abstract

• In this paper, a comparative study of the wavenet PID controllers for applications in non-linear systems is presented. The wavenet PID controllers combine the neural network learning advantage with the wavelet representation for an efficient identification of non-linear dynamic systems, and these have application when we want to control plants of unknown mathematical model with highly non-linear characteristics. There exist different types of PID wavenet controllers i.e. wavenet PID, fuzzy-wavenet PID and multiresolution wavenet PID, these controllers tune online the proportional, integral and derivative gains of a classical discrete PID controller, through the identification of the plant using a radial basis neural network with different daughters wavelet activation functions. For this reason, the performance of the wavenet PID and the fuzzy-wavenet PID controlling a sub-actuated system are compared with the classical PID controller. The simulation results show that the fuzzy-wavenet PID controller has a good performance to carry out the control nonlinear system, for example the inverted pendulum. © 2015 IEEE.

authors

• Algredo-Badillo I.
• Balmat J.-F.
• García Barrientos Abel
• Lafont F.
• Ordaz Oliver J.P.
• Ramos-V L.E.
• Saldaña-O M.A.

publication date

• 2015-01-01

published in

• 2015 12th International Conference on Electrical Engineering, Computing Science and Automatic Control, CCE 2015  Proceedings

keywords

• fuzzy-wavenet PID; inverted pendulum; neural network; wavenet PID Automation; Controllers; Electric control equipment; Fuzzy inference; Linear control systems; Linear systems; Neural networks; Nonlinear systems; Pendulums; Process control; Three term control systems; Discrete pid controllers; fuzzy-wavenet PID; Inverted pendulum; Non-linear dynamic systems; Nonlinear characteristics; Radial basis neural networks; Wavelet activation function; wavenet PID; Proportional control systems

Digital Object Identifier (DOI)

• 10.1109/ICEEE.2015.7357964

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