Abstract
The proposed mechanism of output constraint handling uses a method of output prediction generation, which originates from Model Predictive Control (MPC) algorithms and is based on Hammerstein models. Therefore the mechanism can give very good results in control systems of nonlinear plants. It is relatively easy to use and, at the same time, very efficient, because in the output constraint handling the influence of the control action many sampling instants ahead can be taken into consideration. Moreover, the proposed method is flexible – it is possible to choose how many future predicted output values are constrained.
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References
Camacho, E.F., Bordons, C.: Model Predictive Control. Springer (1999)
Janczak, A.: Identification of nonlinear systems using neural networks and polynomial models: a block–oriented approach. Springer, Heidelberg (2005)
Maciejowski, J.M.: Predictive control with constraints. Prentice Hall, Harlow (2002)
Marusak, P.: Analytical predictive controllers with efficient handling of output constraints. In: Malinowski, K., Rutkowski, L. (eds.) Recent Advances in Control and Automation, pp. 131–140. Academic Publishing House EXIT, Warszawa (2008)
Marusak, P.: On prediction generation in efficient MPC algorithms based on fuzzy Hammerstein models. In: Rutkowski, L., Scherer, R., Tadeusiewicz, R., Zadeh, L.A., Zurada, J.M. (eds.) ICAISC 2010, Part I. LNCS (LNAI), vol. 6113, pp. 136–143. Springer, Heidelberg (2010)
Marusak, P.M.: Efficient predictive control algorithm based on fuzzy Hammerstein models: a case study. In: Gao, X.-Z., Gaspar-Cunha, A., Köppen, M., Schaefer, G., Wang, J. (eds.) Soft Computing in Industrial Applications. AISC, vol. 75, pp. 11–20. Springer, Heidelberg (2010)
Marusak, P.M.: Numerically efficient analytical MPC algorithm based on fuzzy Hammerstein models. In: Dobnikar, A., Lotrič, U., Šter, B. (eds.) ICANNGA 2011, Part II. LNCS, vol. 6594, pp. 177–185. Springer, Heidelberg (2011)
Marusak, P., Tatjewski, P.: Actuator fault tolerance in control systems with predictive constrained set-point optimizers. International Journal of Applied Mathematics and Computer Science 18, 539–551 (2008)
Piegat, A.: Fuzzy Modeling and Control. Physica–Verlag, Berlin (2001)
Rossiter, J.A.: Model–Based Predictive Control. CRC Press, Boca Raton (2003)
Takagi, T., Sugeno, M.: Fuzzy identification of systems and its application to modeling and control. IEEE Trans. Systems, Man and Cybernetics 15, 116–132 (1985)
Tatjewski, P.: Advanced Control of Industrial Processes; Structures and Algorithms. Springer, London (2007)
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Marusak, P.M. (2014). Efficient Mechanism of Output Constraint Handling for Analytical Predictive Controllers Based on Hammerstein Models. In: Szewczyk, R., Zieliński, C., Kaliczyńska, M. (eds) Recent Advances in Automation, Robotics and Measuring Techniques. Advances in Intelligent Systems and Computing, vol 267. Springer, Cham. https://doi.org/10.1007/978-3-319-05353-0_14
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DOI: https://doi.org/10.1007/978-3-319-05353-0_14
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-05352-3
Online ISBN: 978-3-319-05353-0
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