Wyniki wyszukiwania - BazTech

Ograniczanie wyników

3 International Journal of Applied Mathematics and Computer Science

Znaleziono wyników: 3

Liczba wyników na stronie

Wyniki wyszukiwania

Wyszukiwano:
w słowach kluczowych: model wielokrotny

Sortuj według:

Ogranicz wyniki do:

Nonlinear system identification using heterogeneous multiple models

Orjuela R., Marx B., Ragot J., Maquin D.

International Journal of Applied Mathematics and Computer Science

2013

Vol. 23, no. 1

103--115

Multiple models are recognised by their abilities to accurately describe nonlinear dynamic behaviours of a wide variety of nonlinear systems with a tractable model in control engineering problems. Multiple models are built by the interpolation of a set of submodels according to a particular aggregation mechanism, with the heterogeneous multiple model being of particular interest. This multiple model is characterized by the use of heterogeneous submodels in the sense that their state spaces are not the same and consequently they can be of various dimensions. Thanks to this feature, the complexity of the submodels can be well adapted to that of the nonlinear system introducing flexibility and generality in the modelling stage. This paper deals with off-line identification of nonlinear systems based on heterogeneous multiple models. Three optimisation criteria (global, local and combined) are investigated to obtain the submodel parameters according to the expected modelling performances. Particular attention is paid to the potential problems encountered in the identification procedure with a special focus on an undesirable phenomenon called the no output tracking effect. The origin of this difficulty is explained and an effective solution is suggested to overcome this problem in the identification task. The abilities of the model are finally illustrated via relevant identification examples showing the effectiveness of the proposed methods.

Fault tolerance in networked control systems under intermittent observations

Georges J. P., Theilliol D., Cocquempot V., Ponsart J. C., Aubrun C.

International Journal of Applied Mathematics and Computer Science

2011

Vol. 21, no 4

639-648

This paper presents an approach to fault tolerant control based on the sensor masking principle in the case of wireless networked control systems. With wireless transmission, packet losses act as sensor faults. In the presence of such faults, the faulty measurements corrupt directly the behaviour of closed-loop systems. Since the controller aims at cancelling the error between the measurement and its reference input, the real outputs will, in such a networked control system, deviate from the desired value and may drive the system to its physical limitations or even to instability. The proposed method facilitates fault compensation based on an interacting multiple model approach developed in the framework of channel errors or network congestion equivalent to multiple sensors failures. The interacting multiple model method involved in a networked control system provides simultaneously detection and isolation of on-line packet losses, and also performs a suitable state estimation. Based on particular knowledge of packet losses, sensor fault-tolerant controls are obtained by computing a new control law using fault-free estimation of the faulty element to avoid intermittent observations that might develop into failures and to minimize the effects on system performance and safety.

Motor Control: Neural Models and Systems Theory

Doya K., Kimura H., Miyamura A.

International Journal of Applied Mathematics and Computer Science

2001

Vol. 11, no 1

77-104

In this paper, we introduce several system theoretic problems brought forward by recent studies on neural models of motor control. We focus our attention on three topics: (i) the cerebellum and adaptive control, (ii) reinforcement learning and the basal ganglia, and (iii) modular control with multiple models. We discuss these subjects from both neuroscience and systems theory viewpoints with the aim of promoting interplay between the two research communities.