This paper focuses on the problem of minimum time trajectory planning for helicopter UAVs. It is formulated as a nonlinear optimal control subject to the dynamics and limitations of helicopter UAVs. The dynamical syst...
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This paper focuses on the problem of minimum time trajectory planning for helicopter UAVs. It is formulated as a nonlinear optimal control subject to the dynamics and limitations of helicopter UAVs. The dynamical system is defined by a set of fifteen states nonlinear differential equations developed for HeLion, a UAV helicopter constructed in National University of Singapore (NUS). The problem is then solved numerically using pseudospectral method for dynamic optimization. The results show that minimum time trajectories are highly nonlinear that require complicated maneuvering.
Based on the ideal solution approximation, the model for size-dependent melting temperature of pure metal nanoparticles is extended to binary alloy systems. The developed model, free of any adjustable parameter, demon...
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Based on the ideal solution approximation, the model for size-dependent melting temperature of pure metal nanoparticles is extended to binary alloy systems. The developed model, free of any adjustable parameter, demonstrates that the melting temperature is related to the size and composition of alloy nanoparticles. The melting temperature of CuNi, PbBi and Snln binary alloy nanocrystals is found to be consistent with the experiments and molecular dynamics simulations. The research reveals that alloy nanocrystals have similar melting nature as pure metal.
Based on the non-traveling wave solution and a chemical chaos system, chaotic soliton excitations are established for the nonlinear(3+1)-dimensional Burgers system. The chaotic behavior and chaotic evolution of the sy...
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Based on the non-traveling wave solution and a chemical chaos system, chaotic soliton excitations are established for the nonlinear(3+1)-dimensional Burgers system. The chaotic behavior and chaotic evolution of the system are studied.
Context is information that describes the situations in which computing, social and physical interactions take place. The complexity and scope of context information available for utilization by context-consuming appl...
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Context is information that describes the situations in which computing, social and physical interactions take place. The complexity and scope of context information available for utilization by context-consuming applications, such as those executing on smart mobile devices, sensing and tracking platforms, etc. is growing with the increased integration of digital artifacts in smart environments. Similarly, the uptake of Cloud computing has significantly influenced the traditional information processing and infrastructure provision models by offering an agile, scalable and cost effective computing paradigm. This is leading to the adoption of Cloud-based solutions for the pervasive and ubiquitous environments, however, there are significant challenges that need to be overcome before its exploitation by real world applications and users. The context information consumed and produced by the applications and devices needs to be represented, disseminated, processed and consumed by numerous components in a context-aware Cloud system. Significant amount of context consumption, production and processing takes place on devices and there is limited or no support for collaborative modeling, persistence and processing between the device-Cloud ecosystems. In this paper we propose an environment for context processing in a Cloud-based distributed infrastructure that offloads complex context processing from the applications and devices. An experimental analysis of complexity based context-processing categories has been carried out to establish the processing-load boundary. The results demonstrate that the proposed collaborative device-Cloud infrastructure provides significant performance and energy conservation benefits for mobile devices and applications.
Let S be a string of length N compressed into a context- free grammar S of size n. We present two representations of S achieving O(logN) random access time, and either O(n·α_k(n)) construction time and space on ...
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ISBN:
(纸本)9780898719932
Let S be a string of length N compressed into a context- free grammar S of size n. We present two representations of S achieving O(logN) random access time, and either O(n·α_k(n)) construction time and space on the pointer machine model, or O(n) construction time and space on the RAM. Here, α_k(n) is the inverse of the kth row of Ackermann's function. Our representations also efficiently support decompression of any substring in S: we can decompress any substring of length m in the same complexity as a single random access query and additional O(m) time. Combining these results with fast algorithms for uncompressed approximate string matching leads to several efficient algorithms for approximate string matching on grammar-compressed strings without decompression. For instance, we can find all approximate occurrences of a pattern P with at most k errors in time O(n(min{|P|k, k~4+|P|}+logN)+occ), where occ is the number of occurrences of P in S. Finally, we are able to generalize our results to navigation and other operations on grammar-compressed trees. All of the above bounds significantly improve the currently best known results. To achieve these bounds, we introduce several new techniques and data structures of independent interest, including a predecessor data structure, two "biased" weighted ancestor data structures, and a compact representation of heavy-paths in grammars.
Observer-based delay-dependent robust H∞ controller design problem for state and input time-delays systems with a class of nonlinear uncertainties is discussed in this paper. Assuming that the nonlinear uncertain fun...
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Observer-based delay-dependent robust H∞ controller design problem for state and input time-delays systems with a class of nonlinear uncertainties is discussed in this paper. Assuming that the nonlinear uncertain functions in the considered model are gain-bounded, we obtain a sufficient condition for robustly asymptotic stability and H∞ performance of the closed-loop system in the light of Lyapunov stability theory. By solving a pair of linear matrix inequalities (LMIs), we construct delay-dependent state feedback control law which guarantees robustly asymptotic stability of the closed-loop system and reduce the effect of the disturbance input on the controlled output to a prescribed level. The delay-bounds and the H performance bound can be optimized. A numerical example is given to illustrate our results.
It is well known that gene regulatory circuits can be modeled by the deterministic or stochastic approach. In this paper, a three-component coupled positive and negative feedback genetic circuit is firstly modeled det...
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It is well known that gene regulatory circuits can be modeled by the deterministic or stochastic approach. In this paper, a three-component coupled positive and negative feedback genetic circuit is firstly modeled deterministically by Hill kinetics. Then, a corresponding stochastic model is also investigated by using Gellispie's stochastic simulation. Some typical dynamical behaviors of the genetic circuit are further discussed based on the bifurcation analysis of deterministic system, including monostability, bistability, excitability, and oscillation. This paper aims to further investigate the effect of intrinsic noise inherently in stochastic models on steady states transition. It includes: i) For the parameters in deterministically bistable region, intrinsic noise may induce bistable switch for the not too large system volume, which can be observed by the generation of a new stable steady state; ii) For the parameters in deterministically excitable region, intrinsic noise may induce periodic switch for the very large system volume, which can be observed by the stabilization of another unstable steady state and the switching between two stable states; iii) When time delays are introduced in these two models, similar phenomena can be observed. The above results will certainly increase the understanding of the inner relationships between different modeling for the genetic circuit. It sheds some light on the real- world engineering applications, such as the engineering design of synthetic circuits.
We introduce new definitions of semi-continuity for multifunctions, combining the topological and the ordered structure of a Banach space induced by a closed convex cone. We prove two types Nash equilibrium theorems f...
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We introduce new definitions of semi-continuity for multifunctions, combining the topological and the ordered structure of a Banach space induced by a closed convex cone. We prove two types Nash equilibrium theorems for multifunctions using scalarization and the Ky Fan’s inequality. As corollaries we obtain saddle point theorems for convex-concave multifunctions, which can be considered as generalization to the vector-valued set-valued case of the Von Neumann minimax theorem.
Dynamic self-heating effect is characterised in n-channel FinFETs on Silicon-on-Insulator (SOI) platform. RF extraction technique is discussed and dependence of thermal resistance on fin width, number of parallel fins...
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Dynamic self-heating effect is characterised in n-channel FinFETs on Silicon-on-Insulator (SOI) platform. RF extraction technique is discussed and dependence of thermal resistance on fin width, number of parallel fins and fin spacing is studied.
Constrained optimization problems compose a large part of real-world applications. More and more attentions have gradually been paid to solve this kind of problems. An improved particle swarm optimization (IPSO) algor...
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Constrained optimization problems compose a large part of real-world applications. More and more attentions have gradually been paid to solve this kind of problems. An improved particle swarm optimization (IPSO) algorithm based on feasibility rules is presented in this paper to solve constrained optimization problems. The average velocity of the swarm and the best history position in the particle's neighborhood are introduced as two turbulence factors, which are considered to influence the fly directions of particles, into the algorithm so as not to converge prematurely. The performance of IPSO algorithm is tested on 13 well-known benchmark functions. The experimental results show that the proposed IPSO algorithm is simple, effective and highly competitive.
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