INTERNATIONAL JOURNAL OF SCIENTIFIC & TECHNOLOGY RESEARCH VOLUME 3, ISSUE 9, SEPTEMBER 2014 ISSN 2277-8616 314 IJSTR©2014 www.ijstr.org Tuning Of A PID With First-Order-Lag Controller Used With A Highly Oscillating Second-Order Process Galal A. Hassaan Abstract: High oscillation in industrial processes is something undesired and controller tuning has to solve this problems. PID with first-order-lag is a controller type of the PID-family which is suggested to overcome this problem. This research work has proven that using the PID is capable of solving the dynamic problems of highly oscillating processes but with less efficiency than other PID-based controller types. A second order process of 85.45 % maximum overshoot and 8 seconds settling time is controlled using a PID controller with first-order-lag (through simulation). The controller is tuned by minimizing the sum of square of error (ISE) of the control system using MATLAB. The MATLAB optimization toolbox is used assuming that the tuning problem is an unconstrained one. The result was reducing the overshoot from 85.45 % to 15.9 % and decreasing the settling time from 8 seconds to only 0.552 seconds. The performance of the control system using a PID with first-order-lag controller using the present tuning technique is compared with that using the ITAE standard forms tuning technique Index Terms Highly oscillating second-order process ; improving control system performance ; PID with first-order-lag controller, controller tuning ; . ———————————————————— 1 INTRODUCTION Highly oscillating response is present in a number of industrial processes incorporating low damping levels. Conventionally, the PID controller is used and tuned for better performance of the control system. The PID with first-order-lag controller is one of the next generation to PID controllers where research and application is required to investigate its effectiveness compared with PID controllers. Poulin , Pomerleau, Desbiens and Hodouin (1996) described the design of an auto-tuning and adaptive PID controller. The controller can control processes with stable and unstable zeros, processes with integrator and unstable processes [1]. Seraji (1998) introduced a class of simple nonlinear PID-type controllers comprising a sector-bounded nonlinear gain in cascade with a linear fixed- gain P, PD, PI or PID controller [2]. Lelic (1999) extracted the essence of the most recent development of PID control during the 1990’s based on a survey of 333 papers published in various journals [3]. Hamdan and Gao (2000) developed a modified PID (MPID) controller to control and minimize the hysteresis effect in pneumatic proportional valves. The modified controller showed better command following and disturbance rejection qualities than other types [4]. Skogestad (2001) presented an analytical tuning rules as simple as possible but resulting in a good closed-loop behavior. He approximated the process by a first-order plus delay and used a single tuning rule [5]. Podlubny, Petras, Vinagre, O’Leary and Dorcak (2002) presented an approach for the design of analog circuits implementing fractional-order controllers based on the use of continued fraction expansions for the control of very fast processes [6]. Araki and Taguchi (2003) surveyed the important results about two degree of freedom PID controllers including equivalent transformations, the effect of 2DOF structure and relation to the preceded derivative PID and the I-PD controllers [7]. Astrom and Hagglund (2004) presented a design method used to maximize the integral gain subject to a robust constraint giving the best reduction of load disturbance . They revised tuning of PID controllers in the spirit of Ziegler and Nichols technique [8]. Su, Sun and Duan (2005) proposed an enhanced nonlinear PID controller with improved performance than the conventional linear fixed-gain PID controller. They incorporated a sector-bounded nonlinear gain in cascade with the conventional PID controller [9]. Killingsworth and Krstic (2006) presented a method for optimizing the step response of a closed-loop system consisting of a PID controller and an unknown plant with a discrete version of extremum seeking by minimizing a cost function quantifying the performance of the PID controller [10]. Arvanitis, Pasgianos and Kalogeropoulos (2007) investigated the control of unstable second order plus dead-time process using PID-type controllers. They proposed tuning rules based on the satisfaction of gain and phase margin specifications [11]. Madady (2008) proposed a PID type with iterative learning control update law to control discrete-time SISO linear time-invariant systems performing repetitive tasks. He proposed an optimal design method to determine the PID parameters [12]. Coelho (2009) proposed a tuning method to determine the parameters of PID control for an automatic regulator voltage system using chaotic optimization approach based on Lozi map [13]. Khare (2010) developed an internal model mode based PID controller to control the temperature of outlet fluid of the heat exchanger system. His controller demonstrated 84 % improvement in overshoot and 44 % improvement in settling time compared to the classical controller [14]. Ntogramatzidis and Ferrante (2011) introduced a range of techniques for the exact design of PID controllers for feedback control problems involving requirements on the steady-state performance and standard frequency domain specifications. The control parameters had to be calculated on-line meaning that their techniques appear convenient with adaptive and self-tuning control strategies [15]. Yu, Wilson, Currie and Young (2012) investigated the performance of industrial PI and PID controllers in the presence of sampling jitter showing that the derivative component of the PID controller causes excessive controller __________________________  Galal A. Hassaan  Emeritus Professor, Department of Mechanical Design & Production, Faculty of Engineering, Cairo University, Giza, EGYPT galalhassaan@ymail.com