Setpoint weighted PID controller tuning for unstable system using heuristic algorithm

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Abstract

Most of the real time chemical process loops are unstable in nature and designing a suitable controller for such systems are difficult than open loop stable processes. In this work, an attempt is made with a two degree of freedom setpoint weighted PID controller tuning procedure for a class of unstable systems using the recent heuristic algorithms such as Particle Swarm Optimization and Bacterial Foraging Optimization. The problem considered in this study is to aptly tune the controller in order to enhance the overall closed loop performance. A novel objective function proposed in this study is used to monitor the heuristic algorithms in order to get the optimal controller parameters like Kp, Ki, Kd, and α with minimized iteration number. The proposed method is validated with a simulation study and this helps to accomplish enhanced system performance such as smooth reference tracking, satisfactory disturbance rejection, and error minimization for a class of unstable systems

References
  • [1] A. AHMAD and M. SOMANATH: Design of optimum PID controller by Bacterial Foraging Strategy. Proc. of the IEEE Int. Conf. on Ind. Tech (ICIT), (2006), 601-605.

  • [2] B. SUBUDHI, S. RANASINGH and K.A. SWAIN: Evolutionary computation approaches to tip position controller design for a two-link flexible manipulator. Archives of Control Sciences, 21(3), (2011), 269-285.

  • [3] CH-CH. CHEN, H.-P. HUANG and H.-J. LIAW: Setpoint weighted PID controller tuning for time-delayed unstable processes. Ind Eng. Chem. Res., 47(18), (2008), 6983-6990.

  • [4] M. CHIDAMBARAM: Set point weighted PI/PID controllers. Chem. Engg. Communications., 179(1), (2000), 1-13.

  • [5] CH.-T. LIOU and Y.-S. CHIEN: The effect of nonideal mixing on input multiplicity in a CSTR. Chem. Eng. Sci., 46(8), (1991), 2113-2116.

  • [6] H.K. DONG and H.C. JAE: A biologically inspired intelligent PID controller tuning for AVR Systems. Int. J. of Control, 4(5), (2006) 624-636.

  • [7] H.K. DONG: Hybrid GA-BF based intelligent PID controller tuning for AVR system. Applied Soft Computing, 11 (2011), 11-22.

  • [8] H.F. RASHAG, S.P. KOH, A.N. ABDALLA, N.M. TAN, K.H.CHONG and S.K.TIONG: DTC torque ripple minimization based on PSO-PID controller. Sci. Res. and Essays, 7(15), (2012), 1564-1572.

  • [9] H.P. HUANG and C.C. CHEN: Auto-tuning of PID controllers for second order unstable process having dead time.J. Chem. Eng. Jpn., 32(4), (1999), 486-497.

  • [10] C.S. JUNG, H.K. SONG, and J.C. HYUN: A direct synthesis tuning method of unstable first-order-plus-time-delay processes. J. Process Control, 9 (1999), 265-269.

  • [11] J. KENNEDY and R.C. EBERHART: Particle swarm optimization. In Proc. of IEEEInt. Conf. on Neural Networks, (1995), 1942-1948.

  • [12] M.K. PASSINO: Biomimicry of bacterial foraging for distributed optimization and control. IEEE Control Systems Magazine, 22(3), (2002), 52-67.

  • [13] M.K. PASSINO: Bacterial Foraging Optimization. Int. J, of Swarm IntelligenceResearch, 1(1), (2010), 1-16.

  • [14] M. KHALID, Q. LUO and H. DUAN: A cultural algorithm based particle swarm optimization approach to linear brushless DC motor PID controller. Sci. Researchand Essays, 7(3), (2012), 318-326.

  • [15] Y. LEE, J. LEE, and S. PARK: PID controller tuning for integrating and unstable processes with time delay. Chem. Eng. Sci., 55 (2000), 3481-3496.

  • [16] M. ZAMANI, N. SADATI and M.K. GHARTEMANI: Design of an H? PID Controller Using Particle Swarm Optimization. Int. J. of Control, 7(2), (2009), 273-280.

  • [17] M. ZAMANI, M.K. GHARTEMANI, N. SADATI and M. PARNIANI: Design of a fractional order PID controller for an AVR using particle swarm optimization. Cont. Eng. Pra., 17 (2009), 1380-1387.

  • [18] M.A. JOHNSON and M.H. MORADI: PID Control: New identification and design methods. Springer-Verlag London Ltd, 2005.

  • [19] M. ARAKI and H. TAGUCHI: Two-degree-of-freedom PID controllers. Int. J. ofControl, 1(4), (2003), 401-411.

  • [20] N. PILLAY and P. GOVENDER: PSO tuned PI/PID controller for open-loop unstable processes with time delay. EPIA’2011, (2011) 223-237.

  • [21] N. PILLAY and P. GOVENDER: Particle swarm optimization of PID tuning parameters. Lap Lambert Academic Publishing. 2010.

  • [22] P.K. PADHY and S. MAJHI: Relay based PI-PD design for stable and unstable FOPDT processes. Computers and Chem. Engg., 30, (2006), 790-796.

  • [23] R. PADMASREE and M. CHIDAMBARAM: Control of unstable systems. Narosa Publishing House, India, 2006.

  • [24] R. PADMASREE and M. CHIDAMBARAM: Setpoint weighted PID controllers for unstable systems. Chem. Engg. Communications, 192(1), (2005), 1-13.

  • [25] R.C. PANDA: Synthesis of PID controller for unstable and integrating processes. Chem. Eng. Sci., 64(12), (2009), 2807-2816.

  • [26] G. PRASHANTI and M. CHIDAMBARAM: Setpoint weighted PID controllers for unstable systems. J. of the Franklin Institute, 337(2-3), (2000), 201-215.

  • [27] V. RAJINIKANTH and K. LATHA: Bacterial foraging optimization algorithm based PID controller tuning for time delayed unstable system. The Medit. J. of Meas. andCont., 7(1), (2011), 197-203.

  • [28] V. RAJINIKANTH and K. LATHA: Optimization of PID controller parameters for unstable chemical systems using soft computing technique. I. Review of Chem. Eng., 3(3), (2011), 350-358.

  • [29] V. RAJINIKANTH and K. LATHA: I-PD controller tuning for unstable system using bacterial foraging algorithm: A study based on various error criterion. A. Comp. Int.and Soft Comp., (2012), Doi:10.1155/2012/329389.

  • [30] V. RAJINIKANTH and K. LATHA: Controller parameter optimization for nonlinear systems using enhanced bacteria foraging algorithm. A. Comp. Int. and Soft Comp., (2012), Doi:10.1155/2012/214264.

  • [31] R.P. SREE, M.N. SRINIVAS and M. CHIDAMBARAM: A simple method of tuning PID controllers for stable and unstable FOPDT systems. Comput. Chem. Eng., 28 (2004), 2201-2218.

  • [32] T. GANESAN, P. VASANT and I. ELAMVAZUTHY: A hybrid PSO approach for solving non-convex optimization problems. Archives of Control Sciences, 22(1), (2012), 87-105.

  • [33] A. VISIOLI: Optimal tuning of PID controllers for integral and unstable processes. IEE Proc. Control Theory Appl., 148(2), (2001), 180- 184.

  • [34] W.M. KORANI, H.T. DORRAH and H.M. EMARA: Bacterial foraging oriented by particle swarm optimization strategy for PID tuning. Proc. of the 8th IEEE Int. Conf.on Comp. Intel. in Robotics and Autom., (2008), 445-450.

  • [35] B.W. BEQUETTE: Process Control - Modeling, Design and Simulation. Prentice - Hall of India Pvt Ltd., 2003.

  • [36] Z-L. GAING: A particle swarm optimization approach for optimum design of PID controller in AVR System. IEEE Trans. on Energy Conversion, 19(2), (2004), 384-391.

Archives of Control Sciences

The Journal of Polish Academy of Sciences

Journal Information


IMPACT FACTOR 2016: 0.705

CiteScore 2016: 3.11

SCImago Journal Rank (SJR) 2016: 0.231
Source Normalized Impact per Paper (SNIP) 2016: 0.565

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