Process control: An overview and personal perspective

This paper presents an overview and personnal perspective on recent developments and current practice in computer process model. The basic concepts behind conventional process control are reviewed to provide a starting point for the non-control specialist and process engineer. The ensuing sections on Internal Model Control (IMC), Model Predictive Control (MPC) and adaptive control illustrate the evolution of control technology from the traditional multiloop strategies to the modern, multivariable, model-based, computer control systems now being used in industry. The paper does not provide a complete, critical review of process control. However, the discussion and the recommended references should provide a good starting point for anyone wanting to become familiar with current practice and some of the new directions of process control.     

Multivariable controller design in an adaptive control scheme

A multivariable control system design approach in the frequency domain is presented. The issue of control system redesign in an adaptive control scheme is discussed. Expert system techniques have been used for the automated design of controllers for multivariable systems. Design knowledge has been represented using rules, facts and objects. The design process consists of a sequence of operations obtained by heuristics and experience in the the design techniques. An automated design session of a multivariable plant using the expert system demonstrates that the expert system appears to work well in its prototype implementation.     

Pole shifting for matrices over real algebras

Pole shifting of multivariable control system over finite dimensional real algebras is studied. The main results are expressed in terms of the minimal polynomial of A + BF, where F is a feedback.     

Accidents,often the result of an ‘uncontrolled business process’—a study in the (Dutch) chemical industry

Often companies in the (petro‐) chemical industry claim that all possible countermeasures against potential accidents have been taken and therefore accidents are unforeseeable. In this paper we question this statement by analysing the pre‐warning signals (precursors) preceding a number of industrial accidents. 17 accidents that occurred in the (petro‐) chemical industry have been investigated by exploring FACTS, an accident database containing information about industrial accidents worldwide. This paper will demonstrate that the existence of precursor information could have been used to foresee and even prevent these accidents if a proper control action had been initiated. The accidents are analysed further, according to a control model, which was adapted from that of C. Argyris. It demonstrates the ineffectiveness of several elements of business process control loops and that the so‐called ‘double‐loop learning’ cycle is more important than the ‘single‐loop learning’ cycle if one considers safety improvement. Copyright © 2003 John Wiley & Sons, Ltd.     

ON THE ROBUST GLOBAL STABILIZATION OF nth-ORDER REACTIONS

In this paper, we employ a nonlinear adaptive mechanism to globally stabilize n^th-order reactions.     

A new voltage control equipment using fuzzy inference

Power system control equipment needs higher sensitivity and operational reliability. Advanced voltage control equipment is needed for reducing the frequency of tap changes and improving the characteristics (the relationship between the actual voltage and reference voltage) of the voltage to meet today's power system requirements. However, these objectives are in a trade-off relationship. Studies of voltage control derived from a knowledge base suitable for electric power systems can satisfy these objectives using fuzzy inference. Compared with corresponding conventional equipment, the new equipment improved the deviation of 30 min average voltage of 30 percent. This paper describes the design concept of new voltage control equipment using fuzzy inference. In addition, field test results are described along with rules of fuzzy inference, membership functions, and the deviation of 30 min average voltage through detailed simulation.