Hierarchical control and optimisation of the Tennessee Eastman process

Based on integrated system optimisation and parameter estimation a method is described for on-line steady state optimisation which compensates for model-plant mismatch and solves a non-linear optimisation problem by iterating on a linear - quadratic representation. The method requires real process derivatives which are estimated using a dynamic identification technique. The utility of the method is demonstrated using a simulation of the Tennessee Eastman benchmark chemical process.

Remote control systems laboratory

Control systems theory can be a discipline difficult to learn without some laboratory help. With the help of focused laboratories this discipline turns to be very interesting to the students involved. The main problem is that laboratories aren't always available to students, and sometimes, when they are available, aren't big enough to a growing student population. Thus, with computer networks growing so fast, why don't create remote control labs that can be used by a large number of students? Why don't create remote control labs using Internetⓒ Copyright ?2001 IFAC Keywords: Remote Control, Computer Networks, Database, Educational Aids, Laboratory Education, Communication Control Applications.

Optimal control of nonlinear differential algebraic equation systems

A novel iterative procedure is described for solving nonlinear optimal control problems subject to differential algebraic equations. The procedure iterates on an integrated modified linear quadratic model based problem with parameter updating in such a manner that the correct solution of the original non-linear problem is achieved. The resulting algorithm has a particular advantage in that the solution is achieved without the need to solve the differential algebraic equations . Convergence aspects are discussed and a simulation example is described which illustrates the performance of the technique. 1. Introduction When modelling industrial processes often the resulting equations consist of coupled differential and algebraic equations (DAEs). In many situations these equations are nonlinear and cannot readily be directly reduced to ordinary differential equations.

Efficiency and purity control in the preparation of pure and/or aluminum-doped barium ferrites by hydrothermal methods using ferrous ions as reactants

The synthesis of hexagonal barium ferrite (BaFe12O19) was studied under hydrothermal conditions by a method in which a significant amount of ferrous chloride was introduced along side ferric chloride among the starting materials. Though all of the Fe2+ ions in the starting material were converted to Fe3+ ions in the final product, Fe2+ was confirmed to participate differently from the Fe3+ used in the conventional method in the mechanism of forming barium ferrite. Indeed the efficiency of the synthesis and the quality of the product and the lack of impurities such as Fe2O3 and BaFe2O4 were improved when Fe2+ was included. However, the amount of ferrous ions that could be included to obtain the desired product was limited with an optimum ratio of 2:8 for FeCl2/FeCl3 when only 2h of reaction time were needed. It was also found that the role of trivalent Fe3+ could be successfully replaced by Al3+. Up to 50% of their on could be replaced by Al3+ in the reactants to produce Al- doped products. It was also found that the ratio of Fe2+/M3+ could be increased in the presence of Al3+ to produce high quality barium ferrite.

Computer intensive methods in control and signal processing: the curse of dimensionality

This volume is based upon the 2nd IEEE European Workshop on Computer-Intensive Methods in Control and Signal Processing, held in Prague, August 1996.

Advanced methods in adaptive control for industrial applications

This volume is based on a seminar concerned with advanced methods in adaptive control for industrial applications which was held in Prague in May 1990 and which brought together experts in the UK and Czechoslovakia in order to suggest solutions to specific current and anticipated problems faced by industry.