As the biopharmaceutical industry evolves to include more diverse protein formats and processes, more robust control of Critical Quality Attributes (CQAs) is needed to maintain processing flexibility without compromising quality. Active control of CQAs has been demonstrated using model predictive control techniques, which allow development of processes which are robust against disturbances asso...

The performance of a Model Predictive Control (MPC) algorithm depends on the quality of the derived model. Using a divide-and-conquer strategy process operations were partitioned into several operating regions and within each region, a local linear model was developed to model the process. This set of locally linearized models was simply and effectively combined into a global description of a m...

This paper describes a predictive event-based control algorithm focused on practical issues. The Generalized Predictive Control scheme is used as predictive controller, and sensor and actuator deadbands are included in the design procedure to provide event-based capabilities. The first configuration adapts a control structure to deal with asynchronous measurements; the second approach is used f...

The control of multi-input multi-output (MIMO) systems is a common problem in practical control scenarios. However in the last two decades, of the advanced control schemes, only linear model predictive control (MPC) was widely used in industrial process control (Maciejowski, 2002). The fundamental common idea behind all MPC techniques is to rely on predictions of a plant model to compute the op...

This paper describes a new approach to intelligent model based predictive control scheme for deriving a complex system. In the control scheme presented, the main problem of the linear model based predictive control theory in dealing with severe nonlinear and time variant systems is thoroughly solved. In fact, this theory could appropriately be improved to a perfect approach for handling all com...

This article presents a comparison of commercial and model based predictive control strategies aimed at optimizing efficiency of classical heating systems used in greenhouse temperature control. Two kind of heating systems are considered: aerial pipes with hot water and air-fan heaters. By using simple linearized models of the system around the predefined setpoints and a generalized predictive ...

In this paper, a strategy for automatic tuning of predictive controller synthesis parameters based on multi-objective optimization is proposed. This strategy integrates the genetic algorithm to generate the synthesis parameters (the prediction horizon, the control horizon and the cost weighting factor) making a compromise between closed loop performances (the overshoot, the variance of the cont...