Modeling, control and experimental validation of a novel actuator based on shape memory alloys

The paper presents the development of a mechanical actuator using a shape memory alloy with a cooling system based on the thermoelectric effect (Seebeck-Peltier effect). Such a method has the advantage of reduced weight and requires a simpler control strategy as compared to other forced cooling systems. A complete mathematical model of the actuator was derived, and an experimental prototype was implemented. Several experiments are used to validate the model and to identify all parameters. A robust and nonlinear controller, based on sliding-mode theory, was derived and implemented. Experiments were used to evaluate the actuator closed-loop performance, stability, and robustness properties. The results showed that the proposed cooling system and controller are able to improve the dynamic response of the actuator. (C) 2009 Elsevier Ltd. All rights reserved.

Development of Control Systems for Safety Instrumented Systems

Safety Instrumented Systems (SIS) are designed to prevent and / or mitigate accidents, avoiding undesirable high potential risk scenarios, assuring protection of people`s health, protecting the environment and saving costs of industrial equipment. The design of these systems require formal methods for ensuring the safety requirements, but according material published in this area, has not identified a consolidated procedure to match the task. This sense, this article introduces a formal method for diagnosis and treatment of critical faults based on Bayesian network (BN) and Petri net (PN). This approach considers diagnosis and treatment for each safety instrumented function (SIF) including hazard and operability (HAZOP) study in the equipment or system under control. It also uses BN and Behavioral Petri net (BPN) for diagnoses and decision-making and the PN for the synthesis, modeling and control to be implemented by Safety Programmable Logic Controller (PLC). An application example considering the diagnosis and treatment of critical faults is presented and illustrates the methodology proposed.

MODELLING AND CONTROL OF ERSW PROCESSES BY NEURONAL NETWORK

A study on the use of artificial intelligence (AI) techniques for the modelling and subsequent control of an electric resistance spot welding process (ERSW) is presented. The ERSW process is characterized by the coupling of thermal, electrical, mechanical, and metallurgical phenomena. For this reason, early attempts to model it using computational methods established as the methods of finite differences, finite element, and finite volumes, ask for simplifications that lead the model obtained far from reality or very costly in terms of computational costs, to be used in a real-time control system. In this sense, the authors have developed an ERSW controller that uses fuzzy logic to adjust the energy transferred to the weld nugget. The proposed control strategies differ in the speed with which it reaches convergence. Moreover, their application for a quality control of spot weld through artificial neural networks (ANN) is discussed.

Registration of temporal sequences of coronal and sagittal MR images through respiratory patterns

This work discusses the determination of the breathing patterns in time sequence of images obtained from magnetic resonance (MR) and their use in the temporal registration of coronal and sagittal images. The registration is made without the use of any triggering information and any special gas to enhance the contrast. The temporal sequences of images are acquired in free breathing. The real movement of the lung has never been seen directly, as it is totally dependent on its surrounding muscles and collapses without them. The visualization of the lung in motion is an actual topic of research in medicine. The lung movement is not periodic and it is susceptible to variations in the degree of respiration. Compared to computerized tomography (CT), MR imaging involves longer acquisition times and it is preferable because it does not involve radiation. As coronal and sagittal sequences of images are orthogonal to each other, their intersection corresponds to a segment in the three-dimensional space. The registration is based on the analysis of this intersection segment. A time sequence of this intersection segment can be stacked, defining a two-dimension spatio-temporal (2DST) image. The algorithm proposed in this work can detect asynchronous movements of the internal lung structures and lung surrounding organs. It is assumed that the diaphragmatic movement is the principal movement and all the lung structures move almost synchronously. The synchronization is performed through a pattern named respiratory function. This pattern is obtained by processing a 2DST image. An interval Hough transform algorithm searches for synchronized movements with the respiratory function. A greedy active contour algorithm adjusts small discrepancies originated by asynchronous movements in the respiratory patterns. The output is a set of respiratory patterns. Finally, the composition of coronal and sagittal image pairs that are in the same breathing phase is realized by comparing of respiratory patterns originated from diaphragmatic and upper boundary surfaces. When available, the respiratory patterns associated to lung internal structures are also used. The results of the proposed method are compared with the pixel-by-pixel comparison method. The proposed method increases the number of registered pairs representing composed images and allows an easy check of the breathing phase. (C) 2010 Elsevier Ltd. All rights reserved.

Influence of Microstructures on Polarization Resistance and Hydrogen-Induced Cracking of a Micro-Alloyed Steel Submitted to Different Cooling Rates

The effect of different microstructures on the polarization resistance (Rp) and the hydrogen-induced cracking (HIC) of a micro-alloyed steel austenitized and submitted to different cooling rates was studied. Samples 19.1 x 6 x 2 mm, containing the whole thickness of the plate were extracted from a 20 mm plate and heat treated on a quenching dilatometer, were submitted to Rp and HIC corrosion tests. Both Rp and HIC tests followed as close as possible ASTM G59 and NACE standard TM0284-2003, in this case, modified only with regard to the size of the samples. Steel samples transformed from austenite by a slow cooling (cooling rate of 0.5 degrees C.s(-1)) showed higher susceptibility to hydrogen-induced cracking, with large cracks in the middle of the sample propagating along segregation bands, corresponding to the centerline of the plate thickness. For cooling rates of 10 degrees C.s(-1), only small cracks were found in the matrix and micro cracks nucleated at non-metallic inclusions. For higher cooling rates (40 degrees C.s(-1)) very few small cracks were detected, linked to non-metallic inclusions. This result suggests that structures formed by polygonal structures and segregation bands (were cutectoid microconstituents predominate) have higher susceptibility to HIC. Structures predominantly formed by acicular ferrite make it difficult to propagate the cracks among non-oriented and interlaced acicular ferrite crystals. Smaller segregation bands containing eutectoid products also help inhibit cracking and crack propagation; segregation bands can function as pipelines for hydrogen diffusion and offer a path of stress concentration for the propagation of cracks, frequently associated to non-metallic inclusions. Polarization resistance essays performed on the steel in theas received condition, prior to any heat treatment, showed larger differences between the regions of the plate, with a considerably lower Rp in the centerline. The austenitization heat treatments followed by cooling rates of 0.5 e 10 degrees C.s(-1) made more uniform the corrosion resistance along the thickness of the plate. The effects of heat treatments on the corrosion resistance are probably related to the microconstituent formed, allied to the chemical homogenization of the impurities concentrated on the centerline of the plate.

Combining Mager and Steinmetz: The Effect of Grain Size and Maximum Induction on Hysteresis Energy Loss

Twelve samples with different grain sizes were prepared by normal grain growth and by primary recrystallization, and the hysteresis dissipated energy was measured by a quasi-static method. Results showed a linear relation between hysteresis energy loss and the inverse of grain size, which is here called Mager`s law, for maximum inductions from 0.6 to 1.5 T, and a Steinmetz power law relation between hysteresis loss and maximum induction for all samples. The combined effect is better described by a Mager`s law where the coefficients follow Steinmetz law.

Quantification of MgO surface excess on the SnO(2) nanoparticles and relationship with nanostability and growth

In this work, we experimentally showed that the spontaneous segregation of MgO as surface excess in MgO doped SnO(2) nanoparticles plays an important role in the system`s energetics and stability. Using Xray fluorescence in specially treated samples, we quantitatively determined the fraction of MgO forming surface excess when doping SnO(2) with several different concentrations and established a relationship between this amount and the surface energy of the nanoparticles using the Gibbs approach. We concluded that the amount of Mg ions on the surface was directly related to the nanoparticles total free energy, in a sense that the dopant will always spontaneously distribute itself to minimize it if enough diffusion is provided. Because we were dealing with nanosized particles, the effect of MgO on the surface was particularly important and has a direct effect on the equilibrium particle size (nanoparticle stability), such that the lower the surface energy is, the smaller the particle sizes are, evidencing and quantifying the thermodynamic basis of using additives to control SnO(2) nanoparticles stability. (C) 2010 Elsevier B.V. All rights reserved.

Reaction rate and product morphology in carbon composite iron ore pellets with and without Portland cement

The aim of this work is to study the reaction rate and the morphology of intermediate reaction products during iron ore reduction when iron ore and carbonaceous materials are agglomerated together with or without Portland cement. The reaction was performed at high temperatures, and used small size samples in order to minimise heat transfer constraints. Coke breeze and pure graphite were the carbonaceous materials employed. Portland cement was applied as a binder, and pellet diameters were in the range 5.6-6.5 mm. The experimental technique involved the measurement of the pellet weight loss, as well as the interruption of the reaction at different stages, in order to submit the partially reduced pellet to scanning electron microscopy. The experimental temperature was in the range 1423-1623 K, and the total reaction time varied from 240 to 1200 s. It was observed that above 1523 K the formation of liquid slag occurred inside the pellets, which partially dissolved iron oxides. The apparent activation energies obtained were 255 kJ mol(-1) for coke breeze containing pellets, and 230 kJ mol(-1) for those pellets containing graphite. It was possible to avoid heat transfer control of the reaction rate up to 1523 K by employing small composite pellets.

Study on Iron Formation During the Carbothermic Reduction of Iron Ore in Carbon Composite Pellets in the Temperature Range 1423 K-1623 K

The aim of this work is to study the reaction rate and the morphology of the intermediary reaction products during reduction of iron ore, when iron ore and carbonaceous material are agglomerated together as a carbon composite iron ore pellet. The reaction was performed at high temperatures, and in order to avoid heat transfer constraints small size samples were used. The carbonaceous materials employed were coke breeze and pure graphite. Portland cement was employed as a binder, and the pellets diameter was 5.2 mm. The experimental technique involved the measurement of the pellets weight loss, as well as interruption of the reaction at different stages in order to submit the partially reduced pellet to scanning electron microscopy. It has been observed that above 1523 K there is the formation of liquid slag inside the pellets, which partially dissolves iron oxides. The apparent activation energies obtained were 255 kJ/mol for coke breeze containing pellets, and 230 kJ/mol for those pellets containing graphite. It was possible to avoid heat transfer control of the reaction rate up to 1523 K by employing small composite pellets.

Influence of Temperature, Basiscity and Particle Size on MnO Reduction

The aim of this work is to study MnO reduction by solid carbon. The influence of size of carbon particles, slag basicity, and bath temperature on MnO reduction was investigated. Fine Manganese ore particles were used as a source of MnO. Three sizes of carbon particles were used; 0.230 mm, 0.162 mm and 0.057 mm, binary basicity of 1 and 1.5 and temperatures of 1550, 1550 and 1600 degrees C. Curves were drawn for Mn content in the bath as a function of time and temperature for the several studied parameters. The MnO reduction rates were determined using these data. [doi:10.2320/matertrans.M2011007]

In-Line Monitoring of Particle Size during Emulsion Polymerization under Different Operational Conditions using NIR Spectroscopy

In the present work, the sensitivity of NIR spectroscopy toward the evolution of particle size was studied during emulsion homopolymerization of styrene (Sty) and emulsion copolymerization of vinyl acetate-butyl acrylate conducted in a semibatch stirred tank and a tubular pulsed sieve plate reactor, respectively. All NIR spectra were collected online with a transflectance probe immersed into the reaction medium. The spectral range used for the NIR monitoring was from 9 500 to 13 000 cm(-1), where the absorbance of the chemical components present is minimal and the changes in the NIR spectrum can be ascribed to the effects of light scattering by the polymer particles. Off-line measurements of the average diameter of the polymer particles by DLS were used as reference values for the development of the multi-variate NIR calibration models based on partial least squares. Results indicated that, in the spectral range studied, it is possible to monitor the evolution of the average size of the polymer particles during emulsion polymerization reactions. The inclusion of an additional spectral range, from 5 701 to 6 447 cm(-1), containing information on absorbances (""chemical information"") in the calibration models was also evaluated.

Robust integration of real time optimization with linear model predictive control

Here, we study the stable integration of real time optimization (RTO) with model predictive control (MPC) in a three layer structure. The intermediate layer is a quadratic programming whose objective is to compute reachable targets to the MPC layer that lie at the minimum distance to the optimum set points that are produced by the RTO layer. The lower layer is an infinite horizon MPC with guaranteed stability with additional constraints that force the feasibility and convergence of the target calculation layer. It is also considered the case in which there is polytopic uncertainty in the steady state model considered in the target calculation. The dynamic part of the MPC model is also considered unknown but it is assumed to be represented by one of the models of a discrete set of models. The efficiency of the methods presented here is illustrated with the simulation of a low order system. (C) 2010 Elsevier Ltd. All rights reserved.

Real time optimization (RTO) with model predictive control (MPC)

This paper studies a simplified methodology to integrate the real time optimization (RTO) of a continuous system into the model predictive controller in the one layer strategy. The gradient of the economic objective function is included in the cost function of the controller. Optimal conditions of the process at steady state are searched through the use of a rigorous non-linear process model, while the trajectory to be followed is predicted with the use of a linear dynamic model, obtained through a plant step test. The main advantage of the proposed strategy is that the resulting control/optimization problem can still be solved with a quadratic programming routine at each sampling step. Simulation results show that the approach proposed may be comparable to the strategy that solves the full economic optimization problem inside the MPC controller where the resulting control problem becomes a non-linear programming problem with a much higher computer load. (C) 2010 Elsevier Ltd. All rights reserved.

Optimizing model predictive control of an industrial distillation column

The main scope of this work is the implementation of an MPC that integrates the control and the economic optimization of the system. The two problems are solved simultaneously through the modification of the control cost function that includes an additional term related to the economic objective. The optimizing MPC is based on a quadratic program (QP) as the conventional MPC and can be solved with the available QP solvers. The method was implemented in an industrial distillation system, and the results show that the approach is efficient and can be used, in several practical cases. (C) 2011 Elsevier Ltd. All rights reserved.

Stable Model Predictive Control for Integrating Systems with Optimizing Targets

This paper concern the development of a stable model predictive controller (MPC) to be integrated with real time optimization (RTO) in the control structure of a process system with stable and integrating outputs. The real time process optimizer produces Optimal targets for the system inputs and for Outputs that Should be dynamically implemented by the MPC controller. This paper is based oil a previous work (Comput. Chem. Eng. 2005, 29, 1089) where a nominally stable MPC was proposed for systems with the conventional control approach where only the outputs have set points. This work is also based oil the work of Gonzalez et at. (J. Process Control 2009, 19, 110) where the zone control of stable systems is studied. The new control for is obtained by defining ail extended control objective that includes input targets and zone controller the outputs. Additional decision variables are also defined to increase the set of feasible solutions to the control problem. The hard constraints resulting from the cancellation of the integrating modes Lit the end of the control horizon are softened,, and the resulting control problem is made feasible to a large class of unknown disturbances and changes of the optimizing targets. The methods are illustrated with the simulated application of the proposed,approaches to a distillation column of the oil refining industry.