107 research outputs found
The life of a professor, author and industry supporter
No full textKym Anderson might take an economical approach to most things in his life but when it comes to the wine industry this University of Adelaide professor told Stephanie Timotheou he just can't help himself
Optimizing Multi-Target Detection in Stochastic Environments with Active Smart Camera Networks
No full textActive Smart Camera Networks (SCNs) have a wide range of applications in areas such as banks, airports and underground terminals, where it is necessary to monitor open plan spaces reliably and robustly. However, the monitoring efficiency in such environments is affected by various factors which are stochastic in nature, such as the target movement and arrival times, as well as the capabilities of the on-board camera detection module. This paper presents a modelling framework and a subsequent optimization-based solution towards the optimal reconfiguration of the camera network in order to minimize the expected number of undetected targets under uncertainties. The proposed solution is applicable to a variety of scenarios and does not require to have a full view of the area. Simulation results indicate that the proposed solution is robust to varying conditions and is able to achieve good monitoring performance with only a few cameras.© ACM 2017. This is the author's version of the work. It is posted here for your personal use. Not for redistribution. The definitive Version of Record was published in Proceedings of ICDSC 2017, https://doi.org/10.1145/3131885.3131914
Christos Kyrkou, Stelios Timotheou, Theocharis Theocharides, Christos Panayiotou, and Marios Polycarpou. 2017. Optimizing Multi-Target Detection in Stochastic Environments with Active Smart Camera Networks. In Proceedings of the 11th International Conference on Distributed Smart Cameras (ICDSC 2017). ACM, New York, NY, USA, 63-68. DOI: https://doi.org/10.1145/3131885.3131914
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Hardware-In-The-Loop Assessment of Fuzzy and Neural Network Fault Diagnosis Schemes for a Wind Turbine Model
No full textThe fault diagnosis of wind turbines includes extremely challenging aspects that motivate the research issues considered in this paper. In particular, this work studies fault diagnosis solutions that are considered in a viable way and used as advanced techniques for condition monitoring of dynamic processes. To this end, the work proposes the design of fault diagnosis techniques that exploits the estimation of the fault by means of data-driven approaches. These fuzzy and neural network structures are integrated with auto-regressive with exogenous input regressors, thus making them able to approximate unknown nonlinear dynamic functions with arbitrary degree of accuracy. The capabilities of fault diagnosis schemes are validated by using a real-time simulator of a wind turbine system. Moreover, at this stage the benchmark is also useful to analyse the robustness and the reliability characteristics of the developed tools in the presence of model-reality mismatch and modelling error effects featured by the wind turbine simulator. This realistic simulator relies on a hardware-in-the-loop tool that is finally implemented for verifying and validating the performance of the developed fault diagnosis strategies in an actual environment
Towards Improving the Detection Performance in Collaborative Visual Sensor Networks
No full textVisual Sensor Networks (VSNs) exploit the processing and communication capabilities of modern smart cameras to handle a variety of applications such as security and surveillance and critical infrastructure protection. The performance of various tasks in such applications, such as activity recognition, tracking, etc., can be severely affected by the detection module especially when considering low-cost embedded smart cameras with limited processing capabilities. Hence, this paper presents research towards the development of optimization algorithms and decision making solutions to improve the detection performance of such VSNs. Specifically, it introduces a probabilistic detection model that can be used to characterize the detection capabilities of cameras, and shows how it can be used to reconfigure VSNs. Experimental as well as simulation results indicate that the proposed solution is able to effectively improve the robustness and overall detection performance of VSNs.© ACM 2016. This is the author's version of the work. It is posted here for your personal use. Not for redistribution. The definitive Version of Record was published in Proceedings of ICDSC 2016, https://doi.org/10.1145/2967413.2967418
Christos Kyrkou, Stelios Timotheou, Eftychios Christoforou, Theocharis Theocharides, Christos Panayiotou, and Marios Polycarpou. 2016. Towards Improving the Detection Performance in Collaborative Visual Sensor Networks. In Proceedings of the 10th International Conference on Distributed Smart Camera (ICDSC '16). ACM, New York, NY, USA, 8-13. DOI: https://doi.org/10.1145/2967413.2967418
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Moving horizon fault-tolerant traffic state estimation for the Cell Transmission Model
No full textTraffic state estimation is an important problem with significant applications in advanced traveler information systems, transportation management and traffic control. Nonetheless, the often faulty nature of measurement sensors, especially inductive loop detectors, hinders reliable state estimation. This work proposes a systematic, model-based, network-wide, moving-horizon approach for fault-tolerant traffic state estimation. By exploiting information redundancy and fault sparsity, it achieves reliable estimation and simultaneously detects, isolates and corrects measurements from periods of faulty sensor behavior. The approach is examined in relation to the Asymmetric Cell Transmission Model, a popular and powerful macroscopic first-order traffic flow model. In the absence of any faults, the proposed approach achieves similar results with other state-of-the-art estimation approaches while it can achieve better estimation performance when some sensors are faulty. It is further demonstrated that the developed approach can successfully handle multiple faults of different types."© 2016 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works."
S. Timotheou, C. G. Panayiotou and M. M. Polycarpou, "Moving horizon fault-tolerant traffic state estimation for the Cell Transmission Model," 2015 54th IEEE Conference on Decision and Control (CDC), Osaka, 2015, pp. 3451-3456
Online distributed network traffic signal control using the cell transmission model
No full textThis paper considers the solution of the adaptive network traffic signal control problem under a fully distributed architecture. To achieve a system-wide optimal solution, the problem is modeled as a large-scale mixed integer linear program with the traffic dynamics being captured by the cell transmission model. To achieve an online distributed solution to the considered problem, the loosely connected structure of transportation networks is exploited to decompose the problem in both space and time. The proposed solution methodology involves two main phases. In the first phase, binary decision variables are relaxed and the resulting linear program is distributedly solved via the alternating direction method of multipliers. The second phase involves distributed rounding of the obtained relaxed solution. Simulation results demonstrate the effectiveness of the proposed approach in providing close to optimal, online solutions."© 2014 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works."
S. Timotheou, C. G. Panayiotou and M. M. Polycarpou, "Online distributed network traffic signal control using the cell transmission model," 17th International IEEE Conference on Intelligent Transportation Systems (ITSC), Qingdao, 2014, pp. 2523-2528
Hardware–In–The–Loop Assessment of Robust Fuzzy Control Solutions for Hydroelectric and Wind Turbine Models
No full textThe interest towards renewable energy resources is increasing, and in particular it concerns wind and hydro powers, where the key point regards their efficient conversion into electric energy. To this end, control techniques can be used to meet this purpose, especially the ones relying on fuzzy models, due to their capabilities to manage nonlinear dynamic processes working in different conditions, and affected by faults, measurement errors, uncertainty and disturbances. The design methods addressed in this paper were already developed and validated for wind turbine plants, and important results can be achieved from their appropriate design and application to hydroelectric plants. This is the key issue of the paper, which recalls some considerations on the proposed solutions, as well as their validation to these energy conversion systems. Note that works available in the related literature that consider both wind and hydraulic energy conversion systems investigate a limited number of common issues, thus leading to little exchange opportunities and reduced common research aspects. Another important point addressed in the paper is that the proposed control design solutions are able to take into account the different working conditions of these power plants. Moreover, faults, uncertainty, disturbance and model reality mismatch effects are also considered when analyzing the reliability and robustness features of the derived control schemes. To this end, proper hardware in the loop tools are considered to verify and validate the developed control schemes in more realistic environments. Copyright (C) 2022 The Authors
Towards distributed online cooperative traffic signal control using the cell transmission model
No full textTraffic signal control is a key ingredient in intelligent transportation systems (ITS) to increase the capacity of existing urban transportation infrastructure. However, to achieve optimal system-wide operation it is essential to coordinate traffic signals at various intersections. In this paper we model the multiple-intersections traffic signal control problem using the cell transmission model. For its solution, we propose two online distributed strategies, which are based on spatially and temporally decomposing the problem into subproblems associated with different intersections and iteratively solving them by exchanging information between neighboring intersections. Simulation results for a four intersection topology indicate that the proposed strategies achieve distributed, online and close to optimal signal timing plans."© 2014 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works."
S. Timotheou, C. G. Panayiotou and M. M. Polycarpou, "Towards distributed online cooperative traffic signal control using the cell transmission model," 16th International IEEE Conference on Intelligent Transportation Systems (ITSC 2013), The Hague, 2013, pp. 1737-1742
Hardware-In-The-Loop Assessment of a Fault Tolerant Fuzzy Control Scheme for an Offshore Wind Farm Simulator
No full textTo enhance both the safety and the efficiency of offshore wind park systems, faults must be accommodated in their earlier occurrence, in order to avoid costly unplanned maintenance. Therefore, this paper aims at implementing a fault tolerant control strategy by means of a data-driven approach relying on fuzzy logic. In particular, fuzzy modelling is considered here as it enables to approximate unknown nonlinear relations, while managing uncertain measurements and disturbance. On the other hand, the model of the fuzzy controller is directly estimated from the input-output signals acquired from the wind farm system, with fault tolerant capabilities. In general, the use of purely nonlinear relations and analytic methods would require more complex design tools. The design is therefore enhanced by the use of fuzzy model prototypes obtained via a data-driven approach, thus representing the key point if real- time solutions have to implement the proposed fault tolerant control strategy. Finally, a high- fidelity simulator relying on a hardware-in-the-loop tool is exploited to verify and validate the reliability and robustness characteristics of the developed methodology also for on-line and more realistic implementations
Model-based fault diagnosis of sliding gates electro-mechanical actuators transmission components with motor-side measurements
No full textThis paper presents a model-based fault detection and isolation scheme for the transmission components of Electro-Mechanical Actuators, applied to the actuation of sliding gates. The most important failures are investigated by a Failure Mode, Effects, and Criticality Analysis procedure. Following Failure Mode, Effects, and Criticality Analysis, the components selected for the development of the diagnostic algorithm are the nylon gear and pinion of the Electro-Mechanical Actuator, and the rack of the gate. The proposed diagnostic algorithm is able to isolate two out of the three types of faults. The overall procedure is validated by experimental results
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