In this article, two methods of designing a centralized control system for multi-input, multi-output (MIMO) processes are presented. Centralized proportional-integral (PI) controllers are designed based on a direct synthesis method. The inverse of the process transfer function matrix in the direct synthesis method is approximated based on the relative gain array concept. The method is further improved by using a relative normalized gain array, and an equivalent transfer function for each element in the process transfer function matrix is derived for the closed-loop control system. The transpose of the effective transfer function is used to approximate the inverse of the process transfer function matrix. The simulation studies demonstrate the effectiveness of this method. The proposed centralized controllers reduce the interactions better than recently reported decentralized controllers do. A centralized controller designed based on a relative normalized gain array (RNGA) gives a better performance than a centralized controller designed based on a relative gain array (RGA). © 2012 ISA. Published by Elsevier Ltd. All rights reserved.

Vadarevu S.Ramachandra Rao

Manickam Chidambaram

Closed loop control systems

Controllers

Decentralized control

Integrated control

Inverse problems

Multivariable control systems

Multivariable Systems

Transfer functions

Transfer matrix method

Two term control systems

CENTRALIZED CONTROLLERS

Direct synthesis

MULTIVARIABLE PROCESS

RARATA

RNGA

Process control

IIT Madras is a public technical and research university located in Chennai, Tamil Nadu. Founded in 1959, it is recognised as an Institute of National Importance.

IIT Madras has been ranked as the top engineering institute in India for four years in a row by the National Institutional Ranking Framework of the MHRD

It currently offers undergraduate, postgraduate and research degrees across 16 disciplines in Engineering, Sciences, Humanities and Management. About 596 faculty belonging to science and engineering departments and centres of the Institute are engaged in teaching, research and industrial consultancy.

IIT Madras

ISA Transactions

This work presents a novel method for assessing and quantifying the level of interactions in multivariable control systems in a hierarchical manner. The proposed metrics are based on the total directed (causal) power transfer between a pair of variables, constructed from a jointly linear stationary representation of the process. Three prime features of these metrics, specifically, (i) the ease of interpretation and versatility in accommodating different controller structures and operating conditions, (ii) the ability to use both first-principles linearized and data-driven (empirical) models, and (iii) the means for quantifying and evaluating the suitability of a decentralized versus a centralized control scheme, make them highly practical and valuable in the design and assessment of multivariable control schemes. An important outcome of this work is also an operator-friendly visual tool for inspection of interactions in various loops that can be generated for different tuning methods and controller configurations. Simulation studies of four different benchmark processes are presented to demonstrate the efficacy of the proposed method. © 2017 American Chemical Society.

Industrial and Engineering Chemistry Research

Metrics for Interaction Assessment in Multivariable Control Systems Using Directional Analysis

FOPTD model parameters of a centralised (PI) controlled multivariable system are identified by a closed-loop optimisation method. The model parameters are obtained by a non-linear least square minimisation method. An easy procedure is given for the guess values of the parameters. For arbitrary guess values, the minimisation method does not converge. The simulation studies are given for several transfer function matrices. © 2016 Indian Institute of Chemical Engineers.

Indian Chemical Engineer

Identification of Centralised Controlled Multivariable Systems

A method is presented to identify the steady-state gain matrix of a multivariable (SSGM) unstable system under closed-loop control. Effects of disturbances and measurement noise on the identification of SSGM were also studied. Davison's method (Davison, 1976) was modified to design single-stage multivariable PI controllers using only the steady-state gain matrix of the system. Since the overshoots in the responses are larger, a two-stage P-PI control system is proposed. Based on the SSGM, a simple proportional controller matrix was designed by the modified Davison's method (1976) to stabilize the system. Based on the gain matrix of the stabilized system, diagonal PI controllers were designed. The performance of the two-stage control system was evaluated and compared with that of single-stage multivariable controllers. Simulation results on two examples show the effectiveness of the proposed methods for both servo and regulatory problems. © 2015, Taylor & Francis Group, LLC.

Chemical Engineering Communications

Steady-State Gain Identification and Control of Multivariable Unstable Systems

A method is given to design multivariable PI/PID controllers for stable and unstable multivariable systems. The method needs only the steady state gain matrix (SSGM). The method is based on the static decoupler design followed by SISO PI/PID controllers design and combining the resulted decoupler and the diagonal PI(D) controllers as the centralized controllers. The result of the present method is shown to be equivalent to the empirical method proposed by Davison EJ. Multivariable tuning regulators: the feed-forward and robust control of general servo-mechanism problem. IEEE Trans Autom Control 1976;21:35-41. Three simulation examples are given. The performance of the controllers is compared with that of the reported centralized controller based on the multivariable transfer function matrix. © 2014 ISA.

Simple method of designing centralized PI controllers for multivariable systems based on SSGM

In the present work, the method of designing the centralised controllers for the minimum phase multivariable systems proposed by Vijay Kumar et al. is extended to non-minimum phase systems. The controller is designed based on the direct synthesis method. Inverse of process transfer function matrix in the direct synthesis method is approximated based on relative gain array concept. Maclaurin's series is applied to reduce it to a standard proportional and integral form. The method is further improved by using equivalent transfer function matrix derived from relative normalised gain array and relative average residence time array as process inverse transfer function matrix. Effective transfer function is the equivalent transfer function of gij(s) when all other loops are closed. The desired closed-loop transfer function should contain the process right half plane zero. Quadruple tank process with non-minimum phase behaviour is considered to analyse the performance of the proposed centralised controllers. The performance of centralised controllers is compared with a recently proposed decentralised controller. © 2014 © 2014 Indian Institute of Chemical Engineers.

Centralised Multi-input Multi-output Controllers for Non-minimum Phase Systems

Multi-loop PI controller design based on the direct synthesis for interacting multi-time delay processes

Industrial & Engineering Chemistry Research

Decentralized Control System Design for Multivariable ProcessesA Novel Method Based on Effective Relative Gain Array

Relay-enhanced multi-loop PI controllers

Journal of Process Control

Independent design of robust partially decentralized controllers

A Simple Multiloop Tuning Method for PID Controllers with No Proportional Kick

Centralized PI controllers for interacting multivariable processes by synthesis method

Journal	ISA Transactions
Publisher	ISA - Instrumentation, Systems, and Automation Society
ISSN	00190578
Open Access	No