This paper aims to share the results on forecasting power demand using least-squares support vector machines. The development is based on model estimation taking in consideration the past measurements for power demand...
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This paper aims to share the results on forecasting power demand using least-squares support vector machines. The development is based on model estimation taking in consideration the past measurements for power demand and ambient temperature. All approximated models were evaluated using the multiple correlation coefficient (R 2 ) or mean absolute percentage error (MAPE) and maximum error combined as quality parameters.
This paper proposes a fuzzy retrieval system for purchasing cars employing image processing. This system aims to support such persons who are not good with machines or cars. When they try to purchase a car, they can u...
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To improve the responsiveness of engine speed control to disturbances, robust controls were investigated by simulation. The intake air control system of a gasoline engine is a typical nonlinear system, and the disturb...
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To improve the responsiveness of engine speed control to disturbances, robust controls were investigated by simulation. The intake air control system of a gasoline engine is a typical nonlinear system, and the disturbances and parameter perturbations are generally regarded as being the unstable factors with regard to engine control. In this paper, a Mean-Value Engine Model (MVEM) with disturbances and parameter perturbations is investigated using Sliding Mode Control (SMC), which is a form of variable structure control, with a view to address instability in the idle speed control process. The simulation results confirmed that, compared with a conventional PI (Proportional-Integral) controller, the stability of the idle speed for an engine that is being subjected to disturbances, parameter variations and background noise is greatly improved by the application of SMC.
A new class of meta-heuristics called SOMA (Self-Organizing Migrating Algorithm) was proposed in recent literature. SOMA works on a population of potential solutions called specimen and it is based on the self-organiz...
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A new class of meta-heuristics called SOMA (Self-Organizing Migrating Algorithm) was proposed in recent literature. SOMA works on a population of potential solutions called specimen and it is based on the self-organizing behavior of groups of individuals in a ¿social environment¿. This paper proposes a modified SOMA approach to solving the economic load dispatch problem of thermal generators with the valve-point effect. To show the performance of the proposed modified SOMA algorithm based on fundamentals of normative knowledge in cultural algorithms, which was applied to test the power economic problem comprised 10 generating units with valve-point effects and multiple fuels for the load demands of 2400 MW. Simulation results show that the classical and modified SOMA algorithms are efficient and have good convergence property when compared with results of other optimization methods reported in the literature.
作者：
Lu, Y.Ye, L.Wang, D.Wang, X.Su, Z.
School of Aerospace Mechanical and Mechatronic Engineering University of Sydney NSW2006 Australia Urban Systems Program
CSIRO Sustainable Ecosystems Commonwealth Scientific and Industrial Research Organisation 37 Graham Road Highett MelbourneVIC3190 Australia Department of Mechanical Engineering
Hong Kong Polytechnic University Hong Kong Hong Kong
Identification of multiple notches in an aluminium plate was investigated with the aid of probability-based imaging evaluation of Lamb wave signals activated and captured by a piezoelectric sensor network. A signal pr...
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ISBN:
(纸本)9781605950075
Identification of multiple notches in an aluminium plate was investigated with the aid of probability-based imaging evaluation of Lamb wave signals activated and captured by a piezoelectric sensor network. A signal processing algorithm featuring signal synchronization and correlation is proposed to facilitate the extraction of damage-scattered waves, by the means of which the corresponding arrival times of the scattered waves are obtained. Using a virtually-meshed grid in the plate, an image with respect to the probability of the arrival time at individual nodes is achieved, indicating the location of damage as perceived by individual actuator-sensor paths. Compromised and conjunctive data fusion techniques are applied to aggregate the images for all engaged actuator-sensor paths, to provide a complete appraisal of the location of damage. The diagnostic results demonstrate that the proposed approach is capable of identifying multiple notches with good accuracy in terms of their position.
We consider a supply chain, which consists of N stocking locations and one supplier. The locations may be coordinated through replenishment strategies and lateral transshipments, i.e., transfer of a product among loca...
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High computational cost for solving large engineering optimization problems point out the design of parallel optimization algorithms. Population based optimization algorithms provide parallel capabilities that can be ...
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High computational cost for solving large engineering optimization problems point out the design of parallel optimization algorithms. Population based optimization algorithms provide parallel capabilities that can be explored by their implementations done directly in hardware. This paper presents a hardware implementation of particle swarm optimization algorithms using an efficient floating-point arithmetic which performs the computations with high precision. All the architectures are parameterizable by bit-width, allowing the designer to choose the suitable format according to the requirements of the optimization problem. Synthesis and simulation results demonstrate that the proposed architecture achieves satisfactory results obtaining a better performance in therms of elapsed time than conventional software implementations.
This paper is focused on the problem of uncertain process control by using RMPC (robust model predictive control). A relevant class of RMPC algorithms is the one characterized by the use of the LMI framework. This fie...
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ISBN:
(纸本)9781424438716
This paper is focused on the problem of uncertain process control by using RMPC (robust model predictive control). A relevant class of RMPC algorithms is the one characterized by the use of the LMI framework. This field started in the middle of nineties and since then several works applying LMIs in the context of RMPC have been proposed. Most of them assume a polytopic representation of the process uncertainties and require full-state feedback. On the other hand, several works describing the theory and applicability of OBF (orthonormal basis functions) in identification and control fields can be found in the literature. So, the present paper proposes the use of OBF for uncertain process modelling and for RMPC algorithm synthesis. It is shown that, due to the proposed approach, one obtains an output feedback control law, with set-point tracking. This represents an advantage in actual applications. Moreover, well established state feedback RMPC strategies can be reviewed under the OBF modelling perspective. Simulation results illustrate the proposed methodology.
This paper is focused on the problem of uncertain process control by using RMPC（Robust Model Predictive Control）.A relevant class of RMPC algorithms is the one characterized by the use of the LMI *** field started i...
This paper is focused on the problem of uncertain process control by using RMPC（Robust Model Predictive Control）.A relevant class of RMPC algorithms is the one characterized by the use of the LMI *** field started in the middle of nineties and since then several works applying LMIs in the context of RMPC have been *** of them assume a polytopic representation of the process uncertainties and require full-state *** the other hand,several works describing the theory and applicability of OBF（Orthonormal Basis Functions） in identification and control fields can be found in the ***,the present paper proposes the use of OBF for uncertain process modelling and for RMPC algorithm *** is shown that,due to the proposed approach,one obtains an output feedback control law,with set-point *** represents an advantage in actual ***,well established state feedback RMPC strategies can be reviewed under the OBF modelling *** results illustrate the proposed methodology.
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