Abstract
This paper present on minimum value of rider comfortness vibration values to obtain maximum rider comfortness during riding. The simulation model was being achieved with the help of MATLAB/Simulink for further process to Genetic Algorithm through Response surface methodology modeled equation. As the response surface methodology is a long established technique in optimization for experimental process. Recently a new intelligent approach to the quarter car suspension system has been tried with response surface methodology and genetic algorithm which is new in the computational field. For the Response surface methodology, an experimental design was chosen in order to order to obtain the proper modelling equation. Later this modeled equation was served as evaluation function or objective function for further process into genetic algorithm. In Genetic algorithm case, the optimality search was carried without the knowledge of modelling equations between inputs and outputs. This situation is to choose the best values of three control variables. The techniques are performed and results indicated that technique is capable of locating good conditions to evaluate optimal setting, to reduce comfortness vibrations for maximum comfortness.
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Acknowledgments
This research was supported/partially supported by Prof. C.h. Ratnam, Mechanical Department, College of Engineering, Andhra University. We thank our Head of Department of Mechanical Engineering, Dr. Y.V. Hanumanth Rao. Dean of Research and Development, Dr. K.L. Narayana. And authors P. Vigneshwar and Rajasekhar would like to special thanks to Dr. Sumathi, Department of Humanities KL University, P. Manjula Reddy, P. Malla Reddy, and D. Kesava Reddy.
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Sreekar Reddy, M.B.S., Rao, S.S., Vigneshwar, P., Akhil, K., RajaSekhar, D. (2016). An Intelligent Optimization Approach to Quarter Car Suspension System Through RSM Modeled Equation. In: Satapathy, S., Das, S. (eds) Proceedings of First International Conference on Information and Communication Technology for Intelligent Systems: Volume 2. Smart Innovation, Systems and Technologies, vol 51. Springer, Cham. https://doi.org/10.1007/978-3-319-30927-9_10
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DOI: https://doi.org/10.1007/978-3-319-30927-9_10
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