Araştırma Makalesi
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Ant colony based optimal PD control of an underactuated system: An experimental study

Yıl 2023, , 710 - 730, 07.07.2023
https://doi.org/10.25092/baunfbed.1163250

Öz

The inverted pendulum system (IP) is an underactuated, non-linear, unstable and complex-to-control system. In this study, the inverted pendulum system is modeled by taking into account the friction effects. A parallel PD controller, which controls the car position and pendulum angle, whose coefficients are adjusted with the help of the ant colony algorithm, is proposed for the control of the system. Depending on the ant colony algorithm, the ideal ratio and derivative coefficients were obtained with the help of the integral of the square of the error (ISE), the integral of the absolute value of the error (IAE), the integral of the absolute value of the error over time (ITAE) and the mean squared error (MSE) objective functions. The performance of the system has been compared with the classical PD controller by simulation and experimentally with the help of the coefficients found for the position and angle controllers. According to the results obtained, the rise time, settling time and overshoot values were reduced. In step reference, the response performance of the optimized parallel PD controllers is significantly increased.

Kaynakça

  • Saco, R., Subspace Identificaition of an Inverted Pendulum on a Cart using state variables Transformation, IFAC PapersOnLine 52, 11, 244–249, (2019).
  • Gurriet, T., Mote, M., Singletary, A., Nilsson, P., Feron, E., ve Ames, A. D. ‘A scalable safety critical control framework for nonlinear systems, IEEE Access, 8, 187249–187275, (2020).
  • Wang J.J., Simulation studies of inverted pendulum based on PD controllers, Simulation Modelling Practice and Theory, 19, 1, 440–9, (2011).
  • Magdy, M., Marhomy, A.E., Attia, M.A., Modeling of inverted pendulum system with gravitational search algorithm optimized controller, Ain Shams Engineering Journal 10, 129–149, (2019).
  • Jmel, I., Dimassi, H., Said, S.H., M’Sahli, F., An adaptive sliding mode observer for inverted pendulum under mass variation and disturbances with experimental validation, ISA Transactions, 102, 264-279, (2020).
  • Mason, P., Broucke, M., Piccoli, B., Time optimal swing-up of the planar pendulum, IEEE Transactions on Automatic Control, 53, 8, 1876–1886, (2008).
  • Shahnazi, R., Akbarzadeh, T.M.R., PI adaptive fuzzy control with large and fast disturbance rejection for a class of uncertain nonlinear systems, IEEE Transactions on Fuzzy Systems, 16, 1, 187–197, (2008).
  • Wai, R.J., Chang, L.J., Adaptive stabilizing and tracking control for a nonlinear inverted-pendulum system via sliding-mode technique, IEEE Transactions on Industrial Electronics 53, 2, 674–692, (2006).
  • Magana, M.E., Holzapfel, F., Fuzzy-logic control of an inverted pendulum with vision feedback, IEEE Transactions on Education, 41, 2, 165–170, (1998).
  • Ozana, S., Pies, M., Slanina, Z., Hajovsky, R., Design and implementation of LQR controller for inverted pendulum by use of REX control system, IEEE International Conference on Circuits and Systems, 1, 343–347, (2012).
  • Deng, L., Gao, S., The design for the controller of the linear inverted pendulum based on backstepping, International Conference on Electronic and Mechanical Engineering and Information Technology (EMEIT), 6, 2892–2895, (2011).
  • Jörgl, M., Schlacher, K., Gattringer, H., Passivity based control of a cart with inverted pendulum, Applied Mechanics and Materials, 332, 339-344, (2013).
  • Linden, G.W., Lambrecht, P.F., H (infinity) control of an experimental inverted pendulum with dry friction, IEEE Control Systems Magazine, 13, 4, 44–50, (1993).
  • Kılıç, F., Bicakcı, S., Güneş, H., Adaptive gain decoupled sliding mode control of inverted pendulum, J. BAUN Inst. Sci. Techol., 21, 2, 610-622, (2019.)
  • Patra, A. K., Mishra, A. K., Agrawal, R., Patra, A. K., Satapathy, L. M., Kar, S. K., Self-Tuned PI Controller Design for Stabilizing and Trajectory Tracking of Inverted Pendulum, 2019 International Conference on Information Technology (ICIT), 53-58, (2019).
  • Song, S.L., Zhou, J.Z., Wang, H.T., Feng, H.S., He, R., Ant Colony Algorithm and Its Applications to Optimization of PID Parameters, Key Engineering Materials, 431, 568-571, (2010).
  • Chang, W.D., Shih, S.P., PD controller design of nonlinear systems using an improved particle swarm optimization approach, Communications in Nonlinear Science Numerical Simulation, 15, 11, 3632–3639, (2010).
  • Rani, M.R., Selamat, H., Zamzuri, H., Ahmad, F., PID Controller Optimization for a Rotational Inverted Pendulum using Genetic Algorithm, 2011 Fourth International Conference on Modeling, Simulation and Applied Optimization, 1-6, (2011).
  • Liang, Z., Fu, L., Li, X., Feng, Z., Sleigh, J.W. ve Lam, H.K., Ant Colony Optimization PD Control of Hypnosis With Propofol Using Renyi PermutationEntropy as Controlled Variable, IEEE Access, 7, 97689-97703, (2019).
  • Chen, C.S., Chen, W.L., Robust Adaptive Sliding-Mode Control Using Fuzzy Modeling for an Inverted-Pendulum System, IEEE Transactions on Industrial Electronics, 45, 2, 297-306, (1998).
  • Dorigo, M., Birattari, M., Stützle, T., Ant Colony Optimization, IEEE Computational Intelligence Magazine, 1, 4, 28-39, (2006).
  • Long, X., Zhao, J., Scheduling Problem of Movie Scenes Based on Three Meta-Heuristic Algorithms, IEEE Access, 8, 59091 – 59099, (2020).
  • Gonçalves, L.C., Santos, M.F., de S, R.J.F., da Silva, J.L., Rezende, H.B., Development of a PI Controller Through an Ant Colony Optimization Algorithm Applied to a SMAR Didactic Level Plant, 2018 19th International Carpathian Control Conference (ICCC), 150-155, (2018).
  • Keskintürk, T., Söyler, H., Global Ant Colony Optimization, Journal of The aculty of Engineering and Architecture of Gazi University, 21 (4), 689-698, 2006
  • Stützle, T., Hoos, H.H., Max Min Ant System, Journal of Future Generation Computer Systems, 8, 16, 889–914, (2000).
  • Dorigo, M., Gambardella, L.M., Ant Colony System: A Cooperative Learning Approach to the Traveling Salesman Problem, IEEE Transaction on Evolutionary Computation, 1, 53-66, (1997).
  • Mukhairez, H.H.A., Maghari, A.Y.A., Performance Comparison of Simulated Annealing, GA and ACO Applied to TSP, International Journal of Intelligent Computing Research (IJICR), 6, 4, 647-654, (2015).
  • Haroun, S.A., Jamal, B., Hicham, E.H., A Performance Comparison of GA and ACO Applied to TSP, International Journal of Computer Applications, 117, 19, 28-35, (2015).
  • Selvarajan, D., Jabar, A.S.A., Ahmed, I., Comparative Analysis of PSO and ACO Based Feature Selection Techniques for Medical Data Preservation, The International Arab Journal of Information Technology, 16, 4, 731-736, (2019).
  • Gupta, A., Srivastava, S., Comparative Analysis of Ant Colony and Particle Swarm Optimization Algorithms for Distance Optimization, Procedia Computer Science, 173, 245–253, (2020).
  • Wang ,J., Liu G., Hierarchical Sliding-Mode Control of Spatial İnverted Pendulum With Heterogeneous Comprehensive Learning Particle Swarm Optimization, Information Sciences, 495, 14-36, (2019).
  • Magdy, M., El Marhomy, A., Attia, M. A., Modeling of Inverted Pendulum System with Gravitational Search Algorithm Optimized Controller, Ain Shams Engineering Journal, 10, 129-149, (2019).
  • Al-Araji, A. S., An Adaptive Swing-Up Sliding Mode Controller Design for a Real Inverted Pendulum System Based On Culture-Bees Algorithm, European Journal of Control, 45, 45-56, (2019).
  • Lakmesari, S. H., Mahmoodabadi, M.J., Yousef Ibrahim M., Fuzzy Logic and Gradient Descent-Based Optimal Adaptive Robust Controller with Inverted Pendulum Verification Chaos, Solitons and Fractals, 151, 211157, 1-13, (2021).
  • Chang, W., Shih, S., PID Controller Design of Nonlinear Systems Using an Improved Particle Swarm Optimization Approach, Communication in Nonlinear Science and Numerical Simulation, 15, 3632-3639, (2010).
  • Bejarbaneh E. Y., A. Bagheri , B. Y. Bejarbaneh , S. Buyamin , S. N.Chegini, A New Adjusting Technique for PID Type Fuzzy Logic Controller Using PSOSCALF, Optimization Algorithm Applied Soft Computing Journal, 85 105822, 1-26, (2019).
  • Mahmoodabadi, M.J, Jahanshahi, H., Multi-Objective Optimized Fuzzy-PID Controllers for Fourth Order Nonlinear Systems, Engineering Science and Technology an International Journal, 19, 1084–1098, (2016).
  • Tousi, S. M.A., Mostafanasab A., Teshnehlab, M., Design of Self Tuning PID Controller Based on Competitional PSO, 2020 4th Conference on Swarm Intelligence and Evolutionary Computation (CSIEC), 2-6, (2020).
  • Or´ostica, R., Duarte-Mermoud, M. A., J´auregui, C., Inverted Pendulum Stabilization by Means of Fractional Order PID Controllers 2017 CHILEAN Conference on Electrical, Electronics Engineering, Information and Communication Technologies (CHILECON), 1-7, (2017).
  • Singh, K., Nema, S., Padhy, P. K., Modified PSO Based PID Sliding Mode Control for Inverted Pendulum, International Conference on Control, Instrumentation, Communication and Computational Technologies (ICCICCT), 722-727, (2014).
  • Reddy, N., Saketh S., Pal, P., Dey, R., Optimal PID Controller Design of an Inverted Pendulum Dynamics: A Hybrid Pole-Placement & Firefly Algorithm Approach, IEEE First International Conference on Control, Measurement and Instrumentation (CMI), 305-310, (2016).
  • Singh, P., Verma, N., Jain, A., Optimization of PID based Cart-Inverted Pendulum System using GA-LQR, 6th International Conference on Communication and Electronics Systems (ICCES), 1-5, (2021).
  • Sarkar, T, Dewan, L., Pole-Placement, PID and Genetic Algorithm Based Stabilization of Inverted Pendulum, 8th International Conference on Computing, Communication and Networking Technologies (ICCCNT), 2-6, (2017).
  • Srivastava, V., Srivastava, S., Whale Optimization Algorithm (WOA) Based Control Of Nonlinear Systems, 2nd International Conference on Power Energy, Environment and Intelligent Control (PEEIC), 402-406, (2019).
  • Chiu, C. -H., Hung, Y. -T., Peng, Y. -F., Design of a Decoupling Fuzzy Control Scheme for Omnidirectional Inverted Pendulum Real-World Control, IEEE Access, 9, pp. 26083-26092, (2021).
  • Nasir, A. N. K., Razak, A. A. A., Opposition-based spiral dynamic algorithm with an application to optimize type-2 fuzzy control for an inverted pendulum system, Expert Systems with Applications, 195, Article No: 116661, (2022)
  • Bekkar, B., Ferkous, K. Design of Online Fuzzy Tuning LQR Controller Applied to Rotary Single Inverted Pendulum: Experimental Validation. Arab J Sci Eng, 48, 6957–6972 (2023).
  • Mofid, O., Alattas, K. A., Mobayen, S., Vu, M. T., Bouteraa, Y., Adaptive finite-time command-filtered backstepping sliding mode control for stabilization of a disturbed rotary-inverted-pendulum with experimental validation, Journal of Vibration and Control, 29(5-6), 1431-1446, (2023).

Eksik tahrikli bir sistemin karınca kolonisi tabanlı optimal PD kontrolü: Deneysel bir uygulama

Yıl 2023, , 710 - 730, 07.07.2023
https://doi.org/10.25092/baunfbed.1163250

Öz

Ters sarkaç sistemi (IP) eksik tahrikli, doğrusal olmayan, kararsız ve kontrolü karmaşık bir sistemdir. Bu çalışmada ters sarkaç sistemi, sürtünme etkileri de dikkate alınarak modellenmiştir. Sistemin kontrolü için katsayıları karınca kolonisi algoritması yardımıyla ayarlanan araba konumunu ve sarkaç açısını kontrol eden paralel PD kontrolcüsü önerilmiştir. Karınca kolonisi algoritmasına bağlı olarak ideal oran ve türev katsayıları hatanın karesinin integrali (ISE), hatanın mutlak değerinin integrali (IAE), zamana bağlı olarak hatanın mutlak değerinin integrali (ITAE) ve ortalama karesel hata (MSE) amaç fonksiyonları yardımıyla elde edilmiştir. Sistemin performansı, konum ve açı kontrolcüleri için bulunan katsayılar yardımıyla klasik PD kontrolcü ile karşılaştırmalı bir şekilde benzetim ve deneysel olarak incelenmiştir. Elde edilen sonuçlara göre, yükselme zamanı, oturma zamanı ve aşma değerleri azaltılmıştır. Adım referansta, optimizasyonları sağlanan paralel PD kontrolcülerin cevap performansı önemli derecede arttırılmıştır.

Kaynakça

  • Saco, R., Subspace Identificaition of an Inverted Pendulum on a Cart using state variables Transformation, IFAC PapersOnLine 52, 11, 244–249, (2019).
  • Gurriet, T., Mote, M., Singletary, A., Nilsson, P., Feron, E., ve Ames, A. D. ‘A scalable safety critical control framework for nonlinear systems, IEEE Access, 8, 187249–187275, (2020).
  • Wang J.J., Simulation studies of inverted pendulum based on PD controllers, Simulation Modelling Practice and Theory, 19, 1, 440–9, (2011).
  • Magdy, M., Marhomy, A.E., Attia, M.A., Modeling of inverted pendulum system with gravitational search algorithm optimized controller, Ain Shams Engineering Journal 10, 129–149, (2019).
  • Jmel, I., Dimassi, H., Said, S.H., M’Sahli, F., An adaptive sliding mode observer for inverted pendulum under mass variation and disturbances with experimental validation, ISA Transactions, 102, 264-279, (2020).
  • Mason, P., Broucke, M., Piccoli, B., Time optimal swing-up of the planar pendulum, IEEE Transactions on Automatic Control, 53, 8, 1876–1886, (2008).
  • Shahnazi, R., Akbarzadeh, T.M.R., PI adaptive fuzzy control with large and fast disturbance rejection for a class of uncertain nonlinear systems, IEEE Transactions on Fuzzy Systems, 16, 1, 187–197, (2008).
  • Wai, R.J., Chang, L.J., Adaptive stabilizing and tracking control for a nonlinear inverted-pendulum system via sliding-mode technique, IEEE Transactions on Industrial Electronics 53, 2, 674–692, (2006).
  • Magana, M.E., Holzapfel, F., Fuzzy-logic control of an inverted pendulum with vision feedback, IEEE Transactions on Education, 41, 2, 165–170, (1998).
  • Ozana, S., Pies, M., Slanina, Z., Hajovsky, R., Design and implementation of LQR controller for inverted pendulum by use of REX control system, IEEE International Conference on Circuits and Systems, 1, 343–347, (2012).
  • Deng, L., Gao, S., The design for the controller of the linear inverted pendulum based on backstepping, International Conference on Electronic and Mechanical Engineering and Information Technology (EMEIT), 6, 2892–2895, (2011).
  • Jörgl, M., Schlacher, K., Gattringer, H., Passivity based control of a cart with inverted pendulum, Applied Mechanics and Materials, 332, 339-344, (2013).
  • Linden, G.W., Lambrecht, P.F., H (infinity) control of an experimental inverted pendulum with dry friction, IEEE Control Systems Magazine, 13, 4, 44–50, (1993).
  • Kılıç, F., Bicakcı, S., Güneş, H., Adaptive gain decoupled sliding mode control of inverted pendulum, J. BAUN Inst. Sci. Techol., 21, 2, 610-622, (2019.)
  • Patra, A. K., Mishra, A. K., Agrawal, R., Patra, A. K., Satapathy, L. M., Kar, S. K., Self-Tuned PI Controller Design for Stabilizing and Trajectory Tracking of Inverted Pendulum, 2019 International Conference on Information Technology (ICIT), 53-58, (2019).
  • Song, S.L., Zhou, J.Z., Wang, H.T., Feng, H.S., He, R., Ant Colony Algorithm and Its Applications to Optimization of PID Parameters, Key Engineering Materials, 431, 568-571, (2010).
  • Chang, W.D., Shih, S.P., PD controller design of nonlinear systems using an improved particle swarm optimization approach, Communications in Nonlinear Science Numerical Simulation, 15, 11, 3632–3639, (2010).
  • Rani, M.R., Selamat, H., Zamzuri, H., Ahmad, F., PID Controller Optimization for a Rotational Inverted Pendulum using Genetic Algorithm, 2011 Fourth International Conference on Modeling, Simulation and Applied Optimization, 1-6, (2011).
  • Liang, Z., Fu, L., Li, X., Feng, Z., Sleigh, J.W. ve Lam, H.K., Ant Colony Optimization PD Control of Hypnosis With Propofol Using Renyi PermutationEntropy as Controlled Variable, IEEE Access, 7, 97689-97703, (2019).
  • Chen, C.S., Chen, W.L., Robust Adaptive Sliding-Mode Control Using Fuzzy Modeling for an Inverted-Pendulum System, IEEE Transactions on Industrial Electronics, 45, 2, 297-306, (1998).
  • Dorigo, M., Birattari, M., Stützle, T., Ant Colony Optimization, IEEE Computational Intelligence Magazine, 1, 4, 28-39, (2006).
  • Long, X., Zhao, J., Scheduling Problem of Movie Scenes Based on Three Meta-Heuristic Algorithms, IEEE Access, 8, 59091 – 59099, (2020).
  • Gonçalves, L.C., Santos, M.F., de S, R.J.F., da Silva, J.L., Rezende, H.B., Development of a PI Controller Through an Ant Colony Optimization Algorithm Applied to a SMAR Didactic Level Plant, 2018 19th International Carpathian Control Conference (ICCC), 150-155, (2018).
  • Keskintürk, T., Söyler, H., Global Ant Colony Optimization, Journal of The aculty of Engineering and Architecture of Gazi University, 21 (4), 689-698, 2006
  • Stützle, T., Hoos, H.H., Max Min Ant System, Journal of Future Generation Computer Systems, 8, 16, 889–914, (2000).
  • Dorigo, M., Gambardella, L.M., Ant Colony System: A Cooperative Learning Approach to the Traveling Salesman Problem, IEEE Transaction on Evolutionary Computation, 1, 53-66, (1997).
  • Mukhairez, H.H.A., Maghari, A.Y.A., Performance Comparison of Simulated Annealing, GA and ACO Applied to TSP, International Journal of Intelligent Computing Research (IJICR), 6, 4, 647-654, (2015).
  • Haroun, S.A., Jamal, B., Hicham, E.H., A Performance Comparison of GA and ACO Applied to TSP, International Journal of Computer Applications, 117, 19, 28-35, (2015).
  • Selvarajan, D., Jabar, A.S.A., Ahmed, I., Comparative Analysis of PSO and ACO Based Feature Selection Techniques for Medical Data Preservation, The International Arab Journal of Information Technology, 16, 4, 731-736, (2019).
  • Gupta, A., Srivastava, S., Comparative Analysis of Ant Colony and Particle Swarm Optimization Algorithms for Distance Optimization, Procedia Computer Science, 173, 245–253, (2020).
  • Wang ,J., Liu G., Hierarchical Sliding-Mode Control of Spatial İnverted Pendulum With Heterogeneous Comprehensive Learning Particle Swarm Optimization, Information Sciences, 495, 14-36, (2019).
  • Magdy, M., El Marhomy, A., Attia, M. A., Modeling of Inverted Pendulum System with Gravitational Search Algorithm Optimized Controller, Ain Shams Engineering Journal, 10, 129-149, (2019).
  • Al-Araji, A. S., An Adaptive Swing-Up Sliding Mode Controller Design for a Real Inverted Pendulum System Based On Culture-Bees Algorithm, European Journal of Control, 45, 45-56, (2019).
  • Lakmesari, S. H., Mahmoodabadi, M.J., Yousef Ibrahim M., Fuzzy Logic and Gradient Descent-Based Optimal Adaptive Robust Controller with Inverted Pendulum Verification Chaos, Solitons and Fractals, 151, 211157, 1-13, (2021).
  • Chang, W., Shih, S., PID Controller Design of Nonlinear Systems Using an Improved Particle Swarm Optimization Approach, Communication in Nonlinear Science and Numerical Simulation, 15, 3632-3639, (2010).
  • Bejarbaneh E. Y., A. Bagheri , B. Y. Bejarbaneh , S. Buyamin , S. N.Chegini, A New Adjusting Technique for PID Type Fuzzy Logic Controller Using PSOSCALF, Optimization Algorithm Applied Soft Computing Journal, 85 105822, 1-26, (2019).
  • Mahmoodabadi, M.J, Jahanshahi, H., Multi-Objective Optimized Fuzzy-PID Controllers for Fourth Order Nonlinear Systems, Engineering Science and Technology an International Journal, 19, 1084–1098, (2016).
  • Tousi, S. M.A., Mostafanasab A., Teshnehlab, M., Design of Self Tuning PID Controller Based on Competitional PSO, 2020 4th Conference on Swarm Intelligence and Evolutionary Computation (CSIEC), 2-6, (2020).
  • Or´ostica, R., Duarte-Mermoud, M. A., J´auregui, C., Inverted Pendulum Stabilization by Means of Fractional Order PID Controllers 2017 CHILEAN Conference on Electrical, Electronics Engineering, Information and Communication Technologies (CHILECON), 1-7, (2017).
  • Singh, K., Nema, S., Padhy, P. K., Modified PSO Based PID Sliding Mode Control for Inverted Pendulum, International Conference on Control, Instrumentation, Communication and Computational Technologies (ICCICCT), 722-727, (2014).
  • Reddy, N., Saketh S., Pal, P., Dey, R., Optimal PID Controller Design of an Inverted Pendulum Dynamics: A Hybrid Pole-Placement & Firefly Algorithm Approach, IEEE First International Conference on Control, Measurement and Instrumentation (CMI), 305-310, (2016).
  • Singh, P., Verma, N., Jain, A., Optimization of PID based Cart-Inverted Pendulum System using GA-LQR, 6th International Conference on Communication and Electronics Systems (ICCES), 1-5, (2021).
  • Sarkar, T, Dewan, L., Pole-Placement, PID and Genetic Algorithm Based Stabilization of Inverted Pendulum, 8th International Conference on Computing, Communication and Networking Technologies (ICCCNT), 2-6, (2017).
  • Srivastava, V., Srivastava, S., Whale Optimization Algorithm (WOA) Based Control Of Nonlinear Systems, 2nd International Conference on Power Energy, Environment and Intelligent Control (PEEIC), 402-406, (2019).
  • Chiu, C. -H., Hung, Y. -T., Peng, Y. -F., Design of a Decoupling Fuzzy Control Scheme for Omnidirectional Inverted Pendulum Real-World Control, IEEE Access, 9, pp. 26083-26092, (2021).
  • Nasir, A. N. K., Razak, A. A. A., Opposition-based spiral dynamic algorithm with an application to optimize type-2 fuzzy control for an inverted pendulum system, Expert Systems with Applications, 195, Article No: 116661, (2022)
  • Bekkar, B., Ferkous, K. Design of Online Fuzzy Tuning LQR Controller Applied to Rotary Single Inverted Pendulum: Experimental Validation. Arab J Sci Eng, 48, 6957–6972 (2023).
  • Mofid, O., Alattas, K. A., Mobayen, S., Vu, M. T., Bouteraa, Y., Adaptive finite-time command-filtered backstepping sliding mode control for stabilization of a disturbed rotary-inverted-pendulum with experimental validation, Journal of Vibration and Control, 29(5-6), 1431-1446, (2023).
Toplam 48 adet kaynakça vardır.

Ayrıntılar

Birincil Dil Türkçe
Konular Mühendislik
Bölüm Araştırma Makalesi
Yazarlar

Sabri Bıçakçı 0000-0002-2334-8515

Fuat Kılıç 0000-0003-2502-3789

Hüseyin Güneş 0000-0001-6927-5123

Erken Görünüm Tarihi 6 Temmuz 2023
Yayımlanma Tarihi 7 Temmuz 2023
Gönderilme Tarihi 17 Ağustos 2022
Yayımlandığı Sayı Yıl 2023

Kaynak Göster

APA Bıçakçı, S., Kılıç, F., & Güneş, H. (2023). Eksik tahrikli bir sistemin karınca kolonisi tabanlı optimal PD kontrolü: Deneysel bir uygulama. Balıkesir Üniversitesi Fen Bilimleri Enstitüsü Dergisi, 25(2), 710-730. https://doi.org/10.25092/baunfbed.1163250
AMA Bıçakçı S, Kılıç F, Güneş H. Eksik tahrikli bir sistemin karınca kolonisi tabanlı optimal PD kontrolü: Deneysel bir uygulama. BAUN Fen. Bil. Enst. Dergisi. Temmuz 2023;25(2):710-730. doi:10.25092/baunfbed.1163250
Chicago Bıçakçı, Sabri, Fuat Kılıç, ve Hüseyin Güneş. “Eksik Tahrikli Bir Sistemin karınca Kolonisi Tabanlı Optimal PD kontrolü: Deneysel Bir Uygulama”. Balıkesir Üniversitesi Fen Bilimleri Enstitüsü Dergisi 25, sy. 2 (Temmuz 2023): 710-30. https://doi.org/10.25092/baunfbed.1163250.
EndNote Bıçakçı S, Kılıç F, Güneş H (01 Temmuz 2023) Eksik tahrikli bir sistemin karınca kolonisi tabanlı optimal PD kontrolü: Deneysel bir uygulama. Balıkesir Üniversitesi Fen Bilimleri Enstitüsü Dergisi 25 2 710–730.
IEEE S. Bıçakçı, F. Kılıç, ve H. Güneş, “Eksik tahrikli bir sistemin karınca kolonisi tabanlı optimal PD kontrolü: Deneysel bir uygulama”, BAUN Fen. Bil. Enst. Dergisi, c. 25, sy. 2, ss. 710–730, 2023, doi: 10.25092/baunfbed.1163250.
ISNAD Bıçakçı, Sabri vd. “Eksik Tahrikli Bir Sistemin karınca Kolonisi Tabanlı Optimal PD kontrolü: Deneysel Bir Uygulama”. Balıkesir Üniversitesi Fen Bilimleri Enstitüsü Dergisi 25/2 (Temmuz 2023), 710-730. https://doi.org/10.25092/baunfbed.1163250.
JAMA Bıçakçı S, Kılıç F, Güneş H. Eksik tahrikli bir sistemin karınca kolonisi tabanlı optimal PD kontrolü: Deneysel bir uygulama. BAUN Fen. Bil. Enst. Dergisi. 2023;25:710–730.
MLA Bıçakçı, Sabri vd. “Eksik Tahrikli Bir Sistemin karınca Kolonisi Tabanlı Optimal PD kontrolü: Deneysel Bir Uygulama”. Balıkesir Üniversitesi Fen Bilimleri Enstitüsü Dergisi, c. 25, sy. 2, 2023, ss. 710-3, doi:10.25092/baunfbed.1163250.
Vancouver Bıçakçı S, Kılıç F, Güneş H. Eksik tahrikli bir sistemin karınca kolonisi tabanlı optimal PD kontrolü: Deneysel bir uygulama. BAUN Fen. Bil. Enst. Dergisi. 2023;25(2):710-3.