Search results for: real time control

Authors: Desislav Andreev, Veselin Stanev

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Linux operating system continues to gain popularity with every passed year. This is due to its open-source license and a great number of distributions, covering users’ needs. At first glance it seems that Linux can be integrated in every type of systems – it is already present in personal computers, smartphones and even in some embedded systems like Raspberry Pi. However, Linux still does not meet the performance and security requirements to run effectively on a real-time system. Real-time systems are very time-restricted – their processes have to execute and finish at strict time intervals. The Completely Fair Scheduler present in Linux does not have such scheduling capabilities and it is not able to ensure that critical-time processes will execute on time. One of the ways to solve this problem is implementing an Adaptive Partition Scheduler solution similar to that present in QNX Neutrino operating system. This type of scheduling divides the CPU in multiple adaptive partitions where each partition holds a percentage of CPU usage called budget, which allows optimal usage of the CPU resources and also provides protection against cyber attacks such as Denial of Service. This approach will also benefit systems, where functional safety is highly demanded, such as the instrumental clusters in the Automotive industry. The purpose of this paper is to present a concept of Adaptive Partition Scheduler designed for Linux-based operating systems.

Keywords: adaptive partitions, Linux kernel modules, real-time systems, scheduling

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Authors: Othmane Boughazi, Abdelmadjid Boumedienne, Hachemi Glaoui

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This work treats the modeling and simulation of non-linear system behavior of an induction motor using backstepping sliding mode control. First, the direct field oriented control IM is derived. Then, a sliding for direct field oriented control is proposed to compensate the uncertainties, which occur in the control.Finally, the study of Backstepping sliding controls strategy of the induction motor drive. Our non linear system is simulated in MATLAB SIMULINK environment, the results obtained illustrate the efficiency of the proposed control with no overshoot, and the rising time is improved with good disturbances rejections comparing with the classical control law.

Keywords: induction motor, proportional-integral, sliding mode control, backstepping sliding mode control

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Authors: Li Li, Kai-Hsuan Chu

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It is well known that the real estate price depends on a lot of factors. Each house current value is dependent on the location, room number, transportation, living convenience, year and surrounding environments. Although, there are different experienced models for housing agent to estimate the price, it is a case by case study without overall dynamic variation investigation. However, many economic parameters may more or less influence the real estate price variation. Here, the influences of most macroeconomic parameters on real estate price are investigated individually based on least-square scheme and grey correlation strategy. Then those parameters are classified into leading indices, simultaneous indices and laggard indices. In addition, the leading time period is evaluated based on least square method. The important leading and simultaneous indices can be used to establish an artificial intelligent neural network model for real estate price variation prediction. The real estate price variation of Taipei, Taiwan during 2005 ~ 2017 are chosen for this research data analysis and validation. The results show that the proposed method has reasonable prediction function for real estate business reference.

Keywords: real estate price, least-square, grey correlation, macroeconomics

Procedia PDF Downloads 161

Authors: Pengzhou Lu, Liming Xin, Payam Tavakoli, Zhonghua Lin, Roberto V. P. Ribeiro, Mitesh V. Badiwala

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Ex vivo Heart Perfusion (EVHP) has been developed as an alternative strategy to expand cardiac donation by enabling resuscitation and functional assessment of hearts donated from marginal donors, which were previously not accepted. EVHP parameters, such as perfusion flow (PF) and perfusion pressure (PP) are crucial for optimal organ preservation. However, with the heart’s constant physiological changes during EVHP, such as coronary vascular resistance, manual control of these parameters is rendered imprecise and cumbersome for the operator. Additionally, low control precision and the long adjusting time may lead to irreversible damage to the myocardial tissue. To solve this problem, an automatic heart perfusion system was developed by applying a Human-Machine Interface (HMI) and a Programmable-Logic-Controller (PLC)-based circuit to control PF and PP. The PLC-based control system collects the data of PF and PP through flow probes and pressure transducers. It has two control modes: the RPM-flow mode and the pressure mode. The RPM-flow control mode is an open-loop system. It influences PF through providing and maintaining the desired speed inputted through the HMI to the centrifugal pump with a maximum error of 20 rpm. The pressure control mode is a closed-loop system where the operator selects a target Mean Arterial Pressure (MAP) to control PP. The inputs of the pressure control mode are the target MAP, received through the HMI, and the real MAP, received from the pressure transducer. A PID algorithm is applied to maintain the real MAP at the target value with a maximum error of 1mmHg. The precision and control speed of the RPM-flow control mode were examined by comparing the PLC-based system to an experienced operator (EO) across seven RPM adjustment ranges (500, 1000, 2000 and random RPM changes; 8 trials per range) tested in a random order. System’s PID algorithm performance in pressure control was assessed during 10 EVHP experiments using porcine hearts. Precision was examined through monitoring the steady-state pressure error throughout perfusion period, and stabilizing speed was tested by performing two MAP adjustment changes (4 trials per change) of 15 and 20mmHg. A total of 56 trials were performed to validate the RPM-flow control mode. Overall, the PLC-based system demonstrated the significantly faster speed than the EO in all trials (PLC 1.21±0.03, EO 3.69±0.23 seconds; p < 0.001) and greater precision to reach the desired RPM (PLC 10±0.7, EO 33±2.7 mean RPM error; p < 0.001). Regarding pressure control, the PLC-based system has the median precision of ±1mmHg error and the median stabilizing times in changing 15 and 20mmHg of MAP are 15 and 19.5 seconds respectively. The novel PLC-based control system was 3 times faster with 60% less error than the EO for RPM-flow control. In pressure control mode, it demonstrates a high precision and fast stabilizing speed. In summary, this novel system successfully controlled perfusion flow and pressure with high precision, stability and a fast response time through a user-friendly interface. This design may provide a viable technique for future development of novel heart preservation and assessment strategies during EVHP.

Keywords: automatic control system, biomedical engineering, ex-vivo heart perfusion, human-machine interface, programmable logic controller

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Authors: Qian Liu, Steve Furber

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To explore how the brain may recognize objects in its general,accurate and energy-efficient manner, this paper proposes the use of a neuromorphic hardware system formed from a Dynamic Video Sensor~(DVS) silicon retina in concert with the SpiNNaker real-time Spiking Neural Network~(SNN) simulator. As a first step in the exploration on this platform a recognition system for dynamic hand postures is developed, enabling the study of the methods used in the visual pathways of the brain. Inspired by the behaviours of the primary visual cortex, Convolutional Neural Networks (CNNs) are modeled using both linear perceptrons and spiking Leaky Integrate-and-Fire (LIF) neurons. In this study's largest configuration using these approaches, a network of 74,210 neurons and 15,216,512 synapses is created and operated in real-time using 290 SpiNNaker processor cores in parallel and with 93.0% accuracy. A smaller network using only 1/10th of the resources is also created, again operating in real-time, and it is able to recognize the postures with an accuracy of around 86.4% -only 6.6% lower than the much larger system. The recognition rate of the smaller network developed on this neuromorphic system is sufficient for a successful hand posture recognition system, and demonstrates a much-improved cost to performance trade-off in its approach.

Keywords: spiking neural network (SNN), convolutional neural network (CNN), posture recognition, neuromorphic system

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Authors: V. Reyes, P. Ferreira

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In response to high levels of competitiveness, industrial systems have evolved to improve productivity. As a consequence, a rapid increase in volume production and simultaneously, a customization process require lower costs, more variety, and accurate quality of products. Reducing time-cycle production, enabling customizability, and ensure continuous quality improvement are key features in advance intelligent industry. In this scenario, customers and producers will be able to participate in the ongoing production life cycle through real-time interaction. To achieve this vision, transparency, predictability, and adaptability are key features that provide the industrial systems the capability to adapt to customer demands modifying the manufacturing process through an autonomous response and acting preventively to avoid errors. The industrial system incorporates a diversified number of components that in advanced industry are expected to be decentralized, end to end communicating, and with the capability to make own decisions through feedback. The evolving process towards advanced intelligent industry defines a set of stages to empower components of intelligence and enhancing efficiency to achieve the decision-making stage. The integrated system follows an industrial cyber-physical system (CPS) architecture whose real-time integration, based on a set of enabler technologies, links the physical and virtual world generating the digital twin (DT). This instance allows incorporating sensor data from real to virtual world and the required transparency for real-time monitoring and control, contributing to address important features of the advanced intelligent industry and simultaneously improve sustainability. Assuming the industrial CPS as the core technology toward the latest advanced intelligent industry stage, this paper reviews and highlights the correlation and contributions of the enabler technologies for the operationalization of each stage in the path toward advanced intelligent industry. From this research, a real-time integration architecture for a cyber-physical system with applications to collaborative robotics is proposed. The required functionalities and issues to endow the industrial system of adaptability are identified.

Keywords: cyber-physical systems, digital twin, sensor data, system integration, virtual model

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Authors: Darren A. Whitaker, Dan Palmer, Jens Wesholowski, James Flaherty, John Mack, Ahmad B. Albadarin, Gavin Walker

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Traditional mechanosynthesis has been performed by either ball milling or manual grinding. However, neither of these techniques allow the easy application of process control. The temperature may change unpredictably due to friction in the process. Hence the amount of energy transferred to the reactants is intrinsically non-uniform. Recently, it has been shown that the use of Twin-Screw extrusion (TSE) can overcome these limitations. Additionally, TSE enables a platform for continuous synthesis or manufacturing as it is an open-ended process, with feedstocks at one end and product at the other. Several materials including metal-organic frameworks (MOFs), co-crystals and small organic molecules have been produced mechanochemically using TSE. The described advantages of TSE are offset by drawbacks such as increased process complexity (a large number of process parameters) and variation in feedstock flow impacting on product quality. To handle the above-mentioned drawbacks, this study utilizes UV-Vis spectrophotometry (InSpectroX, ColVisTec) as an online tool to gain real-time information about the quality of the product. Additionally, this is combined with real-time process information in an Advanced Process Control system (PharmaMV, Perceptive Engineering) allowing full supervision and control of the TSE process. Further, by characterizing the dynamic behavior of the TSE, a model predictive controller (MPC) can be employed to ensure the process remains under control when perturbed by external disturbances. Two reactions were studied; a Knoevenagel condensation reaction of barbituric acid and vanillin and, the direct amidation of hydroquinone by ammonium acetate to form N-Acetyl-para-aminophenol (APAP) commonly known as paracetamol. Both reactions could be carried out continuously using TSE, nuclear magnetic resonance (NMR) spectroscopy was used to confirm the percentage conversion of starting materials to product. This information was used to construct partial least squares (PLS) calibration models within the PharmaMV development system, which relates the percent conversion to product to the acquired UV-Vis spectrum. Once this was complete, the model was deployed within the PharmaMV Real-Time System to carry out automated optimization experiments to maximize the percentage conversion based on a set of process parameters in a design of experiments (DoE) style methodology. With the optimum set of process parameters established, a series of PRBS process response tests (i.e. Pseudo-Random Binary Sequences) around the optimum were conducted. The resultant dataset was used to build a statistical model and associated MPC. The controller maximizes product quality whilst ensuring the process remains at the optimum even as disturbances such as raw material variability are introduced into the system. To summarize, a combination of online spectral monitoring and advanced process control was used to develop a robust system for optimization and control of two TSE based mechanosynthetic processes.

Keywords: continuous synthesis, pharmaceutical, spectroscopy, advanced process control

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Authors: Tomas Menard

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The synthesis of output-feedback control law has been investigated by many researchers since the last century. While many results exist for the case of Linear Time Invariant systems whose measurements are continuously available, nowadays, control laws are usually implemented on micro-controller, then the measurements are discrete-time by nature. This fact has to be taken into account explicitly in order to obtain a satisfactory behavior of the closed-loop system. One considers here a general class of systems corresponding to an observability normal form and which is subject to uncertainties in the dynamics and sampling of the output. Indeed, in practice, the modeling of the system is never perfect, this results in unknown uncertainties in the dynamics of the model. We propose here an output feedback algorithm which is based on a linear state feedback and a continuous-discrete time observer. The main feature of the proposed control law is that only discrete-time measurements of the output are needed. Furthermore, it is formally proven that the state of the closed loop system exponentially converges toward the origin despite the unknown uncertainties. Finally, the performances of this control scheme are illustrated with simulations.

Keywords: dynamical systems, output feedback control law, sampling, uncertain systems

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Authors: Ha Thi Nguyen, Guangya Yang, Arne Hejde Nielsen, Peter Højgaard Jensen

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Automatic voltage regulator (AVR) plays an important role in volt/var control of synchronous condenser (SC) in power systems. Test AVR performance in steady-state and dynamic conditions in real grid is expensive, low efficiency, and hard to achieve. To address this issue, we implement hardware-in-the-loop (HiL) test for the AVR of SC to test the steady-state and dynamic performances of AVR in different operating conditions. Startup procedure of the system and voltage set point changes are studied to evaluate the AVR hardware response. Overexcitation, underexcitation, and AVR set point loss are tested to compare the performance of SC with the AVR hardware and that of simulation. The comparative results demonstrate how AVR will work in a real system. The results show HiL test is an effective approach for testing devices before deployment and is able to parameterize the controller with lower cost, higher efficiency, and more flexibility.

Keywords: automatic voltage regulator, hardware-in-the-loop, synchronous condenser, real time digital simulator

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Authors: Juneseok You, Kuewhan Jang, Chanho Park, Jaeyeong Choi, Hyunjun Park, Sehyun Shin, Changsoo Han, Sungsoo Na

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Nanomaterials occur toxic effects to human being or ecological systems. Some sensors have been developed to detect toxic materials and the standard for toxic materials has been established. Zinc oxide nanowire (ZnO NW) is known for toxic material. By ionizing in cell body, ionized Zn ions are overexposed to cell components, which cause critical damage or death. In this paper, we detected ZnO NW in water using QCM (Quartz Crystal Microbalance) and ssDNA (single strand DNA). We achieved 30 minutes of response time for real time detection and 100 pg/mL of limit of detection (LOD).

Keywords: zinc oxide nanowire, QCM, ssDNA, toxic material, biosensor

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Authors: Sunday B. Alabi, Edikan P. Felix, Aniediong M. Umo

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Crystal size distribution is of great importance in the sugar factories. It determines the market value of granulated sugar and also influences the cost of production of sugar crystals. Typically, sugar is produced using fed-batch vacuum evaporative crystallizer. The crystallization quality is examined by crystal size distribution at the end of the process which is quantified by two parameters: the average crystal size of the distribution in the mean aperture (MA) and the width of the distribution of the coefficient of variation (CV). Lack of real-time measurement of the sugar crystal size hinders its feedback control and eventual optimisation of the crystallization process. An attractive alternative is to use a soft sensor (model-based method) for online estimation of the sugar crystal size. Unfortunately, the available models for sugar crystallization process are not suitable as they do not contain variables that can be measured easily online. The main contribution of this paper is the development of a regression model for estimating the sugar crystal size as a function of input variables which are easy to measure online. This has the potential to provide real-time estimates of crystal size for its effective feedback control. Using 7 input variables namely: initial crystal size (Lo), temperature (T), vacuum pressure (P), feed flowrate (Ff), steam flowrate (Fs), initial super-saturation (S0) and crystallization time (t), preliminary studies were carried out using Minitab 14 statistical software. Based on the existing sugar crystallizer models, and the typical ranges of these 7 input variables, 128 datasets were obtained from a 2-level factorial experimental design. These datasets were used to obtain a simple but online-implementable 6-input crystal size model. It seems the initial crystal size (Lₒ) does not play a significant role. The goodness of the resulting regression model was evaluated. The coefficient of determination, R² was obtained as 0.994, and the maximum absolute relative error (MARE) was obtained as 4.6%. The high R² (~1.0) and the reasonably low MARE values are an indication that the model is able to predict sugar crystal size accurately as a function of the 6 easy-to-measure online variables. Thus, the model can be used as a soft sensor to provide real-time estimates of sugar crystal size during sugar crystallization process in a fed-batch vacuum evaporative crystallizer.

Keywords: crystal size, regression model, soft sensor, sugar, vacuum evaporative crystallizer

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Authors: Tesnim Charrad, Kaouther Nouira, Ahmed Ferchichi

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In order to reduce the number of deaths due to heart problems, we propose the use of Hierarchical Temporal Memory Algorithm (HTM) which is a real time anomaly detection algorithm. HTM is a cortical learning algorithm based on neocortex used for anomaly detection. In other words, it is based on a conceptual theory of how the human brain can work. It is powerful in predicting unusual patterns, anomaly detection and classification. In this paper, HTM have been implemented and tested on ECG datasets in order to detect cardiac anomalies. Experiments showed good performance in terms of specificity, sensitivity and execution time.

Keywords: cardiac anomalies, ECG, HTM, real time anomaly detection

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Authors: Ionel Zagan, Vasile Gheorghita Gaitan, Adrian Brezulianu

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This paper presents the contributions in designing a mobile system named Tele-ECG implemented for remote monitoring of cardiac patients. For a better flexibility of this application, the authors chose to implement a local memory and multiple communication interfaces. The project described in this presentation is based on the ARM Cortex M0+ microcontroller and the ADAS1000 dedicated chip necessary for the collection and transmission of Electrocardiogram signals (ECG) from the patient to the microcontroller, without altering the performances and the stability of the system. The novelty brought by this paper is the implementation of a remote monitoring system for cardiac patients, having a real-time behavior and multiple interfaces. The microcontroller is responsible for processing digital signals corresponding to ECG and also for the implementation of communication interface with the main server, using GSM/Bluetooth SIMCOM SIM800C module. This paper translates all the characteristics of the Tele-ECG project representing a feasible implementation in the biomedical field. Acknowledgment: This paper was supported by the project 'Development and integration of a mobile tele-electrocardiograph in the GreenCARDIO© system for patients monitoring and diagnosis - m-GreenCARDIO', Contract no. BG58/30.09.2016, PNCDI III, Bridge Grant 2016, using the infrastructure from the project 'Integrated Center for research, development and innovation in Advanced Materials, Nanotechnologies, and Distributed Systems for fabrication and control', Contract No. 671/09.04.2015, Sectoral Operational Program for Increase of the Economic Competitiveness co-funded from the European Regional Development Fund.

Keywords: Tele-ECG, real-time cardiac monitoring, electrocardiogram, microcontroller

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Authors: N. Reichbach, A. Kuperman

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The paper describes a design of a monitoring system for super capacitor packs in propulsion systems, allowing determining the instantaneous energy capacity under power loading. The system contains real-time recursive-least-squares identification mechanism, estimating the values of pack capacitance and equivalent series resistance. These values are required for accurate calculation of the state-of-energy.

Keywords: real-time monitoring, RLS identification algorithm, state-of-energy, super capacitor

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Authors: Pawel Martynowicz

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Vibrations are a crucial problem for slender structures such as towers, masts, chimneys, wind turbines, bridges, high buildings, etc., that is why most of them are equipped with vibration attenuation or fatigue reduction solutions. In this work, a slender structure (i.e., wind turbine tower-nacelle model) equipped with nonlinear, semiactive tuned vibration absorber(s) is analyzed. For this study purposes, magnetorheological (MR) dampers are used as semiactive actuators. Several optimal-based approaches to structural vibration attenuation are investigated against the standard ‘ground-hook’ law and passive tuned vibration absorber(s) implementations. The common approach to optimal control of nonlinear systems is offline computation of the optimal solution, however, so determined open loop control suffers from lack of robustness to uncertainties (e.g., unmodelled dynamics, perturbations of external forces or initial conditions), and thus perturbation control techniques are often used. However, proper linearization may be an issue for highly nonlinear systems with implicit relations between state, co-state, and control. The main contribution of the author is the development as well as numerical and experimental verification of the Pontriagin maximum-principle-based vibration control concepts that produce directly actuator control input (not the demanded force), thus force tracking algorithm that results in control inaccuracy is entirely omitted. These concepts, including one-step optimal control, quasi-optimal control, and optimal-based modified ‘ground-hook’ law, can be directly implemented in online and real-time feedback control for periodic (or semi-periodic) disturbances with invariant or time-varying parameters, as well as for non-periodic, transient or random disturbances, what is a limitation for some other known solutions. No offline calculation, excitations/disturbances assumption or vibration frequency determination is necessary, moreover, all of the nonlinear actuator (MR damper) force constraints, i.e., no active forces, lower and upper saturation limits, hysteresis-type dynamics, etc., are embedded in the control technique, thus the solution is optimal or suboptimal for the assumed actuator, respecting its limitations. Depending on the selected method variant, a moderate or decisive reduction in the computational load is possible compared to other methods of nonlinear optimal control, while assuring the quality and robustness of the vibration reduction system, as well as considering multi-pronged operational aspects, such as possible minimization of the amplitude of the deflection and acceleration of the vibrating structure, its potential and/or kinetic energy, required actuator force, control input (e.g. electric current in the MR damper coil) and/or stroke amplitude. The developed solutions are characterized by high vibration reduction efficiency – the obtained maximum values of the dynamic amplification factor are close to 2.0, while for the best of the passive systems, these values exceed 3.5.

Keywords: magnetorheological damper, nonlinear tuned vibration absorber, optimal control, real-time structural vibration attenuation, wind turbines

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Authors: Ghodbane Azeddine, Saad Maarouf, Boland Jean-Francois, Thibeault Claude

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This paper proposes a new design of an active fault-tolerant flight control system against abrupt actuator faults. This overall system combines a multiple time scale sliding mode controller for fault compensation and a geometric approach for fault detection and diagnosis. The proposed control system is able to accommodate several kinds of partial and total actuator failures, by using available healthy redundancy actuators. The overall system first estimates the correct fault information using the geometric approach. Then, and based on that, a new reconfigurable control law is designed based on the multiple time scale sliding mode technique for on-line compensating the effect of such faults. This approach takes advantages of the fact that there are significant difference between the time scales of aircraft states that have a slow dynamics and those that have a fast dynamics. The closed-loop stability of the overall system is proved using Lyapunov technique. A case study of the non-linear model of the F16 fighter, subject to the rudder total loss of control confirms the effectiveness of the proposed approach.

Keywords: actuator faults, fault detection and diagnosis, fault tolerant flight control, sliding mode control, multiple time scale approximation, geometric approach for fault reconstruction, lyapunov stability

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Authors: Xinwen Zhu, Xingguang Li, Sun Yi

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Crack is one of the most common damages in buildings, bridges, roads and so on, which may pose safety hazards. However, cracks frequently happen in structures of various materials. Traditional methods of manual detection and measurement, which are known as subjective, time-consuming, and labor-intensive, are gradually unable to meet the needs of modern development. In addition, crack detection and measurement need be safe considering space limitations and danger. Intelligent crack detection has become necessary research. In this paper, an efficient method for crack detection and quantification using a 3D sensor, LiDAR, and depth camera is proposed. This method works even in a dark environment, which is usual in real-world applications. The LiDAR rapidly spins to scan the surrounding environment and discover cracks through lasers thousands of times per second, providing a rich, 3D point cloud in real-time. The LiDAR provides quite accurate depth information. The precision of the distance of each point can be determined within around  ±3 cm accuracy, and not only it is good for getting a precise distance, but it also allows us to see far of over 100m going with the top range models. But the accuracy is still large for some high precision structures of material. To make the depth of crack is much more accurate, the depth camera is in need. The cracks are scanned by the depth camera at the same time. Finally, all data from LiDAR and Depth cameras are analyzed, and the size of the cracks can be quantified successfully. The comparison shows that the minimum and mean absolute percentage error between measured and calculated width are about 2.22% and 6.27%, respectively. The experiments and results are presented in this paper.

Keywords: LiDAR, depth camera, real-time, detection and measurement

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Authors: Yong Eun Yoon, Eric N. Johnson, Liling Ren

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Multirotor is one of the most popular types of small unmanned aircraft systems and has already been used in many areas including transport, military, surveillance, and leisure. Together with its popularity, the needs for proper flight control is growing because in most applications it is required to conduct its missions autonomously, which is in many aspects based on autonomous flight control. There have been many studies about the flight control for multirotor, but there is still room for enhancements in terms of performance and efficiency. This paper presents an autonomous flight control method for multirotor based on alternative input output linearization coupled with nested saturations. With alternative choice of the output of the multirotor flight control system, we can reduce computational cost regarding Lie algebra, and the linearized system can be stabilized with the introduction of nested saturations with real poles of our own design. Stabilization of internal dynamics is also based on the nested saturations and accompanies the determination of part of desired states. In particular, outer control loops involving state variables which originally are not included in the output of the flight control system is naturally rendered through this internal dynamics stabilization. We can also observe that desired tilting angles are determined by error dynamics from outer loops. Simulation results show that in any tracking situations multirotor stabilizes itself with small time constants, preceded by tuning process for control parameters with relatively low degree of complexity. Future study includes control of piecewise linear behavior of multirotor with actuator saturations, and the optimal determination of desired states while tracking multiple waypoints.

Keywords: automatic flight control, input output linearization, multirotor, nested saturations

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Authors: Tim Farrelly

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In recent years, AI-powered object detection systems have opened the doors for innovative new applications and products, especially those operating in the real world or ‘on edge’ – namely, in sport. This paper investigates the viability of an ultra-low parameter convolutional neural network specially designed for the detection of footballs on ‘on the edge’ devices. The main contribution of this paper is the exploration of integrating new design features (depth-wise separable convolutional blocks and squeezed and excitation modules) into an ultra-low parameter network and demonstrating subsequent improvements in performance. The results show that tracking the ball from Full HD images with negligibly high accu-racy is possible in real-time.

Keywords: deep learning, object detection, machine vision applications, sport, network design

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Authors: Linda Kauškale, Ineta Geipele

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Due to the rapidly changing external environment, portfolio management strategies became closely interconnected with real estate industry development and macroeconomic development tendencies. The aim of the research is to analyze sustainable real estate market development influencing factors, with particular focus on its economic and management aspects that influences real estate investment decisions as well. Scientific literature and article analysis, data analysis, expert evaluation, and other quantitative and qualitative research methods were used in the research. Developed real estate market sustainability model and index analysis approach can be applied by investors and real estate companies in real estate asset management and can help in risk minimization activities in international entrepreneurship. Future research directions have been identified in the research as well.

Keywords: indexes, investment decisions, real estate market, sustainability

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Authors: Mahdi Daghmhehci Firoozjaei, Minchang Kim, Dima Alhadidi

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In this paper, we present a power profiling model for smart grid consumers based on real time load data acquired smart meters. It profiles consumers’ power consumption behaviour using the dynamic time warping (DTW) clustering algorithm. Due to the invariability of signal warping of this algorithm, time-disordered load data can be profiled and consumption features be extracted. Two load types are defined and the related load patterns are extracted for classifying consumption behaviour by DTW. The classification methodology is discussed in detail. To evaluate the performance of the method, we analyze the time-series load data measured by a smart meter in a real case. The results verify the effectiveness of the proposed profiling method with 90.91% true positive rate for load type clustering in the best case.

Keywords: power profiling, user privacy, dynamic time warping, smart grid

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Authors: R. M. Kalayappan, N. Kathiravan

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In automobile industries, Controller Area Network (CAN) is widely used to reduce the system complexity and inter-task communication. Therefore, this paper proposes the hardware implementation of data frame communication between one controller to other. The CAN data frames and protocols will be explained deeply, here. The data frames are transferred without any collision or corruption. The simulation is made in the KEIL vision software to display the data transfer between transmitter and receiver in CAN. ARM7 micro-controller is used to transfer data’s between the controllers in real time. Data transfer is verified using the CRO.

Keywords: control area network (CAN), automotive electronic control unit, CAN 2.0, industry

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Authors: O. B. Iskender, K. V. Ling, V. Dubanchet, L. Simonini

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This paper discusses the recent advances and future prospects of spacecraft position and attitude control using Model Predictive Control (MPC). First, the challenges of the space missions are summarized, in particular, taking into account the errors, uncertainties, and constraints imposed by the mission, spacecraft and, onboard processing capabilities. The summary of space mission errors and uncertainties provided in categories; initial condition errors, unmodeled disturbances, sensor, and actuator errors. These previous constraints are classified into two categories: physical and geometric constraints. Last, real-time implementation capability is discussed regarding the required computation time and the impact of sensor and actuator errors based on the Hardware-In-The-Loop (HIL) experiments. The rationales behind the scenarios’ are also presented in the scope of space applications as formation flying, attitude control, rendezvous and docking, rover steering, and precision landing. The objectives of these missions are explained, and the generic constrained MPC problem formulations are summarized. Three key design elements used in MPC design: the prediction model, the constraints formulation and the objective cost function are discussed. The prediction models can be linear time invariant or time varying depending on the geometry of the orbit, whether it is circular or elliptic. The constraints can be given as linear inequalities for input or output constraints, which can be written in the same form. Moreover, the recent convexification techniques for the non-convex geometrical constraints (i.e., plume impingement, Field-of-View (FOV)) are presented in detail. Next, different objectives are provided in a mathematical framework and explained accordingly. Thirdly, because MPC implementation relies on finding in real-time the solution to constrained optimization problems, computational aspects are also examined. In particular, high-speed implementation capabilities and HIL challenges are presented towards representative space avionics. This covers an analysis of future space processors as well as the requirements of sensors and actuators on the HIL experiments outputs. The HIL tests are investigated for kinematic and dynamic tests where robotic arms and floating robots are used respectively. Eventually, the proposed algorithms and experimental setups are introduced and compared with the authors' previous work and future plans. The paper concludes with a conjecture that MPC paradigm is a promising framework at the crossroads of space applications while could be further advanced based on the challenges mentioned throughout the paper and the unaddressed gap.

Keywords: convex optimization, model predictive control, rendezvous and docking, spacecraft autonomy

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Authors: Azeddine Ghodbane, David Bensoussan, Maher Hammami

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An innovative approach for controlling unstable and invertible systems has demonstrated superior performance compared to conventional controllers. It has been successfully applied to a levitation system and drone control. Simulations have yielded satisfactory performances when applied to a satellite antenna controller. This design method, based on sensitivity analysis, has also been extended to handle multivariable unstable and invertible systems that exhibit dominant diagonal characteristics at high frequencies, enabling decentralized control. Furthermore, this control method has been expanded to the realm of adaptive control. In this study, we introduce an alternative adaptive architecture that enhances both time and frequency performance, helpfully mitigating the effects of disturbances from the input plant and external disturbances affecting the output. To facilitate superior performance in both the time and frequency domains, we have developed user-friendly interactive design methods using the GeoGebra platform.

Keywords: control theory, decentralized control, sensitivity theory, input-output stability theory, robust multivariable feedback control design

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Authors: Lars Laußat, Manfred Helmus, Kamil Szczesny, Markus König

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As one result of the project “Reactive Construction Project Scheduling using Real Time Construction Logistic Data and Simulation”, a procedure for using data about uncertain resource availability assumptions in reactive scheduling processes has been developed. Prediction data about resource availability is generated in a formalized way using real-time monitoring data e.g. from auto-ID systems on the construction site and in the supply chains. The paper focuses on the formalization of the procedure for monitoring construction logistic processes, for the detection of disturbance and for generating of new and uncertain scheduling assumptions for the reactive resource constrained simulation procedure that is and will be further described in other papers.

Keywords: auto-ID, construction logistic, fuzzy, monitoring, RFID, scheduling

Procedia PDF Downloads 476

Authors: Meena Agrawal, Chaitanya P. Agrawal

Abstract:

The power systems are transforming and becoming smarter with innovations in technologies to enable embark simultaneously upon the sustainable energy needs, rising environmental concerns, economic benefits and quality requirements. The advantages provided by inter-connection of renewable energy resources are becoming more viable and dependable with the smart controlling technologies. The limitation of most renewable resources have their diversity and intermittency causing problems in power quality, grid stability, reliability, security etc. is being cured by these efforts. A necessitate of optimal energy management by intelligent Micro-Grids at the distribution end of the power system has been accredited to accommodate sustainable renewable Distributed Energy Resources on large scale across the power grid. All over the world Smart Grids are emerging now as foremost concern infrastructure upgrade programs. The hardware setup includes NI cRIO 9022, Compact Reconfigurable Input Output microcontroller board connected to the PC on a LAN router with three hardware modules. The Real-Time Embedded Controller is reconfigurable controller device consisting of an embedded real-time processor controller for communication and processing, a reconfigurable chassis housing the user-programmable FPGA, Eight hot-swappable I/O modules, and graphical LabVIEW system design software. It has been employed for signal analysis, controls and acquisition and logging of the renewable sources with the LabVIEW Real-Time applications. The employed cRIO chassis controls the timing for the module and handles communication with the PC over the USB, Ethernet, or 802.11 Wi-Fi buses. It combines modular I/O, real-time processing, and NI LabVIEW programmable. In the presented setup, the Analog Input Module NI 9205 five channels have been used for input analog voltage signals from renewable energy sources and NI 9227 four channels have been used for input analog current signals of the renewable sources. For switching actions based on the programming logic developed in software, a module having Electromechanical Relays (single-pole single throw) with 4-Channels, electrically isolated and LED indicating the state of that channel have been used for isolating the renewable Sources on fault occurrence, which is decided by the logic in the program. The module for Ethernet based Data Acquisition Interface ENET 9163 Ethernet Carrier, which is connected on the LAN Router for data acquisition from a remote source over Ethernet also has the module NI 9229 installed. The LabVIEW platform has been employed for efficient data acquisition, monitoring and control. Control logic utilized in program for operation of the hardware switching Related to Fault Relays has been portrayed as a flowchart. A communication system has been successfully developed amongst the sources and loads connected on different computers using Hypertext transfer protocol, HTTP or Ethernet Local Stacked area Network TCP/IP protocol. There are two main I/O interfacing clients controlling the operation of the switching control of the renewable energy sources over internet or intranet. The paper presents experimental results of the briefed setup for intelligent control of the micro-grid for renewable energy sources, besides the control of Micro-Grid with data acquisition and control hardware based on a microcontroller with visual program developed in LabVIEW.

Keywords: data acquisition and control, LabVIEW, microcontroller cRIO, Smart Micro-Grid

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Authors: Shweta Singh, Dipali Bansal, Rashima Mahajan

Abstract:

Psychoacoustics has become a potential area of research due to the growing interest of both laypersons and medical and mental health professionals. Non-invasive brain computer interface like Electroencephalography (EEG) is widely being used in this field. An attempt has been made in this paper to examine the response of EEG signals to acoustic stimuli further analysing the brain electrical activity. The real time EEG is acquired for 6 participants using a cost effective and portable EMOTIV EEG neuron headset. EEG data analysis is further done using EMOTIV test bench, EDF browser and EEGLAB (MATLAB Tool) application software platforms. Spectral analysis of acquired neural signals (AF3 channel) using these software platforms are clearly indicative of increased brain activity in various bands. The inferences drawn from such an analysis have significant correlation with subject’s subjective reporting of the experiences. The results suggest that the methodology adopted can further be used to assist patients with sleeping and depressive disorders.

Keywords: OM chant, spectral analysis, EDF browser, EEGLAB, EMOTIV, real time acquisition

Procedia PDF Downloads 249

Authors: A. Khernane, N. Khelil, L. Djerou

Abstract:

The aim of this work is to study the numerical implementation of the Hilbert uniqueness method for the exact boundary controllability of Euler-Bernoulli beam equation. This study may be difficult. This will depend on the problem under consideration (geometry, control, and dimension) and the numerical method used. Knowledge of the asymptotic behaviour of the control governing the system at time T may be useful for its calculation. This idea will be developed in this study. We have characterized as a first step the solution by a minimization principle and proposed secondly a method for its resolution to approximate the control steering the considered system to rest at time T.

Keywords: boundary control, exact controllability, finite difference methods, functional optimization

Procedia PDF Downloads 311

Authors: Nizar Tayem, AbuMuhammad Moinuddeen, Ahmed A. Hussain, Redha M. Radaydeh

Abstract:

This research paper introduces an approach for estimating the direction of arrival (DOA) of multiple RF noncoherent sources in a uniform linear array (ULA). The proposed method utilizes a Capon-like estimation algorithm and incorporates LU decomposition to enhance the accuracy of DOA estimation while significantly reducing computational complexity compared to existing methods like the Capon method. Notably, the proposed method does not require prior knowledge of the number of sources. To validate its effectiveness, the proposed method undergoes validation through both software simulations and practical experimentation on a prototype testbed constructed using a software-defined radio (SDR) platform and GNU Radio software. The results obtained from MATLAB simulations and real-time experiments provide compelling evidence of the proposed method's efficacy.

Keywords: DOA estimation, real-time validation, software defined radio, computational complexity, Capon's method, GNU radio

Procedia PDF Downloads 38

Authors: Mohammad Hashemi, John Herbert

Abstract:

Quantifying and measuring Quality of Experience (QoE) are important and difficult concerns in Human Computer Interaction (HCI). Quality of Service (QoS) and the actual User Interface (UI) of the application are both important contributors to the QoE of a user. This paper describes a framework that measures accurately the way a user uses the UI in order to model users' behaviours and profiles. It monitors the use of the mouse and use of UI elements with accurate time measurement. It does this in real-time and does so unobtrusively and efficiently allowing the user to work as normal with the application. This real-time accurate measurement of the user's interaction provides valuable data and insight into the use of the UI, and is also the basis for analysis of the user's QoE.

Keywords: user modelling, user interface experience, quality of experience, user experience, human and computer interaction

Procedia PDF Downloads 467