Based on the comparison of several common methods of electronic compass error compensation, this paper presents a new error compensation method based on Adaptive Differential Evolution-Fourier Neural Networks (ADE-FNN...
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Based on the comparison of several common methods of electronic compass error compensation, this paper presents a new error compensation method based on Adaptive Differential Evolution-Fourier Neural Networks (ADE-FNN) to improve the measurement accuracy of electronic compass. This method uses Fourier neural network to model electronic compass error, and adopts Adaptive Differential Evolution to optimize the weights of neural network, and get more exact error model to compensate measured values. The compensation object is the common electronic compass composed by two-dimensional magnetic resistance sensor. Compared with the compensation effect of Least-square method, BP neural network and Fourier neural networks, It proves that the mode of this method can realize the high precision in the sample space mapping and high non-linear approximation ability, and this method has faster convergence rate, can avoid falling into local minima, reduces the training error, and improves error compensation accuracy. This method decreases the error range from -3.4° ~ 25.2° before compensation to -0.20° ~ 0.72°, and the average of the absolute error is 0.30°. Repeatability tests also proved the compensation plan have a good consistency.
Abstract This paper addresses the problem of distributed connectivity constrained motion coordination of multiple autonomous mobile agents. Different from traditional flat network structure which lacks flexibility and...
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Abstract This paper addresses the problem of distributed connectivity constrained motion coordination of multiple autonomous mobile agents. Different from traditional flat network structure which lacks flexibility and scalability when performing complex spatially distributed tasks, a novel distributed framework for construction of backbone-based hierarchical communication networks is proposed. Firstly, the proposed method periodically extracts a subset of agents which can form the communication backbone from the original network using only local information, thus partitions the system into backbone agents and non-backbone agents. Furthermore, the global network connectivity of the system is maintained at two levels: connectivity-preserving potential functions are used to maintain existing links in the backbone; connectivity between backbone and non-backbone agents is achieved via a leader-follower formation control scheme with backbone agents as the leaders. Finally, nontrivial numerical simulations are worked out to verify the theoretical results.
An efficient evaluation index system and evaluation model is crucial for effectiveness evaluation of the air defense networked fire controlsystem. This paper, based on pre-research for functions and characteristics o...
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Recognizing various traffic signs, especially the popular circular traffic signs, is an essential task for implementing advanced driver assistance system. To recognize circular traffic signs with high accuracy and rob...
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An average consensus protocol is proposed for discrete-time double-integrator multi-agent systems with communication noises under fixed topologies. The proposed consensus protocol is composed of two parts: the agent&...
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An average consensus protocol is proposed for discrete-time double-integrator multi-agent systems with communication noises under fixed topologies. The proposed consensus protocol is composed of two parts: the agent's own state feedback and the relative states between the agent and its neighbor agents. Due to the existence of communication noises, the relative states cannot be obtained accurately. To attenuate the noise effect, a time-varying consensus gain a(k) is applied to the relative states in the proposed protocol. Hence, the closed-loop dynamics of multi-agent systems is a linear stochastic difference equation with variable coefficients. Fortunately, the state transition matrix of this stochastic system can be solved, and the dynamical behavior of linear multi-agent systems can therefore be determined. It is proved that the proposed protocol is able to solve the mean square average consensus problem if and only if the topology graph is connected;and the time-varying gain a(k) satisfies the stochastic-approximation type conditions (Omission)。
In this paper, task allocation of multi-Unmanned Aerial Vehicles (UAVs) is studied, that is, multi-UAVs from different bases should be allocated to attack multiple targets. Based on the existing task allocation model,...
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In this paper, task allocation of multi-Unmanned Aerial Vehicles (UAVs) is studied, that is, multi-UAVs from different bases should be allocated to attack multiple targets. Based on the existing task allocation model, which just take the values of targets, UAVs and weapons into account, the fuel consumption is added into consideration to make the model much more practical. An improved genetic algorithm is proposed for such a multi-UAVs multi-targets task allocation. Simulation results show that the algorithm is significantly effective and the allocation result is reasonable.
An adaptive sliding mode control scheme for electromechanical actuator has been presented. The adaptive control strategy can estimate the uncertain parameters and adaptively compensate the modeled dynamical uncertaint...
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Abstract Common surveillance system is usually limited by the scope of observation, which may increase the probability of missing or misjudging suspicious targets. A wide-field monitoring system based on efficient ima...
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Abstract Common surveillance system is usually limited by the scope of observation, which may increase the probability of missing or misjudging suspicious targets. A wide-field monitoring system based on efficient image mosaicing algorithm is proposed in this paper. It can monitor a wide field for both short and long distance in real time and highlight the detected moving objects simultaneously. The image mosaicing is not only aimed at obtaining the wide field of view, but also utilized in motion detection for forming a wide-field motion mask. A simulation platform is developed to verify the performance of the system. The experiment results show that it satisfies the demands of high resolution and real-time implementation. The system is of high practical value to transportation surveillance or other applications.
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