L. Dorcak

On Fractional PID Controllers: A Frequency Domain Approach

Abstract A more general structure for the classical PID controller is proposed in this paper by using fractional integral and differential operators. A frequency domain approach is used to show the advantages of using these fractional PID controllers, which can be sumarized in the possibility of dealing with a more general class of control problems, in which the fractional nature of the controller can be imposed by the fractional nature of the system to be controlled, or by the special nature of the required time or frequency responses. Some illustrative examples and comments on controller tuning and realizations are given.

On fractional derivatives, fractional-order dynamic systems and PI/sup /spl lambda//D/sup /spl mu//-controllers

This paper deals with some methods used in the fractional calculus (theory of integration and differentiation of an arbitrary order) and applications of the fractional calculus to modelling and control of dynamical systems.

Sintering Process Control

Abstract Sinter is basic metallic charging material for most blast furnaces. Sintering process reengineering can significantly influence sinter mechanical and metallurgical properties. This paper presents improvements of the sintering process and process optimal control.

Modeling and Control of the Sintering Process

Abstract This paper deals with the application of a mathematical model for analysis, optimization and control of the sintering process. The model includes processes in the ignition furnace (fuel combustion, heat transfer) and in the sinter bed (heat transfer, coke combustion, oxidation-reduction reactions of iron oxides, dissociation of carbonates, vaporization). The simulations results were used for instructive representation of system behaviour, its interpretation, optimization and control system design.

Posicast control of a class of fractional-order processes

AbstractThe number of studies on the control of fractional-order processes—processes having dynamics described by differential equations of arbitrary order—has been increasing in the past two decades and it is now ubiquitous. Various methods have emerged and have been proven to effectively control such processes—usually resulting in fractional-order controllers similar to their conventional integer-order counterparts, which include, but are not limited to fractional PID and fractional lead-lag controllers. However, such methods require a lot of computational effort and fractional-order controllers could be challenging when it comes to their synthesis and implementation. In this paper, we propose a simple yet effective delay-based controller with the use of the Posicast control methodology in controlling the overshoot of a fractional-order process of the class

On Fractional Derivatives, Fractional-Order Dynamic Systems and PIW-controllers

\mathcal{P}:\left\{ {P\left( s \right) = {1 \mathord{\left/ {\vphantom {1 {\left( {as^\alpha + b} \right)}}} \right. \kern-\nulldelimiterspace} {\left( {as^\alpha + b} \right)}}} \right\}

Numerical Models for the Simulation of the Fractional-Order Control Systems

having orders 1 < α < 2. Such controllers have proven to be easy to implement because they only require delays and summers. In this paper, the Posicast control methodology introduced in the past few years is modified to minimize the overshoot of the processes step response to a level that is acceptable in control engineering and automation practices. Furthermore, proof of the existence of overshoot for such class of processes, as well as the determination of the peak-time of the open-loop response of a fractional-order process of the class P is presented. Validation through numerical simulations for a class of fractional-order processes are presented in this paper.

Realization of fractional order controllers

Abstract Developed control strategy for blast furnace control is based on black box principles. The control system has two levels. At the basic level, classical control approaches are used. The process level is a combination of model based and AI approaches. Developed models are used in real time for furnace state estimation and prediction as well as for decision support. The efficiency of the control systemes based on local dynamic optimisation. The control system was applied on blast furnace No.3 at VSŽ Kosice, Slovakia.