Abstract In this paper, we introduce a bijective mapping ü ″ n which maps an n-dimensional unit space ¶ n to a subset of the one-dimensional interval ¶, by using a symbolic, 2-adic representation of ea...
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Abstract In this paper, we introduce a bijective mapping ü ″ n which maps an n-dimensional unit space ¶ n to a subset of the one-dimensional interval ¶, by using a symbolic, 2-adic representation of each point of the space. We also demonstrate an application of this method to obtaining sliding manifolds of certain classes of sliding mode controlsystems.
The solution to the problem of finding the reaction kinetic realization of a given system obeying the mass action law containing the minimal/maximal number of reactions and complexes is shown in this paper. The propos...
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ISBN:
(纸本)9783642149405
The solution to the problem of finding the reaction kinetic realization of a given system obeying the mass action law containing the minimal/maximal number of reactions and complexes is shown in this paper. The proposed methods are based on Mixed Integer Linear Programming where the mass action kinetics is encoded into the linear constraints. Although the problems are NP-hard in the current setting, the developed algorithms give a usable answer to some of the questions first raised in [1].
In today's highly complex multi-AGV systems key research objective is finding a scheduling and routing policy that avoids deadlock while assuring that vehicle utilization is as high as possible. It is well known t...
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In today's highly complex multi-AGV systems key research objective is finding a scheduling and routing policy that avoids deadlock while assuring that vehicle utilization is as high as possible. It is well known that finding such an optimal policy is a NP-hard task in general case. Therefore, big part of the research is oriented towards finding various suboptimal policies that can be applied to real world plants. In this paper we propose modified Banker's algorithm for scheduling in multi-AGV systems. A predetermined mission's path is executed in a way that some non-safe states are allowed in order to achieve better utilization of vehicles. A graph-based method of polynomial complexity for verification of these states is given. Algorithm is tested on a layout of a real plant for packing and warehousing palettes. Results shown at the end of the paper demonstrate advantages of the proposed method compared with other methods based on Banker's algorithm.
An iterative bootstrapping-based data over-sampling strategy is presented in this paper together with an adaptive neural-fuzzy inference system (ANFIS) to deal with a severely imbalanced data modelling problem. As rea...
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An iterative bootstrapping-based data over-sampling strategy is presented in this paper together with an adaptive neural-fuzzy inference system (ANFIS) to deal with a severely imbalanced data modelling problem. As real industrial data are often very large, containing hundreds of process variables and a huge number of data records, the selection of a compact set of input variables becomes critical for any successful modelling and analysis operations. Significant efforts have been devoted to identifying the most relevant input variables through correlation analysis and neural network based forward input selection. An optimal majority to minority class data ratio, which controls the level of data imbalance for model training, is then determined through the iterative bootstrapping process such that the combined sensitivity and specificity performance is optimised. The iterative bootstrapping ANFIS modelling strategy is then applied to a real industrial case study for rail quality classification, with the original data being provided by Tata Steel Europe. Preliminary results show a good overall performance through the iterative bootstrapping data over-sampling ANFIS modelling.
This paper deals with design of a synchronous frame control strategy for single-phase inverter-based islanded distributed generation (DG) systems. Although, implementation of these regulators requires a minimum of two...
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This paper deals with design of a synchronous frame control strategy for single-phase inverter-based islanded distributed generation (DG) systems. Although, implementation of these regulators requires a minimum of two independent phases in the system, the required orthogonal phase is generated through the use of a first order all pass filter (APF). The essence of the proposed control strategy is to use a synchronous reference frame PI (SRFPI) controller to regulate output voltage, together with a simple inner capacitor current regulating loop to stabilize the system and a voltage-feedforward loop to improve the system robustness. A detailed design criterion for the proposed control strategy is presented base on a frequency-response approach. Finally, simulation results are presented to validate the proposed method.
The paper presents a tube model predictive control (MPC) scheme of continuous-time nonlinear systems based on robust control invariant set. The optimization problem considered has a general cost functional rather than...
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ISBN:
(纸本)9781612848006
The paper presents a tube model predictive control (MPC) scheme of continuous-time nonlinear systems based on robust control invariant set. The optimization problem considered has a general cost functional rather than the quadratic one. The scheme has the same online computational burden as the standard MPC with guaranteed nominal stability. Robust stability, as well as recursive feasibility, is guaranteed if the optimization problem is feasible at the initial time instant. Furthermore, an optimization based control scheme is proposed, which inherits the robust properties of the tube MPC scheme. The related optimization problem is solved only at the initial time instant. In particular, we consider a scheme to obtain robust control invariant set for Lipschitz nonlinear systems, and show the effectiveness of the proposed schemes by a simple example.
This paper presents a deterministic and adaptive spike model derived from radial basis functionsand a leaky integrate-and-fire sampler developed for training spiking neural networks without directweight manipulation. ...
This paper presents a deterministic and adaptive spike model derived from radial basis functions
and a leaky integrate-and-fire sampler developed for training spiking neural networks without direct
weight manipulation. Several algorithms have been proposed for training spiking neural networks
through biologically-plausible learning mechanisms, such as spike-timing-dependent synaptic plasticity
and Hebbian plasticity. These algorithms typically rely on the ability to update the synaptic strengths,
or weights, directly, through a weight update rule in which the weight increment can be decided
and implemented based on the training equations. However, in several potential applications of
adaptive spiking neural networks, including neuroprosthetic devices and CMOS/memristor nanoscale
neuromorphic chips, the weights cannot be manipulated directly and, instead, tend to change over time
by virtue of the pre- and postsynaptic neural activity. This paper presents an indirect learning method
that induces changes in the synaptic weights by modulating spike-timing-dependent plasticity by means
of controlled input spike trains. In place of the weights, the algorithm manipulates the input spike trains
used to stimulate the input neurons by determining a sequence of spike timings that minimize a desired
objective function and, indirectly, induce the desired synaptic plasticity in the network.
The Discrete Cosine Transform (DCT) is one of the most widely used techniques for image compression. Several algorithms are proposed to implement the DCT-2D. The scaled SDCT algorithm is an optimization of the DCT-1D,...
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To improve the modelling performance, one should either propose new modelling methodologies or make the best of existing models. In this paper, the study is concentrated on the latter solution, where a structure-free ...
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Abstract In this paper, we study the real controllability radius of higher-order linear time-invariant (LTI) systems, LTI descriptor systems, and time-delay LTI systems. The various radii are defined in terms of real ...
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Abstract In this paper, we study the real controllability radius of higher-order linear time-invariant (LTI) systems, LTI descriptor systems, and time-delay LTI systems. The various radii are defined in terms of real parametric perturbations, and computable formulas are derived using generalized real perturbation values of matrix pairs.
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