Control of nonlinear chemical process using sliding mode control

Rasul, Tabassum; Pathak, Monisha

doi:10.1109/icpeices.2016.7853520

Cited by 9 publications

(4 citation statements)

References 6 publications

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“…There are two main ways to reduce the chattering phenomenon of sliding-mode control: dynamic sliding-mode control (DSMC) − and smoothing functions. , Sliding-mode control (SMC) has advanced to deal with uncertainties and has become well-known within the control community to the point that SMC is being used in several engineering fields. One can find applications in electrical engineering, , robotics, − and controlling chemical processes. , Ref has been used for several chemical processes, for example, refs − .…”

Section: Introductionmentioning

confidence: 99%

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Hybrid Approaches-Based Sliding-Mode Control for pH Process Control

et al. 2022

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This paper presents two hybrid control topologies; the topologies are designed by combining artificial intelligence approaches and sliding-mode control methodology. The first topology mixes the learning algorithm for multivariable data analysis (LAMDA) approach with sliding-mode control. The second offers a Takagi–Sugeno multimodel approach, internal model, and sliding-mode control. The process under study is a nonlinear pH neutralization process with high nonlinearities and time-varying parameters. The pH process is simulated for multiple reference changes, disturbance rejection, and noise in the transmitter. Performance indices are used to compare the proposed approaches quantitatively. The hybrid control topologies enhance the performance and robustness of the pH process under study.

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Section: Introductionmentioning

confidence: 99%

“…One can find applications in electrical engineering, 15 , 16 robotics, 17 − 20 and controlling chemical processes. 21 , 22 Ref ( 23 ) has been used for several chemical processes, for example, refs ( 24 − 29 ).…”

Section: Introductionmentioning

confidence: 99%

Hybrid Approaches-Based Sliding-Mode Control for pH Process Control

et al. 2022

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“…CSTR is a benchmark process in industries and shows inverse response, generally arbitrary temperature feed is given to the system which yields less efficent performance in terms of time taken for obtaining final products in chemical reactions. Its non-linearity is also a challenge, controllers were developed in [7][8][9][10][11] including Sliding model [9], model predictive control [11] for CSTR, but tracking was hindered by the initial inverse response. [7][8][9][10][11]12] arbitrary temperature trajectories were used, PID still plays an important role in process industries but its use for these systems is not looked at carefully.…”

Section: Introductionmentioning

confidence: 99%

“…Its non-linearity is also a challenge, controllers were developed in [7][8][9][10][11] including Sliding model [9], model predictive control [11] for CSTR, but tracking was hindered by the initial inverse response. [7][8][9][10][11]12] arbitrary temperature trajectories were used, PID still plays an important role in process industries but its use for these systems is not looked at carefully. Thus, there is a need to for developing an optimized trajectory for input temperature and control schemes which are able to suppress inverse response while showing good tracking bhevaiour.…”

Section: Introductionmentioning

confidence: 99%

Transient analysis of systems exhibiting inverse response and their control with CSTR as a case study

Lakhani¹,

Srinivasan

Ra³

2020

IJEECS

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<span>In this paper the phenomenon of inverse response from systems was investigated and its transient response thoroughly analyzed. Inverse response is shown by non-minimum phase systems and some minimum phase systems. Transient analysis of these systems is lacking in literature A case study was done for a non-linear, non-minimum phase CSTR (Continuous Stirred Tank Reactor), which was identified and a novel optimized trajectory for temperature feed was synthesized, which is a non-linear dynamic constrained optimization problem solved using ACADO for a particular chemical reaction. Different control schemes were also implemented on other systems as well, which exibhit inverse responses, including model reference adaptive control. The finding shows that PID-ZN goes with the inverse response, is unable to suppress it and requires large control effort which can have serious hardware limitations. Robustness is another area where PID is lacking with these systems. MRAC shemes were able to overcome all these issues. For CSTR also, these findings hold true thus points at using advance stratigies in process control industries for maximzing product yield.</span>

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