Análise e desenvolvimento de controladores preditivos multivariáveis baseados em multi-modelos bilineares

This work addresses issues related to analysis and development of multivariable predictive controllers based on bilinear multi-models. Linear Generalized Predictive Control (GPC) monovariable and multivariable is shown, and highlighted its properties, key features and applications in industry. Bilinear GPC, the basis for the development of this thesis, is presented by the time-step quasilinearization approach. Some results are presented using this controller in order to show its best performance when compared to linear GPC, since the bilinear models represent better the dynamics of certain processes. Time-step quasilinearization, due to the fact that it is an approximation, causes a prediction error, which limits the performance of this controller when prediction horizon increases. Due to its prediction error, Bilinear GPC with iterative compensation is shown in order to minimize this error, seeking a better performance than the classic Bilinear GPC. Results of iterative compensation algorithm are shown. The use of multi-model is discussed in this thesis, in order to correct the deficiency of controllers based on single model, when they are applied in cases with large operation ranges. Methods of measuring the distance between models, also called metrics, are the main contribution of this thesis. Several application results in simulated distillation columns, which are close enough to actual behaviour of them, are made, and the results have shown satisfactory

Sistema de secagem solar para frutos tropicais e modelagem da secagem de banana em um secador de coluna estática

In this study were projected, built and tested an electric solar dryer consisting of a solar collector, a drying chamber, an exhaust fan and a fan to promote forced hot air convection. Banana drying experiments were also carried out in a static column dryer to model the drying and to obtain parameters that can be used as a first approximation in the modeling of an electric solar dryer, depending on the similarity of the experimental conditions between the two drying systems. From the banana drying experiments conducted in the static column dryer, we obtained food weight data as a function of aqueous concentration and temperature. Simplified mathematical models of the banana drying were made, based on Fick s and Fourier s second equations, which were tested with the experimental data. We determined and/or modeled parameters such as banana moisture content, density, thin layer drying curves, equilibrium moisture content, molecular diffusivity of the water in banana DAB, external mass transfer coefficient kM, specific heat Cp, thermal conductivity k, latent heat of water evaporation in the food Lfood, time to heat food, and minimum energy and power required to heat the food and evaporate the water. When we considered the shrinkage of radius R of a banana, the calculated values of DAB and kM generally better represent the phenomenon of water diffusion in a solid. The latent heat of water evaporation in the food Lfood calculated by modeling is higher than the latent heat of pure water evaporation Lwater. The values calculated for DAB and KM that best represent the drying were obtained with the analytical model of the present paper. These values had good agreement with those assessed with a numeric model described in the literature, in which convective boundary condition and food shrinkage are considered. Using parameters such as Cp, DAB, k, kM and Lfood, one can elaborate the preliminary dryer project and calculate the economy using only solar energy rather than using solar energy along with electrical energy

Concepção e estudo de um biofiltro para tratamento de compostos orgânicos voláteis COVs

In the last decade, biological purification of gaseous waste has become an important alternative to many conventional methods of exhaust air treatment. More recently, biofiltration has proved to be an effective and inexpensive method for the treatment of air contaminated with volatile organic compounds (VOCs). A biofilter consists in a reactor packed with a porous solid bed material, where the microorganisms are fixed. During the biofiltration process, polluted air is transported through the biofilter medium where the contaminant is degraded. Within the biofilm, the pollutants in the waste gases are energy and carbon sources for microbial metabolism and are transformed into CO2, water and biomass. The bed material should be characterized by satisfactory mechanical and physical properties as structure, void fraction, specific area and flow resistance. The aim of this research was the biofilter construction and study of the biological degradation of ethanol and toluene, as well as the modeling of the process. Luffa cylindrica is a brazilian fiber that was used as the filtering material of the present work. The parameters and conditions studied were: composition of nutrients solution; effect of microflorae strains, namely Pseudomanas putida and Rhodococcus rhodochrous; waste gas composition; air flow rate; and inlet load of VOCs. The biofilter operated in diffusion regime and the best results for remotion capacity were obtained when a microorganisms consortion of Pseudomanas putida and Rhodococcus rhodochrous,were used, with a gas flow rate of 1 m3.h-1 and molar ratio nitrogene/phosphore N/P=2 in the nutrients solution. The maximum remotion capacity for ethanol was around 90 g.m-3.h-1 and 50 g.m-3.h-1 to toluene. It was proved that toluene has inhibitory effect on the ethanol remotion When the two VOCs were present in the same waste gas, there was a decrease of 40% in ethanol remotion capacity. Luffa cylindrica does not present considerable pressure drop. Ottengraf and van Lith models were used to represent the results obtained for ethanol and toluene, respectively. The application of the transient model indicated a satisfactory approximation between the experimental results obtained for ethanol and toluene vapors biofiltration and the ones predicted it

O problema biobjetivo da árvore geradora quadrática em adjacência de arestas

The Quadratic Minimum Spanning Tree Problem (QMST) is a version of the Minimum Spanning Tree Problem in which, besides the traditional linear costs, there is a quadratic structure of costs. This quadratic structure models interaction effects between pairs of edges. Linear and quadratic costs are added up to constitute the total cost of the spanning tree, which must be minimized. When these interactions are restricted to adjacent edges, the problem is named Adjacent Only Quadratic Minimum Spanning Tree (AQMST). AQMST and QMST are NP-hard problems that model several problems of transport and distribution networks design. In general, AQMST arises as a more suitable model for real problems. Although, in literature, linear and quadratic costs are added, in real applications, they may be conflicting. In this case, it may be interesting to consider these costs separately. In this sense, Multiobjective Optimization provides a more realistic model for QMST and AQMST. A review of the state-of-the-art, so far, was not able to find papers regarding these problems under a biobjective point of view. Thus, the objective of this Thesis is the development of exact and heuristic algorithms for the Biobjective Adjacent Only Quadratic Spanning Tree Problem (bi-AQST). In order to do so, as theoretical foundation, other NP-hard problems directly related to bi-AQST are discussed: the QMST and AQMST problems. Bracktracking and branch-and-bound exact algorithms are proposed to the target problem of this investigation. The heuristic algorithms developed are: Pareto Local Search, Tabu Search with ejection chain, Transgenetic Algorithm, NSGA-II and a hybridization of the two last-mentioned proposals called NSTA. The proposed algorithms are compared to each other through performance analysis regarding computational experiments with instances adapted from the QMST literature. With regard to exact algorithms, the analysis considers, in particular, the execution time. In case of the heuristic algorithms, besides execution time, the quality of the generated approximation sets is evaluated. Quality indicators are used to assess such information. Appropriate statistical tools are used to measure the performance of exact and heuristic algorithms. Considering the set of instances adopted as well as the criteria of execution time and quality of the generated approximation set, the experiments showed that the Tabu Search with ejection chain approach obtained the best results and the transgenetic algorithm ranked second. The PLS algorithm obtained good quality solutions, but at a very high computational time compared to the other (meta)heuristics, getting the third place. NSTA and NSGA-II algorithms got the last positions