This study is an effort to give a practical solution in the problem of optimizing the structure of the hierarchical mixture of experts model, which is a natural extension of the associative Gaussian mixture of experts...
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This study is an effort to give a practical solution in the problem of optimizing the structure of the hierarchical mixture of experts model, which is a natural extension of the associative Gaussian mixture of experts system. We present two novel methods for optimizing such structures using genetic algorithms. Special concern is taken for reducing the computational time so as to efficiently allow the structure to "grow" while it evolves with the genetic algorithm. The main contribution of the paper lies on the efficient, topologically oriented, representations of such architectures so as to be optimized through involving genetic algorithms.
A unified and general framework is presented for H/sub /spl infin// control of mixed continuous-time and discrete-time time-varying (periodic) systems. Using the delta operator, a close relationship is shown between t...
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A unified and general framework is presented for H/sub /spl infin// control of mixed continuous-time and discrete-time time-varying (periodic) systems. Using the delta operator, a close relationship is shown between the continuous- and discrete-time solutions. No assumptions are made on certain system matrices being zero or normalized, which makes the approach general and easy to apply. A combined continuous/discrete-time lifting procedure is shown to be useful, especially for ill-conditioned systems. This procedure together with the delta formalism results in a numerically robust design method concerning both short and long sampling periods for systems with W-conditioned dynamics, including widely spread eigenvalues.
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.
According to the multi-model approach a nonlinear dynamical process is approximated in different working points by local valid linear models. The global valid model output is calculated as the weighted sum of the sub-...
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According to the multi-model approach a nonlinear dynamical process is approximated in different working points by local valid linear models. The global valid model output is calculated as the weighted sum of the sub-model outputs. The parameters of the Gaussian weighting function can be chosen by optimization. The computation time can be reduced if instead of the model outputs the parameters (for example static gain and time constant) of the local valid models are merged. The global valid nonlinear model can be used e.g., for model based predictive control. The new, multi-parameter method is illustrated by a heat exchanger example.
A systems re-engineering technique to integrated control and supervision for applications to industrial multi-zone furnaces has been elaborated by using known theories on generalized predictive control and nonlinear p...
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A systems re-engineering technique to integrated control and supervision for applications to industrial multi-zone furnaces has been elaborated by using known theories on generalized predictive control and nonlinear programming. This paper presents the derivation of optimizing equations and inequalities. The design is based on the use of general predictive control to provide optimized set-points under the presumption a well designed regulatory control was implemented at the executive level. Digital implementation of control functions are sought within standard computer processcontrol platform for practical engineering and maintenance reasons.
A procedure for H/sub /spl infin// optimization of low order controllers for discrete-time and sampled-data systems is presented in this paper. Generally, low order H/sub /spl infin// controllers may be achieved by so...
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A procedure for H/sub /spl infin// optimization of low order controllers for discrete-time and sampled-data systems is presented in this paper. Generally, low order H/sub /spl infin// controllers may be achieved by solving bilinear matrix inequalities (BMIs). In this paper an iterative alternation between two LMIs gives a suboptimal solution. To avoid local minima in this search the initial controller is obtained by a frequency weighted controller reduction scheme, where the closed loop properties of a full order controller is taken into account. A minimal number of parameters in the state space realization of the controller also reduces the complexity and improves numerical robustness. The complete presentation is based on delta operator models, which shows a close relationship between the continuous- and discrete-time solutions. The sensitivity of the ordinary discrete-time shift operator LMI formulation to small sampling periods is also analyzed.
This paper addresses the design of robust H 2 filters for a class of nonlinear systems subject to uncertain parameters belonging to a given polytope. The nonlinear system is represented by differential-algebraic equat...
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This paper addresses the design of robust H 2 filters for a class of nonlinear systems subject to uncertain parameters belonging to a given polytope. The nonlinear system is represented by differential-algebraic equations where the system matrices are allowed to be rational functions of the state and uncertain parameters. Linear matrix inequality conditions based on a parameter-dependent Lyapunov function are proposed to design a robust linear filter which ensures an optimized upper-bound on the worst-case asymptotic estimation error variance.
The paper deals with an application of neural networks with orthogonal activation functions (OAFNN) in the sensorless field oriented control structure with induction motor (lM). The OAFNN has been trained to estimate ...
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作者:
Brščić, DraženUniversity of Zagreb
Faculty of Electrical Engineering and Computing Department of Control and Computer Engineering in Automation Unska 3 ZagrebHR-10000 Croatia
This paper presents the current work on the development of a tool for remote control of mobile robots. The tool consists of a local controller on the robot side and a user interface for simulation and remote control t...
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The paper deals with the description of block-oriented nonlinear dynamic systems having multisegment piecewise-linear nonlinearities and with their identification using the Wiener model. A new form of multisegment non...
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