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Genetic algorithms based adaptive active vibration control of a flexible structure

MatDarus I. Z., Tokhi M. O.

Systems Science

2003

Vol. 29, nr 3

65-79

This paper investigates the development of an active vibration control (AVC) mechanism for a flexible plate structure using a genetic modelling strategy where the utilisation of genetic algorithms (GAs) for dynamic modelling of the system is considered. The global search technique of GAs is used to obtain a dynamic model of a flexible plate structure based on one-step-ahead (OSA) prediction and verified within the AVC system. The GA based AVC algorithm thus developed is implemented within a flexible plate simulation environment and its performance in the reduction of deflection at the centre of the plate is assessed. The validation of the algorithm is presented in both the time and frequency domains. An assessment of the results thus obtained is given in comparison to the AVC system using conventional recursive least squares (RLS) method. Investigations reveal that the developed GA based AVC system performs better in the suppression of vibration of a flexible plate structure compared to an RLS based AVC system.

Expert schemes for the obtaining of discrete models for LTI systems using real sampling and parameter identification

De La Sen M., Garrido A.J., Barambones O., Maseda F.J.

Systems Science

2003

Vol. 29, nr 2

95-112

In this paper, we present an expert network scheme designed to obtain discrete transfer functions for LTI systems under real sampling of finite duration rather than an instantaneous ideal one. For this purpose, the expert network handles two different identification methods to derive parametric discrete models techniques of reduced mathematical complexity from measured input-output data series. One of the methods is based on a typically used least-squares minimization, while the other one is based on the Leverrier's algorithm; that is, using a data series of the impulse response of the system to identify a parametric discrete model. These techniques are of particular practical interest when the continuous-time system is unknown or when dealing with discrete-time systems whose analytical expression becomes very complex due, for instance, to the use of finite duration real sampling. The expert network improves the discretization process implementing a biestimation mechanism that switches to the model that provides a better performance at each estimation instant considered for different values of the hold order.

MPC: A paradigm shift for automatic control

Maciejowski J. M.

Systems Science

2000

Vol. 26, nr 4

49-59

Model Predictive Control (MPC) represents a major paradigm shift in the field of automatic control. This radically affects synthesis techniques (illustrated by control of an unstable system) and underlying concepts (illustrated by control of a multivariable system), as well as lifting the Control engineer's focus from prescriptions to specifications ("what" not "how", illustrated by emulation of a conventional autopilot). Part of the objective of this paper is to emphasise the significance of this paradigm shift. Another part is to consider the fact that this shift was missed for many years by the academic community, and what this tells us about teaching and research in the field.