Abstract
In the paper we propose a new approach to control system design. The approach is characterized by automated parameters tuning and structure selection of the controller. Structure selection and parameter tuning are performed using evolutionary algorithm and allow accurate control with elimination or minimizing of unfavourable phenomena like overshoot or harmonic distortion. Our method was tested on a model of quarter car active suspension system.
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Boiko, I.: Variable-structure PID controller for level process. Control Engineering Practice 21(5), 700–707 (2013)
Bartczuk, Ł., Dziwiński, P., Starczewski, J.T.: A new method for dealing with unbalanced linguistic term set. In: Rutkowski, L., Korytkowski, M., Scherer, R., Tadeusiewicz, R., Zadeh, L.A., Zurada, J.M. (eds.) ICAISC 2012, Part I. LNCS, vol. 7267, pp. 207–212. Springer, Heidelberg (2012)
Bartczuk, Ł., Dziwiński, P., Starczewski, J.T.: New Method for Generation Type-2 Fuzzy Partition for FDT. In: Rutkowski, L., Scherer, R., Tadeusiewicz, R., Zadeh, L.A., Zurada, J.M. (eds.) ICAISC 2010, Part I. LNCS (LNAI), vol. 6113, pp. 275–280. Springer, Heidelberg (2010)
Bartczuk, Ł., Przybył, A., Dziwiński, P.: Hybrid state variables - fuzzy logic modelling of nonlinear objects. In: Rutkowski, L., Korytkowski, M., Scherer, R., Tadeusiewicz, R., Zadeh, L.A., Zurada, J.M. (eds.) ICAISC 2013, Part I. LNCS, vol. 7894, pp. 227–234. Springer, Heidelberg (2013)
Bartczuk, Ł., Rutkowska, D.: A New Version of the Fuzzy-ID3 Algorithm. In: Rutkowski, L., Tadeusiewicz, R., Zadeh, L.A., Żurada, J.M. (eds.) ICAISC 2006. LNCS (LNAI), vol. 4029, pp. 1060–1070. Springer, Heidelberg (2006)
Bartczuk, Ł., Rutkowska, D.: Medical Diagnosis with Type-2 Fuzzy Decision Trees. In: Kącki, E., Rudnicki, M., Stempczyńska, J. (eds.) Computers in Medical Activity. AISC, vol. 65, pp. 11–21. Springer, Heidelberg (2009)
Bilski, J., Rutkowski, L.: Numerically Robust Learning Algorithms for Feed Forward Neural Networks. In: Advances in Soft Computing - Neural Networks and Soft Computing, pp. 149–154. Physica-Verlag, A Springer-Verlag Company (2003)
Bilski, J., Smoląg, J.: Parallel Approach to Learning of the Recurrent Jordan Neural Network. In: Rutkowski, L., Korytkowski, M., Scherer, R., Tadeusiewicz, R., Zadeh, L.A., Zurada, J.M. (eds.) ICAISC 2013, Part I. LNCS (LNAI), vol. 7894, pp. 32–40. Springer, Heidelberg (2013)
Bilski, J., Smoląg, J.: Parallel Realisation of the Recurrent Elman Neural Network Learning. In: Rutkowski, L., Scherer, R., Tadeusiewicz, R., Zadeh, L.A., Zurada, J.M. (eds.) ICAISC 2010, Part II. LNCS (LNAI), vol. 6114, pp. 19–25. Springer, Heidelberg (2010)
Bilski, J., Smoląg, J.: Parallel Realisation of the Recurrent Multi Layer Perceptron Learning. In: Rutkowski, L., Korytkowski, M., Scherer, R., Tadeusiewicz, R., Zadeh, L.A., Zurada, J.M. (eds.) ICAISC 2012, Part I. LNCS (LNAI), vol. 7267, pp. 12–20. Springer, Heidelberg (2012)
Cpalka, K.: A Method for Designing Flexible Neuro-fuzzy Systems. In: Rutkowski, L., Tadeusiewicz, R., Zadeh, L.A., Żurada, J.M. (eds.) ICAISC 2006. LNCS (LNAI), vol. 4029, pp. 212–219. Springer, Heidelberg (2006)
Cpałka, K.: On evolutionary designing and learning of flexible neuro-fuzzy structures for nonlinear classification. Nonlinear Analysis Series A: Theory, Methods and Applications 71, 1659–1672 (2009)
Cpałka, K., Łapa, K., Przybył, A., Zalasiński, M.: A new method for designing neuro-fuzzy systems for nonlinear modelling with interpretability aspects. Neurocomputing (in print, 2014), http://dx.doi.org/10.1016/j.neucom.2013.12.031
Cpałka, K., Rutkowski, L.: A New Method for Designing and Reduction of Neuro-fuzzy Systems. In: Proceedings of the 2006 IEEE International Conference on Fuzzy Systems (IEEE World Congress on Computational Intelligence, WCCI 2006), Vancouver, BC, Canada, pp. 8510–8516 (2006)
Cpałka, K., Rutkowski, L.: Flexible Takagi-Sugeno Fuzzy Systems. In: Proceedings of the International Joint Conference on Neural Networks 2005, Montreal, pp. 1764–1769 (2005)
Cpałka, K., Rutkowski, L.: Flexible Takagi-Sugeno Neuro-fuzzy Structures for Nonlinear Approximation. WSEAS Transactions on Systems 4(9), 1450–1458 (2005)
Duana, X.-G., Li, H.-X., Denga, H.: Robustness of fuzzy PID controller due to its inherent saturation. Journal of Process Control 22, 470–476 (2012)
Dziwiński, P., Bartczuk, Ł., Starczewski, J.T.: Fully controllable ant colony system for text data clustering. In: Rutkowski, L., Korytkowski, M., Scherer, R., Tadeusiewicz, R., Zadeh, L.A., Zurada, J.M. (eds.) SIDE 2012 and EC 2012. LNCS, vol. 7269, pp. 199–205. Springer, Heidelberg (2012)
Dziwiński, P., Rutkowska, D.: Algorithm for generating fuzzy rules for WWW document classification. In: Rutkowski, L., Tadeusiewicz, R., Zadeh, L.A., Żurada, J.M. (eds.) ICAISC 2006. LNCS (LNAI), vol. 4029, pp. 1111–1119. Springer, Heidelberg (2006)
Dziwiński, P., Rutkowska, D.: Ant focused crawling algorithm. In: Rutkowski, L., Tadeusiewicz, R., Zadeh, L.A., Zurada, J.M. (eds.) ICAISC 2008. LNCS (LNAI), vol. 5097, pp. 1018–1028. Springer, Heidelberg (2008)
Dziwiński, P., Starczewski, J.T., Bartczuk, Ł.: New linguistic hedges in construction of interval type-2 FLS. In: Rutkowski, L., Scherer, R., Tadeusiewicz, R., Zadeh, L.A., Zurada, J.M. (eds.) ICAISC 2010, Part II. LNCS (LNAI), vol. 6114, pp. 445–450. Springer, Heidelberg (2010)
El-Abd, M.: On the hybridization on the artificial bee colony and particle swarm optimization algorithms. Journal of Artificial Intelligence and Soft Computing Research 2(2), 147–155 (2012)
Fogel, D.B.: Evolutionary Computation: Toward a New Philosophy of Machine Intelligence, 3rd edn. IEEE Press, Piscataway (2006)
Gabryel, M., Cpałka, K., Rutkowski, L.: Evolutionary strategies for learning of neuro-fuzzy systems. In: Proceedings of the I Workshop on Genetic Fuzzy Systems, Granada, pp. 119–123 (2005)
Gabryel, M., Korytkowski, M., Scherer, R., Rutkowski, L.: Object Detection by Simple Fuzzy Classifiers Generated by Boosting. In: Rutkowski, L., Korytkowski, M., Scherer, R., Tadeusiewicz, R., Zadeh, L.A., Zurada, J.M. (eds.) ICAISC 2013, Part I. LNCS (LNAI), vol. 7894, pp. 540–547. Springer, Heidelberg (2013)
Gabryel, M., Woźniak, M., Nowicki, R.K.: Creating Learning Sets for Control Systems Using an Evolutionary Method. In: Rutkowski, L., Korytkowski, M., Scherer, R., Tadeusiewicz, R., Zadeh, L.A., Zurada, J.M. (eds.) EC 2012 and SIDE 2012. LNCS, vol. 7269, pp. 206–213. Springer, Heidelberg (2012)
Horzyk, A., Tadeusiewicz, R.: Self-Optimizing Neural Networks. In: Yin, F.-L., Wang, J., Guo, C. (eds.) ISNN 2004. LNCS, vol. 3173, pp. 150–155. Springer, Heidelberg (2004)
Jelonkiewicz, J., Przybył, A.: Accuracy improvement of neural network state variable estimator in induction motor drive. In: Rutkowski, L., Tadeusiewicz, R., Zadeh, L.A., Zurada, J.M. (eds.) ICAISC 2008. LNCS (LNAI), vol. 5097, pp. 71–77. Springer, Heidelberg (2008)
Korytkowski, M., Rutkowski, L., Scherer, R.: On combining backpropagation with boosting. In: Proceedings of the IEEE International Joint Conference on Neural Network (IJCNN), vols. 1-10, pp. 1274–1277 (2006)
Laskowski, Ł.: A novel hybrid-maximum neural network in stereo-matching process. Neural Comput. & Applic. 23, 2435–2450 (2013)
Laskowski, Ł.: Objects Auto-selection from Stereo-Images Realised by Self-Correcting Neural Network. In: Rutkowski, L., Korytkowski, M., Scherer, R., Tadeusiewicz, R., Zadeh, L.A., Zurada, J.M. (eds.) ICAISC 2012, Part I. LNCS, vol. 7267, pp. 119–125. Springer, Heidelberg (2012)
Li, J., Li, J., Xia, Z.: Delay-dependent generalized H2 control for discrete T-S fuzzy large-scale stochastic systems with mixed delays. International Journal of Applied Mathematics and Computer Science 21(4) (2011)
Lin, J., Lian, R.: Intelligent Control of Active Suspension Systems. IEEE Transactions on Industrial Electronics 58(2), 618–628 (2011)
Lobato, F.S., Steffen Jr., V.: A new multi-objective optimization algorithm based on differential evolution and neighborhood exploring evolution strategy. Journal of Artificial Intelligence and Soft Computing Research 1(4), 259–267 (2011)
Lobato, F.S., Steffen Jr., V., Silva Neto, A.J.: Solution of singular optimal control problems using the improved differential evolution algorithm. Journal of Artificial Intelligence and Soft Computing Research 1(3), 195–206 (2011)
Łapa, K., Przybył, A., Cpałka, K.: A new approach to designing interpretable models of dynamic systems. In: Rutkowski, L., Korytkowski, M., Scherer, R., Tadeusiewicz, R., Zadeh, L.A., Zurada, J.M. (eds.) ICAISC 2013, Part II. LNCS (LNAI), vol. 7895, pp. 523–534. Springer, Heidelberg (2013)
Łapa, K., Zalasiński, M., Cpałka, K.: A new method for designing and complexity reduction of neuro-fuzzy systems for nonlinear modelling. In: Rutkowski, L., Korytkowski, M., Scherer, R., Tadeusiewicz, R., Zadeh, L.A., Zurada, J.M. (eds.) ICAISC 2013, Part I. LNCS (LNAI), vol. 7894, pp. 329–344. Springer, Heidelberg (2013)
Maggio, M., Bonvini, M., Leva, A.: The PID + p controller structure and its contextual autotuning. Journal of Process Control 22, 1237–1245 (2012)
Michalewicz, Z.: Genetic Algorithms + Data Structures = Evolution Programs. Springer (1999)
Nowicki, R., Scherer, R., Rutkowski, L.: A method for learning of hierarchical fuzzy systems. In: Sincak, P., Vascak, J., Kvasnicka, V., Pospichal, J. (eds.) Intelligent Technologies - Theory and Applications, pp. 124–129. IOS Press (2002)
Patan, K., Patan, M.: Optimal training strategies for locally recurrent neural network. Journal of Artificial Intelligence and Soft Computing Research 1(2) (2011)
Pławiak, P., Tadeusiewicz, R.: Approximation of phenol concentration using novel hybrid computational intelligence methods. Applied Mathematics and Computer Science 24(1) (in print, 2014)
Prampero, P.S., Attux, R.: Magnetic particle swarm optimization. Journal of Artificial Intelligence and Soft Computing Research 2(1), 59–72 (2012)
Przybył, A., Cpałka, K.: A new method to construct of interpretable models of dynamic systems. In: Rutkowski, L., Korytkowski, M., Scherer, R., Tadeusiewicz, R., Zadeh, L.A., Zurada, J.M. (eds.) ICAISC 2012, Part II. LNCS (LNAI), vol. 7268, pp. 697–705. Springer, Heidelberg (2012)
Przybył, A., Jelonkiewicz, J.: Genetic algorithm for observer parameters tuning in sensorless induction motor drive. In: Rutkowski, L., Kacprzyk, J. (eds.) Neural Networks and Soft Computing (6th International Conference on Neural Networks and Soft Computing 2002), Zakopane, Poland, pp. 376–381 (2003)
Przybył, A., Smoląg, J., Kimla, P.: Distributed Control System Based on Real Time Ethernet for Computer Numerical Controlled Machine Tool (in Polish). Przeglad Elektrotechniczny 88(2), 342–346 (2010)
Ribića, A.I., Mataušek, M.R.: A dead-time compensating PID controller structure and robust tuning. Journal of Process Control 22, 1340–1349 (2012)
Rutkowski, L.: Computational Intelligence. Springer (2008)
Rutkowski, L.: Multiple Fourier series procedures for extraction of nonlinear regressions from noisy data. IEEE Transactions on Signal Processing 41(10), 3062–3065 (1993)
Rutkowski, L.: Nonparametric identification of quasi-stationary systems. Systems and Control Letters 6, 33–35 (1985)
Rutkowski, L.: On Bayes risk consistent pattern recognition procedures in a quasi-stationary environment. IEEE Transactions on Pattern Analysis and Machine Intelligence PAMI-4(1), 84–87 (1982)
Rutkowski, L., Cpałka, K.: Compromise approach to neuro-fuzzy systems. In: Sincak, P., Vascak, J., Kvasnicka, V., Pospichal, J. (eds.) Intelligent Technologies - Theory and Applications, vol. 76, pp. 85–90. IOS Press (2002)
Rutkowski, L., Cpałka, K.: Flexible weighted neuro-fuzzy systems. In: Proceedings of the 9th International Conference on Neural Information Processing (ICONIP 2002), Orchid Country Club, Singapore, CD, November 18-22 (2002)
Rutkowski, L., Cpałka, K.: Neuro-fuzzy systems derived from quasi-triangular norms. In: Proceedings of the IEEE International Conference on Fuzzy Systems, Budapest, July 26-29, vol. 2, pp. 1031–1036 (2004)
Rutkowski, L., Przybył, A., Cpałka, K.: Novel on-line speed profile generation for industrial machine tool based on flexible neuro-fuzzy approximation. IEEE Transactions on Industrial Electronics 59, 1238–1247 (2012)
Rutkowski, L., Przybył, A., Cpałka, K., Er, M.J.: Online Speed Profile Generation for Industrial Machine Tool Based on Neuro-fuzzy Approach. In: Rutkowski, L., Scherer, R., Tadeusiewicz, R., Zadeh, L.A., Zurada, J.M. (eds.) ICAISC 2010, Part II. LNCS (LNAI), vol. 6114, pp. 645–650. Springer, Heidelberg (2010)
Scherer, R.: Neuro-fuzzy relational systems for nonlinear approximation and prediction. Nonlinear Analysis Series A: Theory, Methods and Applications 71(12), e1420–e1425 (2009)
Scherer, R., Rutkowski, L.: Connectionist fuzzy relational systems. In: Halgamuge, S.K., Wang, L. (eds.) 9th International Conference on Neural Information and Processing; 4th Asia-Pacific Conference on Simulated Evolution and Learning; 1st International Conference on Fuzzy Systems and Knowledge Discovery, Computational Intelligence for Modelling and Prediction Book Series. SCI, vol. 2, pp. 35–47. Springer, Heidelberg (2005)
van der Sande, T.P.J., Gysen, B.L.J., Besselink, I.J.M., Paulides, J.J.H., Lomonova, E.A., Nijmeijer, H.: Robust control of an electromagnetic active suspension system: Simulations and measurements. Mechatronics 23(2) (2013)
Szaleniec, M., Goclon, J., Witko, M., Tadeusiewicz, R.: Application of artificial neural networks and DFT-based parameters for prediction of reaction kinetics of ethylbenzene dehydrogenase. Journal of Computer-Aided Molecular Design 20(3), 145–157 (2006)
Szczypta, J., Przybył, A., Cpałka, K.: Some aspects of evolutionary designing optimal controllers. In: Rutkowski, L., Korytkowski, M., Scherer, R., Tadeusiewicz, R., Zadeh, L.A., Zurada, J.M. (eds.) ICAISC 2013, Part II. LNCS, vol. 7895, pp. 91–100. Springer, Heidelberg (2013)
Theodoridis, D.C., Boutalis, Y.S., Christodoulou, M.A.: Robustifying analysis of the direct adaptive control of unknown multivariable nonlinear systems based on a new neuro-fuzzy method. Journal of Artificial Intelligence and Soft Computing Research 1(1), 59–79 (2011)
Tran, V.N., Brdys, M.A.: Optimizing control by robustly feasible model predictive control and application to drinking water distribution systems. Journal of Artificial Intelligence and Soft Computing Research 1(1), 43–57 (2011)
Zalasiński, M., Cpałka, K.: A new method of on-line signature verification using a flexible fuzzy one-class classifier, pp. 38–53. Academic Publishing House EXIT (2011)
Zalasiński, M., Łapa, K., Cpałka, K.: New Algorithm for Evolutionary Selection of the Dynamic Signature Global Features. In: Rutkowski, L., Korytkowski, M., Scherer, R., Tadeusiewicz, R., Zadeh, L.A., Zurada, J.M. (eds.) ICAISC 2013, Part II. LNCS (LNAI), vol. 7895, pp. 113–121. Springer, Heidelberg (2013)
Zalasiński, M., Cpałka, K.: New Approach for the On-Line Signature Verification Based on Method of Horizontal Partitioning. In: Rutkowski, L., Korytkowski, M., Scherer, R., Tadeusiewicz, R., Zadeh, L.A., Zurada, J.M. (eds.) ICAISC 2013, Part II. LNCS (LNAI), vol. 7895, pp. 342–350. Springer, Heidelberg (2013)
Zalasiński, M., Cpałka, K.: Novel algorithm for the on-line signature verification. In: Rutkowski, L., Korytkowski, M., Scherer, R., Tadeusiewicz, R., Zadeh, L.A., Zurada, J.M. (eds.) ICAISC 2012, Part II. LNCS (LNAI), vol. 7268, pp. 362–367. Springer, Heidelberg (2012)
Zalasiński, M., Cpałka, K.: Novel Algorithm for the On-Line Signature Verification Using Selected Discretization Points Groups. In: Rutkowski, L., Korytkowski, M., Scherer, R., Tadeusiewicz, R., Zadeh, L.A., Zurada, J.M. (eds.) ICAISC 2013, Part I. LNCS (LNAI), vol. 7894, pp. 493–502. Springer, Heidelberg (2013)
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Szczypta, J., Przybył, A., Wang, L. (2014). Evolutionary Approach with Multiple Quality Criteria for Controller Design. In: Rutkowski, L., Korytkowski, M., Scherer, R., Tadeusiewicz, R., Zadeh, L.A., Zurada, J.M. (eds) Artificial Intelligence and Soft Computing. ICAISC 2014. Lecture Notes in Computer Science(), vol 8467. Springer, Cham. https://doi.org/10.1007/978-3-319-07173-2_39
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