The maximum likelihood detector (MLD) for single differential modulation is easy to derive. On the other hand, the MLD problem associated with double differential modulation is much more complicated and solving it was...
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It has been shown that for any nonsingular matrix M, there exists a finite set of ‘unmixing’ matrices S such that at least one member Si ϵ S will exhibit the property that MSi will be stable, i.e. MSi will be a Hurw...
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It has been shown that for any nonsingular matrix M, there exists a finite set of ‘unmixing’ matrices S such that at least one member Si ϵ S will exhibit the property that MSi will be stable, i.e. MSi will be a Hurwitz Matrix. The purpose of this note is to construct such a set for the cases n = 2, 3 and for the specific case of companion matrices of arbitrary dimension. A direct application of such ‘unmixing’ matrices is in the construction of adaptive-type controllers using switching controllers.
This paper describes a virtual reality and haptic interface between human and the Atomic Force Microscope (AFM), which allows the operator to sense and touch the surface and nanoparticles during the manipulation with ...
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We present a possible solution for the multi-vehicle cooperative search problem that is based on the idea of surrogate optimization to adaptively identify a terrain map on-line and use it to produce decentralized cont...
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This paper investigates the utilisation of neural networks (NNs) and parametric linear approaches for modelling a twin rotor multi-input multi-output system (TRMS) in hovering position. A multi-layer perceptron (MLP) ...
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This paper investigates the utilisation of neural networks (NNs) and parametric linear approaches for modelling a twin rotor multi-input multi-output system (TRMS) in hovering position. A multi-layer perceptron (MLP) neuro-model is designed to characterise the TRMS. A parametric model of the system is then developed with the conventional recursive least square (RLS) technique. A comparative assessment of the two model types, in characterising the system, is carried out in the time and frequency domains. Experimental results demonstrate the superiority of the NN approach over the conventional linear modelling approach. The developed neuro-modelling approach will be used for control design and development in future work.
Effective training is essential for human teleoperators to deliver satisfactory performance in actual tasks. Teleoperation is naturally a very difficult task due to the absence of naked-eye vision that cripples the co...
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Effective training is essential for human teleoperators to deliver satisfactory performance in actual tasks. Teleoperation is naturally a very difficult task due to the absence of naked-eye vision that cripples the cognitive behavior of the remote operator. Camera vision somehow is not a satisfactory substitution. However, training with naked-eye vision feedback may help human teleoperators to learn how to deliver satisfactory performance when they actually interact with camera vision. This study was carried out to further investigate this hypothesis, and to quantitatively supplement it with experimental proofs. For this cause, the recently built telerobotic test-bed between KAIST (Korea) and Saga University(Japan) was reshaped to a telerobotic mini-golf system, which is the trial experiment in this study. The performance of the players with and without naked-eye training was compared and quantitatively evaluated. The effectiveness of training with naked-eye vision was verified as an essential part in training human teleoperators.
For a hysteresis structure with energy dissipation devices, the force-displacement relation is nonlinear such that it is very difficult to evaluate the actual damping and stiffness coefficients, even if the force-disp...
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This paper investigates the utilisation of back propagation neural networks (NNs) for modelling flexible beam structures in fixed-free mode; a simple representation of an aircraft wing or robot arm. A comparative perf...
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This paper investigates the utilisation of back propagation neural networks (NNs) for modelling flexible beam structures in fixed-free mode; a simple representation of an aircraft wing or robot arm. A comparative performance of the NN model and conventional recursive least square scheme, in characterising the system is carried out in the time and frequency domains. Simulated results demonstrate that using NN approach the system is modelled well than with the conventional linear modelling approach. The developed neuro-modelling approach would further be utilized in the design and implementation of suitable controllers, for vibration suppression in such system.
This paper is an explanation of an approach to the problem of decision making in a multi agent system using genetic algorithm. The soccer game environment is chosen as the distributed system. This algorithm was tested...
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This paper is an explanation of an approach to the problem of decision making in a multi agent system using genetic algorithm. The soccer game environment is chosen as the distributed system. This algorithm was tested during the Robocop competitions against other teams and could register important accomplishments. We also compare the performance of three averaging methodologies; simple weighted averaging approach, genetic algorithm with simple weighted average function, and genetic algorithm with an OWA function. The paper also elaborates ideas on bounded rationality and memorized estimation employed for making the problem tractable.
The Homogenous Charge Compression Ignition (HCCI) combustion engine has potential to replace the spark ignition and compression ignition engines of today. One of the main problems in making the engine commercially att...
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