replace the inverse classical Preisach model. This work allows for a reduction in the number of experimental parameters and computation time for the inversion of the classical Preisach model. A proportional-integral-derivative (PID) controller is used as a feedback controller to regulate the error between the desired output and the system output. To demonstrate the effectiveness of the proposed controller, real-time control experiment results are presented.

Position control of shape memory alloy actuators using self tuning fuzzy PID controller

Shape Memory Alloy (SMA) actuators, which have the ability to return to a predetermined shape when heated, have many potential applications such as aeronautics, surgical tools, robotics and so on. Although the conventional PID controller can be used with slow response systems, there has been limited success in precise motion control of SMA actuators, since the systems are disturbed by unknown factors beside their inherent nonlinear hysteresis and changes in the surrounding environment of the systems. This paper presents a new development of a SMA position control system by using a self-tuning fuzzy PID controller. This control algorithm is used by tuning the parameters of the PID controller thereby integrating fuzzy inference and producing a fuzzy adaptive PID controller, which can then be used to improve the control performance of nonlinear systems. The experimental results of position control of SMA actuators using conventional and self-tuning fuzzy PID controllers are both included in this paper.

Internal model control for shape memory alloy actuators using fuzzy based Preisach model

This paper investigates a possible application of Preisach model to control shape memory alloy (SMA) actuators using an internal model control strategy. The developed strategy consists in including the Preisach hysteresis model of SMA actuator and the inverse Preisach model within the control structure. In this work, an extrema input hystory and a fuzzy inference is utilized to replace the classical Preisach model. This allows to reduce a large amount of experimental parameters and computation time of the classical Preisach model. To demonstrate the effectiveness of the proposed controller in improving control performance and hysteresis compensation of SMA actuators, experimental results from real time control are presented.

Trajectory Control of Electro Hydraulic Excavator using Fuzzy Self Tuning Algorithm with Neural Network

This paper presents the trajectory control of a 2DOF mini electro-hydraulic excavator by using fuzzy self tuning with neural network algorithm. First, the mathematical model is derived for the 2DOF mini electro-hydraulic excavator. The fuzzy PID and fuzzy self tuning with neural network are designed for circle trajectory following. Its two links are driven by an electric motor controlled pump system. The experimental results demonstrated that the proposed controllers have better control performance than the conventional controller.

Modelling and Control of Shape Memory Alloy Actuators by using Preisach Model, Genetic Algorithm and Fuzzy Logic

Shapememoryalloy (SMA) actuators, which have the ability to return to a predetermined shape when heated, have many potential applications in aeronautics, surgical tools, robotics and so on. Nonlinearity hysteresis effects existing in SMA actuators present a problem in the motion control of these smart actuators. This paper investigates the control problem of SMA actuators in both simulation and experiment. In the simulation, the numerical Preisachmodel with geometrical interpretation is used for hysteresis modeling of SMA actuators. This model is then incorporated in a closed loop PID control strategy. The optimal values of PID parameters are determined by using geneticalgorithm to minimize the mean squared error between desired output displacement and simulated output. However, the control performance is not good compared with the simulation results when these parameters are applied to the real SMA control since the system is disturbed by unknown factors and changes in the surrounding environment of the system. A further automated readjustment of the PID parameters using fuzzylogic is proposed for compensating the limitation. To demonstrate the effectiveness of the proposed controller, real time control experiment results are presented.

Sequential versus non-sequential double ionization in strong laser fields

<p> The recollision model has been applied to separate the probability for double ionization into contributions from electron-impact ionization and electron-impact excitation for intensities at which the dielectronic interaction is important for generating double ionization. For a wavelength of 780 am, electron-impact excitation dominates just above the threshold intensity for double ionization, approximate to 1.2 x 10(14) W cm(-2), with electron-impact ionization becoming more important for higher intensities. For a wavelength of 390 nm, the ratio between electron-impact ionization and electron-impact excitation remains fairly constant for all intensities above the threshold intensity for double ionization, approximate to 6 x 10(14) W cm(-2). The results point to an explanation of the experimental results, but more detailed calculations on the behaviour of excited He+ ions are required.</p>

Non-competitive phenotypic differences can have a strong effect on ideal free distributions

1. We present a model of the ideal free distribution (IFD) where differences between phenotypes other than those involved in direct competition for resources are considered. We show that these post-acquisitional differences can have a dramatic impact on the predicted distributions of individuals.

2. Specifically, we predict that, when the relative abilities of phenotypes are independent of location, there will be a continuum of mixed evolutionarily stable strategy (ESS) distributions (where all phenotypes are present in all patches).

3, When the relative strengths of the post-acquisitional trait in the two phenotypes differ between patches, however, we predict only a single ESS at equilibrium. Further, this distribution may be fully or partially segregated (with the distribution of at least one phenotype being spatially restricted) but it will never be mixed.

4, Our results for post-acquisitional traits mirror those of Parker (1982) for direct competitive traits. This comparison illustrates that it does not matter whether individual differences are expressed before or after competition for resources, they will still exert considerable influence on the distribution of the individuals concerned.

Strong Coupling and Long-Range Collective Interactions in Optomechanical Arrays

We investigate the collective optomechanics of an ensemble of scatterers inside a Fabry-Pérot resonator and identify an optimized configuration where the ensemble is transmissive, in contrast to the usual reflective optomechanics approach. In this configuration, the optomechanical coupling of a specific collective mechanical mode can be several orders of magnitude larger than the single-element case, and long-range interactions can be generated between the different elements since light permeates throughout the array. This new regime should realistically allow for achieving strong single-photon optomechanical coupling with massive resonators, realizing hybrid quantum interfaces, and exploiting collective long-range interactions in arrays of atoms or mechanical oscillators.

Sulfated zirconia in SBA-15 structures with strong Bronsted acidity as observed by H-1 MAS NMR spectroscopy

In order to prepare high surface area highly acidic catalysts, different weight loadings of ZrO2 were incorporated in the SBA-15 structures which are subsequently sulfated by treating in 0.25 M H2SO4. The catalysts were characterized by means of TEM, XRD, N-2 adsorption, and H-1 MAS NMR. Bronsted type acidities of sulfated zirconia included SBA-15 materials were identified by a sharp H-1 MAS NMR line at 10.6 ppm. The highest acidity was obtained in the 25 mol% ZrO2 included SBA-15 catalyst with a BET surface area of 246 m(2)/g.