114 research outputs found

    TERRORIST THREATS AND PUBLIC TRANSPORTATION

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    Public transportation is an activity facing various problems. One of them, very complex and dangerous, is terrorism which together with criminal activities and vandalism, is making the top of the threats affecting public transportation and therefore urban life quality. Public transportation has several characteristics which make it vulnerable to terroris attacks and a main target for them. To compensate for these weeknesses, certain solutions are necessary to prevent the attack or in case it already took place, to reduce the human and material losses.urban area, urban transportation, vandalism, criminal activity.

    Advanced multiparametric optimization and control studies for anaesthesia

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    Anaesthesia is a reversible pharmacological state of the patient where hypnosis, analgesia and muscle relaxation are guaranteed and maintained throughout the surgery. Analgesics block the sensation of pain; hypnotics produce unconsciousness, while muscle relaxants prevent unwanted movement of muscle tone. Controlling the depth of anaesthesia is a very challenging task, as one has to deal with nonlinearity, inter- and intra-patient variability, multivariable characteristics, variable time delays, dynamics dependent on the hypnotic agent, model analysis variability, agent and stability issues. The modelling and automatic control of anaesthesia is believed to (i) benefit the safety of the patient undergoing surgery as side-effects may be reduced by optimizing the drug infusion rates, and (ii) support anaesthetists during critical situations by automating the drug delivery systems. In this work we have developed several advanced explicit/multi-parametric model predictive (mp-MPC) control strategies for the control of depth of anaesthesia. State estimation techniques are developed and used simultaneously with mp-MPC strategies to estimate the state of each individual patient, in an attempt to overcome the challenges of inter- and intra- patient variability, and deal with possible unmeasurable noisy outputs. Strategies to deal with the nonlinearity have been also developed including local linearization, exact linearization as well as a piece-wise linearization of the Hill curve leading to a hybrid formulation of the patient model and thereby the development of multiparametric hybrid model predictive control methodology. To deal with the inter- and intra- patient variability, as well as the noise on the process output, several robust techniques and a multiparametric moving horizon estimation technique have been design and implemented. All the studies described in the thesis are performed on clinical data for a set of 12 patients who underwent general anaesthesia.Open Acces

    Online weight estimation in a robotic gripper arm

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    This paper presents a novel methodology for online, fast and accurate weight estimation technique in a robotic gripper arm. The laboratory setup is inspired from several real life applications of weight estimation in moving cranes, e.g. loading containers in a shipyard, iron scrapping in steel industry, etc. The weight needs to be estimated within a specified time interval and within a tolerance interval for accuracy. The results indicate that the proposed method is suitable for this kind of application and an improvement of 30% has been achieved compared to the current state of work

    Design and practical implementation of a fractional order proportional integral controller (FOPI) for a poorly damped fractional order process with time delay

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    One of the most popular tuning procedures for the development of fractional order controllers is by imposing frequency domain constraints such as gain crossover frequency, phase margin and iso-damping properties. The present study extends the frequency domain tuning methodology to a generalized range of fractional order processes based on second order plus time delay (SOPDT) models. A fractional order PI controller is tuned for a real process that exhibits poorly damped dynamics characterized in terms of a fractional order transfer function with time delay. The obtained controller is validated on the experimental platform by analyzing staircase reference tracking, input disturbance rejection and robustness to process uncertainties. The paper focuses around the tuning methodology as well as the fractional order modeling of the process' dynamics

    Improving Activated Sludge Wastewater Treatment Process Efficiency Using Predictive Control

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    This paper investigates the performance of a new predictive control approach used to improve the energy efficiency and effluent quality of a conventional Wastewater Treatment Plant (WWTP). A modified variant of the well-known Generalized Predictive Control (GPC) method has been applied to control the dissolved oxygen concentration in the aerobic bioreactor of a WWTP. The quadratic cost function was modified to a positional implementation that considers control signal weighting and not its increments, in order to minimize the control energy. The Activated Sludge Process (ASP) optimization using the proposed variant of the GPC algorithm provides an improved aeration system efficiency to reduce energy costs. The control strategy is investigated and evaluated by performing simulations and analyzing the results. Both the set point tracking and the regulatory performances have been tested. Moreover, the effects of some tuning parameters are also investigated. The results show that this control strategy can be efficiently used for dissolved oxygen control in WWTP

    Predictive Adaptive Control of an Activated Sludge Wastewater Treatment Process

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    This paper presents an application regarding a model based predictive adaptive controller used to improve the effluent quality of a conventionalactivated sludge wastewater treatment process. The adaptive control scheme consists of two modules: a robust parameter estimator and a predictive controller. The controller design is based on the process model obtained by recursive estimation. The performances of the adaptive control algorithm are investigated and compared tothenon-adaptive one. Both the set point tracking and the regulatory performances have been tested. The results show that this control strategy will help overcome the challenge for maintaining the discharged water quality to meet the regulations
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