Multivariable control strategy based on bifurcation analysis of an industrial gas-phase polymerization reactor

In an industrial gas-phase polyethylene reactor, the safe operating range of temperature is rather narrow. Even within this temperature range, temperature excursions must be avoided because they can result in low catalyst productivity and significant changes in product properties. If the manipulated variable for temperature control saturates (i.e., the cooling water valve position is completely open), then the reactor operates without a feedback temperature controller, leading to oscillatory behavior and limit cycles. In this work, it has been demonstrated that the saturation in the manipulated variable and the complex non-linear dynamic behavior are removed when auxiliary manipulated variables, obtained by bifurcation analysis, are used in a multivariable control strategy for the reactor temperature control. Two control structures are proposed and compared considering their impact in the reactor production and polymer melt index. In the first control structure, the designed PID controller for the reactor temperature is considered and a switching strategy with a PI controller for the auxiliary manipulated variables is included. In the second control structure, the designed PID controller for the reactor temperature is also used, however, a MPC controller for the auxiliary manipulated variables is considered. The results suggest that the use of gain-scheduling strategy in the PID temperature controller with a MPC controller for the auxiliary manipulated variables avoids the saturation of the manipulated variable and, hence, the undesired non-linear dynamic behavior, reducing the production loss and improving the product quality.     

Laser heat treatments driven by integrated beams: role of irradiation nonuniformities

An analysis is given of how nonuniformities in the laser beam intensity translate into variations on the induced temperature distribution on an irradiated sample. The study involves materials with different thermal conductivities. By use of a reshaped irradiating beam obtained with a multifaceted integrating mirror, a three-dimensional numerical calculation allows us to establish both surface and in-depth temperature distributions. The results show that in the case of materials such as glass (i.e., with low thermal conductivity) large thermal gradients occur both on the surface and in depth during irradiation. However, the lateral heat flow is high enough to strongly reduce the surface gradients as soon as the laser irradiation ends. Conversely, in good thermal conductors such as nickel, the laser intensity nonuniformities induce a thermal peaking of the surface with lateral thermal gradients that are by no means negligible. Experimental evidence during laser glass polishing that confirms the numerical assessments are also provided.     

Real time algorithms for digital pulse processing applied to gamma-ray and hard X-ray spectroscopy

The duration of a single plasma discharge in the next generation of fusion experiments will be much longer than in the present devices. Storing all raw data acquired in each discharge will be more difficult and the high rates achieved by the new digitizers are already contributing to storage overload. This gap can be mitigated by real time (RT) analysis and compression, using devices such as field programmable gate arrays (FPGAs) capable to transfer and process data on the fly. However, to ensure a correct RT analysis, the FPGA algorithm must be adapted to the signal to be acquired. Since minor changes in signal shape may require significant algorithm modifications, it is important to know in advance the signal attributes. For that reason, the availability of more than one RT algorithm, especially during commissioning of new sub-systems and during campaigns with relevant changes in diagnostic conditions, is advantageous. This paper presents an implementation using two RT algorithms processing simultaneously, developed for the gamma-ray and hard X-ray diagnostics of the Joint European Torus (JET). Both algorithms perform pulse height analysis with pile-up rejection. While the first algorithm is suitable for Gaussian shaped pulses, the second is suitable for exponential signals. The algorithms are selectable by the user, during discharge configuration. Tests with radioactive sources made in JET are presented.     

A diagnosis-based approach for tire-road forces and maximum friction estimation

A new approach to estimate vehicle tire forces and road maximum adherence is presented. Contrarily to most of the previous works on this subject, it is not an asymptotic observer-based estimation, but a combination of elementary diagnosis tools and new algebraic techniques for filtering and estimating derivatives of noisy signals. In a first step, instantaneous friction and lateral forces will be computed within this framework. Then, extended braking stiffness concept is exploited to detect which braking efforts allow to distinguish a road type from another. A weighted Dugoff model is used during these ‘distinguishable’ intervals to estimate the maximum friction coefficient. Very promising results have been obtained in noisy simulations and real experimentations for most of the driving situations.     

On the Distortion and Warpage of 7249 Aluminum Alloy After Quenching and Machining

The objective of this study is to determine the effect of solution treatment temperature, quenching media, and various machining sequences on the warpage behavior of aluminum 7249 alloy aged to T6 and T7′ tempers. Large extrusions of 7249 aluminum alloy with fins were cut into 108 “T” sections. The samples were solution-treated, aged, and machined. Three solution temperatures (445, 474, and 505 °C), two quenching media (water and 20% polyalkylene glycol), two aging treatments (T6 and T7′), and three machine sequences were used. The flatness of the samples was measured on the surfaces orthogonal to the z-axis. Three points were on top of both shoulders (six total), six were at the bottom of the sample, and six were on the top of the fin, in the cases where the fin was not milled off. They were then averaged together by surface to represent the overall warpage of each sample.     

Distributed resource allocation in cognitive radio networks with a game learning approach to improve aggregate system capacity

This paper presents a game theoretic solution for joint channel allocation and power control in cognitive radio networks analyzed under the physical interference model. The objective is to find a distributed solution that maximizes the network utility, defined with different criteria, with limited information. The problem is addressed through a non-cooperative game based on local information. Although the existence of a pure Nash Equilibrium cannot be assured for this game, simulation results show that it exists with high probability and with a performance similar to that of a potential game, where each player requires overall network information. The obtained results are compared with a centralized heuristic genetic algorithm to show the correctness of the proposals. From this point, utility functions for the local game are modified to restrict the transmitted power to drive the solution to a more cooperative approach. To overcome the convergence limitations of the local game, no-regret learning algorithms are used to perform the joint channel and power allocation. These algorithms provide stable mixed strategies in any scenario with even better global performance. This opens an interesting perspective to develop realistic protocols based on the modeled interactions and increases the adaptability to perform efficient opportunistic spectrum access.