Dynamic positioning systems: An experimental analysis of sliding mode control

Vessel dynamic positioning (DP) systems are based on conventional PID-type controllers and an extended Kalman filter. However, they present a difficult tuning procedure, and the closed-loop performance varies with environmental or loading conditions since the dynamics of the vessel are eminently nonlinear. Gain scheduling is normally used to address the nonlinearity of the system. To overcome these problems, a sliding mode control was evaluated. This controller is robust to variations in environmental and loading conditions, it maintains performance and stability for a large range of conditions, and presents an easy tuning methodology. The performance of the controller was evaluated numerically and experimentally in order to address its effectiveness. The results are compared with those obtained from conventional PID controller. (c) 2010 Elsevier Ltd. All rights reserved.

On state representations of time-varying nonlinear systems

This work considers a nonlinear time-varying system described by a state representation, with input u and state x. A given set of functions v, which is not necessarily the original input u of the system, is the (new) input candidate. The main result provides necessary and sufficient conditions for the existence of a local classical state space representation with input v. These conditions rely on integrability tests that are based on a derived flag. As a byproduct, one obtains a sufficient condition of differential flatness of nonlinear systems. (C) 2009 Elsevier Ltd. All rights reserved.

Closed-loop model re-identification of processes under MPC with zone control

This work deals with a procedure for model re-identification of a process in closed loop with ail already existing commercial MPC. The controller considered here has a two-layer structure where the upper layer performs a target calculation based on a simplified steady-state optimization of the process. Here, it is proposed a methodology where a test signal is introduced in a tuning parameter of the target calculation layer. When the outputs are controlled by zones instead of at fixed set points, the approach allows the continuous operation of the process without an excessive disruption of the operating objectives as process constraints and product specifications remain satisfied during the identification test. The application of the method is illustrated through the simulation of two processes of the oil refining industry. (c) 2008 Elsevier Ltd. All rights reserved.

A generalized multi-period mean-variance portfolio optimization with Markov switching parameters

In this paper, we deal with a generalized multi-period mean-variance portfolio selection problem with market parameters Subject to Markov random regime switchings. Problems of this kind have been recently considered in the literature for control over bankruptcy, for cases in which there are no jumps in market parameters (see [Zhu, S. S., Li, D., & Wang, S. Y. (2004). Risk control over bankruptcy in dynamic portfolio selection: A generalized mean variance formulation. IEEE Transactions on Automatic Control, 49, 447-457]). We present necessary and Sufficient conditions for obtaining an optimal control policy for this Markovian generalized multi-period meal-variance problem, based on a set of interconnected Riccati difference equations, and oil a set of other recursive equations. Some closed formulas are also derived for two special cases, extending some previous results in the literature. We apply the results to a numerical example with real data for Fisk control over bankruptcy Ill a dynamic portfolio selection problem with Markov jumps selection problem. (C) 2008 Elsevier Ltd. All rights reserved.

The Kumaraswamy Weibull distribution with application to failure data

For the first time, we introduce and study some mathematical properties of the Kumaraswamy Weibull distribution that is a quite flexible model in analyzing positive data. It contains as special sub-models the exponentiated Weibull, exponentiated Rayleigh, exponentiated exponential, Weibull and also the new Kumaraswamy exponential distribution. We provide explicit expressions for the moments and moment generating function. We examine the asymptotic distributions of the extreme values. Explicit expressions are derived for the mean deviations, Bonferroni and Lorenz curves, reliability and Renyi entropy. The moments of the order statistics are calculated. We also discuss the estimation of the parameters by maximum likelihood. We obtain the expected information matrix. We provide applications involving two real data sets on failure times. Finally, some multivariate generalizations of the Kumaraswamy Weibull distribution are discussed. (C) 2010 The Franklin Institute. Published by Elsevier Ltd. All rights reserved.

Flow rate sprinkler development for site-specific irrigation

Due to the rapid depletion of water resources, water must be used more efficiently in agriculture to maintain current levels of yield in irrigated areas. The efficiency of irrigation systems can be increased by adjusting the amount of water applied to specific conditions of soil and crop, which may vary in a field. Taking into account spatial and temporal variability, it is evident that an equipment capable of providing different irrigation levels is necessary to meet the water requirement of the soil. This work aims to develop and evaluate a flow rate sprinkler to be used in center pivots or linear moving irrigation systems, with potential for utilization in irrigation scheduling. A prototype was developed by duplicating its calibrations, and discharge coefficient adjustment was carried out in the laboratory. To predict the flow rate, a successful model that represented the operation of the flow rate sprinkler was established. The calibration of the flow rate sprinkler prototype showed satisfactory statistical and technical results. Automation of the prototype was achieved by driving a step motor using communication from the parallel port of a microcomputer, which was controlled by a software developed for this purpose. The results were satisfactory and technically feasible.

Comparison of the Salmonella/Microsome Microsuspension Assay with the new Microplate Fluctuation Protocol for Testing the Mutagenicity of Environmental Samples

The objective of this study was to compare the responses of the Salmonella/microsome microsuspension assay with the new microplate fluctuation protocol (MPF) for the evaluation of the mutagenic activity of environmental samples. Organic extracts of total particulate atmospheric air samples, surface waters, and effluents were tested in dose-response experiments. The assays were performed with strain TA98 in the absence and presence of S9 mix. Both protocols produced similar results, despite the fact that the maximum score of the MPF is limited to 48 wells, whereas in the regular plate assay it is possible to count up to 1,500 colonies using an automatic counter. Similar sensitivities based on the lowest dose that resulted in a positive response were obtained for both assays. The MPF procedure is less laborious (e.g., all-liquid format, use of multi-channel pipettors) and allows for automation of the pipetting and dispensing steps, thus, reducing time of the analysis which is particularly important in environmental quality monitoring programs or in effect-directed analysis. The results show that the MPF procedure is a promising tool to test environmental samples for mutagenic activity. Environ. Mol. Mutagen. 51:31-38, 2010. (C) 2009 Wiley-Liss, Inc.

Fast evolution strategies

Evolution strategies are a class of general optimisation algorithms which are applicable to functions that are multimodal, nondifferentiable, or even discontinuous. Although recombination operators have been introduced into evolution strategies, the primary search operator is still mutation. Classical evolution strategies rely on Gaussian mutations. A new mutation operator based on the Cauchy distribution is proposed in this paper. It is shown empirically that the new evolution strategy based on Cauchy mutation outperforms the classical evolution strategy on most of the 23 benchmark problems tested in this paper. The paper also shows empirically that changing the order of mutating the objective variables and mutating the strategy parameters does not alter the previous conclusion significantly, and that Cauchy mutations with different scaling parameters still outperform the Gaussian mutation with self-adaptation. However, the advantage of Cauchy mutations disappears when recombination is used in evolution strategies. It is argued that the search step size plays an important role in determining evolution strategies' performance. The large step size of recombination plays a similar role as Cauchy mutation.

Practical parallel coset enumeration

Coset enumeration is a most important procedure for investigating finitely presented groups. We present a practical parallel procedure for coset enumeration on shared memory processors. The shared memory architecture is particularly interesting because such parallel computation is both faster and cheaper. The lower cost comes when the program requires large amounts of memory, and additional CPU's. allow us to lower the time that the expensive memory is being used. Rather than report on a suite of test cases, we take a single, typical case, and analyze the performance factors in-depth. The parallelization is achieved through a master-slave architecture. This results in an interesting phenomenon, whereby the CPU time is divided into a sequential and a parallel portion, and the parallel part demonstrates a speedup that is linear in the number of processors. We describe an early version for which only 40% of the program was parallelized, and we describe how this was modified to achieve 90% parallelization while using 15 slave processors and a master. In the latter case, a sequential time of 158 seconds was reduced to 29 seconds using 15 slaves.

Minimum-order stable recursive filter design via the genetic algorithm approach

In this paper, the minimum-order stable recursive filter design problem is proposed and investigated. This problem is playing an important role in pipeline implementation sin signal processing. Here, the existence of a high-order stable recursive filter is proved theoretically, in which the upper bound for the highest order of stable filters is given. Then the minimum-order stable linear predictor is obtained via solving an optimization problem. In this paper, the popular genetic algorithm approach is adopted since it is a heuristic probabilistic optimization technique and has been widely used in engineering designs. Finally, an illustrative example is sued to show the effectiveness of the proposed algorithm.

Visualization of learning in multilayer perceptron networks using principal component analysis

This paper is concerned with the use of scientific visualization methods for the analysis of feedforward neural networks (NNs). Inevitably, the kinds of data associated with the design and implementation of neural networks are of very high dimensionality, presenting a major challenge for visualization. A method is described using the well-known statistical technique of principal component analysis (PCA). This is found to be an effective and useful method of visualizing the learning trajectories of many learning algorithms such as back-propagation and can also be used to provide insight into the learning process and the nature of the error surface.

Quantum control and quantum entanglement

We discuss quantum error correction for errors that occur at random times as described by, a conditional Poisson process. We shoo, how a class of such errors, detected spontaneous emission, can be corrected by continuous closed loop, feedback.

Controllability of Volterra-Fredholm type systems in Banach spaces

We show the results in Chalishajar [Controllability of mixed Volterra-Fredholm-type integro-differential systems in Banach space, J. Franklin Inst. 344(1) (2007) 12-21] and Chang and Chalishajar [Controllability of mixed Volterra-Fredholm type integro-differential systems in Banach space, J. Franklin Inst., doi:10.1016/j. jfranklin.2008.02.002] are only valid for ordinary differential control systems. As a result the examples provided cannot be recovered as applications of the abstract results. (C) 2008 The Franklin Institute. Published by Elsevier Ltd. All rights reserved.

Improved VDC casting of aluminium alloys through an understanding of the surface properties of the molten metal

Vertical direct chill (VDC) casting of aluminium alloys is a mature process that has evolved over many decades through gradual change to both equipment design and casting practice. Today, air-pressurised, continuous lubrication, hot top mould systems with advanced station automation are selected as the process of choice for producing extrusion billet. Specific sets of operating parameters are employed on these stations for each alloy and size combination to produce optimal billet quality. The designs and parameters are largely derived from past experience and accumulated know-how. Recent experimental work at the University of Queensland has concentrated on understanding the way in which the surface properties of liquid aluminium alloys, e.g., surface tension, wetting angle and oxide skin strength, influence the size and shape of the naturally-stab le meniscus for a given alloy, temperature and atmosphere. The wide range of alloy-and condition-dependent values measured has led to the consideration of how these properties impact the stability of the enforced molten metal meniscus within the hot top mould cavity. The actual shape and position of the enforced meniscus is controlled by parameters such as the upstream conduction distance (UCD) from sub-mould cooling and the molten metal head. The degree of deviation of this actual meniscus from the predicted stable meniscus is considered to be a key driver in surface defect formation. This paper reports on liquid alloy property results and proposes how this knowledge might be used to better design VDC mould systems and casting practices.