Experimental investigation on adaptive robust controller designs applied to a free-floating space manipulator

This paper aims to formulate and investigate the application of various nonlinear H(infinity) control methods to a fiee-floating space manipulator subject to parametric uncertainties and external disturbances. From a tutorial perspective, a model-based approach and adaptive procedures based on linear parametrization, neural networks and fuzzy systems are covered by this work. A comparative study is conducted based on experimental implementations performed with an actual underactuated fixed-base planar manipulator which is, following the DEM concept, dynamically equivalent to a free-floating space manipulator. (C) 2011 Elsevier Ltd. All rights reserved.

Robust Control of Flight Simulator Motion Base

The purpose of this study is to apply robust inverse dynamics control for a six-degree-of-freedom flight simulator motion system. From an implementation viewpoint, simplification of the inverse dynamics control law is introduced by assuming control law matrices as constants. The robust control strategy is applied in the outer loop of the inverse dynamic control to counteract the effects of imperfect compensation due this simplification. The control strategy is designed using the Lyapunov stability theory. Forward and inverse kinematics and a full dynamic model of a six-degree-of-freedom motion base driven by electromechanical actuators are briefly presented. A describing function, acceleration step response and some maneuvers computed from the washout filter were used to evaluate the performance of the controllers.

Robust model predictive controller with output feedback and target tracking

A model predictive controller (MPC) is proposed, which is robustly stable for some classes of model uncertainty and to unknown disturbances. It is considered as the case of open-loop stable systems, where only the inputs and controlled outputs are measured. It is assumed that the controller will work in a scenario where target tracking is also required. Here, it is extended to the nominal infinite horizon MPC with output feedback. The method considers an extended cost function that can be made globally convergent for any finite input horizon considered for the uncertain system. The method is based on the explicit inclusion of cost contracting constraints in the control problem. The controller considers the output feedback case through a non-minimal state-space model that is built using past output measurements and past input increments. The application of the robust output feedback MPC is illustrated through the simulation of a low-order multivariable system.

Robust model predictive control with zone control

Model predictive control (MPC) is usually implemented as a control strategy where the system outputs are controlled within specified zones, instead of fixed set points. One strategy to implement the zone control is by means of the selection of different weights for the output error in the control cost function. A disadvantage of this approach is that closed-loop stability cannot be guaranteed, as a different linear controller may be activated at each time step. A way to implement a stable zone control is by means of the use of an infinite horizon cost in which the set point is an additional variable of the control problem. In this case, the set point is restricted to remain inside the output zone and an appropriate output slack variable is included in the optimisation problem to assure the recursive feasibility of the control optimisation problem. Following this approach, a robust MPC is developed for the case of multi-model uncertainty of open-loop stable systems. The controller is devoted to maintain the outputs within their corresponding feasible zone, while reaching the desired optimal input target. Simulation of a process of the oil re. ning industry illustrates the performance of the proposed strategy.

Stochastic stability analysis for the constant-modulus algorithm

We derive an easy-to-compute approximate bound for the range of step-sizes for which the constant-modulus algorithm (CMA) will remain stable if initialized close to a minimum of the CM cost function. Our model highlights the influence, of the signal constellation used in the transmission system: for smaller variation in the modulus of the transmitted symbols, the algorithm will be more robust, and the steady-state misadjustment will be smaller. The theoretical results are validated through several simulations, for long and short filters and channels.

A Class of Channels Resulting in Ill-Convergence for CMA in Decision Feedback Equalizers

This paper analyzes the convergence of the constant modulus algorithm (CMA) in a decision feedback equalizer using only a feedback filter. Several works had already observed that the CMA presented a better performance than decision directed algorithm in the adaptation of the decision feedback equalizer, but theoretical analysis always showed to be difficult specially due to the analytical difficulties presented by the constant modulus criterion. In this paper, we surmount such obstacle by using a recent result concerning the CM analysis, first obtained in a linear finite impulse response context with the objective of comparing its solutions to the ones obtained through the Wiener criterion. The theoretical analysis presented here confirms the robustness of the CMA when applied to the adaptation of the decision feedback equalizer and also defines a class of channels for which the algorithm will suffer from ill-convergence when initialized at the origin.

On the convergence of successive Galerkin approximation for nonlinear output feedback H(infinity) control

Although the formulation of the nonlinear theory of H(infinity) control has been well developed, solving the Hamilton-Jacobi-Isaacs equation remains a challenge and is the major bottleneck for practical application of the theory. Several numerical methods have been proposed for its solution. In this paper, results on convergence and stability for a successive Galerkin approximation approach for nonlinear H(infinity) control via output feedback are presented. An example is presented illustrating the application of the algorithm.

SELF-SIMILARITY AND LAMPERTI CONVERGENCE FOR FAMILIES OF STOCHASTIC PROCESSES

We define a new type of self-similarity for one-parameter families of stochastic processes, which applies to certain important families of processes that are not self-similar in the conventional sense. This includes Hougaard Levy processes such as the Poisson processes, Brownian motions with drift and the inverse Gaussian processes, and some new fractional Hougaard motions defined as moving averages of Hougaard Levy process. Such families have many properties in common with ordinary self-similar processes, including the form of their covariance functions, and the fact that they appear as limits in a Lamperti-type limit theorem for families of stochastic processes.

Hemichordates and deuterostome evolution: robust molecular phylogenetic support for a hemichordate plus echinoderm clade

Hemichordates were traditionally allied to the chordates, but recent molecular analyses have suggested that hemichordates are a sister group to the echinoderms, a relationship that has important consequences for the interpretation of the evolution of deuterostome body plans. However, the molecular phylogenetic analyses to date have not provided robust support for the hemichordate + echinoderm clade. We use a maximum likelihood framework, including the parametric bootstrap, to reanalyze DNA data from complete mitochondrial genomes and nuclear 18S rRNA. This approach provides the first statistically significant support for the hemichordate + echinoderm clade from molecular data. This grouping implies that the ancestral deuterostome had features that included an adult with a pharynx and a dorsal nerve cord and an indirectly developing dipleurula-like larva.

The HI Parkes All Sky Survey: southern observations, calibration and robust imaging

The acquisition of HI Parkes All Shy Survey (HIPASS) southern sky data commenced at the Australia Telescope National Facility's Parkes 64-m telescope in 1997 February, and was completed in 2000 March. HIPASS is the deepest HI survey yet of the sky south of declination +2 degrees, and is sensitive to emission out to 170 h(75)(-1) Mpc. The characteristic root mean square noise in the survey images is 13.3 mJy. This paper describes the survey observations, which comprise 23 020 eight-degree scans of 9-min duration, and details the techniques used to calibrate and image the data. The processing algorithms are successfully designed to be statistically robust to the presence of interference signals, and are particular to imaging point (or nearly point) sources. Specifically, a major improvement in image quality is obtained by designing a median-gridding algorithm which uses the median estimator in place of the mean estimator.

Choices associated with automobiles for Men and Women: convergence or divergence?

The increase of the women purchase power has led some companies to adopt strategies of products differentiation as well as to produce specific products to the female public. The auto industry is not immune to this phenomenon, once the women represent, approximately half of the automobile sales in the country. Considering the consumption and the behavior differences between women and men, it has set the following question: are there differences between the choices associated to the automobile by men and the choices associated to the automobile by women? It has been presented to the participants items found in the people`s day-by-day, which are valorized by them, and the participants have been asked to choose and associate these items to the automobile. The results analysis revealed there are more similarities than differences between choices associated to the automobile by men ad choices associated to the automobile by women. The similarity between the choices suggests that the representations, the meanings and values assigned. to the car by men ana women are similar and thus the strategy of product differentiation does not apply to the automotive industry

Exponential Rates of Convergence in the Ergodic Theorem: A Constructive Approach

We prove that, once an algorithm of perfect simulation for a stationary and ergodic random field F taking values in S(Zd), S a bounded subset of R(n), is provided, the speed of convergence in the mean ergodic theorem occurs exponentially fast for F. Applications from (non-equilibrium) statistical mechanics and interacting particle systems are presented.

True measures of GDP and convergence

Widely used ''purchasing power parity'' comparisons of per capita GDP are not true quantity indexes and are subject to systematic substitution bins. This bias may distort measurement of convergence and divergence. Extending Varian's nonparametric construction of a true index gives the set of true indexes, including the new Ideal Afriat Index. These indexes are utility-consistent and independent of arbitrary reference price vectors. We establish bounds on the dispersion of true multilateral indexes, hence bounds on convergence. International price indexes understate both true GDP dispersion and, where prices are converging over time, the rate of true quantity convergence.

Robust algorithms for solving stochastic partial differential equations

A robust semi-implicit central partial difference algorithm for the numerical solution of coupled stochastic parabolic partial differential equations (PDEs) is described. This can be used for calculating correlation functions of systems of interacting stochastic fields. Such field equations can arise in the description of Hamiltonian and open systems in the physics of nonlinear processes, and may include multiplicative noise sources. The algorithm can be used for studying the properties of nonlinear quantum or classical field theories. The general approach is outlined and applied to a specific example, namely the quantum statistical fluctuations of ultra-short optical pulses in chi((2)) parametric waveguides. This example uses a non-diagonal coherent state representation, and correctly predicts the sub-shot noise level spectral fluctuations observed in homodyne detection measurements. It is expected that the methods used wilt be applicable for higher-order correlation functions and other physical problems as well. A stochastic differencing technique for reducing sampling errors is also introduced. This involves solving nonlinear stochastic parabolic PDEs in combination with a reference process, which uses the Wigner representation in the example presented here. A computer implementation on MIMD parallel architectures is discussed. (C) 1997 Academic Press.

Depression in Parkinson`s disease: Convergence from voxel-based morphometry and functional magnetic resonance imaging in the limbic thalamus

Depression is the most frequent psychiatric disorder in Parkinson`s disease (PD). Although evidence Suggests that depression in PD is related to the degenerative process that underlies the disease, further studies are necessary to better understand the neural basis of depression in this population of patients. In order to investigate neuronal alterations underlying the depression in PD, we studied thirty-six patients with idiopathic PD. Twenty of these patients had the diagnosis of major depression disorder and sixteen did not. The two groups were matched for PD motor severity according to Unified Parkinson Disease Rating Scale (UPDRS). First we conducted a functional magnetic resonance imaging (fMRI) using an event-related parametric emotional perception paradigm with test retest design. Our results showed decreased activation in the left mediodorsal (MD) thalamus and in medial prefrontall cortex in PD patients with depression compared to those without depression. Based upon these results and the increased neuron count in MD thalamus found in previous studies, we conducted a region of interest (ROI) guided voxel-based morphometry (VBM) study comparing the thalamic volume. Our results showed an increased volume in mediodorsal thalamic nuclei bilaterally. Converging morphological changes and functional emotional processing in mediodorsal thalamus highlight the importance of limbic thalamus in PD depression. In addition this data supports the link between neurodegenerative alterations and mood regulation. (C) 2009 Elsevier Inc. All rights reserved.