Nonlinear Constraint Optimization Based Robust Decentralized PID Controller for a Benchmark CSTR System Using Kharitonov–Hurwitz Stability Analysis

Govind, K. R. Achu; Mahapatra, Subhasish; Mahapatro, Soumya Ranjan

doi:10.1007/s13369-023-08076-1

Cited by 13 publications

(3 citation statements)

References 38 publications

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“…As presented in Ref. 16, a decentralized control method employs separate control loops for each input–output pair. Furthermore, the loop interactions are addressed through the implementation of decouplers.…”

Section: Preliminariesmentioning

confidence: 99%

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Advanced tree‐seed optimization based fractional‐order PID controller design for simplified decoupled industrial tank systems

Kottayathu Rajagopalan,

Mahapatra,

Mahapatro

2024

Int J Numerical Modelling

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Controlling coupled tank systems is challenging due to interactions between tanks, nonlinear dynamics, time delays, uncertainties, and cross‐coupling effects. The design of effective control strategies to address these complexities while ensuring stability and robust performance is difficult. Hence, this study focuses on presenting an innovative approach to enhance level control in coupled tank systems by employing a fractional‐order proportional‐integral‐derivative (FOPID) controller. The FOPID controller is designed by imposing constraints on the performance metric and closed‐loop gain. Besides, the defined optimization problem is solved by employing a tree seed algorithm. Further, the stability is analyzed graphically using the singular value analysis. The inherent complexities of coupled tank systems are effectively addressed by designing decouplers. The unique characteristics of the tree seed algorithm to navigate complex solution spaces and its effective handling of constraints offer a robust optimization framework. The validity and efficiency of the proposed method are analyzed in a range of simulation experiments conducted on distinct interconnected tank systems. Besides, the stability is verified graphically. The analysis highlights the effectiveness of the control law in handling uncertainties and disturbances. Besides, the proposed method reduces the settling time to around . Through a systematic integration of optimization and comprehensive stability analysis, the study provides a holistic solution for optimizing level control in coupled tank systems.

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Section: Preliminariesmentioning

confidence: 99%

“…As reported in Refs. 16,41, the closed‐loop performance of the system depends on the loop gain

{CL}_{AR}

and the performance factor: IAE. The IAE considers the cumulative error and provides a comprehensive assessment of the ability of the controller to minimize deviations from the desired set point.…”

Section: Introductionmentioning

confidence: 99%

Advanced tree‐seed optimization based fractional‐order PID controller design for simplified decoupled industrial tank systems

Kottayathu Rajagopalan,

Mahapatra,

Mahapatro

2024

Int J Numerical Modelling

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“…According to [37], the system facing uncertainty achieves robust stability exclusively when

{\left\Vert {\mathcal{T}}_{\mathcal{MI}}\right\Vert}_{\infty }&amp;lt;\frac{1}{{\left\Vert {\Delta}_{\mathcal{I}}\right\Vert}_{\infty }}.

…”

Section: Controller Designmentioning

confidence: 99%

Design of a decentralized control law for variable area coupled tank systems using H_∞complimentary sensitivity function

K. R.,

Mahapatra,

Ranjan Mahapatro

2023

Asian Journal of Control

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This paper proposes a novel graphical approach to control the liquid levels of the different variable area coupled tank systems using a decentralized controller. The coupled tank systems are common benchmark systems that consist of two tanks interconnected with each other. The primary goal is to maintain the liquid level in the tank at the desired set point by controlling the flow rate. This is attained with a decentralized method wherein the controller values are obtained from the plane. Besides, the robust criteria is enforced to guarantee the robustness. The proposed controller design approach aims to improve the performance of the system in terms of disturbance rejection and tracking. The decentralized control structure uses a distributed control strategy, thereby reducing the computational load which leads to improving the control performance. The loop interactions are minimized with decouplers. Furthermore, first‐order plus dead‐time (FOPDT) models are derived for each of the decoupled subsystems. Besides, the servo and regulatory responses of the controller are verified with input and output disturbances. Additionally, the response of the controller to system uncertainties and parameter variations is also studied. The simulation results demonstrate the effectiveness and robustness of the proposed approach.

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Adaptive Robust Control of Nonlinear Constrained Stirred‐Tank Reactors via Self‐Organizing Fuzzy Neural Network

Cui,

Li,

2024

Adaptive Control & Signal

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This paper presents an adaptive robust constraint controller for a continuous stirred tank reactor (CSTR) system based on a self‐organizing fuzzy neural network (SOFNN). Due to the high complexity of the chemical reactions, the CSTR system contains many strong nonlinearities and uncertainties. This is the first time to introduce the SOFNN into the adaptive controller design of the CSTR system, which improves the adaptability to dynamic system changes through the adjustment of the fuzzy network structure. Meanwhile, the time‐varying integral barrier Lyapunov functions (TVIBLFs) are employed to ensure the dimensionless reactant concentration and mixture temperature within a reasonable scope, which can improve the stability and safety of the CSTR system. Based on Lyapunov stability analysis, all the signals in a closed‐loop system are ultimately bounded. Simulation results substantiate the efficacy of the proposed control scheme.

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Nonlinear Constraint Optimization Based Robust Decentralized PID Controller for a Benchmark CSTR System Using Kharitonov–Hurwitz Stability Analysis

Cited by 13 publications

References 38 publications

Advanced tree‐seed optimization based fractional‐order PID controller design for simplified decoupled industrial tank systems

Advanced tree‐seed optimization based fractional‐order PID controller design for simplified decoupled industrial tank systems

Design of a decentralized control law for variable area coupled tank systems using H_∞complimentary sensitivity function

Adaptive Robust Control of Nonlinear Constrained Stirred‐Tank Reactors via Self‐Organizing Fuzzy Neural Network

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Nonlinear Constraint Optimization Based Robust Decentralized PID Controller for a Benchmark CSTR System Using Kharitonov–Hurwitz Stability Analysis

Cited by 13 publications

References 38 publications

Advanced tree‐seed optimization based fractional‐order PID controller design for simplified decoupled industrial tank systems

Advanced tree‐seed optimization based fractional‐order PID controller design for simplified decoupled industrial tank systems

Design of a decentralized control law for variable area coupled tank systems using H∞complimentary sensitivity function

Adaptive Robust Control of Nonlinear Constrained Stirred‐Tank Reactors via Self‐Organizing Fuzzy Neural Network

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Design of a decentralized control law for variable area coupled tank systems using H_∞complimentary sensitivity function