Most batch processes generally exhibit the characteristics of nonlinear variation. In this paper, a nonlinear monitoring technique is proposed using a multiway kernel independent component analysis based on feature samples (FS-MKICA). This approach first unfolds the three-way dataset of a batch process into the two-way one and then chooses representative feature samples from the large two-way i...

In the recent years, batch process optimization has made significant advances. The efforts that went into the development of ISA-S88/IEC 61512 batch control standard has helped us in this direction. However, in today’s highly competitive environment, optimization of individual manufacturing plants is not enough. In order to maximize the return on investments, control engineers must turn their a...

I n the past half century, developments in control theory have been successfully applied to the lower level control of industrial processes [1]-[5]. In contrast with conventional machine control, however, industrial process control requirements concern product performance instead of the accuracy of the lower level control loop. The process performance is an overall index, including technical an...

The aim of this paper is to present how population based stochastic optimization algorithms can be used for batch process development. The theory of evolutionary and swarm optimization are overviewed and compared. A detailed application example is given to demonstrate how these tools can be applied to solve process optimization problems. The performances of Evolutionary Strategy, Particle Swarm...