896 resultados para Jump linear quadratic (JLQ) control
Resumo:
Change point estimation is recognized as an essential tool of root cause analyses within quality control programs as it enables clinical experts to search for potential causes of change in hospital outcomes more effectively. In this paper, we consider estimation of the time when a linear trend disturbance has occurred in survival time following an in-control clinical intervention in the presence of variable patient mix. To model the process and change point, a linear trend in the survival time of patients who underwent cardiac surgery is formulated using hierarchical models in a Bayesian framework. The data are right censored since the monitoring is conducted over a limited follow-up period. We capture the effect of risk factors prior to the surgery using a Weibull accelerated failure time regression model. We use Markov Chain Monte Carlo to obtain posterior distributions of the change point parameters including the location and the slope size of the trend and also corresponding probabilistic intervals and inferences. The performance of the Bayesian estimator is investigated through simulations and the result shows that precise estimates can be obtained when they are used in conjunction with the risk-adjusted survival time cumulative sum control chart (CUSUM) control charts for different trend scenarios. In comparison with the alternatives, step change point model and built-in CUSUM estimator, more accurate and precise estimates are obtained by the proposed Bayesian estimator over linear trends. These superiorities are enhanced when probability quantification, flexibility and generalizability of the Bayesian change point detection model are also considered.
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We study linear control problems with quadratic losses and adversarially chosen tracking targets. We present an efficient algorithm for this problem and show that, under standard conditions on the linear system, its regret with respect to an optimal linear policy grows as O(log^2 T), where T is the number of rounds of the game. We also study a problem with adversarially chosen transition dynamics; we present an exponentiallyweighted average algorithm for this problem, and we give regret bounds that grow as O(sqtr p T).
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Two beetle-type scanning tunneling microscopes are described. Both designs have the thermal stability of the Besocke beetle and the simplicity of the Wilms beetle. Moreover, sample holders were designed that also allow both semiconductor wafers and metal single crystals to be studied. The coarse approach is a linear motion of the beetle towards the sample using inertial slip–stick motion. Ten wires are required to control the position of the beetle and scanner and measure the tunneling current. The two beetles were built with different sized piezolegs, and the vibrational properties of both beetles were studied in detail. It was found, in agreement with previous work, that the beetle bending mode is the lowest principal eigenmode. However, in contrast to previous vibrational studies of beetle-type scanning tunneling microscopes, we found that the beetles did not have the “rattling” modes that are thought to arise from the beetle sliding or rocking between surface asperities on the raceway. The mass of our beetles is 3–4 times larger than the mass of beetles where rattling modes have been observed. We conjecture that the mass of our beetles is above a “critical beetle mass.” This is defined to be the beetle mass that attenuates the rattling modes by elastically deforming the contact region to the extent that the rattling modes cannot be identified as distinct modes in cross-coupling measurements.
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This study examines and quantifies the effect of adding polyelectrolytes to cellulose nanofibre suspensions on the gel point of cellulose nanofibre suspensions, which is the lowest solids concentration at which the suspension forms a continuous network. The lower the gel point, the faster the drainage time to produce a sheet and the higher the porosity of the final sheet formed. Two new techniques were designed to measure the dynamic compressibility and the drainability of nanocellulose–polyelectrolyte suspensions. We developed a master curve which showed that the independent variable controlling the behaviour of nanocellulose suspensions and its composite is the structure of the flocculated suspension which is best quantified as the gel point. This was independent of the type of polyelectrolyte used. At an addition level of 2 mg/g of nanofibre, a reduction in gel point over 50 % was achieved using either a high molecular weight (13 MDa) linear cationic polyacrylamide (CPAM, 40 % charge), a dendrimer polyethylenimine of high molecular weight of 750,000 Da (HPEI) or even a low molecular weight of 2000 Da (LPEI). There was no significant difference in the minimum gel point achieved, despite the difference in polyelectrolyte morphology and molecular weight. In this paper, we show that the gel point controls the flow through the fibre suspension, even when comparing fibre suspensions with solids content above the gel point. A lower gel point makes it easier for water to drain through the fibre network,reducing the pressure required to achieve a given dewatering rate and reducing the filtering time required to form a wet laid sheet. We further show that the lower gel point partially controls the structure of the wet laid sheet after it is dried. Halving the gel point increased the air permeability of the dry sheet by 37, 46 and 25 %, when using CPAM, HPEI and LPEI, respectively. The resistance to liquid flow was reduced by 74 and 90 %, when using CPAM and LPEI. Analysing the paper formed shows that sheet forming process and final sheet properties can be engineered and controlled by adding polyelectrolytes to the nanofibre suspension.
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Ship seakeeping operability refers to the quantification of motion performance in waves relative to mission requirements. This is used to make decisions about preferred vessel designs, but it can also be used as comprehensive assessment of the benefits of ship-motion-control systems. Traditionally, operability computation aggregates statistics of motion computed over over the envelope of likely environmental conditions in order to determine a coefficient in the range from 0 to 1 called operability. When used for assessment of motion-control systems, the increase of operability is taken as the key performance indicator. The operability coefficient is often given the interpretation of the percentage of time operable. This paper considers an alternative probabilistic approach to this traditional computation of operability. It characterises operability not as a number to which a frequency interpretation is attached, but as a hypothesis that a vessel will attain the desired performance in one mission considering the envelope of likely operational conditions. This enables the use of Bayesian theory to compute the probability of that this hypothesis is true conditional on data from simulations. Thus, the metric considered is the probability of operability. This formulation not only adheres to recent developments in reliability and risk analysis, but also allows incorporating into the analysis more accurate descriptions of ship-motion-control systems since the analysis is not limited to linear ship responses in the frequency domain. The paper also discusses an extension of the approach to the case of assessment of increased levels of autonomy for unmanned marine craft.
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Topology-based methods have been successfully used for the analysis and visualization of piecewise-linear functions defined on triangle meshes. This paper describes a mechanism for extending these methods to piecewise-quadratic functions defined on triangulations of surfaces. Each triangular patch is tessellated into monotone regions, so that existing algorithms for computing topological representations of piecewise-linear functions may be applied directly to the piecewise-quadratic function. In particular, the tessellation is used for computing the Reeb graph, a topological data structure that provides a succinct representation of level sets of the function.
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The paper deals with the basic problem of adjusting a matrix gain in a discrete-time linear multivariable system. The object is to obtain a global convergence criterion, i.e. conditions under which a specified error signal asymptotically approaches zero and other signals in the system remain bounded for arbitrary initial conditions and for any bounded input to the system. It is shown that for a class of up-dating algorithms for the adjustable gain matrix, global convergence is crucially dependent on a transfer matrix G(z) which has a simple block diagram interpretation. When w(z)G(z) is strictly discrete positive real for a scalar w(z) such that w-1(z) is strictly proper with poles and zeros within the unit circle, an augmented error scheme is suggested and is proved to result in global convergence. The solution avoids feeding back a quadratic term as recommended in other schemes for single-input single-output systems.
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Pseudocercospora macadamiae is an important pathogen of macadamia in Australia, causing a disease known as husk spot. Growers strive to control the disease with a number of carbendazim and copper treatments. The aim of this study was to consider the macadamia fruit developmental stage at which fungicide application is most effective against husk spot, and whether application of copper-only applications at full-size fruit developmental stage toward the end of the season contributed to effective disease control. Fungicides were applied to macadamia trees at four developmental stages in three orchards in two subsequent production seasons. The effects of the treatments on disease incidence and severity were quantified using area under disease progress curve (AUDPC) and logistic regression models. Although disease incidence varied between cultivars, incidence and severity on cv. A16 showed consistent differences between the treatments. Most significant reduction in husk spot incidence occurred when spraying commenced at match-head sized-fruit developmental stage. All treatments significantly reduced husk spot incidence and severity compared with the untreated controls, and a significant positive linear relationship (R2 = 73%) between AUDPC and severity showed that timing of the first fungicide application is important for effective disease control. Application of fungicide at full-size fruit stage reduced disease incidence but had no impact on premature fruit drop.
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In this paper, a novel 12-sided polygonal space vector structure is proposed for an induction motor drive. The space vector pattern presented in this paper consists of two 12-sided concentric polygons with the outer polygon having a radius double the inner one. As compared to previously reported 12-sided polygonal space vector structures, this paper subdivides the space vector plane into smaller sized triangles. This helps in reducing the switching frequency of the inverters without deteriorating the output voltage quality. It also reduces the device ratings and dv/dt stress on the devices to half. At the same time, other benefits obtained from the existing 12-sided space vector structure, such as increased linear modulation range and complete elimination of 5th and 7th order harmonics in the phase voltage, are also retained in this paper. The space vector structure is realized by feeding an open-end induction motor with two conventional three-level neutral point clamped (NPC) inverters with asymmetric isolated dc link voltage sources. The neutral point voltage fluctuations in the three-level NPC inverters are eliminated by utilizing the switching state multiplicities for a space vector point. The pulsewidth modulation timings are calculated using sampled reference waveform amplitudes and are explained in detail in this paper. Experimental verification on a laboratory prototype shows that this configuration may be considered suitable for high power drives.
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This paper presents a constructive solution to the problem of designing a reduced-order Luenberger observer for linear systems subject to arbitrary unknown inputs.
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This paper considers the on-line identification of a non-linear system in terms of a Hammerstein model, with a zero-memory non-linear gain followed by a linear system. The linear part is represented by a Laguerre expansion of its impulse response and the non-linear part by a polynomial. The identification procedure involves determination of the coefficients of the Laguerre expansion of correlation functions and an iterative adjustment of the parameters of the non-linear gain by gradient methods. The method is applicable to situations involving a wide class of input signals. Even in the presence of additive correlated noise, satisfactory performance is achieved with the variance of the error converging to a value close to the variance of the noise. Digital computer simulation establishes the practicability of the scheme in different situations.
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Euler–Bernoulli beams are distributed parameter systems that are governed by a non-linear partial differential equation (PDE) of motion. This paper presents a vibration control approach for such beams that directly utilizes the non-linear PDE of motion, and hence, it is free from approximation errors (such as model reduction, linearization etc.). Two state feedback controllers are presented based on a newly developed optimal dynamic inversion technique which leads to closed-form solutions for the control variable. In one formulation a continuous controller structure is assumed in the spatial domain, whereas in the other approach it is assumed that the control force is applied through a finite number of discrete actuators located at predefined discrete locations in the spatial domain. An implicit finite difference technique with unconditional stability has been used to solve the PDE with control actions. Numerical simulation studies show that the beam vibration can effectively be decreased using either of the two formulations.
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In this paper the problem of stabilization of systems by means of stable compensations is considered, and results are derived for systems using observer�controller structures, for systems using a cascade structure, and for nonlinear systems
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This paper presents a method of designing a minimax filter in the presence of large plant uncertainties and constraints on the mean squared values of the estimates. The minimax filtering problem is reformulated in the framework of a deterministic optimal control problem and the method of solution employed, invokes the matrix Minimum Principle. The constrained linear filter and its relation to singular control problems has been illustrated. For the class of problems considered here it is shown that the filter can he constrained separately after carrying out the mini maximization. Numorieal examples are presented to illustrate the results.
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A now procedure for the design of sensitivity-reduced control for linear regulators is described. The control is easily computable and implementable since it requires neither the solution of an increased-order augmented system nor the generation and feedback of a trajectory sensitivity vector. The method provides a trade-off between reduction in sensitivity measure and increase in performance index.