Search

In this contribution, a class of observer-based optimal feedback control is designed. The proposed feedback control is based on the Euler–Lagrange theoretical framework, and it is motivated by the productivity intensification from the chemical reactors, which is optimally increased. A Lagrangian is computed by employing the corresponding mass balance equation of a specifically selected biochemical compound. The resulting optimal controller is coupled with a novel uncertainty estimator with bounded feedback to derive an accurate estimation of the unknown terms and functions, mostly related to the reaction rate. Via Lyapunov analysis, it was shown that the proposed observer is asymptotically stable. The estimation of the unknown terms and functions is used by the proposed controller. The proposed methodology is applied to a generic model of an enzymatic biochemical continuous reactor with complex oscillatory dynamic behavior described by mass balance equations, so, in general, the proposed controller may be applied to any continuous stirred tank bioreactor; that is, the controller is independent of the specific kinetic functions. Numerical simulations show a satisfactory performance of the proposed control strategy. [ABSTRACT FROM AUTHOR]

This work deals with the control and synchronization of chaotic systems. In the first part of the work, a general discrete-time strategy is developed to control a class of second-order uncertain nonlinear systems. The proposed strategy is based on an iterative procedure, borrowed from contraction map methodologies, and provides estimates of unmeasured states and modeling errors. Nonidentical chaotic systems can be synchronized by means of the proposed strategy. By assuming that the exact model of the oscillators is not known and that position is the only state available for measurements, the robust synchronization scheme comprises a recursive feedback-control law. Computer simulations are provided to illustrate the operation of the designed synchronization scheme. Index Terms - Chaos, control systems, synchronization.

This paper deals with a feedback control strategy for chaos suppression. The proposed strategy is an input-output control scheme which comprises an uncertainty estimator and an asymptotic linearizing feedback. The developed control scheme allows chaos suppression in spite of modeling errors and parametric variations. Index Terms - Chaos, Chua's circuit, synchronization, uncertain systems.