Jenő Hetthéssy

A Self-tuning Extremal Controller for the Generalized Hammerstein Model

Abstract A self-tuning extremal controller is presented which provides to find the extremum and to maintain it with minimum variance using the generalized Hammerstein model as the approximate description of a nonlinear dynamic process. A simulation example is given to illustrate the work of the new regulator.

Self-Tuning Load-Frequency Control of the Hungarian Power System

Abstract A combined regulator based on a self-tuning predictor of the area requirement and the RAFT control strategy for the ACE is described for the load-frequency control of the Hungarian Power System. Real-time experiments with the implemented adaptive regulator are also shown.

A Microprocessor-Based Adaptive Composition Control System

Abstract A general multivariable model of the mill-silo system is given. A general multivariable adaptive control system is described. Using a special linearizing and decoupling possibility single variable adaptive control loops are then introduced. Finally the applied μP system and practical results are presented.

Adaptive Composition Control

Abstract The paper deals with the composition control of cement raw mill systems. It presents the control engineering background behind the design of the realized control strategy which is used in several cement factories. The control algorithm makes use of all a priori information, estimates the oxide concentration of the raw materials and guarantees a robust operation. The presented strategy has been applied in cement plants, however, due to its general architecture it is ready for implementation in any other technology where composition control is required.

Basic course in control theory

Course material of basic control theory has been overviewed and updated recently at the Faculty of Electrical Engineering and Informatics, BME. The paper describes shortly the contents and the teaching methods of the course. In the theoretical material the concept of the Youla parametrization has been introduced which gives a new insight into controller design. MATLAB exercises support understanding and interactively applying the theoretical knowledge. New lecture notes were written both for the theoretical material and for the MATLAB laboratory exercises. The course web-site provides the actual information and gives also additional learning materials.

Subspace identification methods: review and re-interpretation

The paper is devoted for a systematic discussion on the subspace based identification methods. The structure of the noise components acting additively at various system signals is considered as the guiding principle for the analysis of the estimation algorithms. It is shown that replacing the state space approach typically applied in this field by a discrete time transfer function system realization the highly involved machinery of the subspace algorithms can be handled in a clearly ordered framework exhibited by a set of over-determined equations to be solved.

Intellicon: An Industrial Multiloop Adaptive Regulator

Abstract The paper describes the design conception of an industrial multiloop adaptive regulator and the practical approach of the implementation of a highly reliable adaptive control strategy.

Practical Experiences on the Setup and Identification of a Distillation Pilot Plant

Abstract A distillation column separating ethanol-water mixture has been built at our Department. The pilot plant is equipped with analogue instrumentation, manipulating board and alarm devices. It is connected to a microcomputer and a supervisor computer. The temperature responses of the top-and the bottom products were identified to changes in the reflux rate, heating power and feed rate. All these models are highly nonlinear, i.e. their parameters depend on the working point and the direction of the excitation.

IDENTIFICATION OF NONLINEAR ERRORS-IN-VARIABLES MODELS

Abstract The paper is about a generalization of a classical eigenvalue-decomposition method originally developed for errors–in-variables linear system identification to handle an important class of nonlinear problems. A number of examples are presented to call the attention to the most critical part of the procedure turning the identification problem to a generalized eigenvalue-eigenvector calculation problem with symmetrical matrices. The elaborated method generates consistent parameter estimation. Simulation results demonstrate the effectiveness of the proposed algorithm.

Modelling, Identification, Design and Simulation of the Control of a Spray Drier

Abstract The paper presents the modelling, identification, design and control of a spray drier. The atomizer is used to produce the compact powder which is pressed in a form and burned out. The aim of the control is to keep the moisture of the product at a given value. A cascade control was developed, where the temperature of the outlet air was used as an internal variable. The simulation was performed by a microprocessor developing system.