In this paper, a novel disturbance observer (DO) for the Mobile Wheeled Inverted Pendulum (MWIP) system is proposed. A choice method of optimal gain matrices is also proposed for a given robust gain, which can improve...
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ISBN:
(纸本)9781467384155
In this paper, a novel disturbance observer (DO) for the Mobile Wheeled Inverted Pendulum (MWIP) system is proposed. A choice method of optimal gain matrices is also proposed for a given robust gain, which can improve the estimation precision of the DO. Combining the proposed DO and Sliding Mode control (SMC), a new sliding mode velocity control method is designed for the MWIP system. The convergency of the DO is proved by Lyapunov theorem. And the stability of the closed-loop system is achieved through the appropriate selection of sliding surface coefficients. The effectiveness of all proposed methods is verified by simulation results for the MWIP system.
Accurate techniques for testing production sections are important when developing horizontal wells, but appropriate methods are also needed for transporting loggers through horizontal well segments. The reciprocating ...
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Accurate techniques for testing production sections are important when developing horizontal wells, but appropriate methods are also needed for transporting loggers through horizontal well segments. The reciprocating grip traction robot is a pipeline robot that has already been tested and broadly accepted for use in horizontal wells. Reciprocating grip traction robots have received a great deal of attention because they are very (more than 40%) efficient, although many other tractors are only 10% to 20% efficient, the remaining energy being converted to waste heat. However, even an efficiency of 40% may constitute a serious thermal problem in high-temperature environments, and cooling methods must be used to remove the heat produced by the waste energy. The research presented here is mainly focused on the development of a thermal management system for the electronics in traction robots. Numerical simulations are used to optimize heat sink and skeleton structure to mitigate the effects of high temperature.
A nuclear export signal (NES) is a sequence of amino acids, which is a protein localization signal, and contributes to regulate localization of cellular proteins. In recent peering works, activity of NESs were introdu...
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Background:Previous studies have indicated that the cognitive deficits in patients with Alzheimer's disease (AD) may be due to topological deteriorations of the brain ***,whether the selection of a specific freque...
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Background:Previous studies have indicated that the cognitive deficits in patients with Alzheimer's disease (AD) may be due to topological deteriorations of the brain ***,whether the selection of a specific frequency band could impact the topological properties is still not *** hypothesis is that the topological properties of AD patients are also ***:Resting state functional magnetic resonance imaging data from l0 right-handed moderate AD patients (mean age:64.3 years; mean mini mental state examination [MMSE]:18.0) and 10 age and gender-matched healthy controls (mean age:63.6 years; mean MMSE:28.2) were enrolled in this *** global efficiency,the clustering coefficient (CC),the characteristic path length (CpL),and "small-world" property were calculated in a wide range of thresholds and averaged within each group,at three different frequency bands (0.01-0.06 Hz,0.06-0.11 Hz,and 0.11-0.25 Hz).Results:At lower-frequency bands (0.01-0.06 Hz,0.06-0.11 Hz),the global efficiency,the CC and the "small-world" properties of AD patients decreased compared to *** at higher-frequency bands (0.11-0.25 Hz),the CpL was much longer,and the "small-world" property was disrupted in AD,particularly at a higher *** topological properties changed with different frequency bands,suggesting the existence of disrupted global and local functional organization associated with ***:This study demonstrates that the topological alterations of large-scale functional brain networks inAD patients are frequency dependent,thus providing fundamental support for optimal frequency selection in future related research.
Spiking neural P systems with astrocytes (SNPA systems, for short) are a class of distributed parallel computing devices inspired from the way spikes pass through the synapses between the neurons. In this work, we inv...
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Taking into account that the present popular methods, such as the judgement of the axle failure based on temperature threshold, and the early warning of axle based on real-time temperature analysis, cannot analyze the...
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Taking into account that the present popular methods, such as the judgement of the axle failure based on temperature threshold, and the early warning of axle based on real-time temperature analysis, cannot analyze the changing of performance trends, a health state analysis method for the axle of high-speed train based on long-term temperature monitoring data is proposed in this paper, which including the following main steps: (1) Preprocessing of the original data to correct the singular zero value and complement the missing values, (2) Smoothing of the processed data in order to automatically extract the beginning and end points of every temperature rising stage of axles, (3) Establishment of the calculation method of temperature rising rate, and evaluating the health sate of axles based on the temperature rising rate. Finally, the proposed method is validated based on the data from a test line, the results demonstrate the effectiveness and practicability of the method.
In this paper, we study the existence and global exponential stability of almost periodic solution for memristor-based neural networks with leakage, time-varying and distributed delays. Using a new Lyapunov function m...
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In this paper, we study the existence and global exponential stability of almost periodic solution for memristor-based neural networks with leakage, time-varying and distributed delays. Using a new Lyapunov function method, we prove that this delayed neural network has a unique almost periodic solution, which is globally exponentially stable. Moreover, the obtained conclusion on the almost periodic solution is applied to prove the existence and stability of periodic solution (or equilibrium point) for this delayed neural network with periodic coefficients (or constant coefficients).
Spiking neural P systems with synapses states characterize the movement of spikes among the neurons. The number of the spikes in neurons can be represented by integers, which provide a way to represent increment, decr...
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Complexity of analysis of landslide hazard is due to uncertainty. In this study, a novel approach multi-gene genetic programming based on separable functional network (MGGPSFN) is presented for predicting landslide di...
Complexity of analysis of landslide hazard is due to uncertainty. In this study, a novel approach multi-gene genetic programming based on separable functional network (MGGPSFN) is presented for predicting landslide displacement. Moreover, Pearson's cross-correlation coefficients and mutual information are adopted to look for the potential input variables for a forecast model in the paper. The performance of new model is verified through one case study in Baishuihe landslide in the Three Gorges Reservoir in China. In addition, we compared it with two methods, back-propagation neural network and radial basis function, and MGGPSFN got the best results in the same measurements.
Membrane algorithms (MAs), which inherit from P systems, constitute a new parallel and distribute framework for approximate computation. In the paper, a membrane algorithm is proposed with the improvement that the i...
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Membrane algorithms (MAs), which inherit from P systems, constitute a new parallel and distribute framework for approximate computation. In the paper, a membrane algorithm is proposed with the improvement that the involved parameters can be adaptively chosen. In the algorithm, some membranes can evolve dynamically during the computing process to specify the values of the requested parameters. The new algorithm is tested on a well-known combinatorial optimization problem, the travelling salesman problem. The em-pirical evidence suggests that the proposed approach is efficient and reliable when dealing with 11 benchmark instances, particularly obtaining the best of the known solutions in eight instances. Compared with the genetic algorithm, simulated annealing algorithm, neural net-work and a fine-tuned non-adaptive membrane algorithm, our algorithm performs better than them. In practice, to design the airline network that minimize the total routing cost on the CAB data with twenty-five US cities, we can quickly obtain high quality solutions using our algorithm.
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