State Space Modelling and Multivariable Stochastic Control of a Pilot Plant Packed-Bed Reactor

Abstract

<p> This study is concerned with the multivariable stochastic regulatory control of a pilot plant fixed bed reactor which is interfaced to a minicomputer. The reactor is non-adiabatic with a highly exothermic, gaseous catalytic reaction, involving several independent species. A low order state space model for the reactor is developed starting from the partial differential equations describing the system. A parameter estimation method is developed to fit the model to experimental data. Noise disturbances present in the system are identified using two methods, and two alternative dynamic-stochastic state space models are obtained. Multivariable stochastic feedback control algorithms are derived from these models and are implemented on the reactor in a series of DDC control studies. The control algorithms are compared with each other and with a single loop controller. The best of the multivariable control algorithms is used to regulate the exit concentrations of the various species from the reactor and the results are compared to data.</p>