1,858,677 research outputs found
The adaptive control system of quadrocopter motion
In this paper we present a system for automatic control of a quadrocopter based on the adaptive control system. The task is to ensure the motion of the quadrocopter along the given route and to control the stabilization of the quadrocopter in the air in a horizontal or in a given angular position by sending control signals to the engines. The nonlinear model of a quadrocopter is expressed in the form of a linear non-stationary system
Dynamic Channel Allocation Techniques Using Adaptive Modulation and Adaptive Antennas
This contribution studies the impact of adaptive quadrature amplitude modulation (AQAM) on network performance when applied to a cellular network, using adaptive antennas in conjunction with both fixed channel allocation (FCA) and locally distributed dynamic channel allocation (DCA) schemes. The performance advantages of using adaptive modulation are investigated in terms of the overall network performance, mean transmitted power, and the average network throughput. Adaptive modulation allowed an extra 51% of users to be supported by an FCA 4-QAM network, while in conjunction with DCA, an additional 54% user capacity was attained. Index TermsâAdaptive antennas, adaptive modulation, adaptive arrays, beam-steering, DCA, dynamic channel allocation
Self-adaptation of Mutation Rates in Non-elitist Populations
The runtime of evolutionary algorithms (EAs) depends critically on their
parameter settings, which are often problem-specific. Automated schemes for
parameter tuning have been developed to alleviate the high costs of manual
parameter tuning. Experimental results indicate that self-adaptation, where
parameter settings are encoded in the genomes of individuals, can be effective
in continuous optimisation. However, results in discrete optimisation have been
less conclusive. Furthermore, a rigorous runtime analysis that explains how
self-adaptation can lead to asymptotic speedups has been missing. This paper
provides the first such analysis for discrete, population-based EAs. We apply
level-based analysis to show how a self-adaptive EA is capable of fine-tuning
its mutation rate, leading to exponential speedups over EAs using fixed
mutation rates.Comment: To appear in the Proceedings of the 14th International Conference on
Parallel Problem Solving from Nature (PPSN
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Reducing the cost of applying adaptive test cases
The testing of a state-based system may involve the application of a number of adaptive test cases. Where the implementation under test (IUT) is deterministic, the response of the IUT to some adaptive test case could be capable of determining the response of the IUT to another adaptive test case $\gamma_2". Thus, the expected cost of applying a set of adaptive test cases depends upon the order in which they are applied. This paper explores properties of adaptive test cases and considers the problem of finding an order of application of the elements from some set of adaptive test cases, which minimises the expected cost of testing
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