Magnetic measurement is a typical inverse problem in Biomedical field. In this kind of problem we always need to locate the positions and moments of one or more magnetic dipoles. Although using the traditional methods...
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Magnetic measurement is a typical inverse problem in Biomedical field. In this kind of problem we always need to locate the positions and moments of one or more magnetic dipoles. Although using the traditional methods to solve this kind of inverse problem has all kinds of shortcomings, BPNN (Back Propagation Neural Networks) method can be used to solve this typical inverse problem fast enough for real time measurement. In the traditional BPNN method, gradient descent search method is performed for error propagation. In this paper the authors propose a new algorithm that Newton method is performed for error propagation. For the cost function is highly nonconvex in the magnetic measurement problem, the new kind of BPNN can get convergent results quickly and precisely. A simulation result for this method is also presented.
This paper deals with a generalized automatic method used for designing artificial neural network (ANN) structures. ANN's are applied in modeling and control of highly nonlinear large-scale processes. One of the m...
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ISBN:
(纸本)0889864012
This paper deals with a generalized automatic method used for designing artificial neural network (ANN) structures. ANN's are applied in modeling and control of highly nonlinear large-scale processes. One of the most important problems is to design the optimal ANN for many real applications. In many applications, optimal ANN structures are designed by heuristic approaches or simply determined by experiments. In this paper, two techniques for automatic finding an optimal ANN structure are proposed. They can be applied in real-time applications as well as in fast nonlinear processes. One possible approach proposed in this paper consists in using the genetic algorithms (GA). It can be used to find an optimal or a minimal ANN structure. The first proposed method deals with designing a structure with one hidden layer. The optimal structure has been verified on a nonlinear model of a hydraulic system. The second algorithm allows to designs ANN with an unlimited number of hidden layers each of them containing of one neuron. This structure has been verified on a highly nonlinear model of a polymerization reactor. The obtained results have been compared with the results yielded by fully connected ANN.
This paper evaluates the possibility of applying a geno-fuzzy control strategy to a magnetorheological semi-active damper for seismic vibration control. The proposed control starategy is designed and then tested and v...
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Signal-based fault detection, as an essential technology in many engineering and industrial applications, has received extensive attention. Nevertheless, in a real-world application setting, collecting samples for som...
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The droop controller is widely used for the parallel operation of inverters. However, the conventional droop controller has a trade-off between the power sharing and the regulations of the output voltage amplitude and...
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Space weather forecasting is of global interest, and its importance is well established in research community and recognized by government, industries and stockholders. Over the past years, many types of predictive mo...
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New delay-efficient configurable multiplier based on Modified Booth's Algorithm (MBA) and Wallace Tree (WT) structure for multiplying two m-bit operands - where m ranges from 8-bit to 128-bit - is introduced. WT s...
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The design and performance analysis of networked controlsystems with random network delay in the forward channel is proposed, which are described in a state-space form. A new control scheme is used to overcome the ef...
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The design and performance analysis of networked controlsystems with random network delay in the forward channel is proposed, which are described in a state-space form. A new control scheme is used to overcome the effects of network transmission delay, which is termed networked predictive control （NPC）. Furthermore, three different ways to choose control input are discussed and the performances are analyzed, respectively. Both real-time simulations and practical experiments show the effectiveness of the control scheme.
Nowadays there exists a need of carrying out new features and improvements in the existing and future tokamak devices as ITER or DEMO. The present capabilities of the controlengineering and the development of fusion ...
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Currently there is no reliable mechanism available to allow continuous monitoring of all process conditions and leather characteristics inside the closed reactors during leather processing, so no real control. Conditi...
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Currently there is no reliable mechanism available to allow continuous monitoring of all process conditions and leather characteristics inside the closed reactors during leather processing, so no real control. Conditions inside the reactors can only be monitored by stopping the reactor to sample the solution and leather. The automation systems for leather industry rely on stale centralised architecture, a critical point of failure imposing operational bottleneck. To improve the efficiency of leather manufacturing process the paper proposes a multi-agent system (MAS) architecture that is fault tolerant, and that provides high flexibility and agility needed by the turbulent environment of leather industry.
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