Keywords: Control System Design, System Identification and Modelling
Abstract: In this paper an approach for adapting a speed controller in order to perform a superposition of the speed of a circulating pump with a sinusoidal excitation is presented. In various applications the injection of a sinusoidal signal can be used for frequency response analysis. In this case the speed control of a circulating pump is adapted in order to perform a speed excitation which can be used for the identification of the pipeline network the pump is embedded in. As the original speed control was implemented with a PI-controller in order to control the operating point of the pump, the control is adapted by adding a resonant controller in parallel to the PI-controller in order to maintain a transfer function similar to the original one while providing an improved behaviour regarding the injection of the speed excitation.

Keywords: Control System Design, Optimization, Linear Systems
Abstract: In this paper a minimum-energy problem of perfect control algorithm dedicated to LTI MIMO plants described in the discrete-time state-space framework is shown. Following the new facts concerning the above-mentioned issue, a new solution based on the mathematical norms utilizing some generalized inverse formulas is given in this paper. The simulation instance confirms the correctness of a new intriguing method, which certainly leads to the final proof of whole, undiscovered yet, modern control theory.

Keywords: Control System Design, Nonlinear Systems
Abstract: Differential flatness and methods based on this property have proved to be very fruitful for tracking controllers and trajectory planning of nonlinear systems. As a dual to the concept of differentially flat outputs, this contribution deals with the computation of flat inputs, and thus with the problem of actuator placement. Given a mathematical description of a system’s behavior and a desired output, we propose an algorithm that constructs such inputs for observable systems. We show that there are no integrability problems which are typical for flat output computations, and exemplify this by an example. For non-observable systems, we show that an additional constraint needs to be fulfilled. It is not obvious how to incorporate this into an algorithm.

Keywords: Control System Design, Adaptive Control, Nonlinear Systems
Abstract: This paper presents the design of a combination of tensor product (TP)-based model transformation and of fuzzy control as a cascade control system (CCS) structure for the position control of the magnetic levitation (Maglev) laboratory equipment. The linearized Maglev system model was first stabilized using two control method: a state-feedback control structure (SF-CS) and a Proportional-Integral-state feedback control structure (PISF-CS). A comparative study of these state-feedback CSs is also included. A parallel distributed compensation technique is used in the TP-based design of the inner state feedback control loops which was next simplified by simple least squares identification algorithms. The modulus optimum method and the modal equivalent principle are used in the next step to design the Takagi-Sugeno fuzzy controller in the outer control loops. A comparative analysis and experimental results are given to validate the efficiency of the proposed CCS structure.

Keywords: Linear Systems, Control System Design, Robust Control
Abstract: This note is concerned with the static output feedback (SOF) H-infinity controller design for linear time-invariant systems. A sufficient bilinear matrix inequality (BMI) condition is developed for finding a stabilizing static output feedback H-infinity controller. For the first time, a novel cone complementary linearization approach within the context of linear matrix inequalities (LMI) is proposed to investigate the feasibility of the stabilizing controller synthesis along with a minimized H-infinity attenuation rate. The proposed method requires neither any apriori assumption generally made on the input/output matrices nor any application of a coordinate transformation. An example is presented for the application of the proposed scheme.

Keywords: Industrial Applications, Modelling, Simulation and CAD Tools, Control System Design
Abstract: In this paper, a simple yet versatile modelling approach for sinusoidal pressure oscillations in an industrial multi-stage condensation system and different control schemes for suppression are presented. The investigated condensation system is embedded in an extensive extraction system and is used to separate a hazardous substance out of a gas mixture. The main problem is posed by unknown and unmeasured process disturbances which may ultimately lead to pressure peaks exceeding the ambient pressure. When an over-pressure occurs the hazardous substance may escape, and a safety shut-down is triggered. A surrogate model, based on observations and the physical motivation that a gas flow contains kinetic and potential energy, is developed. The model is then based on the momentum and the ideal gas equation. The validation shows a good agreement with measurements in the time and frequency domain. To suppress the oscillations and guarantee an under-pressure in the system an linear output feedback controller, an adaptive algorithm for rejection of sinusoidal disturbances and a LQR-Controller with integration of the control error are compared. The simulation shows that the readily implementable linear output feedback control scheme sufficiently suppresses the oscillations and safely keeps the pressure in the under-pressure range.

Keywords: Modelling, Simulation and CAD Tools, Industrial Applications, Control System Design
Abstract: The paper presents the research results regarding process simulation and control of benzene separation in an industrial plant. The main purpose of the paper is to design a control quality system for the distillation column. The paper is structured in four parts, the first one being a review of the main simulation process software’s and ways of using them. The second part contains an overview of the industrial plant for benzene production. The third part is focused on the process simulation in steady state mode and the sensitivity analysis of the process. The last part is focused on the dynamic simulation of the process and basic control systems. The obtained numerical results had validated the dynamic simulation, creating the premises for designing and developing the automated control system of product quality.

Keywords: Control System Design, Other Topics
Abstract: This paper aims to presents the results obtained in electromechanical wind speed emulator of distributed low power system. The results are obtained in insulated regime with a step up/down converter, battery bank and resistive load. All the operating regions are aimed, namely optimization and power limitation one, and also an intermediate operating region is considered in order to ensure smooth transition between these two regions. For control purpose an improved strategy is proposed. Hardware implementation is done under DS1103 controller board running under Matlab and ControlDesk® software. This paper present results from a functional low power wind system, part of a distributed multisource low power system, which offer also the possibility of implementing the behavior and the control of such systems, in grid-connected or disconnected from the national grid. Experimental results show the effectiveness of the proposed system under various conditions.

Keywords: Automotive Control Systems, Control System Design, Optimization
Abstract: Machine learning is an emerging technology that can be used in multiple domains, including autonomous driving. This approach is explored in the present study case of 1:10 scale car components, delivering performances and further thoughts on full-scale implementation of an artificial neural network in the area of self-driving automobiles. The frames taken from live recording pass through an artificial neural network and return a steering angle. Even though the components used had limited specifications, the artificial neural network proved successful, with quite high accuracy in keeping the car on track, parking and maintaining smooth drive.

Keywords: Nonlinear Systems, System Identification and Modelling, Other Topics
Abstract: The paper presents a data-based synthesis method for power control algorithm of a wind turbine in full-load operating region, within a general strategy of gain scheduling type. The proposed method is based on the existence of several efficient solutions for the generation of a detailed mathematical model for a high-power wind system that by its simulation in different operating regimes can provide the necessary data obtained for the design procedure. The synthesis of the control algorithm is based on the construction of a dynamic compensator which can quickly provide the parameters of a PI control law for the rotational speed loop. In the paper the effects of the drive train torsional vibrations in the controller synthesis are analyzed by numerical simulation. Some results obtained with the gain-scheduling control approach are also presented.

Keywords: Optimization, Biomedical Engineering, System Identification and Modelling
Abstract: When dealing with epidemic spread, a very common and dangerous situation is the presence of an epidemic disease and a complication, especially in an elderly population or a weakened one. In this case the complication, that alone is not, in general, a fatal disease, may become risky. The ad hoc resource allocation becomes a mandatory task, aiming at the most rationale control strategy. This is the aim of this work, in which a new model is introduced; five classes are considered: the susceptible one, the class of people that has got the immunity from the first dangerous disease (but not from the complication), the class of patients with first disease, the class of those in the risky situation of having both the diseases, and the category of individuals with only the second disease that can still caught the first serious one. Control actions are introduced, as vaccination and medication, studying the effects of the different strategies. Preliminary simulation results evidenced the effectiveness of the proposed approach, allowing to determine a control strategy that reduces the number of dead, with an efficient resource allocation.

Keywords: Biomedical Engineering, System Identification and Modelling, Optimization
Abstract: Cancer represents one of the leading causes of mortality in this century. Patients suffering from lung cancer (LC) have an average of 5 years life expectancy after diagnosis. This is due usually to late detection. The most common methods to detect lung cancer are computed tomography (CT) and magnetic resonance imaging (MRI). These investigations are invasive to the human body and are performed only based on a doctor’s recommendation, which comes usually after patients develop symptoms – hence the late detection of cancer. Nowadays transthoracic ultrasonography (TUS) and US-guided biopsy have gained a larger field in the management of patients with peripheral pulmonary nodules or masses. From the multiple ultrasonography (US) advantages which made it a well-established solution in the management of tumoral and non-tumoral abdominal pathology, few stand out: it’s non-invasive and has reduced costs. However, until now transthoracic US is underused for lung cancer diagnosis because it can be hard to interpret to determine an accurate diagnosis. In this paper we aim to develop a software application for lung mass classification based on ultrasound image processing. This could be an important step in towards early detection of lung cancer, by introducing the transthoracic ultrasonography in the regular annual check-up, improving the life expectancy of patients or even complete recuperation.

Keywords: Control System Design, Nonlinear Systems, Biomedical Engineering
Abstract: Control algorithms for a bihormonal artificial pancreas are proposed in such a way that insulin and glucagon actions are incorporated, aiming to avoid hypoglicemic and hiperglicemic episodes. Such control algorithms are utilized in order to ensure the blood glucose regulation in type 1 diabetic patients. The mathematical model utilized has experimental validation and represents the glucose-insulin-glucagon dynamics. First-Order Sliding Mode Controllers with and without Boundary Layer were utilized. One desires to reach, in finite time, an equilibrium condition of the closed-loop control system, even in the presence of disturbances related to feeding. The stability proof is presented assuming that the state is known. In the simulation results, exact differentiators are used in order to recover the information associated with the unmeasured state variables of the system. At last, the performance of two control strategy is evaluated by means of numerical examples.

Keywords: Control System Design, Optimization, Biomedical Engineering
Abstract: In this paper the problem of the HIV/AIDS spread reduction is addressed in the framework of optimal control theory. A model recently proposed has been adopted; it considers two classes of susceptible subjects, the wise people and the people with incautious behaviours, and three classes of infected, the ones still not aware of their status, the pre-AIDS patients and the AIDS ones. The control actions involve prevention by information campaign, to reduce the category of subjects with unwise behaviour, by test campaign, to reduce the number of subjects not aware of having the virus, and medication on patients with a positive diagnosis. A cost index aiming at the reduction of patients with positive diagnosis is introduced with the conflicting requirements of using as less resources as possible.

Keywords: Biomedical Engineering, Signal Processing, Computer Vision
Abstract: This paper presents a method for the automatic identification and classification of red cells in different classes of interest for diagnosis using microscopic images of blood smear. The whole system uses different image processing techniques such as binarization, contrast enhancement, noise elimination, morphological operations (dilatation, erosion), labeling and extraction of some features of interest (area, perimeter, diameter). Using this information, some factors (form factor, circularity factor, and deviation factor) involved in the classification of red cells are calculated. The classification process has two phases: the first separates red cells in normal and abnormal type and the second classifies the abnormal in three subclasses. This system does not aim to replace the pathologist, but to assist him / her and to improve the execution time of these types of analyzes.

Keywords: Distributed Systems, Linear Systems, Industrial Applications
Abstract: The model of the axial and torsional vibrations for a drillstring with distributed parameters is obtained using the variational approach within the Hamiltonian Mechanics. Further there is considered the model of the axial vibrations which is a linear system with control and perturbation input signals. To the aforementioned equations of the model a system of equations with deviated argument is associated by integration along the characteristics. The system with deviated argument is of neutral type and allows construction of the basic theory but has its difference operator marginally (critically, not strongly) stable. This aspect is discussed finally and suggests the use of the methodology of the singular perturbations.

Keywords: Modelling, Simulation and CAD Tools, System Identification and Modelling, Computational Intelligence
Abstract: Drilling operations face with three types of vibrations - torsional, axial and lateral, which are coupled oscillations that occur from the interaction of the drillstring with the rock at the bottom of the borehole. The paper focuses on the numerical and computational modeling of the axial vibrations of a drilling system, considering the case of distributed parameters as being tight connected with the physical description of these phenomena and providing high accuracy of system behavior. The system is modeled by hyperbolic partial differential equations with control and perturbation input signals. The computational solution is derived by means of a well-structured procedure which relies on a "convergent Method of Lines" - a semianalytical method used to transform the infinite dimensional system in a finite dimensional one. The computational issues are then tackled via the paradigm of cell-based neural networks which exploit the peculiarities of the approximate system previous obtained. The numerical simulations allow a better understanding of the system dynamics regarding its transient and long-term behavior.

Keywords: Control System Design, Agent-based Systems, Robotics
Abstract: This paper proposes a solution regarding the general consensus of a multi-agent time-delay system in order to achieve interactive and transport operations. The multi-agent system consists of a set of omnidirectional mobile robots equipped with vision-based systems and interactive tools. It is well known that the vision-based systems and the communication between agents produce time-delays, causing stability issues for consensus and formation control. The present work deals with a high precision consensus by means of a time-delay tolerant control law. First, the mathematical model of every agent is presented. Then, this dynamic model is extended to the set of robots conforming the multi-agent system. After that, a control law, consisting on a time-delay tolerant strategy allows orientation and position consensus. The formulation of a simple algorithm for orientation and position formations for the set of robots is presented. Finally, simulation results validate the proposed control strategy and compare the results when time-delay is present in the system or not for an object transport scenario.

Keywords: Computer Vision, Computational Intelligence, Embedded Systems
Abstract: The present paper describes a pipeline digital architecture of a fuzzy rule base grayscale image contrast enhancement system. The proposed system uses a zero order Takagi-Sugeno fuzzy model, adapted to avoid the division operation in the deffuzification block and also to reduce the computational requirements for the fuzzification block. The digital architecture is optimized to benefit from the advantages provided by the Xilinx DSP48E2 slice in terms of speed and logic resource consumption. The design has been synthesized and tested on a Xilinx FPGA device and the reported results confirm its viability to be embedded in real time application systems. Also, the functionality of the proposed system was tested on a set of low contrast images, illustrating heavy traffic conditions.

Keywords: Embedded Systems, Communication Systems
Abstract: Controller Area Network (CAN) is the most used protocol for intra-vehicle communication between Electronic Control Units (ECUs) for decades. Moreover, there are several implementations of industrial networks built on top of CAN, (i.e. CANopen and DeviceNet) that expanded even more its area of application to almost any industrial automation field. The growing needs for data in today’s modern and safe applications led to CAN Flexible Data Rate (CAN FD) in order to increase the network throughput and pushed the data field of the CAN frames beyond the 1Mbps limit of the high speed CAN chips. A low cost CAN-USB interface application for dual CAN bus network monitoring, diagnose and maintenance is proposed which can be easily ported on any member of the ARM Cortex-M microcontroller family with built-in CAN or CAN-FD communication.

Keywords: Linear Systems
Abstract: The role played by column representatives is expanded in the study of the properties exhibited by the trajectories of arbitrary switching linear systems. Previous contributions reported in literature on the employment of column representatives focused on positive dynamics and linear copositive Lyapunov functions associated with exponentially contractive positive sets that are invariant with respect to such dynamics. Our approach refers to arbitrary dynamics (not only positive) and invariant sets with general form for time-dependence (not only exponentially contractive). We address both discrete- and continuous-time cases. Our key finding is that the existence of such invariant sets is fully characterized (if and only if) by the Schur (Hurwitz respectively) stability of the column representatives corresponding to a matrix set adequately built from the original system matrices. Our mathematical developments are illustrated by a numerical example. These developments incorporate the previous contributions mentioned above as particular cases.

Keywords: Linear Systems
Abstract: This paper presents a comparison between different control strategies used for estimation purposes for systems with unknown inputs in the recently proposed Control-based Observer approach. In particular, several robust state and unknown inputs observers are derived using classical controllers such as Proportional or Proportional Integral, Linear Quadratic Regulator or Linear Quadratic Integrator and H1 Full information. They are also compared with criteria such as the quality of the estimation, the speed of the observers, the robustness against the noise and the complexity of the observers. Simulation results are provided to better highlight the comparison.

Keywords: Linear Systems, Other Topics
Abstract: The paper explores the properties of positive interval dynamic systems in continuous-time, via two types of techniques, and develops a comparative study between the two approaches. The first type is based on the properties of the row and column representatives corresponding to the vertex set of the interval matrix A = [A-, A+]. The second type employs the properties of the dominant vertex A+ of the interval matrix. The results, separately derived for the two approaches, show the equivalence between the Hurwitz stability of matrix A+, the existence of several classes of Lyapunov functions, and the existence of several classes of exponentially decreasing sets that are positively invariant with respect to the interval system dynamics.

Keywords: Linear Systems, Optimization, Control System Design
Abstract: In this paper, we propose a generalization of coprime factorization of plants. This generalization does not require the right-/left-coprime factorizabilities and consists of several fractions of given plant. This leads a new method to obtain a stabilizing controller and, analogously to the coprime factorization, alternative different stabilizing controllers. We also present their applications.

Keywords: Linear Systems, Robust Control, Optimization
Abstract: Transient performance problems in stable linear systems were always in focus of the control community. Nevertheless, deviations of trajectories in input-free discrete time systems have been paid much less attention. In this paper, we are interested in estimating the magnitudes of deviations caused by nonzero initial conditions. First, we present examples where the magnitude of peak can be computed in closed form and show that it may take very large values. Next, we propose numerical procedures for the computation of upper bounds on deviations and for the design of peak-attenuating controllers. Finally, we present an extension to the case of uncertain systems. Numerical experiments confirm the efficiency of the approach and demonstrate its low conservatism.

Keywords: Linear Systems, Control System Design, Optimization
Abstract: Lyapunov equations are often encountered in control theory and its applications, including system balancing, model and controller order reduction, and stability analyses. An accuracy-enhancing solver for standard and generalized continuous- and discrete-time Lyapunov equations is investigated in this paper. It has been derived by specializing a solver for algebraic Riccati equations based on Newton's method. The conceptual algorithm and some implementation details are summarized. The numerical results obtained by solving sets of examples of increasing dimension and numerical difficulty from the SLICOT benchmark collections for Lyapunov equations are analyzed and compared to the solutions computed by the state-of-the-art MATLAB and SLICOT solvers. The results show that most often the new solver is more accurate, sometimes by several orders of magnitude, than its competitors, and requires only a small increase of the computational effort.

Keywords: Fault Diagnosis and Fault Tolerant Control, Automotive Control Systems, Control System Design
Abstract: Current trends in the automotive industry are increasingly focusing on the concept of autonomous / automated driving. At the heart of this concept is the need to provide new solutions dedicated to increase safety in operation, reduce the risk of accidents and make automotive systems more efficient. To meet these criteria, the new systems need to be as reliable as possible, provide complete full-time assistance and be also able to provide partial assistance in case of fault (1 FIT – Failure in Time). To this is added the requirement for reduced energy consumption, which implies higher efficiency of the considered systems. The paper presents a theoretical study doubled by a simulation analysis of some efficient strategies for controlling a redundant actuation system, which is viable both in normal and fault mode operation. In order to provide a high level of redundancy in both hardware and software, this concept implies the use of two independent control systems that provide command to two B6 bridge inverters and feeds the phases of a dual stator brushless direct current (BLDC) motor. The proposed system can be successfully integrated both in the electric power steering and braking systems of today's modern vehicles, as well as in autonomous driving platforms. To obtain a reliable and realistic BLDC motor model, the mathematical analysis was matched to a specific model design obtained in FEA (Finite Element Analysis). In order to validate the presented theoretical aspects, this study is followed by the implementation of the equivalent mathematical models in MATLAB / Simulink simulation environment.

Keywords: Theory of Algorithms, Software Engineering, Linear Systems
Abstract: The so-called factored-form Kalman filter (KF)implementations are designed to deal with the problem of numerical instability of the conventional KF. They include Cholesky factorization-based, UD-based and singular value decomposition (SVD) algorithms. The SVD-based estimators are the most recent developments in this realm. They were shown to be more robust with respect to roundoff than the classical KF implementation and the previously derived factored-form methods. This paper discusses further improvements in estimation accuracy and numerical robustness of the recently proposed SVD-based estimators.

Keywords: Other Topics
Abstract: Load current signatures are commonly used to characterize household electricity consumers. This paper introduces a new load signature class, the ellipse class, in addition to the tangent class already used in [10]. For both classes the signature consists of the set of parameters assigned to the two types of analytical functions. Signature determination is based on the operation of samples obtained at a very low frequency of approximately 20 Hz. This paper illustrates applications to both a single consumer and two consumers of the same class or of different classes.

Keywords: Industrial Applications, Control System Design, System Identification and Modelling
Abstract: In the paper, a method to control the strong nonlinear process associated to a separation column used for the 18O isotope production, is presented. In order to obtain an accurate process model, neural networks are used. The proposed control strategy is analyzed both in the case when the main disturbance signals occur and they do not occur in the system. In order to improve the control system performances, the theory of fractional-order controllers is applied, combined with an adaptive algorithm. For a more efficient disturbances effect rejection, the reference model of the separation process is used.

Keywords: Linear Systems, Theory of Algorithms, Real Time Applications
Abstract: In this paper, several general forms of linear time-invariant (LTI) state-space models are explored. In particular, a numerical robustness of the so-called pairwise Kalman filter (PKF) is investigated. We propose stable singular value decomposition (SVD) factorization-based algorithms for implementing the PKF and LTI MIMO estimator, respectively, and explain their practical applicability in econometrics discipline. More precisely, the test for evolving efficiency is expressed in the LTI MIMO form and the newly-derived SVD-based estimator is applied for recovering the Russian market weak-form efficiency process in the last 20 years.

Keywords: Signal Processing, Optimization, Other Topics
Abstract: This paper proposes a new strategy for prototypes initialization in linear vector quantization algorithm (LVQ). Three principles which must be satisfied during the learning stage are shown in the paper. These principles are essential to guarantee appropriate learning for the LVQ algorithm. However, all versions of LVQ algorithms try to answer to one of the principles, but unfortunately contradicting with the other ones. The new strategy proposed in the paper aims to solve this issue and consists of two steps: (1) analyse the a-priori data set and (2) apply a pre-learning algorithm to initialize the prototypes. The pre-learned prototypes resulted from step 2 are used by the LVQ algorithm in the learning process. The examples presented in the case study and the criterion used to assess the training performance of the prototypes reinforce that the training strategy of the prototypes proposed in the paper provides better results in certain situations compared to classical LVQ algorithms.

Keywords: Control System Design, Industrial Applications, Nonlinear Systems
Abstract: A PID based hierarchical control strategy is proposed to improve the WWTP performance from a plantwide perspective. An integral efficiency index (N/E index) is defined that measures the ratio between the nitrogen removed in the activated sludge process (KgrN) and the energy (KWh) required for eliminating that amount of nitrogenated compounds. That index is controlled by an upper level PI controller that changes the dissolved oxygen (DO) set point of the regulation level control loop. When the DO concentration is driven to excessively low limits, the N/E index set-point can be unreachable. Under this situation, the nitrogen elimination can be negatively affected. Therefore, it is not desirable to keep the plant in this situation for a long time. Therefore, an event-based controller is implemented to adapt the N/E index set-point to realistic values preventing long operation periods with the lowest DO concentration

Keywords: Control System Design, Nonlinear Systems
Abstract: The paper addresses the design and analysis of Iterative Learning Control (ILC) method for a wastewater biodegradation process. The bioprocess is considered to take place inside a continuous stirred tank bioreactor. The use of this kind of control methods is motivated by its advantages in the case of complex nonlinear systems like biotechnological processes. There were used two ILC algorithms – one considered a classical approach in the field (PD – type learning algorithm), and the second one which try to exploit some characteristics of the input signal (exponential learning algorithm). These control methods are implemented for the depollution control problem in the case of an anaerobic digestion process. This bioprocess is characterized by strongly nonlinear and not exactly known reaction rates. Furthermore, not all the state variables are measurable. The performance and effectiveness of the presented control algorithms are proven by simulation results.

Keywords: Control System Design, Industrial Applications, Nonlinear Systems
Abstract: This paper addresses the problem of basic control loops in wastewater treatment plants. By basic control loops we are referring to the traditional dissolved oxygen and nitrates. In a usual activated sludge process based wastewater treatment plant, these controls are located, respectively, at the aerated and anoxic sections. They are the basic controls more sophisticated control solutions can be based upon. Therefore it is important that these loops perform in an efficient way. The problem is addressed here within the framework provided by the Benchmark Simulation Model Number 1 (BSM1) and by the use of an event-based solution. As far as to the knowledge of the authors, no solution based on this kind of controllers has been proposed already in the literature. The controllers are taken as of similar complexity as the ones provided as default control strategy in the BSM1, therefor being the main difference, the possibilities provided by the event-based implementation. It will be verified that the solution can slightly improve the performance of the already exiting controllers both at loop level as well as at plant operation level.

Keywords: Nonlinear Systems, Predictive Control, Adaptive Control
Abstract: This paper presents two estimation based control strategies for an aerobic process used in wastewater biological treatment carried out inside a Continuous Stirred Tank Reactor (CSTR). The control objective is to maintain the effluent pollutant concentration at a desired low level correlated with an adequate control of dissolved oxygen concentration. Therefore we propose two new control schemes for robust-adaptive and model predictive control, taking into account the Bayesian based weighted values of the state’s estimations provided by an interval observer and a parameter estimator of the unknown specific growth rate. A comparison of the effectiveness of the two approaches is illustrated by numerical simulations performed under different conditions related to some degree of uncertainness of a continuous wastewater treatment bioprocess.

Keywords: Control System Design, Industrial Applications, Nonlinear Systems
Abstract: Due to the complex and non linear character, wastewater treatment process is difficult to be controlled. And the demand for removing the pollutant, especially for nitrogen (N) and phosphorus (P), as well as reducing the cost of wastewater treatment plant (WWTP) is an important research topic. This paper applies PI control and decentralised model predictive control control to the combined phosphorus removal Benchmark Simulation Model 1 (BSM1-P) wastewater treatment process to enhance the P removal. A default control strategy which contains two control loops and is similar to the one given by the original version of BSM1 was tested on BSM1-P. In addition, linear models have been identified and model predictive controllers implemented for each one of these loops. The simulation results showed that the MPC controllers are able to the controller performance in all the three weather conditions.

Keywords: Nonlinear Systems, Optimization, System Identification and Modelling
Abstract: This paper deals with the optimization of an anaerobic digestion process considering aspects regarding both the economic benefit, expressed through the biogas production, as well as environmental issues, expressed through the quality of the discharged water. The adopted method involves determining the optimal regimes characteristics obtained based on a mathematical model. The optimal set point of the water quality loop, expressed by the Chemical Oxygen Demand, is computed as a function of the influent substrate concentration. The water quality loop includes a robust control solution based on the Quantitative Feedback Theory, thus incorporating the parametric uncertainties that affects this type of processes.

Keywords: Internet of Things, Distributed Systems
Abstract: The term “autonomy” comes from the Greek roots “autos” and “nomos”, which mean “self” and “law” respectively. This survey paper investigates the concept of autonomy in connection with the development of cyber-physical systems. The concept of autonomy refers to a form of self-regulation or self-government of individual or collaborating systems. An autonomously operating system will need to be able to recognise and differentiate itself among other systems to be able to function on different levels. To be able to increase systems’ autonomy, they need self-configuring, self-optimising, self-healing, and self-protecting capabilities. By developing such capabilities, systems will be able to adapt to changes that emerge from within them or in their environment. Networking these systems subsequently allows them to communicate and interact with each other, ultimately enabling them to jointly make decisions. This kind of joint decision making potentially amplifies the autonomy of the whole of interconnected systems in the performance of joint activities.

Keywords: Embedded Systems, Internet of Things, Communication Systems
Abstract: The need to secure property or restrict entrance in special areas by controlling access to them has always been extremely important for life safety and personal assets, as well as those of the organizations. Different mechanical or electronic door locks are available today using keypads and passwords, RFID devices, biometric data, in order to prevent unauthorized access in homes, research labs, banks, stores, etc. This paper presents a secure access control system based on a Raspberry Pi3 model B board connected to Internet via the local area network. The system monitors in real-time the front of the door using a camera and face recognition features, and notify the system administrator if anyone spends time in front of the door more than a specified limit. Registered users have allowed access and may unlock the door through a mobile application, as the identification may be done by face recognition, password, or fingerprint, subject of availability. The system administrator also has access to the camera captured frames and may unlock the door remotely per request. A web server running on the Raspberry Pi3 embedded system maintain a local database containing the registered user list and related data, as well as a log file that provide the system administrator detailed information about any detected and recorded events.

Keywords: Discrete Event Systems, Internet of Things, Other Topics
Abstract: The hyper-connected society, to be developed during the next decades, is facing great challenges. New requirements, that should preserve the well-balanced harmony between natural resources and human capital resources, will involve greater responsibility within the global e-democracy framework. Thus the globalization is a strong influence for enterprise development. Enterprise systems are becoming contextual complex adaptive systems. Such systems rely on complex process models to support enterprise operations. The present paper explores various key aspects of Future Enterprise Systems and discusses their practical implications through a case study involving an application of process mining techniques on streams of events collected from a sensor network.

Keywords: Internet Security, Biologically Inspired Systems, Internet of Things
Abstract: Digital instruments play a vital role in our daily life. It is a routine to produce business papers, watch the news program, write articles and blogs, manage healthcare systems, to purchase online, to send messages and all this is processed by making observations and then manipulating, receiving and availing the diverse data. This electronic data provides the foundation of real time data. All this transmission of data needs to be secured. Security is essential for healthcare systems as the present one where the blood pressure recordings provided by the smart bracelet are sent to the user's mobile phone via Bluetooth. The bracelet monitors the pregnant women, but also other users who wish to have their blood pressure under control. The system's server analyses the recordings and announces the user, as well as the associated persons to the user in case of an emergency. The doctors, the medical staff, user and user's family and caregivers have access to the health recordings belonging to the monitored user. Security is a main feature of the electronic healthcare system based on the smart bracelet.

Keywords: Manufacturing Systems, Networked Control, Internet of Things
Abstract: Edge computing is essential for the Industrial IoT as framework for data acquisition from shop floor devices; distributed intelligence will shift to the edge for speed reasons in real-time handling of big data. This research aims at developing a generic architecture for information and data collection, smart processing and aggregation at the edge of large-scale manufacturing control systems; the edge is represented by the set of shop floor entities (things) – resources and intelligent products that are agentified and communicate in multi-agent systems for decentralized MES tasks. The IIoT architecture integrates a private cloud platform with a network of IoT aggregation nodes composed of IoT gateways, sensors and PC-type workstations hosting the resource agents. Both networks form the distributed MES layer of a semi-heterarchical, cloud-based production control system. The implementing solution is given; experiments report communication with the cloud.

Keywords: Distributed Systems, Databases and Data Mining, Web Services
Abstract: The Internet is ever growing and the information is highly unstructured. Finding the best priced product when shopping online is a difficult task, but shopping search engines help the user identify the desired product. Starting from this reality, this paper presents a distributed framework for information retrieval, processing and presentation of data, which has three main components: a data server cluster, a distributed crawler with a product extraction feature, and a web server for presenting the processed data. The considered use case consists of extracting information about board and card games from specialized websites and presenting the data in a user-friendly website. Efficiency is determined by means of performance evaluation metrics that include crawl and extraction times, and a discussion in terms of scalability. The high modularization of the framework allows it to be an effective teaching tool in classrooms; each module can be easily swapped with a custom implementation. The proposed framework offers students and researchers an environment for developing and testing a wide range of algorithms and programming solutions, e.g., load balancer, crawler, reverse engineering a web template, product extractor from web pages, data normalization, notification services, web APIs, custom database.