This paper surveys various implementation of a memory efficient second order (Broyden, Fletcher, Goldfard and Shanno) BFGS training algorithms which includes novel optimal memory (OM) BFGS neural network training algo...
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This paper surveys various implementation of a memory efficient second order (Broyden, Fletcher, Goldfard and Shanno) BFGS training algorithms which includes novel optimal memory (OM) BFGS neural network training algorithm, proposed by the present authors, which optimises performance in relation to available memory. Simulation results using a control benchmark problems show that OM BFGS, which is mathematically equivalent to full memory (FM) BFGS training when there are no constraints on memory, have performance gain compared to other memory efficient BFGS training algorithms.
This work investigates novel sequential learning methods applied on a decomposed form of training algorithms using radial basis function (RBF) network. The dynamic expansion of RBF network by adding neurons to the hid...
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This work investigates novel sequential learning methods applied on a decomposed form of training algorithms using radial basis function (RBF) network. The dynamic expansion of RBF network by adding neurons to the hidden layer during the course of training facilitates the weight update to be decomposed on neuron by neuron basis. The fast or minimal update approach which can be adopted with ease on a decomposed algorithms are also presented in This work.
Traditionally, when approaching controller design with the Youla-Kucera parametrization of all stabilizing controllers, the denominator of the rational parameter is fixed to a given stable polynomial, and optimization...
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Traditionally, when approaching controller design with the Youla-Kucera parametrization of all stabilizing controllers, the denominator of the rational parameter is fixed to a given stable polynomial, and optimization is carried out over the numerator polynomial. In this work, we revisit this design technique, allowing to optimize simultaneously over the numerator and denominator polynomials. Stability of the denominator polynomial, as well as fixed-order controller design with H/sub /spl infin// performance are ensured via the notion of a central polynomial and LMI conditions for polynomial positivity.
Direct adaptive control algorithms using state variables in control structure are known for their good adaptation capability and tracking performances that result from the fact that they use plant state variables in c...
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Direct adaptive control algorithms using state variables in control structure are known for their good adaptation capability and tracking performances that result from the fact that they use plant state variables in control law as well as in adaptation law. The implementation of standard model reference adaptive control (MRAC) with state variable control structure requires some a priori knowledge about the plant to be controlled including the plant order. This information is crucial for the proper choice of reference model describing the desired closed loop dynamical behavior and consequently for the adaptive system performances. The aim of our paper is to propose the fuzzy adaptation law for MRAC with state variable structure of control law that is able to ensure the adaptation process convergence and tracking capability even in the presence of unmodelled dynamics.
Due to the complexity of neural networks the problem of large computation requirements on computational devices where the network is trained or evaluated and slow network evaluation/training response can appear. The p...
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Two novel linear matrix inequality (LMI)-based procedures to receive stabilizing robust output feedback gain are presented. one of them being modification of previous results of (Oliveira et al..1999). The proposed ro...
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New developments in computer networks and communications provide new possibilities also for control purposes. controlsystems for highly complex plants are themselves very complex and heterogeneous. A new software and...
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A new type of knowledge adaptive control based on the closed-loop response recognition is proposed. This approach tries to mimic the behaviour of an expert, who has a lot of experience with the particular controlled s...
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An analysis of the transportation systems used in the flexible manufacturing systems is introduced in the paper. Based on the analysis a class of the transportation systems is delimited, whose modeling and control is ...
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GO-CAD brings some novel functions and features to the intelligent building design and virtual reality simulation. This paper presents a novel methodology simulation during lighting simulation of a building to acquire...
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