Fractional-Order Model Predictive Control: Development and Application

Dear Colleagues,

Biological, sociocognitive, and economic phenomena, as well as transport, information, and technological systems often require the description by means of linear or nonlinear, non-integer order differential equations. As a consequence, control systems should often also realize fractional-order control algorithms.

The aim of this Special Issue is to gather a collection of papers reflecting the possibility of employing the more and more popular theory of fractional-order differential (finite difference) calculus for modern predictive control, the practical effectiveness of which has been borne out by numerous industrial applications.

The idea of predictive control, which was put forward several dozen years ago and has been intensely developed since then, is considered to be, after many years of operating experience in industry, one of the most universal and effective control methods. Predictive control enables various signal constraints and various kinds of disturbances to be taken into account and may be employed to control processes with practically any number of inputs and outputs. However, in the case of processes with particularly complex properties, its effectiveness depends on the quality of the process model. Additionally, in the case of nonlinear processes, direct nonlinear control algorithms are often too complex in order for computations to be performed online. Therefore, there is a need to develop new predictive control algorithms to cope effectively with the abovementioned difficult cases and to provide new opportunities for control performance and robustness. The introduction of fractional-order differential calculus at the stage of synthesizing the control algorithm offers an additional degree of freedom in tuning a control loop; on the other hand, it enables the specific properties of the controlled process to be better taken into account.

Articles submitted to this Special Issue may focus on research relating to fractional-order model predictive control and its applications to real dynamic systems modeled using integer- and/or fractional-order differential equations. Other important subjects, such as example numerical and computational aspects of proposed control algorithms, may also be explored.

Prof. Dr. Stefan Domek
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 250 words) can be sent to the Editorial Office for assessment.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Fractal and Fractional is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2700 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.