For long time the optimization of controller parameters uses the well-known classical method such as the Ziegler-Nichols and the Cohen-Coon tuning techniques. Despite its effectiveness, these off-line tuning techniques can be time consuming especially for a case of complex nonlinear system. This paper attempts to show a great deal on how Metamodeling techniques can be utilized to tune the PID controller parameters quickly. Note that the plant use in this study is the cruise control system with 2 different models, which are the linear model and the nonlinear model. The difference between both models is that the disturbances were taken into consideration for the nonlinear model, but in the linear model the disturbances were assumed as zero. The Radial Basis Function Neural Network Metamodel is able to prove that it can minimize the time in tuning process as it is able to give a good approximation to the optimum controller parameters in both models of this system.

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His field of study covers mechanics of solid bodies, human biomechanics, theory of system, theory of modelling, theory of experiment, theory of statistics, behavior of materials. He is chairman of the Engineering Mechanics Branch Council, deputy chairman of the Committee of the Czech Society for Biomechanics, head of the society's Moravian branch, member of the scientific board of the Faculty of Education of the Masaryk University in Brno, as well as member of editorial boards of several scientific journals. His publication activity contains 121 scientific articles in journals, 86 papers on conferences and 19 reports of grant projects. He is co-author of the publication "Computational Models in Engineering Practice" and author of the "Systematic Encyclopedia of Selected Disciplines for Engineers".