Ascendancy of level in nonlinear tank system by neuro controller

Marshiana, D.; N.R, Krishnamoorthy; P, Grace Kanmani; A., Mary Joy Kinol; Sabarivani, A.; Harikrishnan,

doi:10.1016/j.rico.2023.100260

Cited by 1 publication

(2 citation statements)

References 31 publications

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“…In such instances, liquids are stored in one tank and then transferred in a controlled way to another tank. It is widely acknowledged that tanks and the mechanisms used to regulate their levels and flows form the backbone of every chemical engineering system [1]. Therefore, effectively controlling of these parameters in the process industries also demonstrates significant economic advantages.…”

Section: Introductionmentioning

confidence: 99%

“…In this case, the Levenberg-Marquardt method was used to train the network. Comparative results show the suggested model performs better in terms of undershoot, settling time, and overshoot in MATLAB platform [34]. An adaptive disturbance attenuation control approach based on the portcontrolled Hamiltonian model is introduced to examine the problems associated with the two-tank liquid level system.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Probabilistic Bi-Level Assessment and Adaptive Control Mechanism for Two-Tank Interacting System

Manna,

Singh,

Ghadi

et al. 2023

IEEE Access

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Liquid level control is a fundamental aspect employed across various industries, where the precise regulation of liquid levels and flow rates is of utmost importance. The Proportional-integral-derivative (PID)controller is widely employed but in practice, the operation of a PID may not always align with the desired outcome due to various factors such as system dynamic behavior, model uncertainties, time-varying parameters, and disturbances. To effectively address these challenges, the article proposes model reference adaptive control (MRAC) based on the Massachusetts Institute of technology (MIT) law feedback PID technique for a two-tank interacting system. The detailed comparative analysis is carried out in MATLAB/Simulink with open loop, PID, and MRAC in respect of time domain specifications. The proposed approach stability is verified using the Lyapunov approach. The robustness of the control mechanism is validated through probabilistic assessment by introducing a bi-level uncertainty framework such as gain mistuning and dynamic system behavior. In the first level, the gain mistuning is accomplished in three aspects i.e., fine-tuned, increased, and decrease gain. In the second level, it is considered that system behavior is dynamic in nature. Based on the findings, the MRAC-PID exhibits superior performance against uncertainties as compared to PID and MRAC with enhanced tracking rapidity, accuracy, and robustness.INDEX TERMS Two-tank interacting system, PID, Model reference adaptive controller (MRAC), MIT law, MRAC-PID.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%