Handling Packet Dropouts and Random Delays for Unstable Delayed Processes in NCS by Optimal Tuning of PI{\lambda}D{\mu} Controllers with Evolutionary Algorithms

TL;DR

This paper proposes an optimal tuning method for fractional order PI{ extlambda}D{ extmu} controllers using evolutionary algorithms to improve control in networked systems with delays and packet dropouts, demonstrating their superiority over traditional PID controllers.

Contribution

It introduces a time domain optimal tuning approach for fractional order controllers in NCS, comparing various evolutionary algorithms and validating the method on unstable, delay-affected plants.

Findings

FOPID controllers outperform PID in NCS scenarios.

The tuning method is plant-independent and applicable to various systems.

Evolutionary algorithms effectively optimize controller parameters.

Abstract

The issues of stochastically varying network delays and packet dropouts in Networked Control System (NCS) applications have been simultaneously addressed by time domain optimal tuning of fractional order (FO) PID controllers. Different variants of evolutionary algorithms are used for the tuning process and their performances are compared. Also the effectiveness of the fractional order PI{\lambda}D{\mu} controllers over their integer order counterparts is looked into. Two standard test bench plants with time delay and unstable poles which are encountered in process control applications are tuned with the proposed method to establish the validity of the tuning methodology. The proposed tuning methodology is independent of the specific choice of plant and is also applicable for less complicated systems. Thus it is useful in a wide variety of scenarios. The paper also shows the superiority of FOPID controllers over their conventional PID counterparts for NCS applications.