Abstract
A new motion controller for the multi-nonlinear system is proposed by using a fuzzy sliding mode controller (FSMC) based on improved genetic algorithm (GA). In controlling the nonlinear element of the system, there are some critical problems such as the limit cycle. As the system has nonlinearities, a robust controller is one of the optimal solutions. The FSMC is a kind of the robust methods to control nonlinearities effectively in a system. Prior to applying a FSMC, genetic algorithm is used for identifying system without manual tuning and obtaining optimal fuzzy set of FSMC. The suggested GA is an improved type to find optimal solution. It uses new type of crossover and mutation with a sigmoid function that is applied to improve the searching ability. Also, an additional compensator and motion controller are suggested in order to improve position tracking. All the processes are investigated through simulations and experimentally verified in a real motor system.
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Kong, JS., Kim, JG. (2006). Improved Genetic Algorithm-Based FSMC Design for Multi-nonlinear System. In: Gabrys, B., Howlett, R.J., Jain, L.C. (eds) Knowledge-Based Intelligent Information and Engineering Systems. KES 2006. Lecture Notes in Computer Science(), vol 4253. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11893011_30
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DOI: https://doi.org/10.1007/11893011_30
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-46542-3
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