Nonlinear angle control of a sectioned airfoil by using shape memory alloys

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Estratégia de controle multifuncional para sistemas fotovoltaicos de geração de energia elétrica

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Nonlinear state estimation and control applied to a manipulator robotic including drive motor

A robotic control design considering all the inherent nonlinearities of the robot engine configuration is developed. The interactions between the robot and joint motor drive mechanism are considered. The proposed control combines two strategies, one feedforward control in order to maintain the system in the desired coordinate, and feedback control system to take the system into a desired coordinate. The feedback control is obtained using State Dependent Riccati Equation (SDRE). For link positioning two cases are considered. Case 1: For control positioning, it is only used motor voltage; Case 2: For control positioning, it is used both motor voltage and torque between the links. Simulation results, including parametric uncertainties in control shows the feasibility of the proposed control for the considered system.

A New Control Architecture for Robust Controllers in Rear Electric Traction Passenger HEVs

It is well known that control systems are the core of electronic differential systems (EDSs) in electric vehicles (EVs)/hybrid HEVs (HEVs). However, conventional closed-loop control architectures do not completely match the needed ability to reject noises/disturbances, especially regarding the input acceleration signal incoming from the driver's commands, which makes the EDS (in this case) ineffective. Due to this, in this paper, a novel EDS control architecture is proposed to offer a new approach for the traction system that can be used with a great variety of controllers (e. g., classic, artificial intelligence (AI)-based, and modern/robust theory). In addition to this, a modified proportional-integral derivative (PID) controller, an AI-based neuro-fuzzy controller, and a robust optimal H-infinity controller were designed and evaluated to observe and evaluate the versatility of the novel architecture. Kinematic and dynamic models of the vehicle are briefly introduced. Then, simulated and experimental results were presented and discussed. A Hybrid Electric Vehicle in Low Scale (HELVIS)-Sim simulation environment was employed to the preliminary analysis of the proposed EDS architecture. Later, the EDS itself was embedded in a dSpace 1103 high-performance interface board so that real-time control of the rear wheels of the HELVIS platform was successfully achieved.

Modeling of active holonic control systems for intelligent buildings

Building facilities have become important infrastructures for modern productive plants dedicated to services. In this context, the control systems of intelligent buildings have evolved while their reliability has evidently improved. However, the occurrence of faults is inevitable in systems conceived, constructed and operated by humans. Thus, a practical alternative approach is found to be very useful to reduce the consequences of faults. Yet, only few publications address intelligent building modeling processes that take into consideration the occurrence of faults and how to manage their consequences. In the light of the foregoing, a procedure is proposed for the modeling of intelligent building control systems, considersing their functional specifications in normal operation and in the of the event of faults. The proposed procedure adopts the concepts of discrete event systems and holons, and explores Petri nets and their extensions so as to represent the structure and operation of control systems for intelligent buildings under normal and abnormal situations. (C) 2012 Elsevier B.V. All rights reserved.

Mouse Housing System Using Pressurized Cages Intraventilated by Direct-Current Microfans

We performed the initial assessment of an alternative pressurized intraventilated (PIV) caging system for laboratory mice that uses direct-current microfans to achieve cage pressurization and ventilation. Twenty-nine pairs of female SPF BALB/c mice were used, with 19 experimental pairs kept in Ply cages and 10 control pairs kept in regular filter-top (FT) cages. Both groups were housed in a standard housing room with a conventional atmospheric control system. For both systems, intracage temperatures were in equilibrium with ambient room temperature. PIV cages showed a significant difference in pressure between days 1 and 8. Air speed (and consequently airflow rate) and the number of air changes hourly in the PIV cages showed decreasing trends. In both systems, ammonia concentrations increased with time, with significant differences between groups starting on day 1. Overall, the data revealed that intracage pressurization and ventilation by using microfans is a simple, reliable system, with low cost, maintenance requirements, and incidence of failures. Further experiments are needed to determine the potential influence of this system on the reproductive performance and pulmonary integrity in mice.

OPTIMIZATION AND CONTROL OF A CONTINUOUS POLYMERIZATION REACTOR

This work studies the optimization and control of a styrene polymerization reactor. The proposed strategy deals with the case where, because of market conditions and equipment deterioration, the optimal operating point of the continuous reactor is modified significantly along the operation time and the control system has to search for this optimum point, besides keeping the reactor system stable at any possible point. The approach considered here consists of three layers: the Real Time Optimization (RTO), the Model Predictive Control (MPC) and a Target Calculation (TC) that coordinates the communication between the two other layers and guarantees the stability of the whole structure. The proposed algorithm is simulated with the phenomenological model of a styrene polymerization reactor, which has been widely used as a benchmark for process control. The complete optimization structure for the styrene process including disturbances rejection is developed. The simulation results show the robustness of the proposed strategy and the capability to deal with disturbances while the economic objective is optimized.

An online data access prediction and optimization approach for distributed systems

Current scientific applications have been producing large amounts of data. The processing, handling and analysis of such data require large-scale computing infrastructures such as clusters and grids. In this area, studies aim at improving the performance of data-intensive applications by optimizing data accesses. In order to achieve this goal, distributed storage systems have been considering techniques of data replication, migration, distribution, and access parallelism. However, the main drawback of those studies is that they do not take into account application behavior to perform data access optimization. This limitation motivated this paper which applies strategies to support the online prediction of application behavior in order to optimize data access operations on distributed systems, without requiring any information on past executions. In order to accomplish such a goal, this approach organizes application behaviors as time series and, then, analyzes and classifies those series according to their properties. By knowing properties, the approach selects modeling techniques to represent series and perform predictions, which are, later on, used to optimize data access operations. This new approach was implemented and evaluated using the OptorSim simulator, sponsored by the LHC-CERN project and widely employed by the scientific community. Experiments confirm this new approach reduces application execution time in about 50 percent, specially when handling large amounts of data.

Optimization and control of a continuous polymerization reactor

This work studies the optimization and control of a styrene polymerization reactor. The proposed strategy deals with the case where, because of market conditions and equipment deterioration, the optimal operating point of the continuous reactor is modified significantly along the operation time and the control system has to search for this optimum point, besides keeping the reactor system stable at any possible point. The approach considered here consists of three layers: the Real Time Optimization (RTO), the Model Predictive Control (MPC) and a Target Calculation (TC) that coordinates the communication between the two other layers and guarantees the stability of the whole structure. The proposed algorithm is simulated with the phenomenological model of a styrene polymerization reactor, which has been widely used as a benchmark for process control. The complete optimization structure for the styrene process including disturbances rejection is developed. The simulation results show the robustness of the proposed strategy and the capability to deal with disturbances while the economic objective is optimized.

Aportaciones al control inverso con modelo de referencia basado en lógica borrosa, redes neuronales y algoritmos genéticos

Programa de doctorado: Ingeniería de Telecomunicación Avanzada.

Modulation Techniques for Multi-Phase Converters and Control Strategies for Multi-Phase Electric Drives

The ever-increasing spread of automation in industry puts the electrical engineer in a central role as a promoter of technological development in a sector such as the use of electricity, which is the basis of all the machinery and productive processes. Moreover the spread of drives for motor control and static converters with structures ever more complex, places the electrical engineer to face new challenges whose solution has as critical elements in the implementation of digital control techniques with the requirements of inexpensiveness and efficiency of the final product. The successfully application of solutions using non-conventional static converters awake an increasing interest in science and industry due to the promising opportunities. However, in the same time, new problems emerge whose solution is still under study and debate in the scientific community During the Ph.D. course several themes have been developed that, while obtaining the recent and growing interest of scientific community, have much space for the development of research activity and for industrial applications. The first area of research is related to the control of three phase induction motors with high dynamic performance and the sensorless control in the high speed range. The management of the operation of induction machine without position or speed sensors awakes interest in the industrial world due to the increased reliability and robustness of this solution combined with a lower cost of production and purchase of this technology compared to the others available in the market. During this dissertation control techniques will be proposed which are able to exploit the total dc link voltage and at the same time capable to exploit the maximum torque capability in whole speed range with good dynamic performance. The proposed solution preserves the simplicity of tuning of the regulators. Furthermore, in order to validate the effectiveness of presented solution, it is assessed in terms of performance and complexity and compared to two other algorithm presented in literature. The feasibility of the proposed algorithm is also tested on induction motor drive fed by a matrix converter. Another important research area is connected to the development of technology for vehicular applications. In this field the dynamic performances and the low power consumption is one of most important goals for an effective algorithm. Towards this direction, a control scheme for induction motor that integrates within a coherent solution some of the features that are commonly required to an electric vehicle drive is presented. The main features of the proposed control scheme are the capability to exploit the maximum torque in the whole speed range, a weak dependence on the motor parameters, a good robustness against the variations of the dc-link voltage and, whenever possible, the maximum efficiency. The second part of this dissertation is dedicated to the multi-phase systems. This technology, in fact, is characterized by a number of issues worthy of investigation that make it competitive with other technologies already on the market. Multiphase systems, allow to redistribute power at a higher number of phases, thus making possible the construction of electronic converters which otherwise would be very difficult to achieve due to the limits of present power electronics. Multiphase drives have an intrinsic reliability given by the possibility that a fault of a phase, caused by the possible failure of a component of the converter, can be solved without inefficiency of the machine or application of a pulsating torque. The control of the magnetic field spatial harmonics in the air-gap with order higher than one allows to reduce torque noise and to obtain high torque density motor and multi-motor applications. In one of the next chapters a control scheme able to increase the motor torque by adding a third harmonic component to the air-gap magnetic field will be presented. Above the base speed the control system reduces the motor flux in such a way to ensure the maximum torque capability. The presented analysis considers the drive constrains and shows how these limits modify the motor performance. The multi-motor applications are described by a well-defined number of multiphase machines, having series connected stator windings, with an opportune permutation of the phases these machines can be independently controlled with a single multi-phase inverter. In this dissertation this solution will be presented and an electric drive consisting of two five-phase PM tubular actuators fed by a single five-phase inverter will be presented. Finally the modulation strategies for a multi-phase inverter will be illustrated. The problem of the space vector modulation of multiphase inverters with an odd number of phases is solved in different way. An algorithmic approach and a look-up table solution will be proposed. The inverter output voltage capability will be investigated, showing that the proposed modulation strategy is able to fully exploit the dc input voltage either in sinusoidal or non-sinusoidal operating conditions. All this aspects are considered in the next chapters. In particular, Chapter 1 summarizes the mathematical model of induction motor. The Chapter 2 is a brief state of art on three-phase inverter. Chapter 3 proposes a stator flux vector control for a three- phase induction machine and compares this solution with two other algorithms presented in literature. Furthermore, in the same chapter, a complete electric drive based on matrix converter is presented. In Chapter 4 a control strategy suitable for electric vehicles is illustrated. Chapter 5 describes the mathematical model of multi-phase induction machines whereas chapter 6 analyzes the multi-phase inverter and its modulation strategies. Chapter 7 discusses the minimization of the power losses in IGBT multi-phase inverters with carrier-based pulse width modulation. In Chapter 8 an extended stator flux vector control for a seven-phase induction motor is presented. Chapter 9 concerns the high torque density applications and in Chapter 10 different fault tolerant control strategies are analyzed. Finally, the last chapter presents a positioning multi-motor drive consisting of two PM tubular five-phase actuators fed by a single five-phase inverter.

Model predictive flight control systems for rotorcraft UAS

Constraints are widely present in the flight control problems: actuators saturations or flight envelope limitations are only some examples of that. The ability of Model Predictive Control (MPC) of dealing with the constraints joined with the increased computational power of modern calculators makes this approach attractive also for fast dynamics systems such as agile air vehicles. This PhD thesis presents the results, achieved at the Aerospace Engineering Department of the University of Bologna in collaboration with the Dutch National Aerospace Laboratories (NLR), concerning the development of a model predictive control system for small scale rotorcraft UAS. Several different predictive architectures have been evaluated and tested by means of simulation, as a result of this analysis the most promising one has been used to implement three different control systems: a Stability and Control Augmentation System, a trajectory tracking and a path following system. The systems have been compared with a corresponding baseline controller and showed several advantages in terms of performance, stability and robustness.

Nonlinear Control of Magnetically Actuated Spacecraft

The topic of this thesis is the feedback stabilization of the attitude of magnetically actuated spacecraft. The use of magnetic coils is an attractive solution for the generation of control torques on small satellites flying inclined low Earth orbits, since magnetic control systems are characterized by reduced weight and cost, higher reliability, and require less power with respect to other kinds of actuators. At the same time, the possibility of smooth modulation of control torques reduces coupling of the attitude control system with flexible modes, thus preserving pointing precision with respect to the case when pulse-modulated thrusters are used. The principle based on the interaction between the Earth's magnetic field and the magnetic field generated by the set of coils introduces an inherent nonlinearity, because control torques can be delivered only in a plane that is orthogonal to the direction of the geomagnetic field vector. In other words, the system is underactuated, because the rotational degrees of freedom of the spacecraft, modeled as a rigid body, exceed the number of independent control actions. The solution of the control issue for underactuated spacecraft is also interesting in the case of actuator failure, e.g. after the loss of a reaction-wheel in a three-axes stabilized spacecraft with no redundancy. The application of well known control strategies is no longer possible in this case for both regulation and tracking, so that new methods have been suggested for tackling this particular problem. The main contribution of this thesis is to propose continuous time-varying controllers that globally stabilize the attitude of a spacecraft, when magneto-torquers alone are used and when a momentum-wheel supports magnetic control in order to overcome the inherent underactuation. A kinematic maneuver planning scheme, stability analyses, and detailed simulation results are also provided, with new theoretical developments and particular attention toward application considerations.

Control of protein degradation pathways by BAG proteins and changes during aging

Many age-related neurodegenerative disorders such as Alzheimer’s disease, Parkinson’s disease, amyotrophic lateral sclerosis and polyglutamine disorders, including Huntington’s disease, are associated with the aberrant formation of protein aggregates. These protein aggregates and/or their precursors are believed to be causally linked to the pathogenesis of such protein conformation disorders, also referred to as proteinopathies. The accumulation of protein aggregates, frequently under conditions of an age-related increase in oxidative stress, implies the failure of protein quality control and the resulting proteome instability as an upstream event of proteinopathies. As aging is a main risk factor of many proteinopathies, potential alterations of protein quality control pathways that accompany the biological aging process could be a crucial factor for the onset of these disorders.rnrnThe focus of this dissertation lies on age-related alterations of protein quality control mechanisms that are regulated by the co-chaperones of the BAG (Bcl-2-associated athanogene) family. BAG proteins are thought to promote nucleotide exchange on Hsc/Hsp70 and to couple the release of chaperone-bound substrates to distinct down-stream cellular processes. The present study demonstrates that BAG1 and BAG3 are reciprocally regulated during aging leading to an increased BAG3 to BAG1 ratio in cellular models of replicative senescence as well as in neurons of the aging rodent brain. Furthermore, BAG1 and BAG3 were identified as key regulators of protein degradation pathways. BAG1 was found to be essential for effective degradation of polyubiquitinated proteins by the ubiquitin/proteasome system, possibly by promoting Hsc/Hsp70 substrate transfer to the 26S proteasome. In contrast, BAG3 was identified to stimulate the turnover of polyubiquitinated proteins by macroautophagy, a catabolic process mediated by lysosomal hydrolases. BAG3-regulated protein degradation was found to depend on the function of the ubiquitin-receptor protein SQSTM1 which is known to sequester polyubiquitinated proteins for macroautophagic degradation. It could be further demonstrated that SQSTM1 expression is tightly coupled to BAG3 expression and that BAG3 can physically interact with SQSTM1. Moreover, immunofluorescence-based microscopic analyses revealed that BAG3 co-localizes with SQSTM1 in protein sequestration structures suggesting a direct role of BAG3 in substrate delivery to SQSTM1 for macroautophagic degradation. Consistent with these findings, the age-related switch from BAG1 to BAG3 was found to determine that aged cells use the macroautophagic system more intensely for the turnover of polyubiquitinated proteins, in particular of insoluble, aggregated quality control substrates. Finally, in vivo expression analysis of macroautophagy markers in young and old mice as well as analysis of the lysosomal enzymatic activity strongly indicated that the macroautophagy pathway is also recruited in the nervous system during the organismal aging process.rnrnTogether these findings suggest that protein turnover by macroautophagy is gaining importance during the aging process as insoluble quality control substrates are increasingly produced that cannot be degraded by the proteasomal system. For this reason, a switch from the proteasome regulator BAG1 to the macroautophagy stimulator BAG3 occurs during cell aging. Hence, it can be concluded that the BAG3-mediated recruitment of the macroauto-phagy pathway is an important adaptation of the protein quality control system to maintain protein homeostasis in the presence of an enhanced pro-oxidant and aggregation-prone milieu characteristic of aging. Future studies will explore whether an impairment of this adaptation process may contribute to age-related proteinopathies.

Theoretical and Experimental Analysis of micro-CHP Energy Systems

In the framework of the micro-CHP (Combined Heat and Power) energy systems and the Distributed Generation (GD) concept, an Integrated Energy System (IES) able to meet the energy and thermal requirements of specific users, using different types of fuel to feed several micro-CHP energy sources, with the integration of electric generators of renewable energy sources (RES), electrical and thermal storage systems and the control system was conceived and built. A 5 kWel Polymer Electrolyte Membrane Fuel Cell (PEMFC) has been studied. Using experimental data obtained from various measurement campaign, the electrical and CHP PEMFC system performance have been determinate. The analysis of the effect of the water management of the anodic exhaust at variable FC loads has been carried out, and the purge process programming logic was optimized, leading also to the determination of the optimal flooding times by varying the AC FC power delivered by the cell. Furthermore, the degradation mechanisms of the PEMFC system, in particular due to the flooding of the anodic side, have been assessed using an algorithm that considers the FC like a black box, and it is able to determine the amount of not-reacted H2 and, therefore, the causes which produce that. Using experimental data that cover a two-year time span, the ageing suffered by the FC system has been tested and analyzed.