Abstract
The optimization of controller parameters or gains is a challenge usually approached using empirical methods that consume valuable time, without the certainty that the obtained gains actually produce the desired behaviour of the controlled plant. There are several analytical and numerical methodologies to find the parameters for PID controllers, however currently there is not enough available information regarding the application of optimization methods for nonlinear controllers. The present work describes the application of the maximum descent method to find the gains of IDA-PBC controller for a ball and beam system. The proposed methodology involves implementing a mathematical model to describe the system’s dynamics, the design of a objective function to measure how closely the plant follows the desired behaviour, and finally the evaluation of a set of gains obtained by the numerical method. The dynamic model and the optimization algorithm were implemented in C language in order to reduce the computer time compared to the use of frameworks such as MATLAB. Numerical simulations to validate the effectiveness of the proposed methodology are included.
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Morales, J.A., Castro, M.A., Garcia, D., Higuera, C., Sandoval, J. (2019). IDA-PBC Controller Tuning Using Steepest Descent. In: Trujillo, L., Schütze, O., Maldonado, Y., Valle, P. (eds) Numerical and Evolutionary Optimization – NEO 2017. NEO 2017. Studies in Computational Intelligence, vol 785. Springer, Cham. https://doi.org/10.1007/978-3-319-96104-0_8
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