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.

ITO/SiOx/Si optical sensor with internal gain

A visible/near-infrared optical sensor based on an ITO/SiOx/n-Si structure with internal gain is presented. This surface-barrier structure was fabricated by a low-temperature processing technique. The interface properties and carder transport were investigated from dark current-voltage and capacitance-voltage characteristics. Examination of the multiplication properties was performed under different light excitation and reverse bias conditions. The spectral and pulse response characteristics are analysed. The current amplification mechanism is interpreted by the control of electron current by the space charge of photogenerated holes near the SiOx/Si interface. The optical sensor output characteristics and some possible device applications are presented.

Long-term outcomes of school-based treatment for control of urinary schistosomiasis: a review of experience in Coast Province, Kenya

Urinary schistosomiasis remains a significant burden for Africa and the Middle East. The success of population-based control programs will depend on their impact, over many years, on Schistosoma haematobium reinfection and associated disease. In a multi-year (1984-1992) control program in Kenya, we examined risk for S. haematobium reinfection and late disease during and after annual school-based treatment. In this setting, long-term risk of new infection was independently associated with location, age, hematuria, and incomplete treatment, but not with sex or frequency of water contact. Thus, very local environmental features and age-related factors played an important role in S. haematobium transmission, such that population-based control programs should optimally tailor their efforts to local conditions on a village-by-village basis. In 2001-2002, the late benefits of earlier participation in school-based antischistosomal therapy were estimated in a cohort of formerly-treated adult residents compared to never-treated adults from the same villages. Among age-matched subjects, current infection prevalence was lower among those who had received remote therapy. In addition, prevalence of bladder abnormality was lower in the treated group, who were free of severe bladder disease. Treatment of affected adults resulted in rapid resolution of infection and any detectable bladder abnormalities. We conclude that continued treatment into adulthood, as well as efforts at long-term prevention of infection (transmission control) are necessary to achieve optimal morbidity control in affected communities.

Hybrid coordination of reinforcement learning-based behaviors for AUV control

This paper proposes a hybrid coordination method for behavior-based control architectures. The hybrid method takes advantages of the robustness and modularity in competitive approaches as well as optimized trajectories in cooperative ones. This paper shows the feasibility of applying this hybrid method with a 3D-navigation to an autonomous underwater vehicle (AUV). The behaviors are learnt online by means of reinforcement learning. A continuous Q-learning implemented with a feed-forward neural network is employed. Realistic simulations were carried out. The results obtained show the good performance of the hybrid method on behavior coordination as well as the convergence of the behaviors

Design and implementation of FPGA-based LQ control of active magnetic bearings

The need for high performance, high precision, and energy saving in rotating machinery demands an alternative solution to traditional bearings. Because of the contactless operation principle, the rotating machines employing active magnetic bearings (AMBs) provide many advantages over the traditional ones. The advantages such as contamination-free operation, low maintenance costs, high rotational speeds, low parasitic losses, programmable stiffness and damping, and vibration insulation come at expense of high cost, and complex technical solution. All these properties make the use of AMBs appropriate primarily for specific and highly demanding applications. High performance and high precision control requires model-based control methods and accurate models of the flexible rotor. In turn, complex models lead to high-order controllers and feature considerable computational burden. Fortunately, in the last few years the advancements in signal processing devices provide new perspective on the real-time control of AMBs. The design and the real-time digital implementation of the high-order LQ controllers, which focus on fast execution times, are the subjects of this work. In particular, the control design and implementation in the field programmable gate array (FPGA) circuits are investigated. The optimal design is guided by the physical constraints of the system for selecting the optimal weighting matrices. The plant model is complemented by augmenting appropriate disturbance models. The compensation of the force-field nonlinearities is proposed for decreasing the uncertainty of the actuator. A disturbance-observer-based unbalance compensation for canceling the magnetic force vibrations or vibrations in the measured positions is presented. The theoretical studies are verified by the practical experiments utilizing a custom-built laboratory test rig. The test rig uses a prototyping control platform developed in the scope of this work. To sum up, the work makes a step in the direction of an embedded single-chip FPGA-based controller of AMBs.

Sensor Fusion of Proprioception, Force and Vision in Estimation and Robot

Sensor-based robot control allows manipulation in dynamic environments with uncertainties. Vision is a versatile low-cost sensory modality, but low sample rate, high sensor delay and uncertain measurements limit its usability, especially in strongly dynamic environments. Force is a complementary sensory modality allowing accurate measurements of local object shape when a tooltip is in contact with the object. In multimodal sensor fusion, several sensors measuring different modalities are combined to give a more accurate estimate of the environment. As force and vision are fundamentally different sensory modalities not sharing a common representation, combining the information from these sensors is not straightforward. In this thesis, methods for fusing proprioception, force and vision together are proposed. Making assumptions of object shape and modeling the uncertainties of the sensors, the measurements can be fused together in an extended Kalman filter. The fusion of force and visual measurements makes it possible to estimate the pose of a moving target with an end-effector mounted moving camera at high rate and accuracy. The proposed approach takes the latency of the vision system into account explicitly, to provide high sample rate estimates. The estimates also allow a smooth transition from vision-based motion control to force control. The velocity of the end-effector can be controlled by estimating the distance to the target by vision and determining the velocity profile giving rapid approach and minimal force overshoot. Experiments with a 5-degree-of-freedom parallel hydraulic manipulator and a 6-degree-of-freedom serial manipulator show that integration of several sensor modalities can increase the accuracy of the measurements significantly.

Hybrid coordination of reinforcement learning-based behaviors for AUV control

This paper proposes a hybrid coordination method for behavior-based control architectures. The hybrid method takes advantages of the robustness and modularity in competitive approaches as well as optimized trajectories in cooperative ones. This paper shows the feasibility of applying this hybrid method with a 3D-navigation to an autonomous underwater vehicle (AUV). The behaviors are learnt online by means of reinforcement learning. A continuous Q-learning implemented with a feed-forward neural network is employed. Realistic simulations were carried out. The results obtained show the good performance of the hybrid method on behavior coordination as well as the convergence of the behaviors

Development of an electrochemical sensor for determination of dissolved oxygen by nickel-salen polymeric film modified electrode

An amperometric oxygen sensor based on a polymeric nickel-salen (salen = N,N'-ethylene bis(salicylideneiminato)) film coated platinum electrode was developed. The sensor was constructed by electropolymerization of nickel-salen complex at platinum electrode in acetonitrile/tetrabutylammonium perchlorate by cyclic voltammetry. The voltammetric behavior of the sensor was investigated in 0.5 mol L-1 KCl solution in the absence and presence of molecular oxygen. Thus, with the addition of oxygen to the solution, the increase of cathodic peak current (at -0.25 V vs. saturated calomel electrode (SCE)) of the modified electrode was observed. This result shows that the nickel-salen film on electrode surface promotes the reduction of oxygen. The reaction can be brought about electrochemically, where the nickel(II) complex is first reduced to a nickel(I) complex at the electrode surface. The nickel(I) complex then undergoes a catalytic oxidation by the molecular oxygen in solution back to the nickel(II) complex, which can then be electrochemically re-reduced to produce an enhancement of the cathodic current. The Tafel plot analyses have been used to elucidate the kinetics and mechanism of the oxygen reduction. A plot of the cathodic current vs. the dissolved oxygen concentration for chronoamperometry (fixed potential = -0.25 V vs. SCE) at the sensor was linear in the 3.95-9.20 mg L-1 concentration range and the concentration limit was 0.17 mg L-1 O-2. The proposed electrode is useful for the quality control and routine analysis of dissolved oxygen in commercial samples and environmental water. The results obtained for the levels of dissolved oxygen are in agreement with the results obtained with a commercial O-2 sensor. (C) 2012 Elsevier B.V. All rights reserved.

Development of an amperometric sensor for potassium ions

Hollandite-type manganese oxides are nanofibrous crystals with sub-nanometer open tunnels that provide a unique property for sensing applications. Sensor based on hollandite-type manganese oxide was investigated for amperometric detection of potassium. With an operating potential of +0.63 V versus SCE, potassium ions produce oxidation currents at the sensor, which can be exploited for quantitative determinations. The amperometric signals are linearly proportional to potassium ions concentration in the range 2.7 x 10(-4) to 9.1 x 10(-4) Mol l(-1) with a correlation coefficient of 0.9990. The construction and renewal are simple and inexpensive.

Development of an electrochemical sensor for potassium ions based on KSr(2)Nb(5)O(15) modified electrode

In the work described by this paper, we studied the development of a selective potassium ion sensor constituted of a carbon paste electrode modified (CPEM) with a novel KSr(2)Nb(2)O(15). The material KSr(2)Nb(2)O(15) is an oxide with the tetragonal tungsten bronze structure (TTB) type are in forefront both in the area of research as well as in industrial applications. The sensor response to potassium ions was linear in the concentration range 1.26 x 10(-5) at 1.62 x 10(-3) mol L(-1) (E (mV) = 32.7 + 51.1 log [K(+)]). The sensor based KSr(2)Nb(2)O(15), of the TTB-type presented very good potentiometric response, with a slope of 51.1 mV/dec (at 25 degrees C) and detection limit for the potassium ions of 7.27 x 10(-5) mol.L(-1)

Sensor for diuron quantitation based on the P450 biomimetic catalyst nickel(II) 1,4,8,11,15,18,22,25-octabutoxy-29H,31H-phthalocyanine

A biomimetic sensor based on a carbon paste electrode modified with the nickel(II) 1,4,8,11,15,18,22,25-octabutoxy-29H,31H-phthalocyanine complex was developed as a reliable alternative technique for the sensitive and selective analysis of the herbicide diuron in environmental media. The sensor was evaluated using cyclic voltammetry and amperometric techniques. The best amperometric responses were obtained at 750 mV vs. Ag/AgCl (KClsat), using 0.1 mol L-1 phosphate buffer solution at pH 8.0. Under these conditions, the sensor showed a linear response for diuron concentrations between 9.9 × 10-6 and 1.5 × 10-4 mol L -1, a sensitivity of 22817 (±261) μA L mol-1, and detection and quantification limits of 6.14 × 10-6 and 2 × 10-5 mol L-1, respectively. The presence of the nickel complex in the carbon paste improved selectivity, stability, and sensitivity (which increased 700%), compared to unmodified paste. The applicability of the sensor was demonstrated using enriched environmental samples (river water and soil). © 2012 Elsevier B.V. All rights reserved.

Desenvolvimento de biossensor baseado em extrato de açaí e sensor biomimético para detecção de hexazinona

Pós-graduação em Química - IQ

An Electrochemical Sensor for Reducing Sugars Based on a Glassy Carbon Electrode Modified with Electropolymerized Molecularly Imprinted Poly-o-phenylenediamine Film

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Ab-initio calculations for a realistic sensor: A study of CO sensors based on nitrogen-rich carbon nanotubes

The use of nanoscale low-dimensional systems could boost the sensitivity of gas sensors. In this work we simulate a nanoscopic sensor based on carbon nanotubes with a large number of binding sites using ab initio density functional electronic structure calculations coupled to the Non-Equilibrium Green's Function formalism. We present a recipe where the adsorption process is studied followed by conductance calculations of a single defect system and of more realistic disordered system considering different coverages of molecules as one would expect experimentally. We found that the sensitivity of the disordered system is enhanced by a factor of 5 when compared to the single defect one. Finally, our results from the atomistic electronic transport are used as input to a simple model that connects them to experimental parameters such as temperature and partial gas pressure, providing a procedure for simulating a realistic nanoscopic gas sensor. Using this methodology we show that nitrogen-rich carbon nanotubes could work at room temperature with extremely high sensitivity. Copyright 2012 Author(s). This article is distributed under a Creative Commons Attribution 3.0 Unported License. [http://dx.doi.org/10.1063/1.4739280]

From inverted pendulum to N-link chain: inertial sensors-based assessment of movement kinematics and dynamics for functional evaluation and rehabilitation

Despite several clinical tests that have been developed to qualitatively describe complex motor tasks by functional testing, these methods often depend on clinicians' interpretation, experience and training, which make the assessment results inconsistent, without the precision required to objectively assess the effect of the rehabilitative intervention. A more detailed characterization is required to fully capture the various aspects of motor control and performance during complex movements of lower and upper limbs. The need for cost-effective and clinically applicable instrumented tests would enable quantitative assessment of performance on a subject-specific basis, overcoming the limitations due to the lack of objectiveness related to individual judgment, and possibly disclosing subtle alterations that are not clearly visible to the observer. Postural motion measurements at additional locations, such as lower and upper limbs and trunk, may be necessary in order to obtain information about the inter-segmental coordination during different functional tests involved in clinical practice. With these considerations in mind, this Thesis aims: i) to suggest a novel quantitative assessment tool for the kinematics and dynamics evaluation of a multi-link kinematic chain during several functional motor tasks (i.e. squat, sit-to-stand, postural sway), using one single-axis accelerometer per segment, ii) to present a novel quantitative technique for the upper limb joint kinematics estimation, considering a 3-link kinematic chain during the Fugl-Meyer Motor Assessment and using one inertial measurement unit per segment. The suggested methods could have several positive feedbacks from clinical practice. The use of objective biomechanical measurements, provided by inertial sensor-based technique, may help clinicians to: i) objectively track changes in motor ability, ii) provide timely feedback about the effectiveness of administered rehabilitation interventions, iii) enable intervention strategies to be modified or changed if found to be ineffective, and iv) speed up the experimental sessions when several subjects are asked to perform different functional tests.