USP Electronic Research Repository

Fractional - order tilt integral derivative controller design using IMC scheme for unstable time - delay processes

Ranjan, Anjana and Mehta, Utkal V. (2023) Fractional - order tilt integral derivative controller design using IMC scheme for unstable time - delay processes. Journal of Control, Automation and Electrical Systems, NA . NA. ISSN 2195-3880

[thumbnail of FractTID IMCSP Unstable JCAES2023.pdf] PDF - Published Version
Restricted to Repository staff only

Download (3MB) | Request a copy

Abstract

The paper proposes a modified IMC-based Smith predictor (SP) control method for unstable time-delay processes. A novel design method to tune the parameters of a fractional-order tilt integral derivative controller has been developed using fractional-order IMC filter and process model parameters. The tuning parameters of the fractional-order filter are calculated from the new robustness index and desired performance constraint. The expected performance constraint satisfies good setpoint tracking and optimal control signal. The significant feature of the presented method is that the fractional IMC-SP structure provides a better outcome without adding much computational complexity. For a given robustness index, the optimal controller, which minimizes the performance constraint, the combination of control effort and integral time squared error, helps calculate the two tuning parameters. The benefit does verify under parameters’ uncertainties, external load disturbances and noise. The comparative study with various numerical examples from recently reported methods shows better overall servo and regulatory performances.

Item Type: Journal Article
Subjects: T Technology > TK Electrical engineering. Electronics Nuclear engineering > Robotics and Automation
Divisions: School of Information Technology, Engineering, Mathematics and Physics (STEMP)
Depositing User: Utkal Mehta
Date Deposited: 25 Jul 2023 03:19
Last Modified: 25 Jul 2023 03:19
URI: https://repository.usp.ac.fj/id/eprint/14089

Actions (login required)

View Item View Item