ISSN (Print) : 2320 – 3765 ISSN (Online): 2278 – 8875 International Journal of Advanced Research in Electrical, Electronics and Instrumentation Engineering Vol. 2, Issue 7, July 2013 Copyright to IJAREEIE www.ijareeie.com 3174 MODEL BASED CONTROL FOR INTERACTING AND NON-INTERACTING LEVEL PROCESS USING LABVIEW M.Lavanya 1 , P.Aravind 2 , M.Valluvan 3 , Dr.B.Elizabeth Caroline 4 PG Scholar[AE], Dept. of ECE, J.J. College of Engineering& Technology, Trichy, Tamilnadu, India 1 PG Scholar[C&I], Dept. of EIE, J.J. College of Engineering & Technology, Trichy, Tamilnadu, India 2 Assistant Professor, Dept. of EIE, J.J. College of Engineering & Technology, Trichy, Tamilnadu, India 3 Professor, Dept. of ECE, J.J. College of Engineering & Technology, Trichy, Tamilnadu, India 4 ABSTRACT: Recent advancements in process industries have enabled the development of combination of interacting and non-interacting of process tank level control system. An experimental setup of three tank level process in interacting and non- interacting mode was studied, to obtain the process models. Different control schemes such as Internal model controller (IMC), IMC-PID and Proportional –Integral and Derivative (PID) were implemented. The goal of the model-based controller is to compensate for shifts in the process and maintain the liquid level on target. The performance of different control schemes were investigated through computer simulation. Keywords:Interacting system, Non-interacting system, IMC, IMC-PID, LabVIEW. I.INTRODUCTION Even though control theory has been developed significantly, the proportional- integral-derivative (PID) controllers are used for a wide range of process control, motor drives, magnetic and optic memories, automotive, flight control, instrumentation, etc. In industrial applications, PID type controllers were widely used.With its three-term functionality covering treatment to both transient and steady-state responses, proportional- integral-derivative (PID) control offers the simplest and yet most efficient solution to many real-world control problems. Since the invention of PID control in 1910 (largely owning to Elmer Sperry’s ship autopilot), and the Ziegler–Nichols’ (Z-N) straightforward tuning methods in 1942 [1], the popularity of PID control has grown tremendously. With advances in technology, the science of automatic control now offers a wide spectrum of choices for control schemes. However, most of industrial controllers were still implementing based around PID algorithms, particularly at lowest levels. This paper presents a [2] case study emphasizes building a mathematical model of a two tank fluid system, followed by system identification and parameter estimation, and finally designing a controller by pole placement. Model based control was developed primarily for processes having a pronounced time delay, the intent being to match the process delay with one in the control system. Model based control is very popular now adays due to the ability of such controllers to handle process with dead time effectively. Model-based control action is “intelligent” and helps in achieving uniformity, disturbance rejection, and set point tracking, all of which translate into better process economics One important type of model based control is Internal Model Control [IMC], which has the combined advantage of both open and closed systems[6]. It gives better performance in tracking the set point and load changes[3]. In [4], IMC design concept is extended to multi input-multi output discrete time systems. A good resource for IMC is [5]. An excellent summary on PID tuning methods can be found in [6], [7], and [8]. However, no tuning method so far can replace the simple Z-N method for lower order systems in terms of familiarity and ease of use to start with. This work is based on real time model based control for the level control of a non-interacting and interacting three tank cylindrical tank system found to be second order with delay process .The process model is experimentally determined from step response analysis and it is interfaced to real time with LabVIEW. The controller settings of IMC, IMC PID and the conventional PID controller are analyzed, based on time domain specifications like peak time, overshoot and settling time.