Adaptive extremum-seeking control of nonisothermal continuous stirred tank reactors

In this paper, we present an adaptive extremum-seeking control scheme for nonisothermal continuous stirred tank reactors. We assume limited knowledge of the reaction kinetics. An adaptive learning technique is introduced to construct an optimum-seeking algorithm that drives the system states to optimal equilibrium concentrations of the reaction mixture. Lyapunov's stability theorem is used in the design of the extremum-seeking controller structure and the development of the parameter-learning laws. Under mild assumptions, the resulting controller is an output-feedback controller. The performance of the technique is demonstrated with the van de Vusse reaction system.