Multidimensional project control system: applicazione di verifica della qualità dei progetti in Despar Italia c.r.l.

La dissertazione affronterà il tema del controllo qualità nei progetti, applicando conoscenze, tecniche e strumenti propri del Project e del Multiproject Management. L’analisi partirà svolgendo, nel primo capitolo, considerazioni introduttive riguardo le due discipline citate. Lo scopo ultimo sarà quello di elaborare un sistema di controllo integrato della qualità, indirizzato principalmente al Project Management che è presente in una qualsiasi organizzazione che opera per progetti. Nel secondo capitolo verrà illustrato il metodo denominato Multidimensional Project control System sul quale il modello sviluppato in seguito si basa. La progettazione di un sistema di controllo è una parte importante dello sforzo di gestione di un progetto. Tale sistema è basato su una serie di obiettivi di progetto e sulla loro importanza relativa e fonda la sua natura su una sistematica valutazione in corso d’opera dello stato di conformità del progetto, sia a livello di processo che a livello di output. Nel capitolo conclusivo si affronta l’obiettivo principale di questo elaborato. Sono stati forniti dati e documenti dall’azienda Despar Italia c.r.l. ed è stato chiesto di sviluppare un metodo di controllo che il Project Management potesse utilizzare per implementare un processo di verifica della qualità di progetto. Viene quindi descritta l’azienda, come il Management pianifica, gestisce e controlla i progetti e quali necessità devono essere soddisfatte. Si procede poi con l’illustrazione e spiegazione del metodo sviluppato, chiarito da un esempio esplicativo. L’elaborato si concluderà con delle riflessioni finali, proponendo critiche e spunti per eventuali sviluppi futuri.

Nonlinear constrained and saturated control of power electronics and electromechanical systems

Power electronic converters are extensively adopted for the solution of timely issues, such as power quality improvement in industrial plants, energy management in hybrid electrical systems, and control of electrical generators for renewables. Beside nonlinearity, this systems are typically characterized by hard constraints on the control inputs, and sometimes the state variables. In this respect, control laws able to handle input saturation are crucial to formally characterize the systems stability and performance properties. From a practical viewpoint, a proper saturation management allows to extend the systems transient and steady-state operating ranges, improving their reliability and availability. The main topic of this thesis concern saturated control methodologies, based on modern approaches, applied to power electronics and electromechanical systems. The pursued objective is to provide formal results under any saturation scenario, overcoming the drawbacks of the classic solution commonly applied to cope with saturation of power converters, and enhancing performance. For this purpose two main approaches are exploited and extended to deal with power electronic applications: modern anti-windup strategies, providing formal results and systematic design rules for the anti-windup compensator, devoted to handle control saturation, and “one step” saturated feedback design techniques, relying on a suitable characterization of the saturation nonlinearity and less conservative extensions of standard absolute stability theory results. The first part of the thesis is devoted to present and develop a novel general anti-windup scheme, which is then specifically applied to a class of power converters adopted for power quality enhancement in industrial plants. In the second part a polytopic differential inclusion representation of saturation nonlinearity is presented and extended to deal with a class of multiple input power converters, used to manage hybrid electrical energy sources. The third part regards adaptive observers design for robust estimation of the parameters required for high performance control of power systems.

Nonlinear Observers for Sensorless Control of Permanent Magnet Synchronous Motors

In this thesis, the industrial application of control a Permanent Magnet Synchronous Motor in a sensorless configuration has been faced, and in particular the task of estimating the unknown “parameters” necessary for the application of standard motor control algorithms. In literature several techniques have been proposed to cope with this task, among them the technique based on model-based nonlinear observer has been followed. The hypothesis of neglecting the mechanical dynamics from the motor model has been applied due to practical and physical considerations, therefore only the electromagnetic dynamics has been used for the observers design. First observer proposed is based on stator currents and Stator Flux dynamics described in a generic rotating reference frame. Stator flux dynamics are known apart their initial conditions which are estimated, with speed that is also unknown, through the use of the Adaptive Theory. The second observer proposed is based on stator currents and Rotor Flux dynamics described in a self-aligning reference frame. Rotor flux dynamics are described in the stationary reference frame exploiting polar coordinates instead of classical Cartesian coordinates, by means the estimation of amplitude and speed of the rotor flux. The stability proof is derived in a Singular Perturbation Framework, which allows for the use the current estimation errors as a measure of rotor flux estimation errors. The stability properties has been derived using a specific theory for systems with time scale separation, which guarantees a semi-global practical stability. For the two observer ideal simulations and real simulations have been performed to prove the effectiveness of the observers proposed, real simulations on which the effects of the Inverter nonlinearities have been introduced, showing the already known problems of the model-based observers for low speed applications.

Robust Nonlinear Output Regulation by Identification Tools

The present thesis focuses on the problem of robust output regulation for minimum phase nonlinear systems by means of identification techniques. Given a controlled plant and an exosystem (an autonomous system that generates eventual references or disturbances), the control goal is to design a proper regulator able to process the only measure available, i.e the error/output variable, in order to make it asymptotically vanishing. In this context, such a regulator can be designed following the well known “internal model principle” that states how it is possible to achieve the regulation objective by embedding a replica of the exosystem model in the controller structure. The main problem shows up when the exosystem model is affected by parametric or structural uncertainties, in this case, it is not possible to reproduce the exact behavior of the exogenous system in the regulator and then, it is not possible to achieve the control goal. In this work, the idea is to find a solution to the problem trying to develop a general framework in which coexist both a standard regulator and an estimator able to guarantee (when possible) the best estimate of all uncertainties present in the exosystem in order to give “robustness” to the overall control loop.

NLGA based Active Control in Aerospace: fault tolerability, disturbance rejection, and parameter estimation

A new control scheme has been presented in this thesis. Based on the NonLinear Geometric Approach, the proposed Active Control System represents a new way to see the reconfigurable controllers for aerospace applications. The presence of the Diagnosis module (providing the estimation of generic signals which, based on the case, can be faults, disturbances or system parameters), mean feature of the depicted Active Control System, is a characteristic shared by three well known control systems: the Active Fault Tolerant Controls, the Indirect Adaptive Controls and the Active Disturbance Rejection Controls. The standard NonLinear Geometric Approach (NLGA) has been accurately investigated and than improved to extend its applicability to more complex models. The standard NLGA procedure has been modified to take account of feasible and estimable sets of unknown signals. Furthermore the application of the Singular Perturbations approximation has led to the solution of Detection and Isolation problems in scenarios too complex to be solved by the standard NLGA. Also the estimation process has been improved, where multiple redundant measuremtent are available, by the introduction of a new algorithm, here called "Least Squares - Sliding Mode". It guarantees optimality, in the sense of the least squares, and finite estimation time, in the sense of the sliding mode. The Active Control System concept has been formalized in two controller: a nonlinear backstepping controller and a nonlinear composite controller. Particularly interesting is the integration, in the controller design, of the estimations coming from the Diagnosis module. Stability proofs are provided for both the control schemes. Finally, different applications in aerospace have been provided to show the applicability and the effectiveness of the proposed NLGA-based Active Control System.

Motor control system in Parkinson’s disease: a modeling approach

Parkinson’s disease is a neurodegenerative disorder due to the death of the dopaminergic neurons of the substantia nigra of the basal ganglia. The process that leads to these neural alterations is still unknown. Parkinson’s disease affects most of all the motor sphere, with a wide array of impairment such as bradykinesia, akinesia, tremor, postural instability and singular phenomena such as freezing of gait. Moreover, in the last few years the fact that the degeneration in the basal ganglia circuitry induces not only motor but also cognitive alterations, not necessarily implicating dementia, and that dopamine loss induces also further implications due to dopamine-driven synaptic plasticity got more attention. At the present moment, no neuroprotective treatment is available, and even if dopamine-replacement therapies as well as electrical deep brain stimulation are able to improve the life conditions of the patients, they often present side effects on the long term, and cannot recover the neural loss, which instead continues to advance. In the present thesis both motor and cognitive aspects of Parkinson’s disease and basal ganglia circuitry were investigated, at first focusing on Parkinson’s disease sensory and balance issues by means of a new instrumented method based on inertial sensor to provide further information about postural control and postural strategies used to attain balance, then applying this newly developed approach to assess balance control in mild and severe patients, both ON and OFF levodopa replacement. Given the inability of levodopa to recover balance issues and the new physiological findings than underline the importance in Parkinson’s disease of non-dopaminergic neurotransmitters, it was therefore developed an original computational model focusing on acetylcholine, the most promising neurotransmitter according to physiology, and its role in synaptic plasticity. The rationale of this thesis is that a multidisciplinary approach could gain insight into Parkinson’s disease features still unresolved.

[Drug-independent blood pressure control through the autonomous nervous system]

Arterial hypertension is a chronic disease with a therapeutical challenge for the patient and the physician involved. Patient-independent techniques with good efficacy and tolerability are wanted. The autonomous nervous system insufficiently therapeutically exploited to date, is now approachable by two types of intervention: renal nerve ablation, an endovascular approach without remaining foreign body, and BAT, baroreflex activating therapy using an implantable device stimulating the carotid sinus. The blood pressure lowering potency of BAT appears more than with renal nerve ablation and also clinical study data are more prevalent. With both treatment options the patients having the most profit are insufficiently defined. Given this knowledge, any form of secondary hypertension needs to be excluded beforehand.

Complex genital system of a haplogyne spider (Arachnida, Araneae, Tetrablemmidae) indicates internal fertilization and full female control over transferred sperm

The female genital organs of the tetrablemmid Indicoblemma lannaianum are astonishingly complex. The copulatory orifice lies anterior to the opening of the uterus externus and leads into a narrow insertion duct that ends in a genital cavity. The genital cavity continues laterally in paired tube-like copulatory ducts, which lead into paired, large, sac-like receptacula. Each receptaculum has a sclerotized pore plate with associated gland cells. Paired small fertilization ducts originate in the receptacula and take their curved course inside the copulatory ducts. The fertilization ducts end in slit-like openings in the sclerotized posterior walls of the copulatory ducts. Huge masses of secretions forming large balls are detectable in the female receptacula. An important function of these secretory balls seems to be the encapsulation of spermatozoa in discrete packages in order to avoid the mixing of sperm from different males. In this way, sperm competition may be completely prevented or at least severely limited. Females seem to have full control over transferred sperm and be able to express preference for spermatozoa of certain males. The lumen of the sperm containing secretory balls is connected with the fertilization duct. Activated spermatozoa are only found in the uterus internus of females, which is an indication of internal fertilization. The sperm cells in the uterus internus are characterized by an extensive cytoplasm and an elongated, cone-shaped nucleus. The male genital system of I. lannaianum consists of thick testes and thin convoluted vasa deferentia that open into the wide ductus ejaculatorius. The voluminous globular palpal bulb is filled with seminal fluid consisting of a globular secretion in which only a few spermatozoa are embedded. The spermatozoa are encapsulated by a sheath produced in the genital system. The secretions in females may at least partly consist of male secretions that could be involved in the building of the secretory balls or play a role in sperm activation. The male secretions could also afford nutriments to the spermatozoa.

Control of recycle processes using neural networks combined with PID controller

This thesis is focused on the control of a system with recycle. A new control strategy using neural network combined with PID controller was proposed. The combined controller was studied and tested on the pressure control of a vaporizer inside a para-xylene production process. The major problems are the negative effects of recycle and the delays on instability and performance. The neural network was designed to move the process close to the set points while the PID accomplishes the finer level of disturbance rejection and offset reductions. Our simulation results show that during control, the neural network was able to determine the nonlinear relationship between steady state and manipulated variables. The results also show the disturbance rejection was handled by PID controller effectively.

Optimal game theoretic distributed control methodologies in small scale power systems

This dissertation presents the competitive control methodologies for small-scale power system (SSPS). A SSPS is a collection of sources and loads that shares a common network which can be isolated during terrestrial disturbances. Micro-grids, naval ship electric power systems (NSEPS), aircraft power systems and telecommunication system power systems are typical examples of SSPS. The analysis and development of control systems for small-scale power systems (SSPS) lacks a defined slack bus. In addition, a change of a load or source will influence the real time system parameters of the system. Therefore, the control system should provide the required flexibility, to ensure operation as a single aggregated system. In most of the cases of a SSPS the sources and loads must be equipped with power electronic interfaces which can be modeled as a dynamic controllable quantity. The mathematical formulation of the micro-grid is carried out with the help of game theory, optimal control and fundamental theory of electrical power systems. Then the micro-grid can be viewed as a dynamical multi-objective optimization problem with nonlinear objectives and variables. Basically detailed analysis was done with optimal solutions with regards to start up transient modeling, bus selection modeling and level of communication within the micro-grids. In each approach a detail mathematical model is formed to observe the system response. The differential game theoretic approach was also used for modeling and optimization of startup transients. The startup transient controller was implemented with open loop, PI and feedback control methodologies. Then the hardware implementation was carried out to validate the theoretical results. The proposed game theoretic controller shows higher performances over traditional the PI controller during startup. In addition, the optimal transient surface is necessary while implementing the feedback controller for startup transient. Further, the experimental results are in agreement with the theoretical simulation. The bus selection and team communication was modeled with discrete and continuous game theory models. Although players have multiple choices, this controller is capable of choosing the optimum bus. Next the team communication structures are able to optimize the players’ Nash equilibrium point. All mathematical models are based on the local information of the load or source. As a result, these models are the keys to developing accurate distributed controllers.

The blood-central nervous system barriers actively control immune cell entry into the central nervous system

Before entering the central nervous system (CNS) immune cells have to penetrate any one of its barriers, namely either the endothelial blood-brain barrier, the epithelial blood-cerebrospinal fluid barrier or the tanycytic barrier around the circumventricular organs, all of which maintain homeostasis within the CNS. The presence of these barriers in combination with the lack of lymphatic vessels and the absence of classical MHC-positive antigen presenting cells characterizes the CNS as an immunologically privileged site. In multiple sclerosis a large number of inflammatory cells gains access to the CNS parenchyma. Studies performed in experimental autoimmune encephalomyelitis (EAE), a rodent model for multiple sclerosis, have enabled us to understand some of the molecular mechanisms involved in immune cell entry into the CNS. In particular, the realization that /alpha4-integrins play a predominant role in leukocyte trafficking to the CNS has led to the development of a novel drug for the treatment of relapsing-remitting multiple sclerosis, which targets /alpha4-integrin mediated immune cell migration to the CNS. At the same time, the involvement of other adhesion and signalling molecules in this process remains to be investigated and novel molecules contributing to immune cell entry into the CNS are still being identified. The entire process of immune cell trafficking into the CNS is strictly controlled by the brain barriers not only under physiological conditions but also during neuroinflammation, when some barrier properties are lost. Thus, immune cell entry into the CNS critically depends on the unique characteristics of the brain barriers maintaining CNS homeostasis.

LOCAL DIGITAL CONTROL OF POWER ELECTRONIC CONVERTERS IN A DC MICROGRID BASED ON A-PRIORI DERIVATION OF SWITCHING SURFACES

In power electronic basedmicrogrids, the computational requirements needed to implement an optimized online control strategy can be prohibitive. The work presented in this dissertation proposes a generalized method of derivation of geometric manifolds in a dc microgrid that is based on the a-priori computation of the optimal reactions and trajectories for classes of events in a dc microgrid. The proposed states are the stored energies in all the energy storage elements of the dc microgrid and power flowing into them. It is anticipated that calculating a large enough set of dissimilar transient scenarios will also span many scenarios not specifically used to develop the surface. These geometric manifolds will then be used as reference surfaces in any type of controller, such as a sliding mode hysteretic controller. The presence of switched power converters in microgrids involve different control actions for different system events. The control of the switch states of the converters is essential for steady state and transient operations. A digital memory look-up based controller that uses a hysteretic sliding mode control strategy is an effective technique to generate the proper switch states for the converters. An example dcmicrogrid with three dc-dc boost converters and resistive loads is considered for this work. The geometric manifolds are successfully generated for transient events, such as step changes in the loads and the sources. The surfaces corresponding to a specific case of step change in the loads are then used as reference surfaces in an EEPROM for experimentally validating the control strategy. The required switch states corresponding to this specific transient scenario are programmed in the EEPROM as a memory table. This controls the switching of the dc-dc boost converters and drives the system states to the reference manifold. In this work, it is shown that this strategy effectively controls the system for a transient condition such as step changes in the loads for the example case.

An insulin infusion advisory system for type 1 diabetes patients based on non-linear model predictive control methods

In this paper, an Insulin Infusion Advisory System (IIAS) for Type 1 diabetes patients, which use insulin pumps for the Continuous Subcutaneous Insulin Infusion (CSII) is presented. The purpose of the system is to estimate the appropriate insulin infusion rates. The system is based on a Non-Linear Model Predictive Controller (NMPC) which uses a hybrid model. The model comprises a Compartmental Model (CM), which simulates the absorption of the glucose to the blood due to meal intakes, and a Neural Network (NN), which simulates the glucose-insulin kinetics. The NN is a Recurrent NN (RNN) trained with the Real Time Recurrent Learning (RTRL) algorithm. The output of the model consists of short term glucose predictions and provides input to the NMPC, in order for the latter to estimate the optimum insulin infusion rates. For the development and the evaluation of the IIAS, data generated from a Mathematical Model (MM) of a Type 1 diabetes patient have been used. The proposed control strategy is evaluated at multiple meal disturbances, various noise levels and additional time delays. The results indicate that the implemented IIAS is capable of handling multiple meals, which correspond to realistic meal profiles, large noise levels and time delays.

Distributed Control Nodes for Material Flow System Controls on the Example of Unit Load Conveyor and Sorter Facilities

The Chair of Transportation and Ware-housing at the University of Dortmund together with its industrial partner has developed and implemented a decentralized control system based on embedded technology and Internet standards. This innovative, highly flexible system uses autonomous software modules to control the flow of unit loads in real-time. The system is integrated into Chair’s test facility consisting of a wide range of conveying and sorting equipment. It is built for proof of concept purposes and will be used for further research in the fields of decentralized automation and embedded controls. This presentation describes the implementation of this decentralized control system.