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.

Development and testing of methodologies for the control and diagnosis of innovative combustion systems

In pursuit of aligning with the European Union's ambitious target of achieving a carbon-neutral economy by 2050, researchers, vehicle manufacturers, and original equipment manufacturers have been at the forefront of exploring cutting-edge technologies for internal combustion engines. The introduction of these technologies has significantly increased the effort required to calibrate the models implemented in the engine control units. Consequently the development of tools that reduce costs and the time required during the experimental phases, has become imperative. Additionally, to comply with ever-stricter limits on 〖"CO" 〗_"2" emissions, it is crucial to develop advanced control systems that enhance traditional engine management systems in order to reduce fuel consumption. Furthermore, the introduction of new homologation cycles, such as the real driving emissions cycle, compels manufacturers to bridge the gap between engine operation in laboratory tests and real-world conditions. Within this context, this thesis showcases the performance and cost benefits achievable through the implementation of an auto-adaptive closed-loop control system, leveraging in-cylinder pressure sensors in a heavy-duty diesel engine designed for mining applications. Additionally, the thesis explores the promising prospect of real-time self-adaptive machine learning models, particularly neural networks, to develop an automatic system, using in-cylinder pressure sensors for the precise calibration of the target combustion phase and optimal spark advance in a spark-ignition engines. To facilitate the application of these combustion process feedback-based algorithms in production applications, the thesis discusses the results obtained from the development of a cost-effective sensor for indirect cylinder pressure measurement. Finally, to ensure the quality control of the proposed affordable sensor, the thesis provides a comprehensive account of the design and validation process for a piezoelectric washer test system.

Motion Control of an Advanced Electric Implement for Agricultural Autonomous Vehicles

Nowadays, the development of intelligent and autonomous vehicles used to perform agricultural activities is essential to improve quantity and quality of agricultural productions. Moreover, with automation techniques it is possible to reduce the usage of agrochemicals and minimize the pollution. The University of Bologna is developing an innovative system for orchard management called ORTO (Orchard Rapid Transportation System). This system involves an autonomous electric vehicle capable to perform agricultural activities inside an orchard structure. The vehicle is equipped with an implement capable to perform different tasks. The purpose of this thesis project is to control the vehicle and the implement to perform an inter-row grass mowing. This kind of task requires a synchronized motion between the traction motors and the implement motors. A motion control system has been developed to generate trajectories and manage their synchronization. Two main trajectories type have been used: a five order polynomial trajectory and a trapezoidal trajectory. These two kinds of trajectories have been chosen in order to perform a uniform grass mowing, paying a particular attention to the constrains of the system. To synchronize the motions, the electronic cams approach has been adopted. A master profile has been generated and all the trajectories have been linked to the master motion. Moreover, a safety system has been developed. The aim of this system is firstly to improve the safety during the motion, furthermore it allows to manage obstacle detection and avoidance. Using some particular techniques obstacles can be detected and recovery action can be performed to overcome the problem. Once the measured force reaches the predefined force threshold, then the vehicle stops immediately its motion. The whole project has been developed by employing Matlab and Simulink. Eventually, the software has been translated into C code and executed on the TI Lauchpad XL board.

LQG control policy design against agent identity privacy problem

This thesis project studies the agent identity privacy problem in the scalar linear quadratic Gaussian (LQG) control system. For the agent identity privacy problem in the LQG control, privacy models and privacy measures have to be established first. It depends on a trajectory of correlated data rather than a single observation. I propose here privacy models and the corresponding privacy measures by taking into account the two characteristics. The agent identity is a binary hypothesis: Agent A or Agent B. An eavesdropper is assumed to make a hypothesis testing on the agent identity based on the intercepted environment state sequence. The privacy risk is measured by the Kullback-Leibler divergence between the probability distributions of state sequences under two hypotheses. By taking into account both the accumulative control reward and privacy risk, an optimization problem of the policy of Agent B is formulated. The optimal deterministic privacy-preserving LQG policy of Agent B is a linear mapping. A sufficient condition is given to guarantee that the optimal deterministic privacy-preserving policy is time-invariant in the asymptotic regime. An independent Gaussian random variable cannot improve the performance of Agent B. The numerical experiments justify the theoretic results and illustrate the reward-privacy trade-off. Based on the privacy model and the LQG control model, I have formulated the mathematical problems for the agent identity privacy problem in LQG. The formulated problems address the two design objectives: to maximize the control reward and to minimize the privacy risk. I have conducted theoretic analysis on the LQG control policy in the agent identity privacy problem and the trade-off between the control reward and the privacy risk.Finally, the theoretic results are justified by numerical experiments. From the numerical results, I expected to have some interesting observations and insights, which are explained in the last chapter.

Neural Network Based UAV Fault Tolerant Control with Aerodynamic Disturbance Estimation and Compensation

In this thesis, the problem of controlling a quadrotor UAV is considered. It is done by presenting an original control system, designed as a combination of Neural Networks and Disturbance Observer, using a composite learning approach for a system of the second order, which is a novel methodology in literature. After a brief introduction about the quadrotors, the concepts needed to understand the controller are presented, such as the main notions of advanced control, the basic structure and design of a Neural Network, the modeling of a quadrotor and its dynamics. The full simulator, developed on the MATLAB Simulink environment, used throughout the whole thesis, is also shown. For the guidance and control purposes, a Sliding Mode Controller, used as a reference, it is firstly introduced, and its theory and implementation on the simulator are illustrated. Finally the original controller is introduced, through its novel formulation, and implementation on the model. The effectiveness and robustness of the two controllers are then proven by extensive simulations in all different conditions of external disturbance and faults.

Design of a bang-bang pressure regulation system for cold gas and plasma engines

In this thesis the design of a pressure regulation system for space propulsion engines (electric and cold gas) has been performed. The Bang-Bang Control (BBC) method has been implemented through the open/close command on a solenoid valve, and the mass flow rate of the propellant has been fixed with suitable flow restrictors. At the beginning, research for the comparison between mechanical and electronic (for BBC) pressure regulators has been performed, which resulted in enough advantages for the selection of the second valve type. The major advantage is about the possibility to have a variable outlet pressure with a variable inlet pressure through a simple remote command, while in mechanical pressure regulators the ratio between inlet and outlet pressures must be mechanically settled. Different pressure control schemes have been analyzed, changing number of solenoid valves, flow restrictors and plenums. For each scheme the valve’s frequencies were evaluated with simplified mathematical models and with the use of simulators implemented on Python; the results obtained from those two methods matched quiet well. From all the schemes it was possible to observe varying frequency and duty cycle, for changes in different parameters. This results, after experimental checks, can be used to design the control system for a given total number of cycles that a specific solenoid valve can guarantee. Finally, tests were performed and it was possible to verify the goodness of the control system. Moreover from the tests it was possible to deduce some tips in order to optimize the running of the simulator.

Simulation and Implementation of a PMSM Sensorless Control Algorithm for Submarine Applications

In this thesis, the study and the simulation of two advanced sensorless speed control techniques for a surface PMSM are presented. The aim is to implement a sensorless control algorithm for a submarine auxiliary propulsion system. This experimental activity is the result of a project collaboration with L3Harris Calzoni, a leader company in A&D systems for naval handling in military field. A Simulink model of the whole electric drive has been developed. Due to the satisfactory results of the simulations, the sensorless control system has been implemented in C code for STM32 environment. Finally, several tests on a real brushless machine have been carried out while the motor was connected to a mechanical load to simulate the real scenario of the final application. All the experimental results have been recorded through a graphical interface software developed at Calzoni.

Influência do treinamento físico aeróbio no transporte mitocondrial de ácidos graxos de cadeia longa no músculo esquelético: papel do complexo carnitina palmitoil transferase

O ácido graxo (AG) é uma importante fonte de energia para o músculo esquelético. Durante o exercício sua mobilização é aumentada para suprir as necessidades da musculatura ativa. Acredita-se que diversos pontos de regulação atuem no controle da oxidação dos AG, sendo o principal a atividade do complexo carnitina palmitoil transferase (CPT), entre os quais três componentes estão envolvidos: a CPT I, a CPT II e carnitina acilcarnitina translocase. A função da CPT I durante o exercício físico é controlar a entrada de AG para o interior da mitocôndria, para posterior oxidação do AG e produção de energia. Em resposta ao treinamento físico há um aumento na atividade e expressão da CPT I no músculo esquelético. Devido sua grande importância no metabolismo de lipídios, os mecanismos que controlam sua atividade e sua expressão gênica são revisados no presente estudo. Reguladores da expressão gênica de proteínas envolvidas no metabolismo de lipídios no músculo esquelético, os receptores ativados por proliferadores de peroxissomas (PPAR) alfa e beta, são discutidos com um enfoque na resposta ao treinamento físico.

Thunderclap headache attributed to reversible cerebral vasoconstriction: view and review

Thunderclap headache attributed to reversible cerebral vasoconstriction (THARCV) is a syndrome observed in a number of reported cases. In this article we reviewed this new headache entity (idiopathic form) using the clinical-radiological findings of 25 reported patients. In this series of patients 72% were women, the mean age at the onset of first headache episode was 39.4 +/- 2.3 years. In addition to the sine quanon condition of being abrupt and severe (thunderclap) at the onset, the headache was usually described as being explosive, excruciating, or crushing. The feature of pulsatility, accompanied or not by nausea was described by 80% of the patients. Forty percent of the cases manifested vomiting and 24% photophobia. Usually the headache was generalized, and in three cases it was unilateral at least at the onset. In 21 of 25 patients (84%) there was at least one recurrence or a sudden increase in the intensity of the headache. A past history of migraine was present in 52% of the patients. Precipitating factors were identified in 56% of the patients. Sexual intercourse was described by six patients. Of the 25 patients with THARCV syndrome studied, 12 (48%) developed focal neurological signs, transitory ischemic attack (n = 1), or ischemic stroke (n = 11, 44%), and two (8%) of them manifested seizures. The THARCV syndrome is a neurological disturbance perhaps more frequent than expected, preferentially affecting middle aged female migraineurs, and having an unpredictable prognosis, either showing a benign course or leading to stroke.

MPC for tracking zone regions

This paper deals with the problem of tracking target sets using a model predictive control (MPC) law. Some MPC applications require a control strategy in which some system outputs are controlled within specified ranges or zones (zone control), while some other variables - possibly including input variables - are steered to fixed target or set-point. In real applications, this problem is often overcome by including and excluding an appropriate penalization for the output errors in the control cost function. In this way, throughout the continuous operation of the process, the control system keeps switching from one controller to another, and even if a stabilizing control law is developed for each of the control configurations, switching among stable controllers not necessarily produces a stable closed loop system. From a theoretical point of view, the control objective of this kind of problem can be seen as a target set (in the output space) instead of a target point, since inside the zones there are no preferences between one point or another. In this work, a stable MPC formulation for constrained linear systems, with several practical properties is developed for this scenario. The concept of distance from a point to a set is exploited to propose an additional cost term, which ensures both, recursive feasibility and local optimality. The performance of the proposed strategy is illustrated by simulation of an ill-conditioned distillation column. (C) 2010 Elsevier Ltd. All rights reserved.

Valve friction and nonlinear process model closed-loop identification

Among several process variability sources, valve friction and inadequate controller tuning are supposed to be two of the most prevalent. Friction quantification methods can be applied to the development of model-based compensators or to diagnose valves that need repair, whereas accurate process models can be used in controller retuning. This paper extends existing methods that jointly estimate the friction and process parameters, so that a nonlinear structure is adopted to represent the process model. The developed estimation algorithm is tested with three different data sources: a simulated first order plus dead time process, a hybrid setup (composed of a real valve and a simulated pH neutralization process) and from three industrial datasets corresponding to real control loops. The results demonstrate that the friction is accurately quantified, as well as ""good"" process models are estimated in several situations. Furthermore, when a nonlinear process model is considered, the proposed extension presents significant advantages: (i) greater accuracy for friction quantification and (ii) reasonable estimates of the nonlinear steady-state characteristics of the process. (C) 2010 Elsevier Ltd. All rights reserved.

Vibratory noise to the fingertip enhances balance improvement associated with light touch

Light touch of a fingertip on an external stable surface greatly improves the postural stability of standing subjects. The hypothesis of the present work was that a vibrating surface could increase the effectiveness of fingertip signaling to the central nervous system (e.g., by a stochastic resonance mechanism) and hence improve postural stability beyond that achieved by light touch. Subjects stood quietly over a force plate while touching with their right index fingertip a surface that could be either quiescent or randomly vibrated at two low-level noise intensities. The vibratory noise of the contact surface caused a significant decrease in postural sway, as assessed by center of pressure measures in both time and frequency domains. Complementary experiments were designed to test whether postural control improvements were associated with a stochastic resonance mechanism or whether attentional mechanisms could be contributing. A full curve relating body sway parameters and different levels of vibratory noise resulted in a U-like function, suggesting that the improvement in sway relied on a stochastic resonance mechanism. Additionally, no decrease in postural sway was observed when the vibrating contact surface was attached to the subject`s body, suggesting that no attentional mechanisms were involved. These results indicate that sensory cues obtained from the fingertip need not necessarily be associated with static contact surfaces to cause improvement in postural stability. A low-level noisy vibration applied to the contact surface could lead to a better performance of the postural control system.

Phase-Locked Loop design applied to frequency-modulated atomic force microscope

The atomic force microscope (AFM) introduced the surface investigation with true atomic resolution. In the frequency modulation technique (FM-AFM) both the amplitude and the frequency of oscillation of the micro-cantilever must be kept constant even in the presence of tip-surface interaction forces. For that reason, the proper design of the Phase-Locked Loop (PLL) used in FM-AFM is vital to system performance. Here, the mathematical model of the FM-AFM control system is derived considering high order PLL In addition a method to design stable third-order Phase-Locked Loops is presented. (C) 2010 Elsevier B.V. All rights reserved.

Vibration-enhanced posture stabilization achieved by tactile supplementation: May blind individuals get extra benefits?

Diminished balance ability poses a serious health risk due to the increased likelihood of falling, and impaired postural stability is significantly associated with blindness and poor vision. Noise stimulation (by improving the detection of sub-threshold somatosensory information) and tactile supplementation (i.e. additional haptic information provided by an external contact surface) have been shown to improve the performance of the postural control system. Moreover, vibratory noise added to the source of tactile supplementation (e.g. applied to a surface that the fingertip touches) has been shown to enhance balance stability more effectively than tactile supplementation alone. In view of the above findings, in addition to the well established consensus that blind subjects show superior abilities in the use of tactile information, we hypothesized that blind subjects may take extra benefits from the vibratory noise added to the tactile supplementation and hence show greater improvements in postural stability than those observed for sighted subjects. If confirmed, this hypothesis may lay the foundation for the development of noise-based assistive devices (e.g. canes, walking sticks) for improving somatosensation and hence prevent falls in blind individuals. (C) 2011 Elsevier Ltd. All rights reserved.

Hardware/firmware implementation of a soft sensor using an improved version of a fuzzy identification algorithm

This paper presents the design and implementation of an embedded soft sensor, i. e., a generic and autonomous hardware module, which can be applied to many complex plants, wherein a certain variable cannot be directly measured. It is implemented based on a fuzzy identification algorithm called ""Limited Rules"", employed to model continuous nonlinear processes. The fuzzy model has a Takagi-Sugeno-Kang structure and the premise parameters are defined based on the Fuzzy C-Means (FCM) clustering algorithm. The firmware contains the soft sensor and it runs online, estimating the target variable from other available variables. Tests have been performed using a simulated pH neutralization plant. The results of the embedded soft sensor have been considered satisfactory. A complete embedded inferential control system is also presented, including a soft sensor and a PID controller. (c) 2007, ISA. Published by Elsevier Ltd. All rights reserved.