In this study, the sliding mode approach is applied to the tracking control problem of a planar arm manipulator system driven by a new type of actuator, which comprises a pneumatic muscle (PM) and a torsion spring. Un...
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In this study, the sliding mode approach is applied to the tracking control problem of a planar arm manipulator system driven by a new type of actuator, which comprises a pneumatic muscle (PM) and a torsion spring. Unlike the traditional agonist/antagonist PM actuator, the PM is arranged in place of bicep and the torsion spring provides opposing torque in the presented actuator. The dynamic model is derived for this system and a sliding mode controller is designed to make the joint angle track a desired trajectory within a guaranteed accuracy even there are modelling uncertainties. A selection method is also proposed to obtain an appropriate spring coefficient, which plays an important role in the tracking control task. The effectiveness of the proposed method is confirmed by simulations. The differences between the control results of using our new actuator and that of using the traditional PM actuator in opposing pair configuration are also compared.
This paper outlines the application of DNA computing in the information security field. In this paper, we describe a kind of parallel XOR function model based on DNA chip, hybridization, and enzyme-cut technology. The...
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This paper outlines the application of DNA computing in the information security field. In this paper, we describe a kind of parallel XOR function model based on DNA chip, hybridization, and enzyme-cut technology. Then we apply the model to the efficient evaluation of the S-boxes' resistance to differential cryptanalysis. From the application, we evaluate the output XOR value distribution statistics of S-boxes and estimate the security of DES.
Inspired by the fact that in most existing swarm models of multi-agent systems the velocity of an agent can be infinite, which is not in accordance with the real applications, we propose a novel swarm model of multi-a...
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Inspired by the fact that in most existing swarm models of multi-agent systems the velocity of an agent can be infinite, which is not in accordance with the real applications, we propose a novel swarm model of multi-agent systems where the velocity of an agent is finite. The Lyapunov function method and LaSalle＇s invariance principle are employed to show that by using the proposed model all of the agents eventually enter into a bounded region around the swarm center and finally tend to a stationary state. Numerical simulations are provided to demonstrate the effectiveness of the theoretical results.
Looking for small universal computing devices is a natural and well investigated topic in computer science. Recently, this topic was also investigated in the framework of spiking neural P systems. One of the small uni...
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Looking for small universal computing devices is a natural and well investigated topic in computer science. Recently, this topic was also investigated in the framework of spiking neural P systems. One of the small universality results is that a small weakly universal extended spiking neural P system with 12 neurons was constructed. In this paper, a new way is introduced for simulating register machines by spiking neural P systems, where only one neuron is used for all instructions of the register machine;in this way, we can use less neurons to construct universal spiking neural P system. Specifically, we give a smaller weakly universal spiking neural P system that uses extended rules and has only 9 neurons. (C) 2010 Elsevier Ltd. All rights reserved.
Simulated annealing technique has mostly been used to solve various optimization and learning problems, and it is well known that the maximum clique problem is one of the most studied NP-hard optimization problems owi...
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Simulated annealing technique has mostly been used to solve various optimization and learning problems, and it is well known that the maximum clique problem is one of the most studied NP-hard optimization problems owing to its numerous applications. In this note, a simple simulated annealing algorithm for the maximum clique problem is proposed and tested on all 80 DIMACS maximum clique instances. Although it is simple, the proposed simulated annealing algorithm is efficient on most of the DIMACS maximum clique instances. The simulation results show that the proposed simulated annealing algorithm outperforms a recent efficient simulated annealing algorithm proposed by Xu and Ma, and the solutions obtained by the proposed simulated annealing algorithm have the equal quality with those obtained by a recent trust region heuristic algorithm of Stanislav Busygin. (C) 2007 Elsevier Inc. All rights reserved.
Diverse modeling frameworks have been utilized with the ultimate goal of translating brain cortical signals into prediction of visible behavior. The inputs to these models are usually multidimensional neural recording...
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Laser Radar Camera can be used to measure 3D data of object surface, its output is called range image. Range images provide direct geometrical information about the shape of visible surfaces so that some problems in 3...
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Laser Radar Camera can be used to measure 3D data of object surface, its output is called range image. Range images provide direct geometrical information about the shape of visible surfaces so that some problems in 3D object recognition and position should be solved more easily. Some range image feature extracting methods are too complex to control and consume a lot of time and space. In order to resolve these problems, this paper presents a multiresolution range image feature extracting method based on lifting scheme. This approach compute very fast and save spaces, so it is especially suitable for real-time applications such as pipeline bin-pick etc.
In the literature （Tan and Wang, 2010）, Tan and Wang investigated the convergence of the split-step backward Euler （SSBE） method for linear stochastic delay integro-differential equations （SDIDEs） and proved the...
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In the literature （Tan and Wang, 2010）, Tan and Wang investigated the convergence of the split-step backward Euler （SSBE） method for linear stochastic delay integro-differential equations （SDIDEs） and proved the mean-square stability of SSBE method under some condition. Unfortu- nately, the main result of stability derived by the condition is somewhat restrictive to be applied for practical application. This paper improves the corresponding results. The authors not only prove the mean-square stability of the numerical method but also prove the general mean-square stability of the numerical method. Furthermore, an example is given to illustrate the theory.
Lamarckian learning has been introduced into evolutionary computation to enhance the ability of local search. The relevant research topic, memetic computation, has received significant amount of interest. In this stud...
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Lamarckian learning has been introduced into evolutionary computation to enhance the ability of local search. The relevant research topic, memetic computation, has received significant amount of interest. In this study, a novel memetic computational framework is proposed by simulating the integrated regulation between neural and immune systems. The Lamarckian learning strategy of simulating the unidirectional regulation of neural system on immune system is designed. Consequently, an immune memetic algorithm based on the Lamarckian learning is proposed for numerical optimization. The proposed algorithm combines the advantages of immune algorithms and mathematical programming, and performs well in both global and local search. The simulation results based on ten low-dimensional and ten high-dimensional benchmark problems show that the immune memetic algorithm outperforms the basic genetic algorithm-based memetic algorithm in solving most of the test problems.
Spiking neural P systems are a class of distributed parallel computing devices inspired from the way neurons communicate by means of spikes. In this paper, the problem of looking for small universal computing devices ...
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Spiking neural P systems are a class of distributed parallel computing devices inspired from the way neurons communicate by means of spikes. In this paper, the problem of looking for small universal computing devices is investigated in the framework of spiking neural P systems. A new approach is introduced to simulate register machines by spiking neural P systems, where only one neuron is used for all instructions of the simulated register machine;in this way, less neurons are used to construct universal spiking neural P systems working in exhaustive mode. Specifically, a universal spiking neural P system with 36 neurons is constructed, which works in exhaustive mode. This significantly improves the already known result, where 125 neurons are used.
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