A simple method of tuning PID controllers for integrator/dead-time processes

Chidambaram, M.; Sree, R. Padma

doi:10.1016/s0098-1354(02)00178-3

Cited by 136 publications

(100 citation statements)

References 7 publications

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“…Using the Simple Internal Model Control (SIMC) Skoges-tad (2001) tuning rules with closed loop time constant, T c = τ , gives α = 0.5 and β = 8. This also holds for the tuning rules deduced in Chidambaram and Sree (2003).…”

Section: Introductionsupporting

confidence: 69%

n Tuning PI Controllers for Integrating Plus Time Delay Systems

Ruscio¹

2010

MIC

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Some analytical results concerning PI controller tuning based on integrator plus time delay models are worked out and presented. A method for obtaining PI controller parameters, K p = α kτ , and, T i = βτ , which ensures a given prescribed maximum time delay error, dτ max , to time delay, τ , ratio parameter δ = dτ max τ , is presented. The corner stone in this method, is a method product parameter,c = αβ. Analytical relations between the PI controller parameters, T i , and, K p , and the time delay error parameter, δ, is presented, and we propose the setting, β =c a (δ + 1), and, α = a δ+1 , which gives, T i =c a (δ + 1)τ , and, K p = a (δ+1)kτ , where the parameter, a, is constant in the method product parameter,c = αβ. It also turns out that the integral time, T i , is linear in, δ, and the proportional gain, K p , inversely proportional to, δ + 1. For the original Ziegler Nichols (ZN) method this parameter is approximately,c = 2.38, and the presented method may e.g., be used to obtain new modified ZN parameters with increased robustness margins, also documented in the paper.

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Section: Introductionsupporting

confidence: 69%

n Tuning PI Controllers for Integrating Plus Time Delay Systems

Ruscio¹

2010

MIC

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“…The Smith predictor (referred to as Smith PID) structure is a strategy used to tune dead-time systems, as given in the work by Chidambaram and Padma Sree (2003).…”

Section: Smith Pid Controller Designmentioning

confidence: 99%

“…The PID controller tuning values for this model have been given by a number of researchers, namely, Kookos and Syrcos (2005), Tyreus and Luyben (1992), Luyben (1996) and Chidambaram (1998), and Chidambaram and Padma Sree (2003). Consider the industrial example of a level control in a distillation column having the open loop transfer function, as in equation (14), with parameters k p = 0.0506 and d = 6 s. Tyreus and Luyben (1992), Visioli (2001), Chidambaram (1998) and Chidambaram and Padma Sree (2003).…”

Section: Examplementioning

confidence: 99%

Design of PID controllers for dead-time systems using hybrid biogeography based optimisation

Ganapathy

Jerome

2012

IJSCIP

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This paper introduces the application of BBO algorithms to Proportional Integral Derivative (PID) controller tuning. Derivative free optimisation methods, namely simplex derivative pattern search and implicit filtering are used to hybridize BBO algorithm resulting in improved convergence than original BBO. The effectiveness of the proposed algorithms namely SDPS-BBO, IMF-BBO are demonstrated using PID and Smith predictor controller schemes applied to unit step set point response for a class of dead-time systems and the results are compared with earlier controller tunings proposed by Kookos and Syrcos, Chidambaram, Luyben, Kanthaswamy and Jovitha Jerome.

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“…The early successful application control strategy in process control is in evolution of the PID controller and Ziegler-Nichols tuning method (Ziegler and Nichols, 1942). Till nowadays, 95% of the controllers implemented in the process industries are PID-type (Chidambaram and See, 2002). However, as (i) the industrial demands (ii) the computational capabilities of controllers and (iii) complexity of systems under control increase, so the challenge is to implement advanced control algorithms.…”

Section: Introductionmentioning

confidence: 99%

“…However, as (i) the industrial demands (ii) the computational capabilities of controllers and (iii) complexity of systems under control increase, so the challenge is to implement advanced control algorithms. There have been commercial successes of the intelligent control methods, but the dominating controller in process industries is still by far the PID-controller (Chidambaram and See, 2002). This stands to the fact that a simple and general purpose automatic controller (for example PID) is demanded in process industries.…”

Section: Introductionmentioning

confidence: 99%