Low Correlated Sequences & Architectures and Algorithms for Analog-to-Information Converters: Theory, Design, Implementation and Applications.

Most electronic systems can be described in a very simplified way as an assemblage of analog and digital components put all together in order to perform a certain function. Nowadays, there is an increasing tendency to reduce the analog components, and to replace them by operations performed in the digital domain. This tendency has led to the emergence of new electronic systems that are more flexible, cheaper and robust. However, no matter the amount of digital process implemented, there will be always an analog part to be sorted out and thus, the step of converting digital signals into analog signals and vice versa cannot be avoided. This conversion can be more or less complex depending on the characteristics of the signals. Thus, even if it is desirable to replace functions carried out by analog components by digital processes, it is equally important to do so in a way that simplifies the conversion from digital to analog signals and vice versa. In the present thesis, we have study strategies based on increasing the amount of processing in the digital domain in such a way that the implementation of analog hardware stages can be simplified. To this aim, we have proposed the use of very low quantized signals, i.e. 1-bit, for the acquisition and for the generation of particular classes of signals.

Coordination and Control of Autonomous Mobile Robots Swarms by using Particle Swarm Optimization Algorithm and Consensus Theory

This thesis presents some different techniques designed to drive a swarm of robots in an a-priori unknown environment in order to move the group from a starting area to a final one avoiding obstacles. The presented techniques are based on two different theories used alone or in combination: Swarm Intelligence (SI) and Graph Theory. Both theories are based on the study of interactions between different entities (also called agents or units) in Multi- Agent Systems (MAS). The first one belongs to the Artificial Intelligence context and the second one to the Distributed Systems context. These theories, each one from its own point of view, exploit the emergent behaviour that comes from the interactive work of the entities, in order to achieve a common goal. The features of flexibility and adaptability of the swarm have been exploited with the aim to overcome and to minimize difficulties and problems that can affect one or more units of the group, having minimal impact to the whole group and to the common main target. Another aim of this work is to show the importance of the information shared between the units of the group, such as the communication topology, because it helps to maintain the environmental information, detected by each single agent, updated among the swarm. Swarm Intelligence has been applied to the presented technique, through the Particle Swarm Optimization algorithm (PSO), taking advantage of its features as a navigation system. The Graph Theory has been applied by exploiting Consensus and the application of the agreement protocol with the aim to maintain the units in a desired and controlled formation. This approach has been followed in order to conserve the power of PSO and to control part of its random behaviour with a distributed control algorithm like Consensus.

Automotive diesel engine transient operation: modeling, optimization and control

Traditionally, the study of internal combustion engines operation has focused on the steady-state performance. However, the daily driving schedule of automotive engines is inherently related to unsteady conditions. There are various operating conditions experienced by (diesel) engines that can be classified as transient. Besides the variation of the engine operating point, in terms of engine speed and torque, also the warm up phase can be considered as a transient condition. Chapter 2 has to do with this thermal transient condition; more precisely the main issue is the performance of a Selective Catalytic Reduction (SCR) system during cold start and warm up phases of the engine. The proposal of the underlying work is to investigate and identify optimal exhaust line heating strategies, to provide a fast activation of the catalytic reactions on SCR. Chapters 3 and 4 focus the attention on the dynamic behavior of the engine, when considering typical driving conditions. The common approach to dynamic optimization involves the solution of a single optimal-control problem. However, this approach requires the availability of models that are valid throughout the whole engine operating range and actuator ranges. In addition, the result of the optimization is meaningful only if the model is very accurate. Chapter 3 proposes a methodology to circumvent those demanding requirements: an iteration between transient measurements to refine a purpose-built model and a dynamic optimization which is constrained to the model validity region. Moreover all numerical methods required to implement this procedure are presented. Chapter 4 proposes an approach to derive a transient feedforward control system in an automated way. It relies on optimal control theory to solve a dynamic optimization problem for fast transients. From the optimal solutions, the relevant information is extracted and stored in maps spanned by the engine speed and the torque gradient.

Design and Control of Robotic Hands

The application of dexterous robotic hands out of research laboratories has been limited by the intrinsic complexity that these devices present. This is directly reflected as an economically unreasonable cost and a low overall reliability. Within the research reported in this thesis it is shown how the problem of complexity in the design of robotic hands can be tackled, taking advantage of modern technologies (i.e. rapid prototyping), leading to innovative concepts for the design of the mechanical structure, the actuation and sensory systems. The solutions adopted drastically reduce the prototyping and production costs and increase the reliability, reducing the number of parts required and averaging their single reliability factors. In order to get guidelines for the design process, the problem of robotic grasp and manipulation by a dual arm/hand system has been reviewed. In this way, the requirements that should be fulfilled at hardware level to guarantee successful execution of the task has been highlighted. The contribution of this research from the manipulation planning side focuses on the redundancy resolution that arise in the execution of the task in a dexterous arm/hand system. In literature the problem of coordination of arm and hand during manipulation of an object has been widely analyzed in theory but often experimentally demonstrated in simplified robotic setup. Our aim is to cover the lack in the study of this topic and experimentally evaluate it in a complex system as a anthropomorphic arm hand system.

Dynamics and control issues of multi-rotor platforms

This thesis deals with the analytic study of dynamics of Multi--Rotor Unmanned Aerial Vehicles. It is conceived to give a set of mathematical instruments apt to the theoretical study and design of these flying machines. The entire work is organized in analogy with classical academic texts about airplane flight dynamics. First, the non--linear equations of motion are defined and all the external actions are modeled, with particular attention to rotors aerodynamics. All the equations are provided in a form, and with personal expedients, to be directly exploitable in a simulation environment. This has requited an answer to questions like the trim of such mathematical systems. All the treatment is developed aiming at the description of different multi--rotor configurations. Then, the linearized equations of motion are derived. The computation of the stability and control derivatives of the linear model is carried out. The study of static and dynamic stability characteristics is, thus, addressed, showing the influence of the various geometric and aerodynamic parameters of the machine and in particular of the rotors. All the theoretic results are finally utilized in two interesting cases. One concerns the design of control systems for attitude stabilization. The linear model permits the tuning of linear controllers gains and the non--linear model allows the numerical testing. The other case is the study of the performances of an innovative configuration of quad--rotor aircraft. With the non--linear model the feasibility of maneuvers impossible for a traditional quad--rotor is assessed. The linear model is applied to the controllability analysis of such an aircraft in case of actuator block.

Relevance of the pig stomach for the detection of dietary factors and gut maturation and control

In this thesis two approaches were applied to achieve a double general objective. The first chapter was dedicated to the study of the distribution of the expression of genes of several bitter and fat receptor in several gastrointestinal tracts. A set of 7 genes for bitter taste and for 3 genes for fat taste was amplified with real-time PCR from mRNA extracted from 5 gastrointestinal segments of weaned pigs. The presence of gene expression for several chemosensing receptors for bitter and fat taste in different compartments of the stomach confirms that this organ should be considered a player for the early detection of bolus composition. In the second chapter we investigated in young pigs the distribution of butyrate-sensing olfactory receptor (OR51E1) receptor along the GIT, its relation with some endocrine markers, its variation with age, and after interventions affecting the gut environment and intestinal microbiota in piglets and in different tissues. Our results indicate that OR51E1 is strictly related to the normal GIT enteroendocrine activity. In the third chapter we investigated the differential gene expression between oxyntic and pyloric mucosa in seven starter pigs. The obtained data indicate that there is significant differential gene exression between oxintic of the young pig and pyloric mucosa and further functional studies are needed to confirm their physiological importance. In the last chapter, thymol, that has been proposed as an oral alternative to antibiotics in the feed of pigs and broilers, was introduced directly into the stomach of 8 weaned pigs and sampled for gastric oxyntic and pyloric mucosa. The analysis of the whole transcript expression shoes that the stimulation of gastric proliferative activity and the control of digestive activity by thymol can influence positively gastric maturation and function in the weaned pigs.

Insights on epidemiology and control of Marek’s disease through traditional and novel molecular tools

Marek's disease (MD) is a contagious, lymphoproliferative and neuropathic disease of poultry caused by a ubiquitous lymphotropic and oncogenic virus, Gallid alphaherpesvirus 2 (GaHV-2). MD has been reported in all poultry-rearing countries and is among the viral diseases with the highest economic impact in the poultry industry worldwide, including Italy. MD has been also recognized as one of the leading causes of mortality in backyard poultry. The present doctoral thesis aimed at exploring Marek's disease virus molecular epidemiology in Italian commercial and backyard chicken flocks and, for the first time, in commercial turkeys affected by clinical MD. Molecular biology techniques targeting the full-length meq gene, the major GaHV-2 oncogene, were used to detect and characterize the circulating GaHV-2 strains searching for genetic markers of virulence. A final study focused on the development of rapid, sensitive, and species-specific loop-mediated isothermal amplification assays coupled with a lateral flow device readout for the detection of conventional and recombinant HVT-based vaccines is included in the thesis. HVT vaccines, currently used to protect chickens from MD, are referred to as "leaky", as they do not impede the infection, replication, and shedding of field GaHV-2: vaccinal and field viruses can coexist in the vaccinated host and molecular tests able to discriminate between GaHV-2 and HVT are required. These new simple, fast, and accurate tests for the monitoring of MD vaccination success in the field could be greatly beneficial for field veterinarians, small laboratories, and more broadly for resource-limited settings.

Design and testing of innovative, artificial intelligence-based techniques to model and control the combustion process and to reduce the Co2 emissions in modern, high-performance, gasoline direct injection engines

This work deals with the development of calibration procedures and control systems to improve the performance and efficiency of modern spark ignition turbocharged engines. The algorithms developed are used to optimize and manage the spark advance and the air-to-fuel ratio to control the knock and the exhaust gas temperature at the turbine inlet. The described work falls within the activity that the research group started in the previous years with the industrial partner Ferrari S.p.a. . The first chapter deals with the development of a control-oriented engine simulator based on a neural network approach, with which the main combustion indexes can be simulated. The second chapter deals with the development of a procedure to calibrate offline the spark advance and the air-to-fuel ratio to run the engine under knock-limited conditions and with the maximum admissible exhaust gas temperature at the turbine inlet. This procedure is then converted into a model-based control system and validated with a Software in the Loop approach using the engine simulator developed in the first chapter. Finally, it is implemented in a rapid control prototyping hardware to manage the combustion in steady-state and transient operating conditions at the test bench. The third chapter deals with the study of an innovative and cheap sensor for the in-cylinder pressure measurement, which is a piezoelectric washer that can be installed between the spark plug and the engine head. The signal generated by this kind of sensor is studied, developing a specific algorithm to adjust the value of the knock index in real-time. Finally, with the engine simulator developed in the first chapter, it is demonstrated that the innovative sensor can be coupled with the control system described in the second chapter and that the performance obtained could be the same reachable with the standard in-cylinder pressure sensors.

New knowledge, diagnostic and control tools to limit the impact of viral nervous necrosis (VNN) in the Mediterranean aquaculture sector

The role of aquaculture in satisfying the global seafood demand is essential. The expansion of the aquaculture sector and the intensification of its activities have enhanced the circulation of infectious agents. Among these, the nervous necrosis virus (NNV) represents the most widespread in the Mediterranean basin. The NNV is responsible for a severe neuropathological condition named viral nervous necrosis (VNN), impacting hugely on fish farms due to the serious disease-associated losses. Therefore, it is fundamental to develop new strategies to limit the impact of VNN in this area, interconnecting several aspects of disease management, diagnosis and prevention. This PhD thesis project, focusing on aquatic animals’ health, deals with these topics. The first two chapters expand the knowledge on VNN epidemiology and distribution, showing the possibility of interspecies transmission, persistent infections and a potential carrier role for invertebrates. The third study expands the horizon of VNN diagnosis, by developing a quick and affordable multiplex RT-PCR able to detect and simultaneously discriminate between NNV variants, reducing considerably the time and costs of genotyping. The fourth study, with the development of a fluorescent in situ hybridization technique and its application to aquatic vertebrates and invertebrates’ tissues, contributes to expand the knowledge on NNV distribution at cellular level, localizing also the replication site of the virus. Finally, the last study dealing with an in vitro evaluation of the NNV susceptibility to a commercial biocide, stress the importance to implement proper disinfectant procedures in fish farms to prevent virus spread and disease outbreaks.

Development and experimental validation of a knock induced damage model and real-time implementation of model-based strategies to control knock intensity in boosted gasoline engines

This PhD thesis reports the main activities carried out during the 3 years long “Mechanics and advanced engineering sciences” course, at the Department of Industrial Engineering of the University of Bologna. The research project title is “Development and analysis of high efficiency combustion systems for internal combustion engines” and the main topic is knock, one of the main challenges for boosted gasoline engines. Through experimental campaigns, modelling activity and test bench validation, 4 different aspects have been addressed to tackle the issue. The main path goes towards the definition and calibration of a knock-induced damage model, to be implemented in the on-board control strategy, but also usable for the engine calibration and potentially during the engine design. Ionization current signal capabilities have been investigated to fully replace the pressure sensor, to develop a robust on-board close-loop combustion control strategy, both in knock-free and knock-limited conditions. Water injection is a powerful solution to mitigate knock intensity and exhaust temperature, improving fuel consumption; its capabilities have been modelled and validated at the test bench. Finally, an empiric model is proposed to predict the engine knock response, depending on several operating condition and control parameters, including injected water quantity.

Fault detection, diagnosis and active fault tolerant control for a satellite attitude control system

Modern control systems are becoming more and more complex and control algorithms more and more sophisticated. Consequently, Fault Detection and Diagnosis (FDD) and Fault Tolerant Control (FTC) have gained central importance over the past decades, due to the increasing requirements of availability, cost efficiency, reliability and operating safety. This thesis deals with the FDD and FTC problems in a spacecraft Attitude Determination and Control System (ADCS). Firstly, the detailed nonlinear models of the spacecraft attitude dynamics and kinematics are described, along with the dynamic models of the actuators and main external disturbance sources. The considered ADCS is composed of an array of four redundant reaction wheels. A set of sensors provides satellite angular velocity, attitude and flywheel spin rate information. Then, general overviews of the Fault Detection and Isolation (FDI), Fault Estimation (FE) and Fault Tolerant Control (FTC) problems are presented, and the design and implementation of a novel diagnosis system is described. The system consists of a FDI module composed of properly organized model-based residual filters, exploiting the available input and output information for the detection and localization of an occurred fault. A proper fault mapping procedure and the nonlinear geometric approach are exploited to design residual filters explicitly decoupled from the external aerodynamic disturbance and sensitive to specific sets of faults. The subsequent use of suitable adaptive FE algorithms, based on the exploitation of radial basis function neural networks, allows to obtain accurate fault estimations. Finally, this estimation is actively exploited in a FTC scheme to achieve a suitable fault accommodation and guarantee the desired control performances. A standard sliding mode controller is implemented for attitude stabilization and control. Several simulation results are given to highlight the performances of the overall designed system in case of different types of faults affecting the ADCS actuators and sensors.

Methods for objective and interpretative evaluation of function and motor control: gait in perturbed condition and in the aquatic therapy

Gait analysis allows to characterize motor function, highlighting deviations from normal motor behavior related to an underlying pathology. The widespread use of wearable inertial sensors has opened the way to the evaluation of ecological gait, and a variety of methodological approaches and algorithms have been proposed for the characterization of gait from inertial measures (e.g. for temporal parameters, motor stability and variability, specific pathological alterations). However, no comparative analysis of their performance (i.e. accuracy, repeatability) was available yet, in particular, analysing how this performance is affected by extrinsic (i.e. sensor location, computational approach, analysed variable, testing environmental constraints) and intrinsic (i.e. functional alterations resulting from pathology) factors. The aim of the present project was to comparatively analyze the influence of intrinsic and extrinsic factors on the performance of the numerous algorithms proposed in the literature for the quantification of specific characteristics (i.e. timing, variability/stability) and alterations (i.e. freezing) of gait. Considering extrinsic factors, the influence of sensor location, analyzed variable, and computational approach on the performance of a selection of gait segmentation algorithms from a literature review was analysed in different environmental conditions (e.g. solid ground, sand, in water). Moreover, the influence of altered environmental conditions (i.e. in water) was analyzed as referred to the minimum number of stride necessary to obtain reliable estimates of gait variability and stability metrics, integrating what already available in the literature for over ground gait in healthy subjects. Considering intrinsic factors, the influence of specific pathological conditions (i.e. Parkinson’s Disease) was analyzed as affecting the performance of segmentation algorithms, with and without freezing. Finally, the analysis of the performance of algorithms for the detection of gait freezing showed how results depend on the domain of implementation and IMU position.