A decentralized model-based predictive controller is used for the design of discrete-time control systems aiming at regulating the air temperature and heat supply in greenhouses. Moreover, alternative techniques are p...
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A decentralized model-based predictive controller is used for the design of discrete-time control systems aiming at regulating the air temperature and heat supply in greenhouses. Moreover, alternative techniques are proposed for the approximation of the decentralized part of the control and the on-line improvement of the overall control problem. A state space model is used to predict the corresponding local indoor temperature over a long-range time-period and approximate models are used to predict the interactions among the subsystems. The sun radiation and outdoor temperature are treated as external disturbances that affect the overall system dynamics. A series of energy fluxes consist the heating system and the predictive controllers have proved to be powerful in controlling the supply temperature.
In this paper, we propose a new approach to object match-ing and shape reconstruction across two views . The approach relies on the topological relationship among the feature points and a crude rigidity constraint (ep...
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In this paper, we propose a new approach to object match-ing and shape reconstruction across two views . The approach relies on the topological relationship among the feature points and a crude rigidity constraint (epipolar condition) in carrying the object from the model view to the scene view to a first good approximation. The correspondences are then refined by fitting an active contour model to the. transferred feature points on the scene view, which automatically assumes the shape of the object on correct matching. Under the assumption of weak perspective projection, it could be shown that the establishment of such correct correspondences would result in the full determination of the relative dept.s of all the matched object points in 3-D space and thus recovery of the complete 3-D structure of the. object.
This paper deals with a fuzzy-based system to solve the capacitated vehicle routing problem. The proposed method makes use of a neural network with unsupervised learning guided by a fuzzy rule base. The algorithm impl...
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This paper deals with a fuzzy-based system to solve the capacitated vehicle routing problem. The proposed method makes use of a neural network with unsupervised learning guided by a fuzzy rule base. The algorithm implements a policy of penalties and rewards, a strategy of neuron inhibition, insertion and pruning, and also takes into account certain statistical characteristics of the input space. The fuzzy theory is considered to minimize drawbacks related to uncertainty and availability of partial information, leading to an adaptive process of constraint relaxation. The effectiveness of the proposed method is attested by means of a series of computational simulations. As the proposed approach has no adaptation to any particular instance, it represents a good candidate to provide the initial condition for more dedicated approaches, like tabu search.
It is concluded from the results of testing the frequency characteristics of the sub micron precision machine tool servo control system, that the existence of several oscillating modalities is the main factor that aff...
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It is concluded from the results of testing the frequency characteristics of the sub micron precision machine tool servo control system, that the existence of several oscillating modalities is the main factor that affects the performance of the control system. To compensate for this effect,several concave filters are utilized in the system to improve the control accuracy. The feasibility of compensating for several oscillating modalities with a single concave filter is also studied. By applying a modified Butterworth concave filter to the practical system, the maximum stable state output error remains under ±10 nm in the closed loop positioning system.
In this paper we address the problem of designing energy minimizing collision-free maneuvers for multiple agents moving on a plane. We show that the problem is equivalent to that of finding the shortest geodesic in a ...
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This paper presents the smooth walking trajectory for a biped robot using genetic algorithm. Suitable velocities and accelerations at the via-points are required for dynamic smooth walking since the incorrect via-poin...
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In the past decade robotics and the Internet, fed by the great advances in computing and networking, matured into giant interdisciplinary scientific fields. Therefore, it is not surprising that many are trying to merg...
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The increase of the need for image storage and transmission in computer systems has increased the importance of signal and image compression algorithms. The approach involving vector quantization (VQ) relies on design...
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The increase of the need for image storage and transmission in computer systems has increased the importance of signal and image compression algorithms. The approach involving vector quantization (VQ) relies on designing of a finite set of codes which will substitute the original signal during transmission with a minimal of distortion, taking advantage of the spatial redundancy of image to compress them. Algorithms such as LGB and SOM work in an unsupervised way toward finding a good codebook for a given training data. However, the number of code vectors (N) needed for VQ increases with the vector dimension, and full-search algorithms such as LGB and SOM can lead to large training and coding times. An alternative for reducing the computational complexity is the use of a tree-structured vector quantization algorithm. This paper presents an application of a hierarchical SOM for image compression in which reduces the search complexity from O(N) to O(log N), enabling a faster training and image coding. Results are given for conventional SOM, LBG and HSOM showing the advantage of the proposed method.
We revisit the optimal code generation or evaluation order determination problem-the problem of generating an instruction sequence from a data dependence graph (DDG). In particular, we are interested in generating an ...
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This paper addresses networking and traffic control problems in network systems along with the potential for introducing soft-computing applications at supervisory control level. The incentive Stackelberg strategy con...
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