Parametric and Nonparametric PI Controller Tuning Method for Integrating Processes Based on Magnitude Optimum

Abstract

Integrating systems are frequently encountered in the oil industry (oil–water–gas separators, distillation columns), power plants, paper-production plants, polymerisation processes, and in storage tanks. Due to the non-self-regulating character of the processes, any disturbance can cause a drift of the process output signal. Therefore, efficient closed-loop control of such processes is required. There are many PI and PID controller tuning methods for integrating processes. However, it is hard to find one requiring only a simple tuning procedure on the process, while the tuning method is based either on time-domain measurements or on a process transfer function of arbitrary order, which are the advantages of the magnitude optimum multiple integration (MOMI) tuning method. In this paper, we propose the extension of the MOMI tuning method to integrating processes. Besides the mentioned advantages, the extension provides efficient closed-loop control, while PI controller parameters calculation is still based on simple algebraic expressions, making it suitable for less-demanding hardware, like simpler programmable logic controllers (PLC). Additionally, the proposed method incorporates reference weighting factor b that allows users to emphasize either the disturbance-rejection or reference-following response. The proposed extension of the MOMI method (time-domain approach) was also tested on a charge-amplifier drift-compensation system, a laboratory hydraulic plant, on an industrial autoclave, and on a solid-oxide fuel-cell temperature control. All closed-loop responses were relatively stable and fast, all in accordance with the magnitude optimum criteria.

Parametric and Nonparametric PID Controller Tuning Method for Integrating Processes Based on Magnitude Optimum

“…As will be shown in Section 7, the method was also tested on a real process with present noise. Moreover, the proposed method for the PI controller [1] has also been tested on several processes with measurement noise. In all the mentioned tests, it was shown that the calculated areas and, therefore, the controller parameters, are not extensively sensitive on high-frequency process noise.…”

“…Weighting factor b influences the disturbance-rejection and tracking performance. When b approaches 1, the integral gain K I (21) approaches 0 [1]. For b = 1, we obtained the following PID controller:…”

“…This paper is an extension of a previous study [1] that proposed tuning of the proportional-integral (PI) controller for integrating processes. A proportional-integral-derivative (PID) controller, in single or cascade loops and with or without derivative/integral terms, is the most commonly used control algorithm in industry [2][3][4], although several more advanced control structures have been developed.…”

“…Numerous IP tuning methods have been proposed so far [9,34]. These techniques can be classified according to their IP model structure, i.e., tuning methods for ITD [20,, for IFOTD [8,32,34,, for higher-order IPs with time-delay [108][109][110][111][112][113][114], and nonparametric tuning methods for IPs [1,[115][116][117].…”

“…Since the resulting PD controller cannot reject input disturbances, the original MOMI tuning rule cannot be used for IPs. However, in Reference [1], Kos et al proposed an extension of the MOMI tuning method for IPs controlled by a 2-DOF PI controller.…”