State variable analysis of four tank system

Jayaprakash, J.; Kumar, M. E. Hari

doi:10.1109/icgccee.2014.6922341

Cited by 7 publications

(3 citation statements)

References 6 publications

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“…The framework displays communicating multivariable elements on the grounds that every one of the pumps influences both of the outputs. A scientific model in light of physical information together with its linearization around a working point is determined in [4,12,20,21,22,23,24,25]. (1) Where, the input mass flow-rate (qini),is given as:-…”

Section: -Qts Modelingmentioning

confidence: 99%

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Optimal Control of Quadruple Tank System Using Genetic Algorithm

Alawad¹

2019

IJCDS

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Multivariable framework includes in excess of one control loop, these loops communicate with each other, in such a way, to the point that solitary information influences its own output as well as influences different process outputs. The quadruple tank system is basically a water level control issue and the best research facility case to break down the nonlinearities and interactions in process enterprises. Traditional controller techniques, similar to (PI) with (IMC), don't advance the framework. Consequently the optimization techniques, for example, Bacteria Foraging optimization(BFO), Particle swarm Optimization(PSO),and the proposed strategy Genetic Algorithm(G.A),are used to enhance the dynamic and steady state error execution of the framework to deal with the nonlinearities and interactions. Mat lab recreations are utilized to appear the best execution and reasonable comparison between all controllers' strategies.

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Section: -Qts Modelingmentioning

confidence: 99%

“…To beat the trouble, the linearization is required. The equ.3 is tackled utilizing Taylor arrangement taken after by Jacobian matrix change to acquire a state space type of the QTS[20, 22,25].The state-space conditions are:-…”

Section: -Qts Modelingmentioning

confidence: 99%

Optimal Control of Quadruple Tank System Using Genetic Algorithm

Alawad¹

2019

IJCDS

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“…Numerous studies have been conducted regarding this system, dealing with different controllers. For example, a Proportional Integral (PI) controller is discussed in [5], an Internal Model Control (IMC) and a Dynamic Matrix Control (DMC) algorithm has been created on the system's state space model in [6], also a PI controller is compared with a PID controller's results in [7], and a General Predictive Controller's (GPC) results are examined in [8]. In paper [9] we can read about the hybrid modeling of a system similar to the one presented in this paper, although structurally it is different, so its dynamics change as well and the control theory applied is model predictive control.…”

Section: Hybrid Controllermentioning

confidence: 99%

Hybrid modeling and model based control of the four tank process

Kardos

Kutasi

2017

MACRo 2015

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Hybrid systems contain both continuous dynamics and discrete elements, where discrete transitions happen between different continuous operating modes as a consequence of certain events. The notion of modeling these types of systems is discussed in regard to the four tank process, which has hybrid and nonlinear characteristics. This paper describes the modeling of this system in Simscape software and a hybrid model is created as well, with a hybrid controller being built around it that includes finite-state automata and PI controller. Simulations implemented in Matlab Simulink software prove the viability and correctitude of the method presented.

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