In this paper, we generalize retrospective cost adaptive NARMAX control (RCANC) to a command-following problem for uncertain Hammerstein systems. In particular, RCANC with ersatz nonlinearities is applied to linear systems cascaded with input nonlinearities. We assume that one Markov parameter of the linear plant is known. RCANC also uses knowledge of the monotonicity properties of the input no...

the control of fluidized-bed operations processes is still one of the major areas of research due to the complexity of the process and the inherent nonlinearity and varying dynamics involved in its operation. there are varieties of problems in chemical engineering that can be formulated as nonlinear programming (nlps). the quality of the developed solution significantly affects the performance ...

This paper presents an application of the feedback error learning technique for online control of an inverted pendulum which has uncertain friction nonlinearity. In order to build up online adaptive learning control, i) the preliminary offline training and the scaling factor for the neural network to escape from the local minimum, and ii) twostage learning scheme are introduced. After some lear...

Piezoelectric materials show nonlinear hysteresis behaviour when they are under high electrical field and mechanical load. Fundamental study of PEA depicts that the Hysteresis effect deteriorate the tracking performance of The PEA. This paper proposes a nonlinear model which quantifies the Hysteresis nonlinearity generated in Piezoactuators in response to applied driving voltages. A novel perfe...

A framework for the assessment of nonlinearity in controlled processes is developed. Assuming that the process can be represented by a twice differentiable process map, the extent of nonlinearity is measured by evaluating the induced local curvature of the process response. The magnitude of this curvature is assessed with respect to an appropriately chosen scaling region. This approach provides...

Xavier BOMBOIS est directeur de recherche au CNRS. Il possède une forte expertise en identification des systèmes, commande robuste et analyse du signal. Sa thématique de recherche consiste à optimiser l’interaction entre identification et commande (robuste). Il a été nommé au CNRS en 2015 pour étendre celle-ci aux systèmes non-linéaires. Voir aussi : http://www.amperelyon.fr/spip.php?article815 .

In this paper, with the weak cross-Kerr nonlinearity, we first present a special experimental scheme called controlled-path gate with which the realization of all possible bipartite positive-operator-value measurements of two-photon polarization states may be nearly deterministic. Following the same technique, the realization of quantum control gates, including the controlled-NOT gate, Fredkin ...

In this paper, a class of uncertain chaotic systems preceded by unknown backlash nonlinearity is investigated. Combining backstepping technique with fuzzy neural network identifying, an adaptive backstepping fuzzy neural controller (ABFNC) for uncertain chaotic systems with unknown backlash is proposed. The proposed ABFNC system is comprised of a fuzzy neural network identifier (FNNI) and a rob...

This paper studies the output tracking control of a class of sandwich-like systems with state-dependent deadzone nonlinearity between two cascaded subsystems (e.g., the gear transmission systems). An exact differentiator-based backstepping control for such a sandwich-like nonlinear system is proposed. The proposed controller utilizes the high-order sliding mode robust exact differentiator to co...

Linear control may be favorable over nonlinear control because linear design techniques greatly facilitate the controller design process and because linear controllers impose lower requirements on the implementation and operation as compared to nonlinear controllers. It is therefore a tempting idea to use linear models and linear controller design methods also for nonlinear systems. It is for i...