Model based Controller Design for Level Process

Aravind, P.; Valluvan, M.; Sangeetha, B.

doi:10.5120/15455-4012

Cited by 3 publications

(3 citation statements)

References 10 publications

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“…Where k p is the steady state gain, τ d is the apparent transport lag and τ is the apparent first order time constant [9]. The model is calculated with the real time parameters as ( ) III.…”

Section: Methodsmentioning

confidence: 99%

IMC Based Design of PI Controller for Real Time Pressure Process

Diwakar¹,

M²,

Brindaa³

et al. 2015

International Journal of Innovative Research in Electrical, Ele

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Abstract:The objective of the work is to maintain the pressure in the closed loop at desired set value. The pressurized tank has the features of nonlinearity, sluggishness by tuning conventional PI methods. This paper focus on implementation of internal mode control (IMC) to obtain an optimal PI control setting for pressure process. System identification of the process is done by process reaction curve method. To improve the robustness, internal model control method (IMC) is employed in tuning the PI controller and is applied to the First Order plus Time-Delay (FOPTD) model. Here delay is approximated with First Order plus Pade Approximation. At first, a Proportional Integral (PI) controller based on IMC-PI setting is designed and the results are compared with Ziegler Nichols (ZN) controller settings. The robustness of the controllers are endorsed by imposing both servo and regulatory disturbances. The simulation results confirm that IMC-PI controller has improved dynamic performance on disturbance rejection.Keywords: IMC, Ziegler Nichols, PI controller, Pressure process. I. INTRODUCTIONThe PI control is the most commonly application of control strategy nowadays, with its simple arrangement, good robustness and wide application range, it is gradually highlighted in the control theory. It has been observed that, however, the existing PI controllers may not perform well in the complex control processes, such as the higher-order system and time-delay system. Efforts have been put to fix this problem, and numerous effective PI controller design and tuning methods for complex processes have been stated [1] PI tuning has certainly been the key to reasonable performance and robustness. PI controller setting is proposed for several process model, especially for First Order plus Time Delay (FOPDT). There are two commonly used method of PI tuning, they are ZieglerNichols setting [2] and Cohen-coon setting [3], which still used in several industrial applications. Internal Model Control [4] allow system designer to specify the anticipated system behaviour. The robustness and performance of the model can controlled by the single parameter (λ). IMC-PI setting is one of the greatest closedloop method among experts and researchers since it is the easy way to understand. In the context of IMC, Parameter of consequent close-loop models are enhanced with respect to error performance criteria such as Integral of Time Weighted Absolute Error (ITAE) [5], Integral Square Error (ISE) and Integral Absolute Error (IAE). The Internal Model Control (IMC) structure offers an appropriate structure for satisfying the ideas. IMC [6] theory has been used earlier and autonomously by a number of other scholars. Using the IMC setting design technique, controller difficulty depends entirely on two factors: the difficulty of the model and the performance necessities indicated by the designer. IMC denotes to a methodical technique for control design based on the Qparameterization [7] idea that is the source for many current control methods. IMC offer...

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Section: Methodsmentioning

confidence: 99%

IMC Based Design of PI Controller for Real Time Pressure Process

Diwakar¹,

M²,

Brindaa³

et al. 2015

International Journal of Innovative Research in Electrical, Ele

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show abstract

“…The optimal values of the PI controller parameters Kp, Ki are found using GA. All possible sets of controller parameter values are chromosomes whose values are adjusted so as to minimize the objective function, which in this case is the error criterion [8].…”

Section: Implementation Of Gamentioning

confidence: 99%

“…Optimum solution is attained by Simply adjusting Proportion, Integral and Derivative controller gain parameters [2,3]. In the control strategy literature, there is number of conventional tuning methods are available to tune the parameter of PID controllers, model based controllers [8] ,optimization tuning methods, artificial neural networks , Fuzzy Logic controller. Likewise still new control techniques are emerging.…”

Section: Introductionmentioning

confidence: 99%

Application of Optimization Technique to Tune PID Controller for a Level Process

Aravind¹,

Kumar²

2014

IJCA

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In any processes industry, process variables that need to be controlled are temperature, level, pressure and flow. This paper deals with an application of genetic algorithm to find the PID controller values to control the liquid level in the cylindrical tank. A process is identified as first order plus dead time model (FOPTD) and is validated. The intension of this paper is to obtain a minimum rise time, minimum setting time, and stable controlled system by obtaining the PID controller using conventional tuning method and Genetic Algorithm optimization technique. The simulation analysis was carried out for the mentioned PID controller settings. From the results based on time domain analysis, it is proved that the PID values are obtained using GA optimization technique yield a better perform than the conventional tuning method. General TermsControl System.

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Particle swarm optimization based PID controller tuning for level control of two tank system

Vincent

Nersisson

2017

IOP Conf. Ser.: Mater. Sci. Eng.

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Model based Controller Design for Level Process

Cited by 3 publications

References 10 publications

IMC Based Design of PI Controller for Real Time Pressure Process

IMC Based Design of PI Controller for Real Time Pressure Process

Application of Optimization Technique to Tune PID Controller for a Level Process

Particle swarm optimization based PID controller tuning for level control of two tank system

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