Predictive control of systems with fast dynamics using computational reduction based on feedback control information

Predictive control is a method, which is suitable for control of linear discrete dynamical systems. However, control of systems with fast dynamics could be problematic using predictive control. The calculation of a predictivecontrol algorithm can exceed the sampling period. This situation occurs in case with higher prediction horizons and many constraints on variables in the predictive control. In this contribution, an improving of the classical approach is presented. The reduction of the computational time is performed using an analysis of steady states in the control. The presented approach is based on utilization of information from the feedback control. Then this information is applied in the control algorithm. Finally, the classical method is compared to the presented modification using the time analyses. © Springer International Publishing Switzerland 2015

Multivariable Control and Online State Estimation of an FCC Unit

The purpose of this paper is to realize multivariable control , tuning and online state estimation of some parameters of the FCC unit . We implemented two control structures with the manipulated variables being the air inlet flow rate in the regenerator, the regenerated catalyst flow rate and the feed flow rate and, the controlled variable being the temperatures in the riser and in the densed bed of the regenerator. A novel four transfer function is built and used for controllability studies. Hard constraints are imposed with respect to the manipulated variables. Simulation results show that the configuration made of two inputs and two outputs is more easy to tune for control purposes. Althought there are important dynamic interactions between the components of the FCC and important nonlinearities, linear model predictive control is able to maintain a smooth multivariable control of the plant, while taking into account the different constraints. Tuning strategy is implemented to improve the tracking of the set point. Online state estimation is carried out with the use of the extended Kalman filter. The estimation gives results that can be used for monitoring purposes even in the presence of model mismatch

Dispersion in a multitube microreactor: Experimental and modeling study

The hydrodynamics were examd. of a multichannel (340 channels) tubular microreactor by exptl. detn. of the residence time distribution (RTD) using Ar or He in N2 and by theor. modeling. The dispersion was caused primarily by the laminar velocity profile and mol. diffusion, as well as by the velocity difference between channels. [on SciFinder (R)