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Real-time Implementation (real-time + implementation)
Selected AbstractsReal-Time Control and Identification of a Thermal Process Based on Multiple-Modeling ApproachASIA-PACIFIC JOURNAL OF CHEMICAL ENGINEERING, Issue 3-4 2005A. Aminzadeh This article presents implementation of Real-Time Control and Identification algorithms based on a Multiple-Modeling approach for an experimental thermal process. The thermal process is a nonlinear plant; therefore, based on variations of the input and disturbance, four local operating regimes are defined. The linear local ARMAX models are identified for different regimes and integrated into a NARMAX model by combining them via proper validity and interpolation functions. Results of modeling the plant with a single model and multiple models show superior performance of the Multiple-Modeling technique which is also more flexible. Moreover, the Real-Time Control of the plant with four locally designed controllers is addressed. The platform used for the Real-Time implementation is Matlab/Simulink/Real-Time-Workshop with Visual C++ and Watcom compilers using a DAQ interface. The Real-Time application of the global controller based on the Multiple-Model approach demonstrates excellent performance for this design when compared to a single PID controller. [source] Real-time implementation of digital relay models using MATLAB/SIMULINK and RTDSEUROPEAN TRANSACTIONS ON ELECTRICAL POWER, Issue 3 2010Christos A. Apostolopoulos Abstract In this paper, an integrated environment for real-time simulation, analysis and validation of digital relay models, based on MATLAB/SIMULINK and RTDS, is presented. A detailed analysis and discussion for this environment is given and example cases are used to illustrate its implementation. Copyright © 2008 John Wiley & Sons, Ltd. [source] A simple LMS-based approach to the structural health monitoring benchmark problemEARTHQUAKE ENGINEERING AND STRUCTURAL DYNAMICS, Issue 6 2005J. Geoffrey Chase Abstract A structure's health or level of damage can be monitored by identifying changes in structural or modal parameters. However, the fundamental modal frequencies can sometimes be less sensitive to (localized) damage in large civil structures, although there are developing algorithms that seek to reduce this difficulty. This research directly identifies changes in structural stiffness due to modeling error or damage using a structural health monitoring method based on adaptive least mean square (LMS) filtering theory. The focus is on computational simplicity to enable real-time implementation. Several adaptive LMS filtering based approaches are used to analyze the data from the IASC,ASCE Structural Health Monitoring Task Group Benchmark problem. Results are compared with those from the task group and other published results. The proposed methods are shown to be very effective, accurately identifying damage to within 1%, with convergence times of 0.4,13.0 s for the twelve different 4 and 12 degree of freedom benchmark problems. The resulting modal parameters match to within 1% those from the benchmark problem definition. Finally, the methods developed require 1.4,14.0 Mcycles of computation and therefore could easily be implemented in real time. Copyright © 2004 John Wiley & Sons, Ltd. [source] Multiple input,multiple output adaptive feedback control strategies for the active headrest system: design and real-time implementationINTERNATIONAL JOURNAL OF ADAPTIVE CONTROL AND SIGNAL PROCESSING, Issue 10 2003Marek Pawelczyk Abstract In this article, multiple input,multiple output adaptive feedback control techniques for acoustic noise control in a headrest system are developed. The main goal underlying their design is to provide acoustic comfort to the user, i.e. high noise attenuation level over possibly large areas at the ears. Classical Internal Model Control system does not yield acceptable performance. An approach based on estimates of the residual noise at the ears is then proposed. It is shown that increase in the number of secondary sources to operate for one channel improves the performance. The experiments of tonal noise control are performed on an originally set-up prototype of the active headrest system. The results obtained are illustrated in the promoted form of distribution of zones of quiet. Copyright © 2003 John Wiley & Sons, Ltd. [source] A compact dynamic channel assignment scheme based on Hopfield networks for cellular radio systemsINTERNATIONAL JOURNAL OF COMMUNICATION SYSTEMS, Issue 1 2009A. Dang Abstract In this paper, a new channel assignment strategy named compact dynamic channel assignment (CDCA) is proposed. The CDCA differs from other strategies by consistently keeping the system in the utmost optimal state, and thus the scheme allows to determine a call succeeding or failing by local information instead of that of the whole network. It employs Hopfield neural networks for optimization which avoids the complicated assessment of channel compactness and guarantees optimum solutions for every assignment. A scheme based on Hopfield neural network is considered before; however, unlike others, in this algorithm an energy function is derived in such a way that for a neuron, the more a channel is currently being allocated in other cells, the more excitation the neuron will acquire, so as to guarantee each cluster using channels as few as possible. Performance measures in terms of the blocking probability, convergence rate and convergence time are obtained to assess the viability of the proposed scheme. Results presented show that the approach significantly reduces stringent requirements of searching space and convergence time. The algorithm is simple and straightforward, hence the efficient algorithm makes the real-time implementation of channel assignment based on neural network feasibility. Copyright © 2008 John Wiley & Sons, Ltd. [source] MAP fusion method for superresolution of images with locally varying pixel qualityINTERNATIONAL JOURNAL OF IMAGING SYSTEMS AND TECHNOLOGY, Issue 4 2008Kio Kim Abstract Superresolution is a procedure that produces a high-resolution image from a set of low-resolution images. Many of superresolution techniques are designed for optical cameras, which produce pixel values of well-defined uncertainty, while there are still various imaging modalities for which the uncertainty of the images is difficult to control. To construct a superresolution image from low-resolution images with varying uncertainty, one needs to keep track of the uncertainty values in addition to the pixel values. In this paper, we develop a probabilistic approach to superresolution to address the problem of varying uncertainty. As direct computation of the analytic solution for the superresolution problem is difficult, we suggest a novel algorithm for computing the approximate solution. As this algorithm is a noniterative method based on Kalman filter-like recursion relations, there is a potential for real-time implementation of the algorithm. To show the efficiency of our method, we apply this algorithm to a video sequence acquired by a forward looking sonar system. © 2008 Wiley Periodicals, Inc. Int J Imaging Syst Technol, 18, 242,250, 2008; Published online in Wiley InterScience (www.interscience.wiley.com). [source] High-confidence control: Ensuring reliability in high-performance real-time systemsINTERNATIONAL JOURNAL OF INTELLIGENT SYSTEMS, Issue 4 2004Tariq Samad Technology transfer is an especially difficult proposition for real-time control. To facilitate it, we need to complement the "high-performance" orientation of control research with an emphasis on establishing "high confidence" in real-time implementation. Two particular problems are discussed and recent research directed at their solutions is presented. First, the use of anytime algorithms requires dynamic resource management technology that generally is not available today in real-time systems. Second, complex algorithms have unpredictable computational characteristics that, nevertheless, need to be modeled; statistical verification is suggested as a possible approach. In both cases, a synthesis of control engineering and computer science is required if effective solutions are to be devised. Simulation-based demonstrations with uninhabited aerial vehicles (UAVs) serve to illustrate the research efforts. © 2004 Wiley Periodicals, Inc. [source] RT-GROG: parallelized self-calibrating GROG for real-time MRIMAGNETIC RESONANCE IN MEDICINE, Issue 1 2010Haris Saybasili Abstract A real-time implementation of self-calibrating Generalized Autocalibrating Partially Parallel Acquisitions (GRAPPA) operator gridding for radial acquisitions is presented. Self-calibrating GRAPPA operator gridding is a parallel-imaging-based, parameter-free gridding algorithm, where coil sensitivity profiles are used to calculate gridding weights. Self-calibrating GRAPPA operator gridding's weight-set calculation and image reconstruction steps are decoupled into two distinct processes, implemented in C++ and parallelized. This decoupling allows the weights to be updated adaptively in the background while image reconstruction threads use the most recent gridding weights to grid and reconstruct images. All possible combinations of two-dimensional gridding weights GG are evaluated for m,n = {,0.5, ,0.4, ,, 0, 0.1, ,, 0.5} and stored in a look-up table. Consequently, the per-sample two-dimensional weights calculation during gridding is eliminated from the reconstruction process and replaced by a simple look-up table access. In practice, up to 34× faster reconstruction than conventional (parallelized) self-calibrating GRAPPA operator gridding is achieved. On a 32-coil dataset of size 128 × 64, reconstruction performance is 14.5 frames per second (fps), while the data acquisition is 6.6 fps. Magn Reson Med 64:306,312, 2010. © 2010 Wiley-Liss, Inc. [source] FCCU simulation based on first principle and artificial neural network modelsASIA-PACIFIC JOURNAL OF CHEMICAL ENGINEERING, Issue 6 2009Maria Mihe Abstract A first principle model has been developed for the reactor,regenerator system based on construction and operating data from an industrial fluid catalytic cracking unit (FCCU). The first principle model takes into account the main FCCU subsystems: reactor riser, regenerator, stripper, catalyst circulation lines, air blower, wet gas compressor and main fractionator. A five-lump kinetic scheme has been considered for the reactions taking place in the reactor riser. Subsequently, an artificial neural network (ANN) model has been built for the complex FCCU system. The dynamic simulator, based on the previously developed first principle model, served as the source of reliable data for ANN design, training and testing. The ANN developed model was successfully trained and tested. Comparison between first principle and neural network based model leads to a very good match between the two models. Results show the substantial reduction of the computation time featured by the ANN model compared to the first principle model, demonstrating its potential use for real-time implementation in model-based control algorithms. Copyright © 2009 Curtin University of Technology and John Wiley & Sons, Ltd. [source] | |||||||||||||