Injection velocity control of thermoplastic injection molding via a double controller scheme

Injection velocity has been recognized as a key variable in thermoplastic injection molding. Its closed-loop control is, however, difficult due to the complexity of the process dynamic characteristics. The basic requirements of the control system include tracking of a pre-determined injection velocity curve defined in a profile, load rejection and robustness. It is difficult for a conventional control scheme to meet all these requirements. Injection velocity dynamics are first analyzed in this paper. Then a novel double-controller scheme is adopted for the injection velocity control. This scheme allows an independent design of set-point tracking and load rejection and has good system robustness. The implementation of the double-controller scheme for injection velocity control is discussed. Special techniques such as profile transformation and shifting are also introduced to improve the velocity responses. The proposed velocity control has been experimentally demonstrated to be effective for a wide range of processing conditions.

Application of TS-Fuzzy Controller for Active Power and DC Capacitor Voltage Control in DFIG-Based Wind Energy Conversion Systems

This chapter focuses on the implementation of the TS (Tagaki-Sugino) fuzzy controller for the Doubly Fed Induction Generator (DFIG) based wind generator. The conventional PI control loops for mantaining desired active power and DC capacitor voltage is compared with the TS fuzzy controllers. DFIG system is represented by a third-order model where electromagnetic transients of the stator are neglected. The effectiveness of the TS-fuzzy controller on the rotor speed oscillations and the DC capacitor voltage variations of the DFIG damping controller on converter ratings is also investigated. The results from the time domain simulations are presented to elucidate the effectiveness of the TS-fuzzy controller over the conventional PI controller in the DFIG system. The proposed TS-fuzzy con-troller can improve the fault ride through capability of DFIG compared to the conventional PI controller.

Fuzzy-logic based frequency controller for wind farms augmented with energy storage systems

Displacement of conventional synchronous generators by non-inertial units such as wind or solar generators will result in reduced-system inertia affecting under-frequency response. Frequency control is important to avoid equipment damage, load shedding, and possible blackouts. Wind generators along with energy storage systems can be used to improve the frequency response of low-inertia power system. This paper proposes a fuzzy-logic based frequency controller (FFC) for wind farms augmented with energy storage systems (wind-storage system) to improve the primary frequency response in future low-inertia hybrid power system. The proposed controller provides bidirectional real power injection using system frequency deviations and rate of change of frequency (RoCoF). Moreover, FFC ensures optimal use of energy from wind farms and storage units by eliminating the inflexible de-loading of wind energy and minimizing the required storage capacity. The efficacy of the proposed FFC is verified on the low-inertia hybrid power system.

Adolescent self-reported physical activity and autonomy: A case for constrained and structured environments?

The provision of autonomy supportive environments that promote physical activity engagement have become popular in contemporary youth settings. However, questions remain about whether adolescent perceptions of their autonomy have implications for physical activity. The purpose of this investigation was to examine the association between adolescents’ self-reported physical activity and their perceived autonomy. Participants (n = 384 adolescents) aged between 12 and 15 years were recruited from six secondary schools in metropolitan Brisbane, Australia. Self-reported measures of physical activity and autonomy were obtained. Logistic regression with inverse probability weights were used to examine the association between autonomy and the odds of meeting youth physical activity guidelines. Autonomy (OR 0.61, 95% CI 0.49-0.76) and gender (OR 0.62, 95% CI 0.46-0.83) were negatively associated with meeting physical activity guidelines. However, the model explained only a small amount of the variation in whether youth in this sample met physical activity guidelines (R2 = 0.023). For every 1 unit decrease in autonomy (on an index from 1 to 5), participants were 1.64 times more likely to meet physical activity guidelines. The findings, which are at odds with several previous studies, suggest that interventions designed to facilitate youth physical activity should limit opportunities for youth to make independent decisions about their engagement. However, the small amount of variation explained by the predictors in the model is a caveat, and should be considered prior to applying such suggestions in practical settings. Future research should continue to examine a larger age range, longitudinal observational or intervention studies to examine assertions of causality, as well as objective measurement of physical activity.

Constrained Linear Spectral Unmixing Technique for Regional Land Cover Mapping Using MODIS Data

Over the last few decades, there has been a significant land cover (LC) change across the globe due to the increasing demand of the burgeoning population and urban sprawl. In order to take account of the change, there is a need for accurate and up-to-date LC maps. Mapping and monitoring of LC in India is being carried out at national level using multi-temporal IRS AWiFS data. Multispectral data such as IKONOS, Landsat-TM/ETM+, IRS-ICID LISS-III/IV, AWiFS and SPOT-5, etc. have adequate spatial resolution (similar to 1m to 56m) for LC mapping to generate 1:50,000 maps. However, for developing countries and those with large geographical extent, seasonal LC mapping is prohibitive with data from commercial sensors of limited spatial coverage. Superspectral data from the MODIS sensor are freely available, have better temporal (8 day composites) and spectral information. MODIS pixels typically contain a mixture of various LC types (due to coarse spatial resolution of 250, 500 and 1000 in), especially in more fragmented landscapes. In this context, linear spectral unmixing would be useful for mapping patchy land covers, such as those that characterise much of the Indian subcontinent. This work evaluates the existing unmixing technique for LC mapping using MODIS data, using end-members that are extracted through Pixel Purity Index (PPI), Scatter plot and N-dimensional visualisation. The abundance maps were generated for agriculture, built up, forest, plantations, waste land/others and water bodies. The assessment of the results using ground truth and a LISS-III classified map shows 86% overall accuracy, suggesting the potential for broad-scale applicability of the technique with superspectral data for natural resource planning and inventory applications. Index Terms-Remote sensing, digital

Reservoir Operation for Hydropower Optimization: A Chance-Constrained Approach

This paper presents a chance-constrained linear programming formulation for reservoir operation of a multipurpose reservoir. The release policy is defined by a chance constraint that the probability of irrigation release in any period equalling or exceeding the irrigation demand is at least equal to a specified value P (called reliability level). The model determines the maximum annual hydropower produced while meeting the irrigation demand at a specified reliability level. The model considers variation in reservoir water level elevation and also the operating range within which the turbine operates. A linear approximation for nonlinear power production function is assumed and the solution obtained within a specified tolerance limit. The inflow into the reservoir is considered random. The chance constraint is converted into its deterministic equivalent using a linear decision rule and inflow probability distribution. The model application is demonstrated through a case study.

A probabilistic constrained nonlinear optimization framework to optimize RED parameters

The random early detection (RED) technique has seen a lot of research over the years. However, the functional relationship between RED performance and its parameters viz,, queue weight (omega(q)), marking probability (max(p)), minimum threshold (min(th)) and maximum threshold (max(th)) is not analytically availa ble. In this paper, we formulate a probabilistic constrained optimization problem by assuming a nonlinear relationship between the RED average queue length and its parameters. This problem involves all the RED parameters as the variables of the optimization problem. We use the barrier and the penalty function approaches for its Solution. However (as above), the exact functional relationship between the barrier and penalty objective functions and the optimization variable is not known, but noisy samples of these are available for different parameter values. Thus, for obtaining the gradient and Hessian of the objective, we use certain recently developed simultaneous perturbation stochastic approximation (SPSA) based estimates of these. We propose two four-timescale stochastic approximation algorithms based oil certain modified second-order SPSA updates for finding the optimum RED parameters. We present the results of detailed simulation experiments conducted over different network topologies and network/traffic conditions/settings, comparing the performance of Our algorithms with variants of RED and a few other well known adaptive queue management (AQM) techniques discussed in the literature.

A direct adaptive neural command controller design for an unstable helicopter

This paper presents an off-line (finite time interval) and on-line learning direct adaptive neural controller for an unstable helicopter. The neural controller is designed to track pitch rate command signal generated using the reference model. A helicopter having a soft inplane four-bladed hingeless main rotor and a four-bladed tail rotor with conventional mechanical controls is used for the simulation studies. For the simulation study, a linearized helicopter model at different straight and level flight conditions is considered. A neural network with a linear filter architecture trained using backpropagation through time is used to approximate the control law. The controller network parameters are adapted using updated rules Lyapunov synthesis. The off-line trained (for finite time interval) network provides the necessary stability and tracking performance. The on-line learning is used to adapt the network under varying flight conditions. The on-line learning ability is demonstrated through parameter uncertainties. The performance of the proposed direct adaptive neural controller (DANC) is compared with feedback error learning neural controller (FENC).

Intelligent thermal energy meter cum controller for solar water heating systems

A microcontroller based, thermal energy meter cum controller (TEMC) suitable for solar thermal systems has been developed. It monitors solar radiation, ambient temperature, fluid flow rate, and temperature of fluid at various locations of the system and computes the energy transfer rate. It also controls the operation of the fluid-circulating pump depending on the temperature difference across the solar collector field. The accuracy of energy measurement is +/-1.5%. The instrument has been tested in a solar water heating system. Its operation became automatic with savings in electrical energy consumption of pump by 30% on cloudy days.

Left-Handed DNA in Synthetic and Topologically Constrained Form V-DNA

We have investigated structural transitions in Poly(dG-dC) and Poly(dG-Me5dC) in order to understand the exact role of cations in stabilizing left-handed helical structures in specific sequences andthe biological role, if any, of these structures. From a novel temperature dependent transition it has been shown that a minor fluctuation in Na+ concentration at ambient temperature can bring about Β to Ζ transition. Forthe first time, wehave observed a novel double transition in poly(dG-Me5dC) as the Na+ concentration is gradually increased. This suggests that a minor fluctuation in Na+ concentration in conjunction with methylation may transform small stretches of CG sequences from one conformational state to another. These stretches could probably serve as sites for regulation. Supercoiled formV DNA reconstituted from pBR322 and pßG plasmids have been studied as model systems, in order to understand the nature and role of left-handed helical conformation in natural sequences. A large portion of DNA in form V, obtained by reannealing the two complementary singlestranded circles is forced to adopt left-handed double helical structure due to topological constraints (Lk = 0). Binding studies with Z-DNA specific antibody and spectroscopic studies confirm the presence of left-handed Z-structure in the pßG and pßR322 form V DNA. Cobalt hexamine chloride, which induces Z-form in Poly(dG-dC) stabilizes the Z-conformation in form V DNA even in the non-alternating purine-pyrimidine sequences. A reverse effect is observed with ethidium bromide. Interestingly, both topoisomerase I and II (from wheat germ) act effectively on form V DNA to give rise to a species having an electrophoretic mobility on agarose gel similar to that of open circular (form II) DNA. Whether this molecule is formed as a result of the left-handed helical segments of form V DNA undergoing a transition to the right-handed B-form during the topoisomerase action remains to be solved.

Reliable stabilization using a multi-controller configuration

Given a plant P, we consider the problem of designing a pair of controllers C1 and C2 such that their sum stabilizes P, and in addition, each of them also stabilizes P should the other one fail. This is referred to as the reliable stabilization problem. It is shown that every strongly stabilizable plant can be reliably stabilized; moreover, one of the two controllers can be specified arbitrarily, subject only to the constraint that it should be stable. The stabilization technique is extended to reliable regulation.

Gittins indices and constrained allocation in clinical trials

We explore the use of Gittins indices to search for near optimality in sequential clinical trials. Some adaptive allocation rules are proposed to achieve the following two objectives as far as possible: (i) to reduce the expected successes lost, (ii) to minimize the error probability at the end. Simulation results indicate the merits of the rules based on Gittins indices for small trial sizes. The rules are generalized to the case when neither of the response densities is known. Asymptotic optimality is derived for the constrained rules. A simple allocation rule is recommended for one-stage models. The simulation results indicate that it works better than both equal allocation and Bather's randomized allocation. We conclude with a discussion of possible further developments.

Flow of metal in constrained plane-strain extrusion forging- Part II

With many innovations in process technology, forging is establishing itself as a precision manufacturing process: as forging is used to produce complex shapes in difficult materials, it requires dies of complex configuration of high strength and of wear-resistant materials. Extensive research and development work is being undertaken, internationally, to analyse the stresses in forging dies and the flow of material in forged components. Identification of the location, size and shape of dead-metal zones is required for component design. Further, knowledge of the strain distribution in the flowing metal indicates the degree to which the component is being work hardened. Such information is helpful in the selection of process parameters such as dimensional allowances and interface lubrication, as well as in the determination of post-forging operations such as heat treatment and machining. In the presently reported work the effect of aperture width and initial specimen height on the strain distribution in the plane-strain extrusion forging of machined lead billets is observed: the distortion of grids inscribed on the face of the specimen gives the strain distribution. The stress-equilibrium approach is used to optimise a model of flow in extrusion forging, which model is found to be effective in estimating the size of the dead-metal zone. The work carried out so far indicates that the methodology of using the stress-equilibrium approach to develop models of flow in closed-die forging can be a useful tool in component, process and die design.

Development and Simulation of a Variable Rate Controller for an Air search and Air Sampling Unmanned Aerial System

This report describes the development and simulation of a variable rate controller for a 6-degree of freedom nonlinear model. The variable rate simulation model represents an off the shelf autopilot. Flight experiment involves risks and can be expensive. Therefore a dynamic model to understand the performance characteristics of the UAS in mission simulation before actual flight test or to obtain parameters needed for the flight is important. The control and guidance is implemented in Simulink. The report tests the use of the model for air search and air sampling path planning. A GUI in which a set of mission scenarios, in which two experts (mission expert, i.e. air sampling or air search and an UAV expert) interact, is presented showing the benefits of the method.

The Alpha-Method Direct Transcription In Path Constrained Dynamic Optimization

Numerically discretized dynamic optimization problems having active inequality and equality path constraints that along with the dynamics induce locally high index differential algebraic equations often cause the optimizer to fail in convergence or to produce degraded control solutions. In many applications, regularization of the numerically discretized problem in direct transcription schemes by perturbing the high index path constraints helps the optimizer to converge to usefulm control solutions. For complex engineering problems with many constraints it is often difficult to find effective nondegenerat perturbations that produce useful solutions in some neighborhood of the correct solution. In this paper we describe a numerical discretization that regularizes the numerically consistent discretized dynamics and does not perturb the path constraints. For all values of the regularization parameter the discretization remains numerically consistent with the dynamics and the path constraints specified in the, original problem. The regularization is quanti. able in terms of time step size in the mesh and the regularization parameter. For full regularized systems the scheme converges linearly in time step size.The method is illustrated with examples.