Optimal control of non-linear systems through hybrid cell-mapping/artificial-neural-networks techniques

In this paper, a real-time optimal control technique for non-linear plants is proposed. The control system makes use of the cell-mapping (CM) techniques, widely used for the global analysis of highly non-linear systems. The CM framework is employed for designing approximate optimal controllers via a control variable discretization. Furthermore, CM-based designs can be improved by the use of supervised feedforward artificial neural networks (ANNs), which have proved to be universal and efficient tools for function approximation, providing also very fast responses. The quantitative nature of the approximate CM solutions fits very well with ANNs characteristics. Here, we propose several control architectures which combine, in a different manner, supervised neural networks and CM control algorithms. On the one hand, different CM control laws computed for various target objectives can be employed for training a neural network, explicitly including the target information in the input vectors. This way, tracking problems, in addition to regulation ones, can be addressed in a fast and unified manner, obtaining smooth, averaged and global feedback control laws. On the other hand, adjoining CM and ANNs are also combined into a hybrid architecture to address problems where accuracy and real-time response are critical. Finally, some optimal control problems are solved with the proposed CM, neural and hybrid techniques, illustrating their good performance.

Inhibition of nitro-oxidative stress attenuates pulmonary and systemic injury induced by high-tidal volume mechanical ventilation

Mechanisms contributing to pulmonary and systemic injury induced by high tidal volume (VT) mechanical ventilation are not well known. We tested the hypothesis that increased peroxynitrite formation is involved in organ injury and dysfunction induced by mechanical ventilation. Male Sprague-Dawley rats were subject to low- (VT, 9 mL/kg; positive end-expiratory pressure, 5 cmH2O) or high- (VT, 25 mL/kg; positive end-expiratory pressure, 0 cmH2O) VT mechanical ventilation for 120 min, and received 1 of 3 treatments: 3-aminobenzamide (3-AB, 10 mg/kg, intravenous, a poly adenosine diphosphate ribose polymerase [PARP] inhibitor), or the metalloporphyrin manganese(III) tetrakis(1-methyl-4-pyridyl)porphyrin (MnTMPyP, 5 mg/kg intravenous, a peroxynitrite scavenger), or no treatment (control group), 30 min before starting the mechanical ventilation protocol (n = 8 per group, 6 treatment groups). We measured mean arterial pressure, peak inspiratory airway pressure, blood chemistry, and gas exchange. Oxidation (fluorescence for oxidized dihydroethidium), protein nitration (immunofluorescence and Western blot for 3-nitrotyrosine), PARP protein (Western blot) and gene expression of the nitric oxide (NO) synthase (NOS) isoforms (quantitative real-time reverse transcription polymerase chain reaction) were measured in lung and vascular tissue. Lung injury was quantified by light microscopy. High-VT mechanical ventilation was associated with hypotension, increased peak inspiratory airway pressure, worsened oxygenation; oxidation and protein nitration in lung and aortic tissue; increased PARP protein in lung; up-regulation of NOS isoforms in lung tissue; signs of diffuse alveolar damage at histological examination. Treatment with 3AB or MnTMPyP attenuated the high-VT mechanical ventilation-induced changes in pulmonary and cardiovascular function; down-regulated the expression of NOS1, NOS2, and NOS3; decreased oxidation and nitration in lung and aortic tissue; and attenuated histological changes. Increased peroxynitrite formation is involved in mechanical ventilation-induced pulmonary and vascular dysfunction.

Studies of sustainable strategies to control phytopathogen agents

Choosing natural enemies to suppress pest population has been for a long the key of biological control. Overtime the term biological control has also been applied to the use of suppressive soils, bio-disinfection and biopesticides. Biological control agents (BCA) and natural compounds, extracted or fermented from various sources, are the resources for containing phytopathogens. BCA can act through direct antagonism mechanisms or inducing hypovirulence of the pathogen. The first part of the thesis focused on mycoviruses infecting phytopathogenic fungi belonging to the genus Fusarium. The development of new approaches capable of faster dissecting the virome of filamentous fungi samples was performed. The semiconductor-based sequencer Ion Torrent™ and the nanopore-based sequencer MinION have been exploited to analyze DNA and RNA referable to viral genomes. Comparison with GeneBank accessions and sequence analysis allowed to identify more than 40 putative viral species, some of these mycovirus genera have been studied as inducers of hypovirulence in several phytopathogenic fungi, therefore future works will focus on the comparison of the morphology and physiology of the fungal strain infected and cured by the viruses identified and their possible use as a biocontrol agent. In a second part of the thesis the potential of botanical pesticides has been evaluated for the biocontrol of phloem limited phytopathogens such as phytoplasmas. The only active compounds able to control phytoplasmas are the antibiotic oxytetracyclines and in vitro direct and fast screening of new antimicrobials compounds on media is almost impossible due to the difficulty to culture phytoplasmas. For this reason, a simple and reliable screening method was developed to evaluate the effects of antimicrobials directly on phytoplasmas by an “ex-vivo” approach. Using scanning electron microscopy (SEM) in parallel with molecular tools (ddRT-PCR), the direct activity of tetracyclines on phytoplasma cells was verified, identifying also a promising compound showing similar activity.

Development and testing of innovative methodologies for modelling and control of normal and knocking combustion and implementation of novel rapid prototyping solutions

The thesis work deals with topics that led to the development of innovative control-oriented models and control algorithms for modern gasoline engines. Knock in boosted spark ignition engines is the widest topic discussed in this document because it remains one of the most limiting factors for maximizing combustion efficiency in this kind of engine. First chapter is thus focused on knock and a wide literature review is proposed to summarize the preliminary knowledge that even represents the background and the reference for discussed activities. Most relevant results achieved during PhD course in the field of knock modelling and control are then presented, describing every control-oriented model that led to the development of an adaptive model-based combustion control system. The complete controller has been developed in the context of the collaboration with Ferrari GT and it allowed to completely redefine the knock intensity evaluation as well as the combustion phase control. The second chapter is focused on the activity related to a prototyping Port Water Injection system that has been developed and tested on a turbocharged spark ignition engine, within the collaboration with Magneti Marelli. Such system and the effects of injected water on the combustion process were then modeled in a 1-D simulation environment (GT Power). Third chapter shows the development and validation of a control-oriented model for the real-time calculation of exhaust gas temperature that represents another important limitation to the performance increase in modern boosted engines. Indeed, modelling of exhaust gas temperature and thermocouple behavior are themes that play a key role in the optimization of combustion and catalyst efficiency.

Employment of Real-Time/FPGA Architectures for Test and Control of Automotive Engines

Nowadays the production of increasingly complex and electrified vehicles requires the implementation of new control and monitoring systems. This reason, together with the tendency of moving rapidly from the test bench to the vehicle, leads to a landscape that requires the development of embedded hardware and software to face the application effectively and efficiently. The development of application-based software on real-time/FPGA hardware could be a good answer for these challenges: FPGA grants parallel low-level and high-speed calculation/timing, while the Real-Time processor can handle high-level calculation layers, logging and communication functions with determinism. Thanks to the software flexibility and small dimensions, these architectures can find a perfect collocation as engine RCP (Rapid Control Prototyping) units and as smart data logger/analyser, both for test bench and on vehicle application. Efforts have been done for building a base architecture with common functionalities capable of easily hosting application-specific control code. Several case studies originating in this scenario will be shown; dedicated solutions for protype applications have been developed exploiting a real-time/FPGA architecture as ECU (Engine Control Unit) and custom RCP functionalities, such as water injection and testing hydraulic brake control.

Modelling, control and testing of internal combustion engines to minimize consumption and pollutant emissions

The objective of the PhD thesis was to research technologies and strategies to reduce fuel consumption and pollutants emission produced by internal combustion engines. In order to meet this objective my activity was focused on the research of advanced controls based on cylinder pressure feedback. These types of control strategies were studied because they present promising results in terms of engine efficiency enhancement. In the PhD dissertation two study cases are presented. The first case is relative to a control strategy to be used at the test bench for the optimisation of the spark advance calibration of motorcycle Engine. The second case is relative to a control strategy to be used directly on board of mining engines with the objective or reducing the engine consumption and correct ageing effects. In both cases the strategies proved to be effective but their implementation required the use of specific toolchains for the measure of the cylinder pressure feedback that for a matter of cost makes feasible the strategy use only for applications: • At test bench • In small-markets like large off-road engines The major bottleneck that prevents the implementation of these strategies on mass production is the cost of cylinder pressure sensor. In order to tackle this issue, during the PhD research, the development of a low-cost sensor for the estimation of cylinder pressure was studied. The prototype was a piezo-electric washer designed to replace the standard spark-plug washer or high-pressure fuel injectors gasket. From the data analysis emerged the possibility to use the piezo-electric prototype signal to evaluate with accuracy several combustion metrics compatible for the implementation of advanced control strategies in on-board applications. Overall, the research shows that advanced combustion controls are feasible and beneficial, not only at the test bench or on stationary engines, but also in mass-produced engines.

Modelling, simulation and control of rotary-wing aircraft in multi-agent scenario

The topic of this thesis is the design and the implementation of mathematical models and control system algorithms for rotary-wing unmanned aerial vehicles to be used in cooperative scenarios. The use of rotorcrafts has many attractive advantages, since these vehicles have the capability to take-off and land vertically, to hover and to move backward and laterally. Rotary-wing aircraft missions require precise control characteristics due to their unstable and heavy coupling aspects. As a matter of fact, flight test is the most accurate way to evaluate flying qualities and to test control systems. However, it may be very expensive and/or not feasible in case of early stage design and prototyping. A good compromise is made by a preliminary assessment performed by means of simulations and a reduced flight testing campaign. Consequently, having an analytical framework represents an important stage for simulations and control algorithm design. In this work mathematical models for various helicopter configurations are implemented. Different flight control techniques for helicopters are presented with theoretical background and tested via simulations and experimental flight tests on a small-scale unmanned helicopter. The same platform is used also in a cooperative scenario with a rover. Control strategies, algorithms and their implementation to perform missions are presented for two main scenarios. One of the main contributions of this thesis is to propose a suitable control system made by a classical PID baseline controller augmented with L1 adaptive contribution. In addition a complete analytical framework and the study of the dynamics and the stability of a synch-rotor are provided. At last, the implementation of cooperative control strategies for two main scenarios that include a small-scale unmanned helicopter and a rover.

Magnetic Resonance Imaging-Derived biomarkers of Isocitrate-Dehydrogenase mutation in diffuse gliomas: a conventional MR and Diffusion Weighted Imaging study.

The introduction of molecular criteria into the classification of diffuse gliomas has added interesting practical implications to glioma management. This has created a new clinical need for correlating imaging characteristics with glioma genotypes, also known as radiogenomics or imaging genomics. Whilst many studies have primarily focused on the use of advanced magnetic resonance imaging (MRI) techniques for radiogenomics purposes, conventional MRI sequences still remain the reference point in the study and characterization of brain tumours. Moreover, a different approach may rely on diffusion-weighted imaging (DWI) usage, which is considered a “conventional” sequence in line with recently published directions on glioma imaging. In a non-invasive way, it can provide direct insight into the microscopic physical properties of tissues. Considering that Isocitrate-Dehydrogenase gene mutations may reflect alterations in metabolism, cellularity, and angiogenesis, which may manifest characteristic features on an MRI, the identification of specific MRI biomarkers could be of great interest in managing patients with brain gliomas. My study aimed to evaluate the presence of specific MRI-derived biomarkers of IDH molecular status through conventional MRI and DWI sequences.

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.

On the motion planning & control of nonlinear robotic systems

In the last decades, we saw a soaring interest in autonomous robots boosted not only by academia and industry, but also by the ever in- creasing demand from civil users. As a matter of fact, autonomous robots are fast spreading in all aspects of human life, we can see them clean houses, navigate through city traffic, or harvest fruits and vegetables. Almost all commercial drones already exhibit unprecedented and sophisticated skills which makes them suitable for these applications, such as obstacle avoidance, simultaneous localisation and mapping, path planning, visual-inertial odometry, and object tracking. The major limitations of such robotic platforms lie in the limited payload that can carry, in their costs, and in the limited autonomy due to finite battery capability. For this reason researchers start to develop new algorithms able to run even on resource constrained platforms both in terms of computation capabilities and limited types of endowed sensors, focusing especially on very cheap sensors and hardware. The possibility to use a limited number of sensors allowed to scale a lot the UAVs size, while the implementation of new efficient algorithms, performing the same task in lower time, allows for lower autonomy. However, the developed robots are not mature enough to completely operate autonomously without human supervision due to still too big dimensions (especially for aerial vehicles), which make these platforms unsafe for humans, and the high probability of numerical, and decision, errors that robots may make. In this perspective, this thesis aims to review and improve the current state-of-the-art solutions for autonomous navigation from a purely practical point of view. In particular, we deeply focused on the problems of robot control, trajectory planning, environments exploration, and obstacle avoidance.

Integration of ROS for the control of industrial robotic systems in a proprietary environment

The paper deals with the integration of ROS, in the proprietary environment of the Marchesini Group company, for the control of industrial robotic systems. The basic tools of this open-source software are deeply studied to model a full proprietary Pick and Place manipulator inside it, and to develop custom ROS nodes to calculate trajectories; speaking of which, the URDF format is the standard to represent robots in ROS and the motion planning framework MoveIt offers user-friendly high-level methods. The communication between ROS and the Marchesini control architecture is established using the OPC UA standard; the tasks computed are transmitted offline to the PLC, supervisor controller of the physical robot, because the performances of the protocol don’t allow any kind of active control by ROS. Once the data are completely stored at the Marchesini side, the industrial PC makes the real robot execute a trajectory computed by MoveIt, so that it replicates the behaviour of the simulated manipulator in Rviz. Multiple experiments are performed to evaluate in detail the potential of ROS in the planning of movements for the company proprietary robots. The project ends with a small study regarding the use of ROS as a simulation platform. First, it is necessary to understand how a robotic application of the company can be reproduced in the Gazebo real world simulator. Then, a ROS node extracts information and examines the simulated robot behaviour, through the subscription to specific topics.

Application of the Extended Kalman filter for speed sensorless control of PM synchronous machines

The increasing interest in the decarbonization process led to a rapidly growing trend of electrification strategies in the automotive industry. In particular, OEMs are pushing towards the development and production of efficient electric vehicles. Moreover, research on electric motors and their control are exploding in popularity. The increase of computational power in embedded control hardware is allowing the development of new control algorithm, such as sensorless control strategy. Such control strategy allows the reduction of the number of sensors, which implies reduced costs and increased system reliability. The thesis objective is to realize a sensorless control for high-performance automotive motors. Several algorithms for rotor angle observers are implemented in the MATLAB and Simulink environment, with emphasis on the Kalman observer. One of the Kalman algorithms already available in the literature has been selected, implemented and benchmarked, with emphasis on its comparison with the Sliding Mode observer. Different models characterized by increasing levels of complexity are simulated. A simplified synchronous motor with ”constant parameters”, controlled by an ideal inverter is first analyzed; followed by a complete model defined by real motor maps, and controlled by a switching inverter. Finally, it was possible to test the developed algorithm on a real electric motor mounted on a test bench. A wide range of different electric motors have been simulated, which led to an exhaustive review of the sensorless control algorithm. The final results underline the capability of the Kalman observer to effectively control the motor on a real test bench.

Design and Implementation of Single phase 230V to Three Phase Inverter Based on the Embedded System STM-32 Applied to motor control

In the field of Power Electronics, several types of motor control systems have been developed using STM microcontroller and power boards. In both industrial power applications and domestic appliances, power electronic inverters are widely used. Inverters are used to control the torque, speed, and position of the rotor in AC motor drives. An inverter delivers constant-voltage and constant-frequency power in uninterruptible power sources. Because inverter power supplies have a high-power consumption and low transfer efficiency rate, a three-phase sine wave AC power supply was created using the embedded system STM32, which has low power consumption and efficient speed. It has the capacity of output frequency of 50 Hz and the RMS of line voltage. STM32 embedded based Inverter is a power supply that integrates, reduced, and optimized the power electronics application that require hardware system, software, and application solution, including power architecture, techniques, and tools, approaches capable of performance on devices and equipment. Power inverters are currently used and implemented in green energy power system with low energy system such as sensors or microcontroller to perform the operating function of motors and pumps. STM based power inverter is efficient, less cost and reliable. My thesis work was based on STM motor drives and control system which can be implemented in a gas analyser for operating the pumps and motors. It has been widely applied in various engineering sectors due to its ability to respond to adverse structural changes and improved structural reliability. The present research was designed to use STM Inverter board on low power MCU such as NUCLEO with some practical examples such as Blinking LED, and PWM. Then we have implemented a three phase Inverter model with Steval-IPM08B board, which converter single phase 230V AC input to three phase 380 V AC output, the output will be useful for operating the induction motor.

Cardiac Magnetic Resonance Assessment Of Interstitial Myocardial Fibrosis And Cardiomyocyte Hypertrophy In Hypertensive Mice Treated With Spironolactone.

Nearly 50% of patients with heart failure (HF) have preserved LV ejection fraction, with interstitial fibrosis and cardiomyocyte hypertrophy as early manifestations of pressure overload. However, methods to assess both tissue characteristics dynamically and noninvasively with therapy are lacking. We measured the effects of mineralocorticoid receptor blockade on tissue phenotypes in LV pressure overload using cardiac magnetic resonance (CMR). Mice were randomized to l-nitro-ω-methyl ester (l-NAME, 3 mg/mL in water; n=22), or l-NAME with spironolactone (50 mg/kg/day in subcutaneous pellets; n=21). Myocardial extracellular volume (ECV; marker of diffuse interstitial fibrosis) and the intracellular lifetime of water (τic; marker of cardiomyocyte hypertrophy) were determined by CMR T1 imaging at baseline and after 7 weeks of therapy alongside histological assessments. Administration of l-NAME induced hypertensive heart disease in mice, with increases in mean arterial pressure, LV mass, ECV, and τic compared with placebo-treated controls, while LV ejection fraction was preserved (>50%). In comparison, animals receiving both spironolactone and l-NAME (l-NAME+S) showed less concentric remodeling, and a lower myocardial ECV and τic, indicating decreased interstitial fibrosis and cardiomyocyte hypertrophy (ECV: 0.43 ± 0.09 for l-NAME versus 0.25 ± 0.03 for l-NAME+S, P<0.001; τic: 0.42 ± 0.11 for l-NAME groups versus 0.12 ± 0.05 for l-NAME+S group). Mice treated with a combination of l-NAME and spironolactone were similar to placebo-treated controls at 7 weeks. Spironolactone attenuates interstitial fibrosis and cardiomyocyte hypertrophy in hypertensive heart disease. CMR can phenotype myocardial tissue remodeling in pressure-overload, furthering our understanding of HF progression.

The Influence Of Altered Occlusion On Pro-inflammatory Cytokine Levels In The Tmj Synovial Tissues Of Rats.

The aim of this study was to evaluate whether altered occlusion affects both the condylar cartilage thickness and the cytokine levels of the TMJs of rats. Thirty adult-male rats (n=30) were randomly assigned to three experimental conditions: a control group that underwent sham operations with unaltered occlusion; an FPDM group that underwent functional posterior displacement of the mandible that was induced by an incisor guiding appliance; and an iOVD group in which the increased occlusal vertical dimension was induced in the molars. The rats were subjected to the FPDM or iOVD model for 14 days and then killed. Both the right and left TMJs were removed and randomly assigned to examination with staining or immunoassay techniques. Toluidine blue staining was used to measure the thicknesses of the four layers of the articular cartilage (i.e., the fibrous, proliferating, mature, and hypertrophic layers). ELISA assays were used to assess the concentrations of the pro-inflammatory cytokines IL-1α, IL-1β, IL-6, and tumour necrosis factor (TNF-α). The measurements of the articular cartilage layers and cytokine concentrations were analyzed with ANOVA and Tukey's tests and Kruskal-Wallis and Dunn tests, respectively (α=5%). The thickness of articular cartilage in the FPDM group (0.3±0.03mm) was significantly greater than those of the control (0.2±0.01mm) and iOVD (0.25±0.03mm) groups. No significant difference was observed between the control and iOVD groups. The four articular cartilage layers were thicker in the FPDM group than in the control and iOVD groups, and the latter two groups did not differ one from each other. Both the FPDM and iOVD groups exhibited higher cytokine levels than did the control (p<0.05) group. Compared to the FPDM group, the iOVD group exhibited significantly higher levels of IL-1β and TNF-α. Both models induced inflammation in the TMJ and caused significant structural changes in the TMJ and surrounding tissues.