Abstract

The RTD-A (robust, tracking, disturbance rejection and aggressiveness) controller is a novel control scheme that substitutes the classical proportional integral derivative (PID) controller. This novel controller’s performance depends on the four controller tuning parameters (θR, θT, θD and θA). The tuning of RTD-A controller is more transparent than classic PID controllers. The RTD-A tuning parameters values lies between ZERO and ONE. Availability of a tool to design optimal parameters for this controller and evaluating the performance on a given system is necessary for the researchers. In this paper, the new simulation tool is presented to deal with the RTD-A control scheme. There are four graphical user interface tools included in the proposed tool and working of each tool is explained in detail. To demonstrate the proposed tool, two examples, which involve a liquid level control application and an air pressure control application, are presented in this work. The performance of the RTD-A controller is compared with PID controller. RTD-A controllers are tuned using optimization algorithms and their performances are observed and analyzed in both cases under deterministic and uncertain conditions.

Highlights

  • The proportional integral and derivative (PID) controllers are mostly used to control the critical processes in all over the industries

  • The main contribution of this paper is to introduce a new graphical user interface (GUI) simulation tool for RTD-A controller based on MATLAB, which contains two tuning rules on a single platform in order to control the chosen process as well as analyze the performance of the same

  • Since RTD-A has an independent tuning parameter for robustness it can handle the systems with uncertain behavior

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Summary

Introduction

The proportional integral and derivative (PID) controllers are mostly used to control the critical processes in all over the industries. In 2005, Ogunnaike and Kapil Mukati had introduced a new control algorithm RTD-A, which is more efficient than PID for chemical and other industrial processes [11]. The main contribution of this paper is to introduce a new graphical user interface (GUI) simulation tool for RTD-A controller based on MATLAB, which contains two tuning rules on a single platform in order to control the chosen process as well as analyze the performance of the same. There are bio-inspired optimization algorithms that can be used to tune the classical and RTD-A controller parameters [21]. Bilal introduced an improved cuckoo search algorithm is used to self-tune PID for the hydraulic cylinder pressure control [23].

There adequate research loop block
State Variable Form
Polynomial Form
Tool Design
Flowchart
Galactic Swarm Optimization
Particle Swarm Optimization
Genetic Algorithm
Firefly Algorithm
Graphical
Evaluation
Example 1
Methods
10. Example
11. Example 1
1: Regulatory response with the controller
Example 2
12. Example
22. Example c0
24. Comparison
25. Example
Conclusions
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