Results 241 to 250 of about 1,307,908 (292)
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ISA Transactions, 2001
A mill is a mechanical device that grinds mined or processed material into small particles. The process is known to display significant deadtime, and, more notably, severe nonlinear behavior. Over the past 25 years attempts at continuous mill control have met varying degrees of failure, mainly due to model mismatch caused by changes in the mill process
G, Martin, S, McGarel
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A mill is a mechanical device that grinds mined or processed material into small particles. The process is known to display significant deadtime, and, more notably, severe nonlinear behavior. Over the past 25 years attempts at continuous mill control have met varying degrees of failure, mainly due to model mismatch caused by changes in the mill process
G, Martin, S, McGarel
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IEEE Transactions on Automatic Control, 2000
Repetitive controllers are generally applied to reject periodic disturbances and to track periodic reference signals with a known period. Their design is based on the internal model principle, proposed by Francis and Wonham (1975). This paper describes a new finite-dimensional SISO repetitive controller for two different classes of nonlinear plants ...
Jayati Ghosh, Brad Paden
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Repetitive controllers are generally applied to reject periodic disturbances and to track periodic reference signals with a known period. Their design is based on the internal model principle, proposed by Francis and Wonham (1975). This paper describes a new finite-dimensional SISO repetitive controller for two different classes of nonlinear plants ...
Jayati Ghosh, Brad Paden
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42nd IEEE International Conference on Decision and Control (IEEE Cat. No.03CH37475), 2004
This paper presents piecewise nonlinear control for piecewise Takagi-Sugeno fuzzy systems described by a local Takagi-Sugeno fuzzy model in each piecewise region. We provide a piecewise sector nonlinearity idea to construct a piecewise Takagi-Sugeno fuzzy model from given nonlinear dynamics.
Hiroshi Ohtake +2 more
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This paper presents piecewise nonlinear control for piecewise Takagi-Sugeno fuzzy systems described by a local Takagi-Sugeno fuzzy model in each piecewise region. We provide a piecewise sector nonlinearity idea to construct a piecewise Takagi-Sugeno fuzzy model from given nonlinear dynamics.
Hiroshi Ohtake +2 more
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Dynamics of Nonlinear Feedback Control
Neural Computation, 2007Feedback control in neural systems is ubiquitous. Here we study the mathematics of nonlinear feedback control. We compare models in which the input is multiplied by a dynamic gain (multiplicative control) with models in which the input is divided by a dynamic attenuation (divisive control). The gain signal (resp.
Herman P. Snippe, J. H. van Hateren
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Nonlinear controllers for nonlinear systems with input nonlinearities
Proceedings of the 36th IEEE Conference on Decision and Control, 1999The authors consider control systems of the type \[ \dot x= f(x,\sigma(u)),\quad x(0)= x_0,\quad t\geq 0, \] where \(\sigma\) denotes an input nonlinearity -- in many cases saturation -- and present a methodology for designing globally stabilizing nonlinear controllers.
Haddad, Wassim M. +2 more
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Information Sciences, 1992
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
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Issues on Nonlinear Digital Control
European Journal of Control, 2001zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Salvatore Monaco +1 more
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Set Computation for Nonlinear Control
Reliable Computing, 2004The paper discusses, for a nonlinear discrete-time system, the problem to determine a control sequence which has to satisfy given set-membership specifications for the state and output vectors, and which (sometimes) has to be robust under some type of perturbations.
Jaulin, Luc, Ratschan, S., Hardouin, L.
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Control of Nonlinear Mechanical Systems
European Journal of Control, 2001zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Isabelle Fantoni, Rogelio Lozano
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Computational Nonlinear Control.
1992Abstract : The goals of this research project were the development of control and estimation algorithms for nonlinear systems which are computationally feasible with robust performance despite numerical and modeling errors. The approach was based on the recent generalization of linear worst case (H-infinity) controllers to nonlinear systems.
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