Modern living is more and more dependent on the intricate web of critical infrastructure systems. The failure or damage of such systems can cause huge disruptions. Traditional design of this web of critical infrastruc...
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Modern living is more and more dependent on the intricate web of critical infrastructure systems. The failure or damage of such systems can cause huge disruptions. Traditional design of this web of critical infrastructure systems was based on the principles of functionality and reliability. However, it is increasingly being realized that such design objectives are not sufficient. Threats, disruptions and faults often compromise the network, taking away the benefits of an efficient and reliable design. Thus, traditional network design parameters must be combined with self-healing mechanisms to obtain a resilient design of the network. In this paper, we present RNEDE a resilient network design environment that not only optimizes the network for performance but tolerates fluctuations in its structure that result from external threats and disruptions. The environment evaluates a set of remedial actions to bring a compromised network to an optimal level of functionality. The environment includes a visualizer that enables the network administrator to be aware of the current state of the network and the suggested remedial actions at all times.
By introducing a deadwzone scheme, a new neural network based adaptive iterative learning control （ILC） （NN-AILC） scheme is presented for nonlinear discrete-time systems, where the NN weights are time-varying. The...
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By introducing a deadwzone scheme, a new neural network based adaptive iterative learning control （ILC） （NN-AILC） scheme is presented for nonlinear discrete-time systems, where the NN weights are time-varying. The most distinct contribution of the proposed NN-AILC is the relaxation of the identical conditions of initial state and reference trajectory, which are common requirements in traditional ILC problems. Convergence analysis indicates that the tracking error converges to a bounded ball, whose size is determined by the dead-zone nonlinearity. computer simulations verify the theoretical results.
Improving the control of shading blinds, lights, natural ventilation, and HVAC systems while satisfying human comfort requirements can result in significant energy cost savings with time-of-day electricity pricing. Tr...
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Improving the control of shading blinds, lights, natural ventilation, and HVAC systems while satisfying human comfort requirements can result in significant energy cost savings with time-of-day electricity pricing. Traditionally, the above-mentioned devices are controlled separately. In this paper, a novel formulation for the integrated control and the corresponding solution methodology are presented. The problem is to minimize daily energy costs of lights and HVAC systems while satisfying equipment capacities, system dynamics, and human comfort. The problem is complicated since 1) individual rooms are coupled as they compete for the HVAC with limited capacity and nonlinear characteristics, and 2) the problem is believed to be NP-hard in view that decision variables are all discrete. A solution methodology that combines Lagrangian relaxation and stochastic dynamic programming is developed within the surrogate optimization framework to obtain near-optimal strategies. These strategies are further refined to become novel control rules for easy practical implementation. Numerical simulation results show that both of the above strategies can effectively reduce the total energy cost, and that the integrated control works better than selected traditional control strategies.
The gaming industry has reached a point where improving graphics has only a small effect on how much a player will enjoy a game. The focus has turned to adding more humanlike characteristics into computer game agents....
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Color image histograms are very useful tools for content based image retrieval (CBIR) that can be applied on features such as colour, texture and shape. As these kinds of histograms results with large variations betwe...
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Echo State Network (ESN) is a new type of Recurrent Neural Network (RNN) proposed in recent years. The training process of ESN is easier and requires less computational effort than regular RNN which has the same size....
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In this paper, we present several considerations centered around the data-driven system approaches. We briefly explore three main issues: the evolving relationship between off-line and on-line data processing methods,...
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In this paper, we present several considerations centered around the data-driven system approaches. We briefly explore three main issues: the evolving relationship between off-line and on-line data processing methods, the complementary relationship between the data-driven and model-based methods, and the perspectives of data-driven system approaches. Instead of offering solutions to data-driven system problems, which is impossible at the present level of knowledge and research, in this article we aim at categorizing and classifying open problems, exploring possible directions that may offer alternatives or potentials for the four key fields of interests: control, decision making, scheduling, and fault diagnosis.
Color image histograms are very useful tools for content based image retrieval (CBIR) that can be applied on features such as colour, texture and shape. As these kinds of histograms results with large variations betwe...
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Color image histograms are very useful tools for content based image retrieval (CBIR) that can be applied on features such as colour, texture and shape. As these kinds of histograms results with large variations between neighbouring bins, they seem so sensitive to any kind of changes such as noise, illumination. To overcome this problem, in this paper, fuzzy linking histogram approach based on OWA aggregation operator is proposed, which is capable of projecting 3-dimensional (L*a*b*) colour histograms into single-dimension. The proposed method have been evaluated and compared with five other related methods in retrieving similar images from the common dataset which is available on http://***/~konkonst. The experimental results on 100 images within two categories of Cat and Sky reveals better performance of the proposed method in comparison with the other mentioned methods.
A three hierarchical sliding mode control is presented for a class of an underactuated system which can overcome the mismatched perturbations. The considered underactuated system is a double inverted pendulum (DIP), c...
A three hierarchical sliding mode control is presented for a class of an underactuated system which can overcome the mismatched perturbations. The considered underactuated system is a double inverted pendulum (DIP), can be modeled by three subsystems. Such structure allows the construction of several designs of hierarchies for the controller. For all hierarchical designs, the asymptotic stability of every layer sliding mode surface and the sliding mode surface of subsystems are proved theoretically by Barbalat’s lemma. Simulation results show the validity of these methods.
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