This paper addresses the issues related to the design of robust controller using genetic algorithms (GA) for lightweight, one-link flexible manipulators working under dynamic environments and other uncertain influence...
详细信息
This paper addresses the issues related to the design of robust controller using genetic algorithms (GA) for lightweight, one-link flexible manipulators working under dynamic environments and other uncertain influences. By selecting sensitivity weight functions properly using the GA method, a mixed sensitivity H infin controller is developed to ensure robustness of manipulator controlsystems for varying payloads and other modeling uncertainties. Numeric simulation has been conducted and the results have demonstrated the effectiveness of the proposed method
To found the suitable models to describe the behavior of biochemistry systems, the dynamic epsiv-SVM method was proposed on the basis of SVM. Each training sample uses different error. The existed methods for selectin...
详细信息
To found the suitable models to describe the behavior of biochemistry systems, the dynamic epsiv-SVM method was proposed on the basis of SVM. Each training sample uses different error. The existed methods for selecting the parameters of SVM not only consume time, but also are difficult to find the optimal parameters. The optimal parameters were automatically decided by using multi-object genetic algorithm (MOGA). A new modeling method that combined MOGA with the dynamic epsiv-SVM was presented. The model for penicillin titer pre-estimate was developed by it in Matlab 6.5 with data collected from real plant. The model possesses the strong capability of fitting and generalization. Experiments show that the dynamic epsiv-SVM is superior to the standard SVM modeling method. MOGA is very feasible and efficient too
A variety of problems in operations research, performance analysis, manufacturing, and communication networks, etc., can be modelled as discrete event systems with minimum and maximum constraints. When such systems re...
详细信息
A variety of problems in operations research, performance analysis, manufacturing, and communication networks, etc., can be modelled as discrete event systems with minimum and maximum constraints. When such systems require only maximum constraints （or dually, only minimum constraints）, they can be studied using linear methods based on max-plus algebra. systems with mixed constraints are called min-max systems in which rain, max and addition operations appear simultaneously. A significant amount of work on such systems can be seen in literature. In this paper we provide some new results with regard to the balance problem of min-max functions; these are the structure properties of min-max systems. We use these results in the structural stabilization. Our main results are two sufficient conditions for the balance and one sufficient condition for the structural stabilization. The block technique is used to analyse the structure of the systems. The proposed methods, based on directed graph and max-plus algebra are constructive in nature. We provide several examples to demonstrate how the methods work in practice.
This paper analyzes when a Hopf bifurcation occurs for a class of delay differential systems, and constructs the algorithms for determining the bifurcation's occurrence. By using some algebraic criteria, the "...
详细信息
This paper analyzes when a Hopf bifurcation occurs for a class of delay differential systems, and constructs the algorithms for determining the bifurcation's occurrence. By using some algebraic criteria, the "complete discrimination system for polynomials" and Hurwitz criterion, on-line determining bifurcation's occurrence can be realized. The methods unify and generalize the relevant results in the literature.
In this paper, design principles and application of a thin and flexible intravascular top hat monopole probe with increased signal-to-noise ratio (SNR) and improved longitudinal and radial coverage are described and c...
详细信息
On the basis of the standard SVM for regression, the dynamic Ε-SVM method was proposed to establish precise mathematical models to describe the behavior of biochemistry systems, namely each training sample used diffe...
详细信息
On the basis of the standard SVM for regression, the dynamic Ε-SVM method was proposed to establish precise mathematical models to describe the behavior of biochemistry systems, namely each training sample used different error. At the same time, an improved multi-objective Genetic Algorithm (MOGA) was used to automatically select the dynamic Ε-SVM parameters. A new modeling method that combined improved MOGA with dynamic Ε-SVM regression was presented. The model for titer pre-estimate was developed in Matlab6.5 with data collected from real plant. The model possessed the strong capability of fitting and generalization. It is shown that the method achieves significant improvement in the generalization performance in comparison with the modeling method based on MOGA and the standard SVM.
Preventative diagnosis and maintenance of transformers has become more popular in recent times in order to improve the reliability of electric power systems. A number of transformers have recently been tested using Re...
详细信息
Three typical path planning methods, i.e. artificial potential field, probabilistic path planning and biologically inspired neural network, were introduced. The analysis and comparisons were made in relating to genera...
详细信息
Three typical path planning methods, i.e. artificial potential field, probabilistic path planning and biologically inspired neural network, were introduced. The analysis and comparisons were made in relating to general aspects of the complexity, robustness and adaptability of the methods.
Molding and simulation of time series prediction based on dynamic neural network(NN) are studied. Prediction model for non-linear and time-varying system is proposed based on dynamic Jordan NN. Aiming at the intrinsic...
详细信息
Molding and simulation of time series prediction based on dynamic neural network(NN) are studied. Prediction model for non-linear and time-varying system is proposed based on dynamic Jordan NN. Aiming at the intrinsic defects of back-propagation (BP) algorithm that cannot update network weights incrementally, a hybrid algorithm combining the temporal difference (TD) method with BP algorithm to train Jordan NN is put forward. The proposed method is applied to predict the ash content of clean coal in jigging production real-time and multi-step. A practical example is also given and its application results indicate that the method has better performance than others and also offers a beneficial reference to the prediction of nonlinear time series.
暂无评论