Multiloop PI controller tuning for interacting multivariable processes

Lee, Jietae; Cho, Wonhui; Edgar, Thomas F.

doi:10.1016/s0098-1354(98)00230-0

Cited by 66 publications

(59 citation statements)

References 12 publications

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“…Manuscript received date; revised date tuning methods suggested to tune decentralised controllers for multivariable processes such as detuning [2] , sequential design [3] , independent design [4] and iterative [5] methods. These tuning methods have achieved a certain degree of success in the design approach.…”

Section: Introductionmentioning

confidence: 99%

PID controller tuning for a multivariable glass furnace process by genetic algorithm

Rajarathinam

Gomm

et al. 2016

Int. J. Autom. Comput.

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Abstract:Standard genetic algorithms (SGAs) are investigated to optimise the discrete-time PID controller parameters by three tuning approaches for a multivariable glass furnace process with loop interaction. Initially, SGAs are used to identify control oriented models of the plant which are subsequently used for controller optimisation. An individual tuning approach without loop interaction is considered first to categorise the genetic operators, cost functions and improve searching boundaries to attain the desired performance criteria. The second tuning approach considers controller parameters optimisation with loop interaction and individual cost functions. While, the third tuning approach utilises a modified cost function which includes the total effect of both controlled variables, glass temperature and excess oxygen. This modified cost function is shown to exhibit improved control robustness and disturbance rejection under loop interaction.

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Section: Introductionmentioning

confidence: 99%

PID controller tuning for a multivariable glass furnace process by genetic algorithm

Rajarathinam

Gomm

et al. 2016

Int. J. Autom. Comput.

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“…Most industrial processes are multi-input and multi-output (MIMO) systems, where the applications of multi-loop PID controllers (decentralized control schemes) are very common due to their simplicity in implementation [1]. Nevertheless, the performance of decentralized PID controllers in MIMO processes is often limited by the presence of process interactions.…”

Section: Introductionmentioning

confidence: 99%

Inter-Communicative Decentralized Multi-Scale Control (ICD-MSC) Scheme: A New Approach to Overcome MIMO Process Interactions

Nandong

Zang

2014

Chemical Product and Process Modeling

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Decentralized PID control has been extensively used in process industry due to its functional simplicity. But designing an effective decentralized PID control system is very challenging because of process interactions and dead times, which often impose limitations on control performance. In practice, to alleviate the detrimental effect of process interactions on control performance, decoupling controllers are often incorporated into a decentralized control scheme. In many cases, these conventional decoupling controllers are not physically realizable or too complex for practical implementation. In this paper, we propose an alternative scheme to overcome the performance limitation imposed by process interactions. This new control scheme is extended from the SISO multi-scale control scheme previously developed for nonminimum-phase processes. The salient feature of the new control scheme lies in its communicative structure enabling collaborative communication among all the sub-controllers in the system. This communicative structure serves the purpose of reducing the detrimental effect of process interactions leading to improved control performance and performance robustness. Extensive numerical study shows that the new control scheme is able to outperform some existing decentralized control schemes augmented with traditional decoupling controllers.

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“…A literature search reveals that there are several classified tuning methods suggested to tune decentralised controllers for multivariable processes such as Detuning method [2], Sequential design method [3], and Iterative method [4]. These tuning methods have achieved a certain degree of success in the design approach.…”

Section: Introductionmentioning

confidence: 99%