Kaskat Sistemler için Genetik Algoritma ile Optimize Edilmiş Gelişmiş Kaskat Kontrolör Tasarımı ve Deneysel Uygulaması

Year 2023, , 1 - 15, 31.01.2023

Mustafa Nalbantoğlu , İbrahim Kaya

https://doi.org/10.31202/ecjse.989791

Abstract

Tek döngülü geleneksel kontrolör, kontrol edilen değişken ayar noktasından sapmadıkça bozulmalar için herhangi bir düzeltici eylemi başlatmaz. Böyle bir durumda, özellikle bozulmaları olan bir kademeli sistemde bu kontrol sisteminin performansını iyileştirmek için kademeli bir kontrol stratejisi kullanılabilir. Klasik kademeli kontrol yapısında, hem iç hem de dış döngüde Oransal-İntegral-Türev (PID) tipi kontrolörler kullanılır. Bununla birlikte, PID kontrolörleri, açık döngü kararsız süreçler ve transfer fonksiyonlarında bir integratör bulunan süreçler için iyi performans göstermeyebilir. Bazı durumlarda, kademeli kontroldeki dış döngü transfer fonksiyonu açık döngü kararsız olabilir veya bir integratör içerebilir. Bu nedenle, kontrol edilen sisteme ilişkin kapalı döngü yanıtı tatmin edici olmayabilmektedir. Bu çalışmada, dış döngüde bir PI-PD kontrolörünün kullanıldığı geliştirilmiş bir kademeli kontrol yapısı önerilmiştir. Önerilen geliştirilmiş kademeli kontrol şemasında kontrolörlerin optimal parametrelerinin ayarlanması, Genetik Algoritma (GA) kullanılarak eş zamanlı olarak elde edilmiştir. Önerilen geliştirilmiş kademeli kontrol yapısının literatürde önerilen bazı kademeli kontrol şemalarına göre üstünlüğü simülasyon örnekleri ile gösterilmiştir. Ayrıca, önerilen geliştirilmiş kademeli kontrol yapısının geçerliliğini göstermek için DIGIAC 1750 süreç kontrol seti üzerinde gerçek zamanlı uygulama gerçekleştirilmiştir.

Keywords

Kaskat Kontrol, Optimal Kontrol, PID, PI-PD, Performans Kriteri.

Design and Experimental Application of an Improved Cascade Controller Optimized via Genetic Algorithm for Cascade Systems

Abstract

A single loop conventional controller will not initiate corrective action for disturbances unless the output variable moves away from the set-point. In this case, cascade control strategy can be benefitted to obtain better the control system performance, especially in existence of strong disturbances. Proportional-Integral-Derivative (PID) type controllers are usually preferred in both loops of a classical cascade control structure. However, if the outer loop transfer function of cascade control has an unstable pole or an integrator then its performance may not be as good as desired due to limitations of PID controllers. In this study, an improved cascade control structure incorporating a PI-PD controller in its outer loop is being proposed. Optimal parameters of controllers in the proposed improved cascade control scheme has been obtained simultaneously using Genetic Algorithm (GA). The superiority of the proposed improved cascade control structure over some cascade control schemes suggested in the literature has been shown by simulation examples. Also, real-time application on DIGIAC 1750 process control set has been performed to illustrate the validity of the proposed improved cascade control structure.

Keywords

Cascade control, Optimal control, PID, PI-Pd, Performance criteria

References

• [1]. Franks, R. G., Worley, C.W., Quantitive Analysis of Cascade Control. Industrial and Engineering Chemistry Research, 1956, 48, 1074-1079
• [2]. Hang, C.C., Loh, A.P., Vasnani, V.U., Relay Feedback Auto tuning of Cascade Controllers, IEEE Transactions Control System Technology, 1994, 2, 42-45.
• [3]. Huang, H.P., Chien, I. L.,Lee, Y.C., Simple Method for Tuning Cascade Control Systems, Chemical Engineering Communications, 1998, 165, 89-121.
• [4]. Lee, Y.H., Park, S.W., Lee, M.Y., PID Controller Tuning to Obtain Desired Closed Loop Responses for Cascade Control Systems, Industrial and Engineering Chemistry Research, 1998, 37, 1859-1865.
• [5]. Tan, K.K., Lee, T.H., Ferdous, R., Simultaneous Online Automatic Tuning of Cascade Control for Open Loop Stable Processes, ISA Transactions, 2000, 39, 233-242.
• [6]. Song, S.H., Cai, W.J., Wang, Y.G., Auto-Tuning of Cascade Control Systems, ISA Transactions, 2003, 42, 63-72.
• [7]. Kaya, I., Improving Performance Using Cascade Control and Smith Predictor, ISA Transactions, 2001, 40, 223-234.
• [8]. Smith, O.J., A Controller to Overcome Dead-Time, ISA J., 1959, 6, 28-23.
• [9]. Lee. Y., Oh, S., Park, S., Enhanced Control with A General Cascade Control Structure, Industrial and Engineering Chemistry Research, 2002, 41, 2679-2688.
• [10]. Kaya, I., Tan, N., Atherton, D.P., Improved Cascade Control Structure for Enhanced Performance, Journal of Process Control, 2007, 17, 3-16.
• [11]. Morari, M., Zafiriou, E., Robust Process Control, Prentice Hall, 1989, Englewood Cliffs.
• [12]. Kaya, I., Atherton, D.P., Use of Smith Predictor in The Outer Loop for Cascaded Control of Unstable and Integrating Processes, Industrial and Engineering Chemistry Research, 2008, 47, 1981-1987.
• [13]. Uma, S., Chidambaram, M., Rao, A.S., Enhanced Control of Unstable Cascade Processes with Time Delays Using a Modified Smith Predictor, Industrial and Engineering Chemistry Research, 2009, 48, 3098–3111.
• [14]. Padhan, P. G., Majhi, S., Modified Smith Predictor Based Cascade Control of Unstable Time Delay Processes, ISA Transactions, 2012, 51, 95-104.
• [15]. Padhan, P. G., Majhi, S., (2013). Enhanced Cascade Control for A Class of Integrating Processes with Time Delay, ISA Transactions, 2013, 52, 45-55.
• [16]. Çakıroglu, O., Güzelkaya, M., Eksin, İ., Improved Cascade Controller Design Methodology Based On Outer-Loop Decomposition, Transactions of The Institute of Measurement and Control, 2014, 37, 623-635.
• [17]. Jeng, J.C., Liao, S.J., A Simultaneous Tuning Method for Cascade Control Systems Based On Direct Use of Plant Data, Industrial and Engineering Chemistry Research, 2013, 5, 16820-16831.
• [18]. Jeng, J.C., Simultaneous Closed-Loop Tuning of Cascade Controllers Based Directly On Set-Point Step-Response Data, Journal of Process Control, 2014, 24, 652–662.
• [19]. Kaya, I., Tan, N., Atherton, D.P., A Refinement Procedure for PID Controllers, Electrical Engineering, 2006, 88, 215-221.
• [20]. Majhi, S., Atherton, D.P., Modified Smith Predictor and Controller for Processes with Time Delay, IEE Proceedings-Control Theory and Applications, 1999, 146, 359-366.
• [21]. Kaya, I., A PI-PD Controller Design for Control of Unstable and Integrating Processes, ISA Transactions, 2003, 42, 111-121.
• [22]. Goldberg, D.E., Genetic Algorithms in Search, Optimization and Machine Learning, 1989, Addison-Wesley Longman, Boston.
• [23]. Shinskey, F.G., Process Control Systems. 1967, Mcgraw Hill, New York.
• [24]. Holland. J.H., Adaptation in Natural and Artificial System, The University of Michigan, 1975, Ann Arbor.
• [25]. Keskenler, M., Keskenler, E., Solution And Performance Analysis Of Subset Sum Problem With A New Metaheuristic Approach, El-Cezeri, 2020, 7(2), 503-512.
• [26]. Urazel, B., Keskin, K., A Hybrid Solution Approach for Electric Vehicle Routing Problem with Soft Time-Windows, El-Cezeri , 2021, 8 (2), 994-1006.
• [27]. Ersoy, M., Yiğit, T., Yüksel, A., A Decision Support Tool for Indoor 801.11ac WLAN Modeling Using Optimization Techniques, El-Cezeri, 2020, 7 (3) , 1231-1244.
• [28]. Dündar, M., Öztürk, Z., An Evaluation For Optimizing Construction And Operation Costs Of Metro Systems, El-Cezeri, 2015, 2 (3) , 39-51.
• [29]. Karr, C.L. & Freeman, L.M. (1999). Industrial Applications of Genetic Algorithms. CRC Press, New York.
• [30]. Haupt, R.L. & Haupt, S.E. (2004). Practical Genetic Algorithms. 2nd Ed. Wiley-Interscience, Hoboken
• [31]. De Jong, K.A. (1975). Analysis of The Behavior of a Class of Genetic Adaptive Systems. Phd Thesis. University of Michigan.
• [32]. Grefenstette, J.J. (1986). Optimization of Control Parameters for Genetic Algorithms. IEEE Transactions On Systems, Man, And Cybernetic. Vol. 16, Pp.122-128.
• [33]. Yin, C., Qiang, Wang, H Tao, Sun, Q., Zhao, L. (2019). Improved Cascade Control System for A Class of Unstable Processes with Time Delay. Int. J. Control Autom. Syst. Vol. 17, Pp.126–135.
• [34]. Alkaya, A. & Eker, I. (2014). Luenberger Observer-Based Sensor Fault Detection: Online Application to DC Motor. Turkish Journal of Electrical Engineering and Computer Sciences. Vol. 22, Pp.363–370.
• [35]. Misza, K. (2009). Handbook of Practical MATLAB for Engineers. CRC Press, Boca Raton
• [36]. Eker, I. (2010). Second-Order Sliding Mode Control with Experimental Application. ISA Transactions. Vol. 49, Pp.394-405.