Controlador multiresolución para sistemas no lineales basado en WaveNets

Oscar Federico García-Castro; Mario Alejandro Vega-Navarrete; Luis Enrique Ramos-Velasco; Rodolfo García-Rodríguez; Enrique Escamilla-Hernández

doi:10.29057/icbi.v11iEspecial4.11391

Oscar Federico García-Castro Universidad Politécnica Metropolitana de Hidalgo https://orcid.org/0000-0003-2208-8333
Mario Alejandro Vega-Navarrete Universidad Politécnica Metropolitana de Hidalgo https://orcid.org/0000-0003-2739-8840
Luis Enrique Ramos-Velasco Universidad Politécnica Metropolitana de Hidalgo https://orcid.org/0000-0002-8715-9641
Rodolfo García-Rodríguez Universidad Politécnica Metropolitana de Hidalgo https://orcid.org/0000-0002-4402-6072
Enrique Escamilla-Hernández Instituto Politécnico Nacional https://orcid.org/0000-0002-4832-8270

DOI: https://doi.org/10.29057/icbi.v11iEspecial4.11391

Keywords: Multi-resolution analysis, Intelligent control, Wavelet function, Quanser helicopter, Neural network

Abstract

The design of robust and free-model controllers has been an open problem for many years. Although many approaches have been reported in the literature, the PID controller is the most used for its simplicity and speed response under some conditions. Thus, in many approaches, PID-like controllers are a recurrent controller structure. In recent years, due to the systems carrying more complex tasks subject to different environmental conditions, as in aircraft or robots, artificial intelligence tools such as neural networks have been used to self-tune feedback gain controllers. Based on the wavelet transformation, this paper proposes a multi-resolution proportional controller (PMR) scheme to control non-linear systems, avoiding system information. The PMR decomposes the tracking error to obtain different information on scale and frequency, which allows for compensation for various uncertainties in the system. The wavelet~neural network (WaveNet) information approximates the dynamic input-output model and is used for self-tuning feedback gains. Numerical simulation results for a 2-degree-of-freedom Quanser helicopter are presented, under different conditions, to verify the performance of the PMR controller.

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