We address robust stabilization problem for networked controlsystems with nonlinear uncertainties and packet losses by modelling such systems as a class of uncertain switched systems. Based on theories on switched Ly...
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ISBN:
(纸本)9781424445233
We address robust stabilization problem for networked controlsystems with nonlinear uncertainties and packet losses by modelling such systems as a class of uncertain switched systems. Based on theories on switched Lyapunov functions, we derive the robustly stabilizing conditions for state feedback stabilization and design packet-loss dependent controllers by solving some matrix inequalities. A numerical example and some simulations are worked out to demonstrate the effectiveness of the proposed design method.
Investigating the evolutionary dynamics of game theoretical interactions in populations where individuals are arranged on a graph can be challenging in terms of computation time. Here, we propose an efficient method t...
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Investigating the evolutionary dynamics of game theoretical interactions in populations where individuals are arranged on a graph can be challenging in terms of computation time. Here, we propose an efficient method to study any type of game on arbitrary graph structures for weak selection. In this limit, evolutionary game dynamics represents a first-order correction to neutral evolution. Spatial correlations can be empirically determined under neutral evolution and provide the basis for formulating the game dynamics as a discrete Markov process by incorporating a detailed description of the microscopic dynamics based on the neutral correlations. This framework is then applied to one of the most intriguing questions in evolutionary biology: the evolution of cooperation. We demonstrate that the degree heterogeneity of a graph impedes cooperation and that the success of tit for tat depends not only on the number of rounds but also on the degree of the graph. Moreover, considering the mutation-selection equilibrium shows that the symmetry of the stationary distribution of states under weak selection is skewed in favor of defectors for larger selection strengths. In particular, degree heterogeneity—a prominent feature of scale-free networks—generally results in a more pronounced increase in the critical benefit-to-cost ratio required for evolution to favor cooperation as compared to regular graphs. This conclusion is corroborated by an analysis of the effects of population structures on the fixation probabilities of strategies in general 2×2 games for different types of graphs. Computer simulations confirm the predictive power of our method and illustrate the improved accuracy as compared to previous studies.
The memory state feedback control problem for a class of discrete-time systems with input delay and unknown state delay is addressed based on LMIs and Lyapunov-Krasovskii functional method. Under the action of our des...
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The memory state feedback control problem for a class of discrete-time systems with input delay and unknown state delay is addressed based on LMIs and Lyapunov-Krasovskii functional method. Under the action of our designed adaptive control law, the unknown time-delay parameter is included in memory state feedback controller. Using LMI technique, delay-dependent sufficient conditions for the existence of the feedback controller are obtained. Finally, the effectiveness of the proposed design method is demonstrated by a numerical example.
The wavelet edge detecting method was introduced to the welding seam image processing in this paper, which can make up the defect of usual edge detecting methods in antinoise ability and precise locating ability. The ...
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The wavelet edge detecting method was introduced to the welding seam image processing in this paper, which can make up the defect of usual edge detecting methods in antinoise ability and precise locating ability. The B spline wavelet was applied to extract the image edge and the similarity distance was defined to compare the extracting results. The contrasting results demonstrate the wavelet edge detection is better than the usual methods, which justified the validity that the wavelet transform can be used efficiently in the welding seam image processing.
A model-based matching method is proposed for welded joint localization and recognition. Simple parameterized joint models are defined, which approach the actual joint pose fast in a iterative style by using the parti...
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A model-based matching method is proposed for welded joint localization and recognition. Simple parameterized joint models are defined, which approach the actual joint pose fast in a iterative style by using the partial Hausdorff distance (PHD) as the similarity measurement. Statistical analysis is employed to determine the matching parameters adaptively, and the dimension of parameter space is decreased by performing the estimation on the structured light plane, which make a robust and real-time performance. Experiments show that accurate result can be acquired in real time, which meets the actual applications' requirements.
A control scheme combined with backstepping, radius basis function (RBF) neural networks and adaptive control is proposed for the stabilization of nonlinear system with input and state delay. By using state transforma...
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In the letter [Neurocomputing 71(1–3) (2007) 428–438], there exists one minor error in computing the derivative of V 2 ( ɛ ( t ) ) and thus, the proof of Theorem 1 needs some improvement.
In the letter [Neurocomputing 71(1–3) (2007) 428–438], there exists one minor error in computing the derivative of V 2 ( ɛ ( t ) ) and thus, the proof of Theorem 1 needs some improvement.
Object states estimation and data association are main facets of multi-object tracking. Under complex situations, one object often grouped with others, or occluded by other objects or background, which can increase th...
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A novel color correlogram based particle filter was proposed for an object tracking in visual surveillance. By using the color correlogram as object feature, spatial information is incorporated into object representat...
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The decoupling and linearize (D&L) control of induction motor is an important approach to improve the performance further. The analytical inverse system can realize D&L of nonlinear system when the model is ex...
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The decoupling and linearize (D&L) control of induction motor is an important approach to improve the performance further. The analytical inverse system can realize D&L of nonlinear system when the model is exactly known, but for the induction motor with parameters varying and disturbance, the D&L is destroyed. So the neural network inverse system (NNIS) theory was adapted to approximate the analytical inverse system in order to weaken the couple of rotor flux and speed, the NNIS was designed for the induction motor in the synchronous rotating (dq) reference frame in this paper. Through the analytical inverse system expression we pointed out that the D&L effect is unrelated to the position of d axis. Subsequently, the neural network inverse control (NNIC) structure was proposed. As a special case, the NNIS of induction motor in rotor field oriented (MT) reference frame was also given, the comparison of this NNIC with direct rotor field oriented control (DRFOC) was done and we conclude that it is an improved method of DRFOC. At last, the simulation and experiment were done to test the proposed structures.
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