A comparative study on existing and new methods to design internal model controllers for non-square systems

Saidi, Imen; Touati, Nahla; Dhahri, Ahmed; Soudani, Dhaou

doi:10.1177/0142331219834608

Cited by 14 publications

(4 citation statements)

References 31 publications

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“…The proposed controller steady-state gain is equal to the inverse of the model steady-state gain. Offsetfree control is then obtained for constant setpoints and output disturbances [28].…”

Section: The Discrete Imc Control For Mimo Systemsmentioning

confidence: 99%

Dahlin Deadbeat Internal Model Control for Discrete MIMO Systems

Touati,

Saidi

2024

Int. j. electr. comput. eng. syst. (Online)

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Controlling Multiple Input Multiple Output (MIMO) systems present a considerable challenge, particularly when dealing with time delays, nonlinearities, and disturbances. While the Dahlin algorithm and deadbeat control can offer good performance for such systems especially for systems requiring aperiodic responses or those where overshoot and setteling time need to be minimized, their effectiveness can diminish if the model parameters are inaccurate or in the presence of disturbances which lead to steady-state errors. To address these limitations, we propose combining these approaches with Internal Model Control, known for its robustness in handling variations in process dynamics, ensuring accurate setpoint tracking and disturbance rejection. In this paper, we introduce the Dahlin Deadbeat Internal Model Control (DDIMC) for discrete MIMO systems. Initially designed for linear processes with multiple time delays, this control strategy addresses complex control challenges arising from coupling effects and time delays. For nonlinear processes, we extend this controller using a multimodal control strategy which involves describing the nonlinear system with multiple linear discrete models, each paired with a Dahlin Deadbeat controller. A fusion technique is then employed to select the most suitable controller for application. Simulation case studies performed using the MATLAB software validate the effectiveness of these strategies, demonstrating their ability to consistently ensure satisfactory dynamic and robust performance.

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“…The proposed controller steady-state gain is equal to the inverse of the model steady-state gain. Offsetfree control is then obtained for constant setpoints and output disturbances [28].…”

Section: The Discrete Imc Control For Mimo Systemsmentioning

confidence: 99%

Dahlin Deadbeat Internal Model Control for Discrete MIMO Systems

Touati,

Saidi

2024

Int. j. electr. comput. eng. syst. (Online)

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“…To successfully apply our approach, firstly we need to modify the IMC basic structure mentioned in Figure 1, so that it becomes applicable to underactuated systems with more outputs than control inputs. Secondly, we design an approximate inverse of the model plant which is inspired by the studies of [16,17] in the case of MIMO systems and over-actuated systems [18].…”

Section: Imc Structure Based On Virtual Inputs (Vi)mentioning

confidence: 99%

“…The Virtual Inputs Controller C VIN (z) design presented in Figure 4 is based on the inversion method reported in [18,19]. For sufficiently high values of a , the controller C VIN (z) approaches the inverse of internal model Ğ m (z):…”

Section: Imc Structure Based On Virtual Inputs (Vi)mentioning

confidence: 99%

A Novel Discrete Internal Model Control Method for Underactuated System

Saidi¹,

Beaojui²,

Xibilia³

2021

Interdisciplinary Description of Complex Systems

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This article provides a comparative analysis of two common control configurations used to control the side-stream distillation used to separate benzene, toluene and xylene as suggested by Doukas and Lyben. Their under-actuated model has been considered as the model of distillation column and the internal model controller is designed considering a Singular Value Decomposition (SVD) and Virtual Inputs (VI) techniques. An internal controller design based on VI is proposed in this article for this kind of underactuated systems. This design is used to control in parallel the distillation process and its model in real time. The proposed controller design is simple and systematic in relation with the desired closed loop specifications of the internal model control structure. Furthermore, the controller obtained ensure robustness to process variations. The SVD technique can realize the decoupling of under-actuated processes and wipe out unrealizable factors by introducing compensation terms, affecting the dynamic of the system. The aim of this article is to make a comparison between our proposed VI controller and the SVD approach. The results we obtained confirmed the potentials of the proposed controller based on VI considering the set point tracking and its robustness.

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“…Modeling and control of non-square systems using relay-feedback method were discussed by Kalpana et al (2015). Saidi et al (2019) studied the comparsion of internal model controller for non-square systems. In many of the above works, a dummy variable has been added to make the system as squared one for making the design to follow conventional way.…”

Section: Introductionmentioning

confidence: 99%

Time domain modeling and control of complex non-linear chemical processes using relay feedback test

Sujatha

Panda

2020

Transactions of the Institute of Measurement and Control

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This study analyzes with the technology of auto tuning using relay feedback test for non-square MIMO system through process modeling, identification, input-output pairing and control strategies. However, the control configuration selection based on conventional steady-state Relative Gain Array (RGA) matrix sometimes degrades the loop performance and it needs attention. This study also deals with the real challenges in time domain modeling and appropriate pairing of loops for non-linear chemical processes. The choice of input-output pairing for square system has been extended to non-linear chemical processes. This ensures the system’s stability by selecting an appropriate manipulated-controlled variable pairing in non-linear chemical processes and the same is also tested for benchmark of non-linear chemical processes. In this study, two types of non-square systems are considered: one is systems with excess input than output variables and the other is systems with excess output than input variables. Some benchmark non-linear chemical processes, such as processes with mild nonlinearity, moderate to high nonlinearity and highly nonlinearity, are also taken for this study. Three standard benchmark processes are used in analysis of nonlinear chemical processes, namely: (1) Continuous Stirred Tank Reactor (CSTR) process; (2) hydrogen-ion- concentration (pH) process and (3) distillation column and this procedure is illustrated via simulation of 3-by-2 and 2-by-3 non-linear chemical processes.

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A comparative study on existing and new methods to design internal model controllers for non-square systems

Cited by 14 publications

References 31 publications

Dahlin Deadbeat Internal Model Control for Discrete MIMO Systems

Dahlin Deadbeat Internal Model Control for Discrete MIMO Systems

A Novel Discrete Internal Model Control Method for Underactuated System

Time domain modeling and control of complex non-linear chemical processes using relay feedback test

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