A combined multiple model adaptive control (CMMAC) scheme, which is a proper combination of the estimator-based MMAC scheme and the unfalsified MMAC scheme, has been proposed with the aim of taking advantage of the strength of each scheme while avoiding their weaknesses. The major novelty of the CMMAC scheme lies in the fact that it monitors not only the adequacy of candidate models in terms of their estimation performances but also the performance of the active candidate controller. As an application of the CMMAC scheme and one example of such new multiple model adaptive controllers, a CMMAC based controller has been designed for a class of nonlinear systems with nonlinear parameterization. Under some sufficient conditions, a strong finite...
Several multiple model adaptive control architectures have been proposed in the literature. Despite ...
Abstract: Control based on multiple models (MM) is an effective strategy to cope with structural and...
This research effort addresses the important issue of developing an adaptive strategy for Model Pred...
A novel dwell-time-switching based multiple model adaptive control (MMAC) scheme is proposed for the...
A dwell-time-switching based MMAC scheme is proposed for the adaptive output feedback control proble...
In this paper, an adaptive multiple-model controller is developed for nonlinear systems in parametri...
Multiple model adaptive control has been investigated extensively during the last ten years in which...
Multiple model adaptive control schemes offer the potential of improved performance over conventiona...
The purpose of this paper is to marry the two concepts of multiple model adaptive control and safe a...
The purpose of this paper is to marry the two concepts of multiple model adaptive control and safe a...
This paper details a multiple model adaptive control strategy for model predictive control (MPC). To...
UnrestrictedDespite the remarkable theoretical accomplishments and successful applications of adapti...
International audienceThis paper aims to present a fault-tolerant control architecture based on the ...
Several multiple model adaptive control architectures have been proposed in the literature. Despite ...
Back propagation (BP) neural network is used to approximate the dynamic character of nonlinear discr...
Several multiple model adaptive control architectures have been proposed in the literature. Despite ...
Abstract: Control based on multiple models (MM) is an effective strategy to cope with structural and...
This research effort addresses the important issue of developing an adaptive strategy for Model Pred...
A novel dwell-time-switching based multiple model adaptive control (MMAC) scheme is proposed for the...
A dwell-time-switching based MMAC scheme is proposed for the adaptive output feedback control proble...
In this paper, an adaptive multiple-model controller is developed for nonlinear systems in parametri...
Multiple model adaptive control has been investigated extensively during the last ten years in which...
Multiple model adaptive control schemes offer the potential of improved performance over conventiona...
The purpose of this paper is to marry the two concepts of multiple model adaptive control and safe a...
The purpose of this paper is to marry the two concepts of multiple model adaptive control and safe a...
This paper details a multiple model adaptive control strategy for model predictive control (MPC). To...
UnrestrictedDespite the remarkable theoretical accomplishments and successful applications of adapti...
International audienceThis paper aims to present a fault-tolerant control architecture based on the ...
Several multiple model adaptive control architectures have been proposed in the literature. Despite ...
Back propagation (BP) neural network is used to approximate the dynamic character of nonlinear discr...
Several multiple model adaptive control architectures have been proposed in the literature. Despite ...
Abstract: Control based on multiple models (MM) is an effective strategy to cope with structural and...
This research effort addresses the important issue of developing an adaptive strategy for Model Pred...